case study of respiratory failure

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Reviewed By Behavioral Science Assembly

Submitted by

Lokesh Venkateshaiah, MD

Division of Pulmonary, Critical Care and Sleep Medicine

The MetroHealth System, Case Western Reserve University

Cleveland, Ohio

Bruce Arthur, MD

J. Daryl Thornton, MD, MPH

Assistant Professor

Division of Pulmonary, Critical Care and Sleep Medicine, Center for Reducing Health Disparities

Submit your comments to the author(s).

A 60-year-old man presented to the emergency department complaining of persistent right-sided chest pain and cough. The chest pain was pleuritic in nature and had been present for the last month. The associated cough was productive of yellow sputum without hemoptysis. He had unintentionally lost approximately 30 pounds over the last 6 months and had nightly sweats. He had denied fevers, chills, myalgias or vomiting. He also denied sick contacts or a recent travel history. He recalled childhood exposures to persons afflicted with tuberculosis. 

The patient smoked one pack of cigarettes daily for the past 50 years and denied recreational drug use. He reported ingesting twelve beers daily and had had delirium tremens, remote right-sided rib fractures and a wrist fracture as a result of alcohol consumption. He had worked in the steel mills but had discontinued a few years previously. He collected coins and cleaned them with mercury. 

The patient’s past medical history was remarkable for chronic “shakes” of the upper extremities for which he had not sought medical attention. Other than daily multivitamin tablets, he took no regular medications. 

Hospital course  He was initially admitted to the general medical floor for treatment of community-acquired pneumonia (see Figure 1) and for the prevention of delirium tremens. He was initiated on ceftriaxone, azithromycin, thiamine and folic acid. Diazepam was initiated and titrated using the Clinical Institute Withdrawal Assessment for Alcohol Scale (CIWAS-Ar), a measure of withdrawal severity (1).  By hospital day 5, his respiratory status continued to worsen, requiring transfer to the intensive care unit (ICU) for hypoxemic respiratory failure. His neurologic status had also significantly deteriorated with worsening confusion, memory loss, drowsiness, visual hallucinations (patient started seeing worms) and worsening upper extremity tremors without generalized tremulousness despite receiving increased doses of benzodiazepines.

Physical Exam

White blood cell count was 11,000/mm 3 with 38% neutrophils, 8% lymphocytes, 18 % monocytes and 35% bands

Hematocrit 33%

Platelet count was 187,000/mm 3

Serum sodium was 125 mmol/L, potassium 3 mmol/L, chloride 91 mmol/L, bicarbonate 21 mmol/L, blood urea nitrogen 14 mg /dl, serum creatinine  0.6 mg/dl and anion gap of 14.

Urine sodium <10 mmol/L, urine osmolality 630 mosm/kg

Liver function tests revealed albumin 2.1 with total protein 4.6, normal total bilirubin, aspartate transaminase (AST) 49, Alanine transaminase (ALT) 19 and alkaline phosphatase 47.

Three sputum samples were negative for acid-fast bacilli (AFB).

Bronchoalveolar lavage (BAL) white blood cell count 28 cells/µl, red blood cell count 51 cells/µl, negative for AFB and negative Legionella culture.  BAL gram stain was without organisms or polymorphonuclear leukocytes.

Blood cultures were negative for growth.

Sputum cultures showed moderate growth of Pasteurella multocida.

2D transthoracic ECHO of the heart showed normal valves and an ejection fraction of 65% with a normal left ventricular end-diastolic pressure and normal left atrial size.  No vegetations were noted.

Purified protein derivative (PPD) administered via Mantoux testing was 8 mm in size at 72 hr after placement.

Human immunodeficiency virus (HIV) serology was negative. 

Arterial blood gas (ABG) analysis performed on room air on presentation to the ICU: pH 7.49, PaCO 2 29 mm Hg, PaO 2 49 mm Hg.

case study of respiratory failure

After admission to the ICU, the patient was noted to be in acute lung injury (ALI), a subset of acute respiratory distress syndrome (ARDS). The diagnosis of ALI requires all three of the following:  (a) bilateral pulmonary infiltrates, (b) a PaO 2 :FiO 2 ratio of ≤ 300 and (c) echocardiographic evidence of normal left atrial pressure or pulmonary-artery wedge pressure of ≤ 18 mm Hg (2). 

While patients with ALI and ARDS can be maintained with pressure-limited or volume-limited modes of ventilation, only volume assist-control ventilation was utilized in the ARDS Network multicenter randomized controlled trial that demonstrated a mortality benefit.

Noninvasive ventilation has not been demonstrated to be superior to endotracheal intubation in the treatment of ARDS or ALI and is not currently recommended (4).

This is a case of heavy metal poisoning with mercury.  The patient used mercury to clean coins.  Family members who had visited his house while he was hospitalized found several jars of mercury throughout his home.  The Environmental Protection Agency (EPA) was notified and visited the home.  They found aerosolized mercury levels of > 50,000 PPM and had the home immediately demolished. 

Alcoholic hallucinosis is a rare disorder occurring in 0.4 - 0.7% of alcohol-dependent inpatients (5).  Affected persons experience predominantly auditory but occasionally visual hallucinations.  Delusions of persecution may also occur.  However, in contrast to alcohol delirium, other alcohol withdrawal symptoms are not present and the sensorium is generally unaffected.

Delerium tremens (DT) occurs in approximately 5% of patients who withdraw from alcohol and is associated with a 5% mortality rate. DT typically occurs between 48 and 96 hr following the last drink and lasts 1-5 days.  DT is manifested by generalized alteration of the sensorium with vital sign abnormalities.  Death often results from arrhythmias, pneumonia, pancreatitis or failure to identify another underlying problem (6).  While DT certainly could have coexisted in this patient, an important initial step in the management of DT is to identify and treat alternative diagnoses.

Delirium is frequent among older patients in the ICU (7), and may be complicated by pneumonia and sepsis.  However, pneumonia and sepsis as causes for delirium are diagnoses of exclusion and should only be attributed after other possibilities have been ruled out. 

Frontal lobe stroke is unlikely, given the absence of other findings in the history or physical examination present to suggest an acute cerebrovascular event. 

In 1818, Dr. John Pearson coined the term erethism for the characteristic personality changes attributed to mercury poisoning (8).  Erethism is classically the first symptom in chronic mercury poisoning (9).  It is a peculiar form of timidity most evident in the presence of strangers and closely resembles an induced paranoid state.  In the past, when mercury was used in making top hats, the term “mad as a hatter” was used to describe the psychiatric manifestations of mercury intoxication.  Other neurologic manifestations include tremors, especially in patients with a history of alcoholism, memory loss, drowsiness and lethargy.  All of these were present in this patient. 

Acute respiratory failure (ALI/ARDS) can occur following exposure to inhalation of mercury fumes (10). Mercury poisoning has also been associated with acute kidney injury (11). 

Although all of the options mentioned above could possibly contribute to the development of delirium, only mercury poisoning would explain the constellation of findings of confusion, upper extremity tremors, visual hallucinations, somnolence and acute respiratory failure (ALI/ARDS).

Knowledge of the form of mercury absorbed is helpful in the management of such patients, as each has its own distinct characteristics and toxicity. There are three types of mercury: elemental, organic and inorganic. This patient had exposure to elemental mercury from broken thermometers. 

Elemental mercury is one of only two known metals that are liquid at room temperature and has been referred to as quicksilver (12). It is commonly found in thermometers, sphygmomanometers, barometers, electronics, latex paint, light bulbs and batteries (13).  Although exposure can occur transcutaneously or by ingestion, inhalation is the major route of toxicity.  Ingested elemental mercury is poorly absorbed and typically leaves the body unchanged without consequence (bioavailability 0.01% [13]). However, inhaled fumes are rapidly absorbed through the pulmonary circulation allowing distribution throughout the major organ systems.  Clinical manifestations vary based on the chronicity of the exposure (14).  Mercury readily crosses the blood-brain barrier and concentrates in the neuronal lysosomal dense bodies. This interferes with major cell processes such as protein and nucleic acid synthesis, calcium homeostasis and protein phosphorylation.  Acute exposure symptoms manifest within hours as gastrointestinal upset, chills, weakness, cough and dyspnea.

Inorganic mercury salts are earthly-appearing, red ore found historically in cosmetics and skin treatments.  Currently, most exposures in the United States occur from exposure through germicides or pesticides (15).  In contrast to elemental mercury, inorganic mercury is readily absorbed through multiple routes including the gastrointestinal tract.  It is severely corrosive to gastrointestinal mucosa (16).  Signs and symptoms include profuse vomiting and often-bloody diarrhea, followed by hypovolemic shock, oliguric renal failure and possibly death (12).

Organic mercury, of which methylmercury is an example, has garnered significant attention recently following several large outbreaks as a result of environmental contamination in Japan in 1956 (17) and grain contamination in Iraq in 1972 (18).  Organic mercury is well absorbed in the GI tract and collects in the brain, reaching three to six times the blood concentration (19).  Symptoms may manifest up to a month after exposure as bilateral visual field constriction, paresthesias of the extremities and mouth, ataxia, tremor and auditory impairments (12).  Organic mercury is also present in a teratogenic agent leading to development of a syndrome similar to cerebral palsy termed "congenital Minamata disease" (20).

The appropriate test depends upon the type of mercury to which a patient has been exposed.  After exposure to elemental or inorganic mercury, the gold standard test is a 24-hr urine specimen for mercury.  Spot urine samples are unreliable.  Urine concentrations of greater than 50 μg in a 24-hr period are abnormal (21).  This patient’s 24-hr urine level was noted to be 90 μg.  Elemental and inorganic mercury have a very short half-life in the blood.

Exposure to organic mercury requires testing hair or whole blood.  In the blood, 90% of methyl mercury is bound to hemoglobin within the RBCs.  Normal values of whole blood organic mercury are typically < 6 μg/L. This patient’s whole blood level was noted to be 26 μg/L.  This likely reflects the large concentration of elemental mercury the patient inhaled and the substantial amount that subsequently entered the blood.

Mercury levels can be reduced with chelating agents such as succimer, dimercaprol (also known as British anti-Lewisite (BAL)) and D-penicillamine, but their effect on long-term outcomes is unclear (22-25).

  • Sullivan JT, Sykora K, Schneiderman J, et al. Assessment of alcohol withdrawal: the revised clinical institute withdrawal assessment for alcohol scale (CIWA-Ar). Br J Addict 1989;84:1353-1357.
  • Bernard GR, Artigas A, Brigham KL, et al. The American-European Consensus Conference on ARDS. Definitions, mechanisms, relevant outcomes, and clinical trial coordination. Am J Respir Crit Care Med 1994;149:818-824.
  • The Acute Respiratory Distress Syndrome Network. Ventilation with lower tidal volumes as compared with traditional tidal volumes for acute lung injury and the acute respiratory distress syndrome. N Engl J Med 2000;342:1301-1308.
  • Agarwal R, Reddy C, Aggarwal AN, et al. Is there a role for noninvasive ventilation in acute respiratory distress syndrome? A meta-analysis. Respir Med 2006;100:2235-2238.
  • Soyka M. Prevalence of alcohol-induced psychotic disorders. Eur Arch Psychiatry Clin Neurosci 2008;258:317-318.
  • Tavel ME, Davidson W, Batterton TD. A critical analysis of mortality associated with delirium tremens. Review of 39 fatalities in a 9-year period. Am J Med Sci 1961;242:18-29.
  • McNicoll L, Pisani MA, Zhang Y, et al. Delirium in the intensive care unit: occurrence and clinical course in older patients. J Am Geriatr Soc 2003;51:591-598.
  • Bateman T. Notes of a case of mercurial erethism. Medico-Chirurgical Transactions 1818;9:220-233.
  • Buckell M, Hunter D, Milton R, et al. Chronic mercury poisoning. 1946. Br J Ind Med 1993;50:97-106.
  • Rowens B, Guerrero-Betancourt D, et al. Respiratory failure and death following acute inhalation of mercury vapor. A clinical and histologic perspective. Chest 1991;99:185-190.
  • Aguado S, de Quiros IF, Marin R, et al. Acute mercury vapour intoxication: report of six cases. Nephrol Dial Transplant 1989;4:133-136.
  • Ibrahim D, Froberg B, Wolf A, et al. Heavy metal poisoning: clinical presentations and pathophysiology. Clin Lab Med 2006;26:67-97, viii.
  • A fact sheet for health professionals - elemental mercury. Available from: http://www.idph.state.il.us/envhealth/factsheets/mercuryhlthprof.htm
  • Clarkson TW, Magos L, Myers GJ. The toxicology of mercury - current exposures and clinical manifestations. N Engl J Med 2003;349:1731-1737.
  • Boyd AS, Seger D, Vannucci S, et al. Mercury exposure and cutaneous disease. J Am Acad Dermatol 2000;43:81-90.
  • Dargan PI, Giles LJ, Wallace CI, et al. Case report: severe mercuric sulphate poisoning treated with 2,3-dimercaptopropane-1-sulphonate and haemodiafiltration. Crit Care 2003;7:R1-6.
  • Eto K. Minamata disease. Neuropathology 2000;20:S14-9.
  • Bakir F, Damluji SF, Amin-Zaki L, et al. Methylmercury poisoning in Iraq. Science 1973;181:230-241.
  • Berlin M, Carlson J, Norseth T. Dose-dependence of methylmercury metabolism. A study of distribution: biotransformation and excretion in the squirrel monkey. Arch Environ Health 1975;30:307-313.
  • Harada M. Congenital Minamata disease: intrauterine methylmercury poisoning. Teratology 1978;18:285-288.
  • Graeme KA, Pollack CVJ. Heavy metal toxicity Part I: Arsenic and mercury. J Emerg Med 1998;16:45-56.
  • Aaseth J, Frieheim EA. Treatment of methylmercury poisoning in mice with 2,3-dimercaptosuccinic acid and other complexing thiols. Acta Pharmacol Toxicol (Copenh) 1978;42:248-252.
  • Archbold GP, McGuckin RM, Campbell NA. Dimercaptosuccinic acid loading test for assessing mercury burden in healthy individuals. Ann Clin Biochem 2004;41:233-236.
  • Kosnett MJ. Unanswered questions in metal chelation. J Toxicol Clin Toxicol 1992;30:529-547.
  • Zimmer LJ, Carter DE. The efficacy of 2,3-dimercaptopropanol and D-penicillamine on methyl mercury induced neurological signs and weight loss. Life Sci 1978;23:1025-1034.

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case study of respiratory failure

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Presentation

The condition, patient course, lessons for the clinician, suggested readings, case 6: acute-onset respiratory failure in a 4-month-old girl.

AUTHOR DISCLOSURE

Dr Harper has disclosed no financial relationships relevant to this article. This commentary does not contain a discussion of an unapproved/investigative use of a commercial product/device.

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Beth D. Harper; Case 6: Acute-onset Respiratory Failure in a 4-month-old Girl. Pediatr Rev July 2017; 38 (7): 338–339. https://doi.org/10.1542/pir.2016-0093

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A 4-month-old girl presents with a 1-week history of a temperature to 102°F (38.9°C), congestion, rhinorrhea, and cough. She has had fatigue and diaphoresis with feedings over the last week, although this did not occur before this time. She was born at term following normal findings on prenatal ultrasonography. Initially, she had difficulty gaining weight, but she is now growing along the 10th percentile. She had 1 overnight hospitalization for bronchiolitis at age 2 months and was treated with albuterol for a total of 1 week. Her mother has a history of asthma in childhood.

On physical examination, the girl is febrile and has a heart rate of 150 beats/min, respiratory rate of 46 breaths/min, and intercostal and subcostal retractions. Chest auscultation reveals bilateral coarse breath sounds. A rapid respiratory syncytial virus (RSV) antigen test is positive, and she is admitted to the inpatient ward. She remains tachycardic, with an increased heart rate to 170 beats/min. Following administration of a 20-mL/kg normal saline bolus, her respiratory distress acutely worsens. Her respiratory rate increases to 70 breaths/min and she exhibits head bobbing with ongoing retractions. Re-examination reveals a new S3 gallop on auscultation, and a liver edge is now palpable. Chest radiography shows haziness in both lung fields, small pleural effusions bilaterally, and an enlarged cardiac silhouette ( Fig 1 ). Additional studies reveal the diagnosis.

Figure 1. Chest radiograph shows haziness in both lung fields, small pleural effusions bilaterally, and an enlarged cardiac silhouette.

Chest radiograph shows haziness in both lung fields, small pleural effusions bilaterally, and an enlarged cardiac silhouette.

The girl’s initial presentation was concerning for bronchiolitis, and she had an RSV infection confirmed. Other primary respiratory causes, including pneumonia and reactive airway disease, were also considered. However, cardiac dysfunction was suspected because of the development of gallop and a palpable liver edge after fluid administration. Electrocardiography showed left ventricular hypertrophy and deep Q waves in the inferior leads ( Fig 2 ). Infectious myocarditis and cardiomyopathies were considered. Her troponin T concentration was elevated at 0.03 ng/mL (0.3 μg/L). Echocardiography showed severe left ventricular dysfunction and a probable anomalous left coronary artery from the pulmonary artery (ALCAPA). At cardiac catheterization, the diagnosis of ALCAPA was confirmed.

Figure 2. Electrocardiography shows evidence of left ventricular hypertrophy (tall S waves in V1 and tall R waves in V6) and deep Q waves in the inferior leads.

Electrocardiography shows evidence of left ventricular hypertrophy (tall S waves in V1 and tall R waves in V6) and deep Q waves in the inferior leads.

ALCAPA, previously known as Bland-White-Garland syndrome, is a rare form of congenital heart disease. As the name implies, the left coronary artery originates from the pulmonary artery rather than branching from the aorta. At birth, the condition is often asymptomatic and unrecognized because physiologically elevated pulmonary artery pressure allows sufficient anterograde flow through the left coronary artery. With decreasing pulmonary pressures after birth, blood may not flow from the pulmonary artery into the aberrant coronary, resulting in the development of myocardial ischemia and necrosis in the first few postnatal months. In some affected infants, ischemia may be subclinical due to collateral coronary vessels originating from the right coronary artery. This may delay the development of symptoms and, therefore, the diagnosis.

ALCAPA is often diagnosed in the first few months after birth in infants presenting with cardiac dysfunction. Infants may present with myocardial ischemia, cardiac dysfunction, elevated cardiac enzymes, or cardiac failure and cardiogenic shock. Reported symptoms include failure to thrive, poor feeding, fatigue, and diaphoresis. It can also present with acute respiratory failure and sudden cardiac death and may mimic myocarditis. Although some of these clinical manifestations are due to changing infant cardiac physiology, a concurrent illness that adds stress to the cardiopulmonary system may also precipitate heart failure. However, there are cases of patients surviving into adulthood with undetected ALCAPA.

Chest radiography usually demonstrates cardiomegaly. Electrocardiography may reveal ischemia or infarction, particularly in the anterior leads. Echocardiography can often identify the anomalous origin of the left coronary artery. In some cases where there is low flow in the coronary artery, visualization on echocardiography may be difficult, and cardiac catheterization with direct angiography may be necessary to confirm the diagnosis and for preoperative planning. Without repair, the prognosis of ALCAPA is poor.

Treatment of ALCAPA is surgical correction. Such correction is often accomplished with a coronary transfer procedure in which the left main coronary artery is reimplanted into the aorta, although other operative procedures do exist. Mitral valve repair may also be indicated at the time of surgery. Myocardial function improves postoperatively, even in cases with prior ischemia. Prognosis is excellent following repair, with long-term follow-up studies demonstrating greater than 98% survival at 20 years and low rates of repeat surgery. Results of echocardiography, electrocardiography, and chest radiography also normalize.

The girl was intubated and started on inotropic support. She underwent cardiac surgery 1 day after admission, recovered well, and was discharged 2 weeks later.

Heart failure should be considered in cases of respiratory failure that are not responsive to supportive care or that worsen with fluid administration.

Fluid boluses should be administered with caution in the setting of suspected heart failure.

Anomalous left coronary artery from the pulmonary artery (ALCAPA) can cause myocardial ischemia in infancy, and its acute presentation may mimic myocarditis.

The prognosis for ALCAPA is excellent with timely diagnosis and surgical repair.

AAP Textbook of Pediatric Care, 2nd Edition

Appendix A: Pediatric Cardiopulmonary Resuscitation - https://pediatriccare.solutions.aap.org/chapter.aspx?sectionId=138300647&bookId=1626&resultClick=1#160132374

For a comprehensive library of AAP parent handouts, please go to the Pediatric Patient Education site at http://patiented.aap.org .

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BEEM Cases 3 – Acute Respiratory Failure: NIPPV & POCUS

acute respiratory failure

BEEM Cases 3 on EM Cases – Acute Respiratory Failure. BEEM Cases  is a collaboration between Andrew Worster of Best Evidence in Emergency Medicine (BEEM) and Emergency Medicine Cases’ Anton Helman, Rory Spiegel and Justin Morgenstern.

Written by Justin Morgenstern (@First10EM), edited by Anton Helman (@EMCases), September 2016

Dypnea & Acute Respiratory Failure: Sometimes the Cause is Not So Obvious

The case….

A 73-year-old woman presents to the emergency department via EMS with increasing shortness of breath and cough over the past day. She has a history of COPD, CHF, hypertension, and hyperlipidemia. On arrival, she is breathing rapidly at 34 breaths a minute and is using all her accessory muscles. Her heart rate is 115, BP 155/95, Temp 37.5 and oxygen saturation 89% on 4L via nasal cannula. You perform a rapid physical exam, but you still aren’t sure exactly what is causing her dyspnea. Your RT turns to you and asks what you’d like to do.

Shortness of breath is a very common chief complaint in the emergency department, but despite our familiarity with this symptom, management is not always straightforward. The differential diagnosis is extensive, including the common cardiorespiratory conditions, but extending to toxicologic, hematologic, neuromuscular, metabolic, and psychiatric causes. Over the past decade, we have seen the widespread adoption of new technologies to help us manage these patients. This post will look at some new evidence on two of those technologies: noninvasive positive pressure ventilation (NIPPV) and ultrasound (POCUS). We will answer 3 questions based on 3 systematic reviews using the BEEM critical appraisal framework:

Question #1

Does noninvasive positive pressure ventilation (NIPPV) reduce mortality in acute respiratory failure?

Jump to Question 1 Discussion

Question #2

Does prehospital CPAP or BiPAP improve clinical outcomes for patients in acute respiratory failure?

Jump to Question 2 Discussion

Question #3

What is the sensitivity and specificity of POCUS using B-lines in diagnosing acute cardiogenic pulmonary edema in patients presenting to the ED with acute dyspnea?

Jump to Question 3 Discussion

Question #1 Does noninvasive positive pressure ventilation (NIPPV) reduce mortality in acute respiratory failure?

Cabrini L, Landoni G, Oriani A. Noninvasive ventilation and survival in acute care settings: a comprehensive systematic review and metaanalysis of randomized controlled trials. Critical care medicine. 43(4):880-8. 2015.

Study details (PICO)

Systematic review and meta-analysis

Key results

This meta-analysis found 78 trials that fit the inclusion criteria, with a total of 7365 patients. For the primary outcome of mortality, they found that noninvasive positive pressure ventilation decreased overall mortality (RR=0.73 [95% CI: 0.66, 0.81]) with a NNT=19.

BE EM   critique

This is the largest review of NIPPV to date and its primary outcome is mortality, the ultimate clinical outcome. Although 60% of the data is from the ICU setting, the results are probably still applicable to the ED and provide convincing evidence that patients with acute respiratory distress (except asthma) should be considered for NIPPV as a first line therapy. The suggestion that early NIPPV is better than late requires further study.

Key EBM point : Heterogeneity. The trials included in this meta-analysis displayed high heterogeneity. This simply means that the trials were different from each other in some way. There are two key types of heterogeneity. Clinical heterogeneity occurs when there is variability in key clinical aspects of trials. For example, two trials may look at different populations of patients or measure different outcomes. Statistical heterogeneity refers to the likelihood that the variability among the different results (one trial might report a 2% benefit whereas another reports a 18% benefit) is due to chance alone. Heterogeneity matters because if trials are too dissimilar it may not be appropriate to combine them into a single statistical analysis.

Case continued…

You start the patient on BiPAP and within 10 minutes her numbers have improved and she looks a lot better. One of the paramedics who brought her in is surprised by the rapid improvement and asks you if they should be starting some kind of non-invasive ventilation in the ambulance before arriving at the emergency department.

Question #2 Does NIPPV improve clinical outcomes in acute respiratory failure?

Goodacre S, Stevens JW, Pandor A. Prehospital noninvasive ventilation for acute respiratory failure: systematic review, network meta-analysis, and individual patient data meta-analysis. Academic emergency medicine : official journal of the Society for Academic Emergency Medicine. 21(9):960-70. 2014.

Primary outcome (mortality): Key results

  • CPAP reduced morality (OR=0.41; 95% credible interval [Crl] 0.20 to 0.77)
  • The effect of BiPAP on mortality was unclear (OR=1.94; 95% Crl = 0.65 to 6.14)

Secondary outcome (intubation):

  • CPAP reduced intubations (OR=0.32; 95% Crl 0.17 to 0.62)
  • The effect of BiPAP on intubation was unclear (OR=0.40; 95% Crl = 0.14 to 1.16)

The benefits of NIPPV for patients in acute respiratory failure are well documented. Also, NIPPV is likely to be most effective when introduced early. The evidence supporting at least CPAP from this study is encouraging but differences in outcomes between CPAP and BiPAP reflects more upon the lack of large RCTs rather than the actual clinical difference between them. Regardless, the cost of equipping ambulances with NIPPV gear has to be taken into consideration when assessing its effectiveness in the prehospital setting.

The patient is improving, but you still aren’t sure about the diagnosis. There might have been an elevated JVP, but her neck isn’t easy to examine. The lungs sound a little wheezy, but there were probably some fine crackles there as well. You are resigned on waiting for the chest x-ray, when your resident asks if lung ultrasound might help diagnose pulmonary edema.

Question #3 Accuracy of POCUS for Diagnosing Acute Heart Failure

What is the sensitivity and specificity of point of care ultrasound (POCUS) using B-lines in diagnosing acute cardiogenic pulmonary edema in patients presenting to the ED with acute dyspnea?

Al Deeb M, Barbic S, Featherstone R, Dankoff J, Barbic D. Point-of-care ultrasonography for the diagnosis of acute cardiogenic pulmonary edema in patients presenting with acute dyspnea: a systematic review and meta-analysis. Academic emergency medicine : official journal of the Society for Academic Emergency Medicine. 21(8):843-52. 2014.

They identified 7 studies that included a total of 1075 patients. Two of the studies were ED studies. The other 5 took place in the ICU, hospital wards, or prehospital environment.

Diagnostic characteristics:

  • Sensitivity of B lines of POCUS to diagnose acute pulmonary edema: 94% [95% CI: 81.3%, 98.3%]
  • Specificity of B lines of POCUS to diagnose acute pulmonary edema: 92% [95% CI: 84.2%, 96.4%]
  • Positive likelihood ratio 12.4 [95% CI: 5.7, 26.8]
  • Negative likelihood ratio 0.06 [95% CI: 0.02, 0.22]

The question asked in this review is relevant but as the authors admit, there is no standardized threshold for the diagnosis of acute cardiac pulmonary edema (ACPE) and no definitive gold standard. Like the first study reviewed in this BEEM Cases, this one was too heterogeneous. While this study was exhaustive in searching for ultrasound diagnostics performed at the bedside it was not restrictive in settings, patient demographics, or ultrasound training of provider and this would lead to heterogeneity. Another issue that contributes to the heterogeneity and challenges the validity of the results is the lack of standardization of the ultrasound exam: The identification of ACPE using B-lines via the Volpicelli method is dependent upon patient position as well as position duration.

The conclusion that B-line on ultrasound can confirm the diagnosis when the pretest probability of disease is high or low has little utility. Diagnostic tests are valuable when they can confirm or refute a diagnosis when the pretest probability is indeterminate.

Case Resolution…

The patient rapidly improves after being placed on BiPAP. Your bedside ultrasound was consistent with CHF, but understanding the limitations of the test you also ordered your traditional work-up including blood work, ECG, and chest x-ray. Within a few hours in the department, after treatment with nitroglycerin and furosemide, you are able to titrate down and then discontinue the positive pressure ventilation. On a repeat bedside ultrasound, the b-lines have disappeared. Combining the ultrasound findings with the remainder of your tests, and most importantly your clinical judgement and frequent reassessments of the patient, you diagnose her with an exacerbation of CHF and admit her to the medical team for monitoring and adjustment of her medications.

About the Author: Anton Helman

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Hi Anton, great post! Q # 1 – The majority of trials are on patients with either COPD exacerbation or ACPE. For these 2 categories, NPPV efficacy in terms of ETI reduction and mortality are okay. Bottom line 1: NPPV is first choice in ACPE or COPDex – Acute hypoxemic respiratory failure (except ACPE) is still controversial. Few positive RCTs on pneumonia (Confalonieri M goo.gl/K4EHZV, Brambilla AM goo.gl/uKKDpx, Cosentini R goo.gl/rReh7f), one recent positive RCT on ARDS (Patel BK oo.gl/lKNqkv). Bottom line2: NPPV for pneumonia –> 1. okay in the immunocompromised population, 2. In the immunocompetent population: early application, that is patient selection is the key (and short trial) – ARDS. Patient selection seems the key, however needs further confirmation – Asthma. Primum non nocere!

Q # 2 Pre-hospital NPPV modality of choice might be CPAP. 1.The majority of patients have AHF/ACPE, 2. easier to learn and carry, 3. cheaper

Q # 3 LUS is already in every acute dyspnoea algorythm (Lichtenstein blue protocol goo.gl/yEy6ug) When in doubt (pretest probability indeterminate) more useful if negative (SNOUT) than positive (SPIN), since interstitial syndrome might be due to other causes (pneumonia, ARDS, fibrosis)

Thanks again for your work Roberto

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Thanks for the excellent comment Roberto.

With regards to question one, I think you hit on the key issue. Acute respiratory failure is not a single condition, but actually a collection of many different conditions, and NIPPV might (and probably does) have different effects on different conditions. This is a large part of the BEEM focus on the heterogeneity of the underlying trials. Although not the focus of the paper, NIPPV clearly has an indication in COPD and CHF (as well as ARDS and post-extubation, but those are less relevant in the emergency department). There aren’t great studies in asthma, but I think the evidence favours NIPPV. I definitely use NIPPV early in severe asthma. I would not use NIPPV long term in pneumonia. However, I think the key take home for the emergency department, where we have undifferentiated patients, is that NIPPV seems to lower mortality overall, and should be started early while we work on determining the underlying cause of this patient’s respiratory distress.

With regards to pre-hospital NIPPV, ease of use and cost are definitely important issues. (I would also like to see more compatibility between prehospital equipment and inhospital equipment, both for cost and ease of patient care.) Unless we see large advantages to BiPAP, and I agree that CPAP probably makes the most sense for EMS. However, all of the questions are relatively complex. EMS agencies with longer transport time might benefit from BiPAP – although that assumption currently doesn’t have any evidence to back it up.

In terms of lung ultrasound, I will tell you I use it every shift. However, the widespread use of ultrasound and adoption into protocols does not mean that we are practicing evidenced based medicine. I think the numbers here (which are pretty consistent with all the studies I have seen, including that Lichtenstein paper) show that lung ultrasound is about as accurate for ruling in as it is for ruling out (sensitivity and specificity are both in the low to mid 90s). However, the studies that give us those number have a number of issues that could be inflating the accuracy. The diagnosis in many patients is obvious without ultrasound, and the patients who are less obvious clinically are also less obvious on ultrasound. I love ultrasound an will continue to use it, with the caveat that in the initially undifferentiated patient (pretrest probability of 50%), the numbers reported for ultrasound don’t get be above a 95% post test probability if positive, nor do they get me under a 5% post test probability if negative, so I am am constantly aware that my ultrasound diagnosis might be wrong.

Cheers Justin

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  • Breathe (Sheff)
  • v.17(1); 2021 Mar

Logo of breathe

A case of hypercapnic respiratory failure

Julie van woensel.

1 Dept of Pulmonology, Zuyderland Medical Center, Heerlen/Sittard, The Netherlands

Pieter Goeminne

2 Dept of pulmonology, AZ Nikolaas Hospital, Sint-Niklaas, Belgium

Yvan Valcke

Associated data.

Please note: supplementary material is not edited by the Editorial Office, and is uploaded as it has been supplied by the author.

Supplementary audio EDU-0217-2020.SUPPLEMENT1

Supplementary video EDU-0217-2020.SUPPLEMENT2

A 55-year-old man was referred to the department of respiratory disease with a polycythaemia. Underlying haematological disease was already excluded. Blood results are shown in table 1.

Short abstract

A systematic work-up is important in case of hypercapnia. Pay attention to the shape of the flow–volume curve and any abnormal breathing sounds. In case of stridor, vocal cord paralysis should be suspected and, if confirmed, neurological investigations are advised. https://bit.ly/34APMi8

A 55-year-old man was referred to the department of respiratory disease with a polycythaemia. Underlying haematological disease was already excluded. Blood results are shown in table 1 . The patient complained of exertional dyspnoea, asthenia and intermittent daytime sleepiness. He did not experience headaches or dizziness. Heteroanamnesis revealed that that patient snored heavily without the presence of apnoeas. He had a history of nephrolithiasis, hypertension and diverticulitis, and he was a former smoker, accumulating a total of 12 pack-years. He did not use alcohol or drugs. His medication consisted of a proton pump inhibitor, an antihistaminic and aspirin.

Table 1

Laboratory results for the patient

Lung auscultation revealed normal breathing sounds. In particular, no stridor was present in the upright position. There were no signs of cardiac decompensation or cardiac murmurs. The body mass index of the patient was 28 kg·m −2 .

A chest radiograph was performed which did not show any significant findings ( figure 1 ). Arterial blood gas analysis (ABG) revealed a severe hypoxaemia with combined hypercapnia ( table 2 ). The normal pH indicates a chronic hypercapnia with metabolic compensation.

An external file that holds a picture, illustration, etc.
Object name is EDU-0217-2020.01.jpg

Radiograph of the thorax.

Table 2

ABG analysis of the patient

P CO 2 : carbon dioxide tension; P O 2 : oxygen tension.

What is the most likely mechanism of hypoxaemia in this patient?

  • a) Diffusion limitation
  • c) Alveolar ventilation ( V ʹ A )/perfusion ( Q ʹ) mismatch
  • d) Hypoventilation

d. Hypoventilation.

Table 3 explains the five pathophysiological mechanisms causing hypoxaemia. In this case, two parameters are pivotal to determine the underlying mechanism. First, hypercapnia indicates hypoventilation ( figure 2 ) [ 1 ]. The other causes do not explain this finding. Secondly, the alveolar–arterial gradient (A–a gradient) is often essential in the differential diagnosis of hypoxaemia ( table 3 ) [ 1 , 2 ]. The A–a gradient is the difference between the alveolar oxygen pressure and the arterial oxygen pressure ( P AO 2 – P aO 2 ). P AO 2 is calculated using the alveolar gas equation:

An external file that holds a picture, illustration, etc.
Object name is EDU-0217-2020.02.jpg

Relationship between V ʹ A and partial pressure of oxygen (red line) and carbon dioxide (blue line). P ACO 2 : alveolar carbon dioxide tension. Reproduced from [ 1 ], with permission.

Table 3

Pathophysiological mechanisms and related causes of hypoxaemia

P IO 2 : inspired oxygen tension; P AO 2 : alveolar oxygen tension; P aO 2 : arterial oxygen tension; P A–aO 2 : alveolar–arterial oxygen tension difference; AV: arteriovenous; CNS: central nervous system.

( P atm − P H 2 O )· F IO 2 − P aCO 2 /RQ”.

P atm is the atmospheric pressure (at sea level 101.33 kPa), P H 2 O is the partial pressure of water (∼6 kPa), F IO 2 is the fraction of inspired oxygen (0.21), P aCO 2 is the arterial carbon dioxide tension and RQ is the respiratory quotient (value is around 0.82 for human diet). The A–a gradient is not a steady state. A physiological A–a gradient exists due to a physiological ventilation–perfusion mismatch and changes based on a patient's age. The expected A–a gradient can be calculated by the formula: Age+10/4 [ 2 , 3 ].

This patient has a calculated A–a gradient of 1.53 kPa, which is not elevated given the age adjusted reference value of 2 kPa.

The hypercapnia and normal A–a gradient therefore indicate that the cause of his hypoxaemia is hypoventilation.

Next, the patient performed lung function tests ( figure 3 ).

An external file that holds a picture, illustration, etc.
Object name is EDU-0217-2020.03.jpg

Lung function tests of the patient. LLN: lower limit of normal, for spirometry values as the fifth percentile of the distribution of the standard deviation score; VC: vital capacity, FVC: forced vital capacity; FEV 1 : forced expiratory volume in 1 s; TLC: total lung capacity; RV: residual volume; D LCO : diffusing capacity of the lung for carbon monoxide; K CO: transfer coefficient of the lung for carbon monoxide.

Which one of the following disorders is most likely to be the cause of hypoventilation in our patient?

  • b) Variable extrathoracic airway obstruction
  • c) Neuromuscular disease
  • d) Drug-induced hypoventilation
  • e) Obesity hypoventilation syndrome

b. Variable extrathoracic airway obstruction.

The key to this answer is the flow–volume curve of the spirometry. There is an inspiratory airflow plateau while the expiratory part is normal, suggesting a variable extrathoracic airway obstruction [ 4 , 5 ]. The static and dynamic lung volumes are above the lower limit of normal, excluding COPD and neuromuscular diseases. His body mass index is compatible with overweight but not obesity and he does not use medication which suppresses respiration.

Which examination will you request next?

  • a) Otorhinolaryngological (ORL) examination
  • b) Cardiac evaluation
  • c) Measurement of the fraction exhaled nitric oxide
  • d) Lung scintigraphy

a. ORL examination.

When a flow–volume curve suggests an extrathoracic airway obstruction, an ORL evaluation with endoscopy of the upper airways should be prompted. The sound in the audio fragment is suggestive for an inspiratory stridor, also indicating an obstruction in the upper airway.

A computed tomography scan excluded a mass in the neck or mediastinum as a possible cause of the extrathoracic airway obstruction. During a second visit to the clinic, the patients partner presented a recording of the sleep related sound (see supplementary material audio fragment ).

The patient was referred to an ORL specialist. A video fragment of the laryngoscopy is included in the supplementary material .

Because of the daytime sleepiness, the hypercapnia and the nocturnal stridor, the respiratory physician requested a polysomnography (PSG). This revealed a complex sleep apnoea syndrome with an apnoea–hypopnoea index (AHI) of 25.7 events·h −1 sleep. Mainly obstructive hypopnoeas with also a high amount of central apnoeas were registered. Furthermore, it revealed a decreased sleep efficiency with many arousals. The arousal index was 24.1 events·h −1 sleep. His oxygen saturation was remarkably low during the whole registration, with an average saturation of 73.6% (maximum 89.9%, minimum 61.2%). No clear relationship existed between the oxygen saturation and the sleep stages or respiratory events. The oxygen desaturation index (ODI) was 64.1 ( figures 4 and ​ and5 5 ).

An external file that holds a picture, illustration, etc.
Object name is EDU-0217-2020.04.jpg

PSG of the patient. a) Registration of the respiratory events and AHI. b) Hypnogram with the different sleep stadia, oxygen saturation and body position. OAHI: obstructive apnoea–hypopnoea index; OAI: obstructive apnoea index; CAHI: central apnoea–hypopnoea index; HYPNO: hypnogram; A: awake; R: REM (rapid eye movement) sleep; 1–4: sleep stage 1–4; S AO 2 : oxygen saturation; POS: body position; BUK: abdominal position; RUG: back position; LNK: left side position; REC: right side position.

An external file that holds a picture, illustration, etc.
Object name is EDU-0217-2020.05.jpg

PSG of the patient. Three selected 5-min parts of the PSG record. VTH: thoracal movements; VAB: abdominal movements; NAF1: oronasal flow measured with temperature gradient; NAF2P: oronasal flow measured with pressure gradient; PHONO: sound recording (stridor in this case); EMG: electromyogram of the chin and jaw muscles; CenA: central apnoea; ObsA: obstructive apnoea; ObsH: obstructive hypopnoea; ArApn: arousal after apnoea.

What is your next step keeping all of the above results in mind?

  • a) Starting positive airway pressure therapy without further investigation
  • b) Steroid therapy
  • c) Watchful waiting
  • d) Neurological examination with magnetic resonance imaging (MRI) of the brain and neck

d. Neurological examination with MRI of the brain and neck

Laryngoscopy showed bilateral vocal cord paralysis (VCP) and is probably the cause of the obstructive sleep pattern. However, it does not explain the central apnoeas that were registered. Literature suggests that 20–25% of VCP cases result from a neurological disorder [ 6 , 7 ]. Thus, further neurological examination is warranted. In patients with sleep apnoea and suspicion of an underlying causative disorder, the diagnosis and treatment of this disorder has priority.

In this case, continuous positive airway pressure (CPAP) therapy was started because of the symptoms, the mixed respiratory failure and the ODI. At the same time, our patient was referred for further neurological analysis. Based on clinical neurological examination and electroneuromyography, motor neurone disease was excluded. Initial brain and cervical MRI appeared normal, but after revision by a second radiologist the sagittal plane of the cervical MRI was protocolled as abnormal with a protrusion of the cerebellar tonsils in the foramen magnum and a syringomyelic cavity involving C2. These findings are pathognomonic for a Chiari malformation type 1 (CM1) ( figure 6 ).

An external file that holds a picture, illustration, etc.
Object name is EDU-0217-2020.06.jpg

Chiari malformation type I diagnosed by a cervical MRI (sagittal plane, T1 sequence). The white arrow indicates the protrusion of the cerebellar tonsils into the upper spinal canal (black arrow). Black asterisk: medulla oblongata; white asterisk: spinal cord.

The patient was diagnosed with CM1, with a subsequent bilateral VCP combined with a sleep-relating breathing disorder (SRBD). The therapeutic advice from a tertiary centre was to perform a posterior fossa decompression (PFD) followed by an arytenoidectomy.

What is your preoperative advice as a pulmonologist to the neurosurgeon?

  • a) Preoperative therapy with steroids
  • b) Consult the ORL specialist about placing a tracheostomy preoperatively
  • c) Post-operative bronchodilatation therapy
  • d) Post-operative tracheostomy and invasive ventilation

b. Consult the ORL specialist about placing a tracheostomy preoperatively.

Securing the airway by a tracheostomy or other local techniques prior to brain surgery is recommended in patients with a VCP due to CM1. This recommendation is based on data from case series, retrospective studies and expert opinions [ 7 , 8 ].

After the PFD, the degree and time of improvement of the VCP is variable and not predictable. Available literature shows that only 50% of the cases with bilateral VCP resolves completely after brain surgery. In some cases, the paralysis does even not improve after 1 year. The risk of irreversible damage is higher in adult patients than in children [ 7 , 8 ]. Thus, these patients have a high risk of acute respiratory failure after extubating if the airway is not secured.

Our patient received decompressive brain surgery first. After extubating, the patient developed acute respiratory failure caused by a combination of residual vocal cord palsy and laryngeal oedema. A tracheostomy was placed immediately, after which his condition was stable. He was then transferred to a tertiary centre for laryngeal surgery.

This case represents a rare presentation of CM1, with a chronic mixed respiratory failure, a bilateral VCP and a SRBD.

The exercise related dyspnoea and sleep-related symptoms were the sole presenting signs in our case, whereas in adults, the most common presenting symptoms are headache, vertigo and neurological deficits [ 9 , 10 ]. M assimi et al. [ 10 ] reported cases with CM1 with acute onset events, including respiratory failure within 48 h. They reported seven adult cases (age ranging from 32 to 58 years with a median of 38 years). An additional literature search revealed a further 18 reported cases with acute and chronic hypercapnic respiratory failure.

The underlying pathophysiology of hypercapnic respiratory failure in CM1 is multifactorial. CM1 can cause cranial-nerve dysfunction by a stretch or compressive effect. This can lead to damage to afferent connections from the chemoreceptors in the carotid bodies to the medulla respiratory centres, with subsequent reduced response to hypercapnia [ 10 , 11 ]. Furthermore, central sleep apnoea (CSA) in patients with CM can lead to hypercapnic respiratory failure. To a lesser extent, airway obstruction ( e.g. due to impaired muscle function or VCP) may also contribute to the development of hypercapnia.

In this case, all of the above mechanisms are present. The hypercapnic respiratory failure is mainly caused by the CSA events and central hypoventilation. The airway obstruction and obstructive sleep apnoea (OSA) probably play a minor role considering the moderate level of the AHI.

The association between CM and SRBD has been reported in case reports, retrospective and prospective studies [ 9 , 12 – 16 ]. They report a prevalence of SRBD in adults with CM1 ranging from 50 to 75% [ 9 , 12 – 16 ]. Mainly OSA and mixed sleep apnoea have been described in these cases. The prevalence of CSA and hypoventilation in these cases is less frequent [ 9 , 13 – 16 ]. One study reported a prevalence of 57.6% for OSA and 15.4% for CSA in adults. The frequency of OSA significantly increased in older age groups [ 13 ].

Given the high prevalence of SRBD in CM, experts recommend a routine screening with a PSG in these patients, regardless of the presence of symptoms [ 7 ,  9 , 13 ]. It is questioned whether all patients with SRBD should be screened for CM with a brain MRI. No recommendations exist on this theme. There are no distinct patterns of sleep apnoea that would suggest a CM1. Possible indications for screening are treatment failure, CSA in children and CSA in adults without other risk factors [ 9 , 13 ].

The exact cause of OSA and CSA in CM1 is unclear. In our case the OSA was mostly caused by the VCP. Although, hypothetically, a CM1 can directly lead to airway obstruction by compression of cranial nerves 9 and 10. These nerves innervate the pharyngeal and laryngeal muscles. An impaired function will cause an upper airway collapse, especially during sleep when the tone of the upper airway muscles is already physiologically decreased [ 9 ]. Several mechanisms are proposed for the origin of central apnoeas: compression of the medulla oblongata could cause a dysfunction of the respiratory centre, possibly through an ischaemic lesion; the afferent signal from the chemoreceptors in the carotid bodies to the medulla could be disturbed due to stretching of nerve 9 [ 9 , 11 , 12 ]. Obstructive sleep events may also trigger central apnoeas. One study showed a predictive value for VCP in CSA [ 12 ].

In patients with CM1 and SRBD, the treatment of choice is decompressive brain surgery to relieve the underlying cause [ 9 ]. However, in most cases, the SRBD is diagnosed prior to the CM and ventilation therapy is initiated before surgery [ 17 – 19 ].

In our patient CPAP therapy was also started preoperatively before the diagnosis of CM was clear. The decision to initiate ventilation was based on his symptoms and respiratory failure with a high ODI. In retrospect, preoperative ventilation was not needed in our case as his respiratory failure was compensated and the underlying cause could be managed. However, preoperative ventilation should be started in patients with severe symptoms and decompensated respiratory failure as a bridge to surgery. This recommendation is based on case reports and expert opinion [ 9 , 11 ]. Two case reports demonstrate a superior effect from bilevel positive airway pressure over CPAP in patients with CM with combined CSA and OSA [ 17 , 18 ].

The response of SRBD on decompressive brain surgery is variable [ 9 ]. Several studies have documented definite improvement of sleep apnoea after PFD, objectified with a PSG [ 12 , 13 , 17 , 18 ]. However, cases with residual or recurrent sleep apnoea, especially CSA, are reported [ 12 , 19 , 20 ].

Importantly, post-operative awareness for respiratory failure due to residual sleep apnoea and/or residual VCP should be high in patients with CM1.

The post-operative acute respiratory failure in our patient was explained by laryngeal oedema post-intubation in combination with residual VCP. This was documented by an upper airway endoscopy at the intensive care unit. This event illustrates the importance of securing the airway prior to decompressive brain surgery. After a temporal tracheostomy followed by an arytenoidectomy, his symptoms improved. Not only the nocturnal stridor resolved, but also the daytime sleepiness and dyspnoea. A post-operative ABG ( table 4 ) did not show any residual respiratory insufficiency.

Table 4

A post-operative ABG analysis with tracheostomy

Further research is warranted to determine the optimal timing of surgery and post-operative followup with PSG in patients with CM and SRBD.

This case illustrates a stepwise approach towards patients with chronic hypercapnic respiratory failure. Asking the patient about sleep-related symptoms, breathing sounds and medication use is essential. Evaluation of the flow–volume curve shape is key as it can reveal important information about the airways. VCP is a possible cause of an extrathoracic obstruction and obstructive sleep apnoea. In case of a documented VCP, a neurological cause should be excluded.

Supplementary material

Acknowledgments.

We thank K. Strobbe, respiratory physician at AZ Nikolaas hospital, Sint Niklaas, Belgium, for providing the polysomnography and helping with its interpretation; A. Otte, respiratory physician at Zuyderland medical center, Heerlen, The Netherlands, for a second revision of the polysomnography; and M. van der Steege, English teacher, for revising the English writing style.

This article has supplementary material available from breathe.ersjournals.com

Conflict of interest: J. Van Woensel has nothing to disclose.

Conflict of interest: P. Goeminne has nothing to disclose.

Conflict of interest: Y. Valcke has nothing to disclose.

  • Case Report
  • Open access
  • Published: 04 January 2024

Chronic COVID-19 infection in an immunosuppressed patient shows changes in lineage over time: a case report

  • Sheridan J. C. Baker 1 , 2 , 3 , 4 ,
  • Landry E. Nfonsam 5 , 6 ,
  • Daniela Leto 5 , 6 ,
  • Candy Rutherford 4 ,
  • Marek Smieja 2 , 4 , 5 , 6 &
  • Andrew G. McArthur 1 , 2 , 3  

Virology Journal volume  21 , Article number:  8 ( 2024 ) Cite this article

Metrics details

The COVID-19 pandemic, caused by the Severe Acute Respiratory Syndrome Coronavirus 2 virus, emerged in late 2019 and spready globally. Many effects of infection with this pathogen are still unknown, with both chronic and repeated COVID-19 infection producing novel pathologies.

Case presentation

An immunocompromised patient presented with chronic COVID-19 infection. The patient had history of Hodgkin’s lymphoma, treated with chemotherapy and stem cell transplant. During the course of their treatment, eleven respiratory samples from the patient were analyzed by whole-genome sequencing followed by lineage identification. Whole-genome sequencing of the virus present in the patient over time revealed that the patient at various timepoints harboured three different lineages of the virus. The patient was initially infected with the B.1.1.176 lineage before coinfection with BA.1. When the patient was coinfected with both B.1.1.176 and BA.1, the viral populations were found in approximately equal proportions within the patient based on sequencing read abundance. Upon further sampling, the lineage present within the patient during the final two timepoints was found to be BA.2.9. The patient eventually developed respiratory failure and died.

Conclusions

This case study shows an example of the changes that can happen within an immunocompromised patient who is infected with COVID-19 multiple times. Furthermore, this case demonstrates how simultaneous coinfection with two lineages of COVID-19 can lead to unclear lineage assignment by standard methods, which are resolved by further investigation. When analyzing chronic COVID-19 infection and reinfection cases, care must be taken to properly identify the lineages of the virus present.

A patient repeatedly tested positive for COVID-19 over 16 months.

Infection progressed from one lineage to coinfection with a second lineage, before clearance of coinfection and reinfection with a third, different lineage.

Coinfection was difficult to identify through genomic methods.

Coronavirus disease 2019 (COVID-19) is caused by Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2). As of October 22, 2023, over 771 million cases have been reported worldwide with over 6.9 million deaths as a result of COVID-19 [ 1 ]. SARS-CoV-2 primarily enters host cells by binding of its spike (S) protein to human cell-surface angiotensin-converting enzyme 2 (ACE2) receptors [ 2 , 3 ]. SARS-CoV-2 is a positive-sense, single-stranded RNA virus, with a genome 29–30 kB in size, organized as methyl-capped-5″UTR-ORF1a/b-S-ORF3-E-M-ORF6-ORF7a/b-ORF8-N/ORF9b-ORF9c-ORF10-3’UTR-poly-A-tail [ 4 , 5 , 6 ]. The S, E, M, and N genes encode key structural proteins found in the mature virion—the Spike, Envelope, Membrane, and Nucleocapsid structures respectively [ 7 ]. COVID-19 primarily affects the respiratory tract, and manifests as an acute upper and/or lower respiratory syndrome that can vary in severity [ 8 ]. The disease can result in asymptomatic viral shedding, or symptomatic disease associated with fever, cough, fatigue, myalgia, arthralgia, rhinorrhea, sore throat, and conjunctivitis [ 8 , 9 , 10 ]. However, the disease can also progress to more severe outcomes, including persistent fever, hemoptysis, hypoxia, chest discomfort and/or pain, respiratory failure, and multiorgan failure [ 9 , 10 ]. Impairment of smell and/or taste is also a common symptom of COVID-19 [ 11 ]. Typical, non-chronic, mild and moderate cases of COVID-19 are usually associated with improvement of symptoms about 10 days after onset of symptoms, though in rare cases the infection for persist for a number of weeks, known as chronic or long COVID-19 when symptoms last longer than 3 weeks [ 12 , 13 ]. While the body of work surrounding comorbidities for COVID-19 infection remains large, relatively less information is available regarding potential comorbidities and risk factors for chronic COVID-19 infection or COVID-19 reinfection (a new COVID-19 infection unrelated to the previous infection) [ 14 , 15 ], both of which were seen in this case. Changes in lineage (when a patient initially is found to be infected with a certain lineage, and a second, later test identifies infection by a new, distinct lineage) is often indicative of reinfection rather than within-host evolution [ 15 , 16 ]. There remains a limited number of reports detailing cases of chronic COVID-19 infection and/or repeated infection. We present a chronic infection followed by reinfection, over a 16-month period, in a severely immunocompromised patient.

Initial diagnosis and treatment

A male, in his early fifties, and heavily immunosuppressed with history of Hodgkin’s lymphoma (HL) was initially treated with ABVD (doxorubicin, bleomycin, vinblastine, and dacarbazine) chemotherapy, and later, GDP (gemcitabine, dexamethasone, and cisplatin) chemotherapy, followed by autologous stem cell transplant (SCT) for relapsed HL one-year post-completion of initial chemotherapy. The patient was maintained on the CD30 antibody–drug conjugate Brentuximab until he was noted to again have HL disease progression, for which he underwent an allogeneic SCT 1.5 years post-autologous transplant. His post-transplant course was complicated by Epstein–Barr Virus (EBV) reactivation and associated post-transplant lymphoproliferative disorder (PTLD), requiring repeated courses of rituximab (twelve doses overall) and graft versus host disease (GVHD) of the skin, gut, and possibly lung, requiring multiple doses of prednisone.

The first episode of COVID-19 infection was one-month post-allogeneic SCT, prior to the diagnosis of PTLD. There were no other microbiological findings in the patient’s lungs. Shortly thereafter, the patient required rituximab for EBV reactivation, followed by recurrent episodes of EBV reactivation and CT-confirmed PTLD, leading to further courses of rituximab. Initial presenting symptoms of COVID-19 were mild upper respiratory tract infection (URTI) symptoms, and Bamlanivimab was received. However, four months after the initial infection, the patient was admitted to hospital with progressive cough and shortness of breath. Upon admission, the patient again tested positive for COVID-19. Treatment included Remdesivir, dexamethasone, and Bamlanivimab with good response. Six months later, the patient developed a progressive chronic cough and was eventually hospitalized (fourteen months after the initial COVID-19 infection) with shortness of breath and new diffuse bilateral lung consolidations. This admission, treatment included sotrovimab along with another course of remdesivir and dexamethasone. Despite initial improvement in respiratory status, the patient developed worsening renal dysfunction and shortness of breath along with progressive lung infiltrates, leading to respiratory failure and ultimately death. Pulmonary issues were multifactorial, including chronic COVID-19 infection, possible lung GVHD, and cardio-renal syndrome. The timeline of COVID-19 lineages, disease symptoms, and treatments received is summarized in Table  1 .

Genetic profiling

From March 2021 to June 2022, eleven samples from the patient were amplified for SARS-CoV-2 using the ARTIC V3 or ARTIC V4 protocol as outlined in Nasir et al. 2020 [ 17 ] and sequenced using an Illumina NextSeq platform. After sequencing, FASTQ files were analyzed via FastQC [ 18 ], barcode and adaptor sequences were removed using Trimmomatic [ 19 ], and SPAdes [ 20 ] was used to assemble genomes. The resulting genomes were analyzed using the SARS-CoV-2 Illumina GeNome Assembly Line (SIGNAL) pipeline ( https://github.com/jaleezyy/covid-19-signal ). After lineage assignment by Phylogenetic Assignment of Named Global Outbreak Lineages (PANGOLIN; github.com/cov-lineages/pangolin) within the SIGNAL workflow, mutation profiles and minor variants within samples were determined using breseq [ 21 ]. The most prevalent lineages in Ontario at the timepoints the patient was sampled were determined using VirusSeq Public Health of Ontario data (virusseq-dataportal.ca/explorer). Canonical sequences for the Alpha, Delta, and Omicron variants of SARS-CoV-2 and the most prevalent lineages at the time of patient samplings were downloaded from the NCBI Virus SARS-CoV-2 Data Hub ( https://www.ncbi.nlm.nih.gov/labs/virus/vssi ). Using these sequences, a maximum-likelihood phylogenetic tree was constructed by first carrying out single-nucleotide polymorphism (SNP) analysis using Parsnp [ 22 ] followed by maximum-likelihood phylogenetic tree construction using the RAxML-HPC BlackBox platform with the GTRGAMMA + I substitution model and automatic bootstrapping [ 23 ].

Lineages of patient samples, approximate dates of sampling and prevalence rates for patient lineages and most common lineages in Ontario at the time of patient samplings are shown in Table  2 , and a phylogenetic tree containing canonical Alpha, Delta, and Omicron samples, the patient samples, and the most prevalent circulating strains over time in Ontario is shown in Fig.  1 . Of the first eight sequenced samples, all characteristic mutations of B.1.1.176 were present with the exception of four mutations that were consistently missing in all samples. These missing mutations were L3674 in ORF1a, R203K and G204N in N, and S84LO in ORF8. There were also 10 mutations present in all eight samples that were not characteristic of B.1.1.176. These were C→T at position 241 of the genome in an intergenic region; a 3 bp deletion in ORF1; L642F, P1950L, K2029N, and N2603S in ORF1ab; C→T in the intergenic region between S and ORF3; L95F in ORF3a; a 3 bp change to AAC in N; and G→T in the intergenic region after ORF10. There were also five mutations present in the first four or five samples that were not present in samples six through eight. Present in the first four samples were S6096G in ORF1ab, T307I in S, and N269T in N; present in the first five samples were E484A and Y1155H in S. These mutations decreased in prevalence across time before not being identified in samples five or six. There were also five mutations that were gained across time, not being present in sample 7 and present in nearly 100% of reads in sample 8: a 15 bp deletion in ORF1ab, A5376V in ORF1ab, F490L and S494P in S, and T271I in N.

figure 1

Maximum-likelihood phylogenetic tree showing SARS-CoV-2 reference sequence (MN908947.3), an Alpha lineage (B.1.1.7), a Delta lineage (B.1.617.2) and two Omicron lineages (B.1.1.529 and XBB.1.5), as well as the most prevalent lineages in Ontario at the times the patient was sampled (B.1.1.7, AY.74, BA.2, and BA.2.12.1). Bootstrap values are shown at the nodes

The next sample in the series (sample 9) was initially not assigned a lineage; however, breseq analysis revealed an infection that was a mix of B.1.1.176 and BA.1 at proportions of approximately 50% each. Mutations that were present in samples 1–8 but lost in sample 9 are shown in Table  3 , while mutations that were first present in sample 9 are shown in Table  4 . There were four nonsynonymous mutations present in 100% of reads in samples 1–9: C→T in the intergenic region before ORF1ab (a mutation characteristic of neither lineage), a 6 bp deletion in ORF1ab (characteristic of both B.1.1.176 and BA.1), P4715L in ORF1ab (characteristic of both B.1.1.176 and BA.1), and D614G in S (characteristic of only B.1.1.176). There were 13 nonsynonymous mutations present in samples 1–8 that were present in less than 40% of reads in sample 9 (referred to as lost mutations) and 43 nonsynonymous mutations that were present in greater than 40% of reads in sample 9 after not being present in the first 8 samples (referred to as gained mutations). These are shown in Tables  1 and 2 respectively. Of note for the gained mutations is the mutation S371F in S, which is not characteristic of either B.1.1.176 or BA.1, however the mutation S371L is characteristic of BA.1. There were also 11 nonsynonymous mutations that were not present in sample 1, appeared in some of samples 2–8, and were not present in sample 9, or were present in the intermediate samples, lost, and then reappeared in sample 9. These are shown in Table  5 and are referred to as fleeting mutations.

While sample 9 appeared to be a mixed infection of B.1.1.176 and BA.1, samples 10 and 11 were both assigned the lineage of BA.2.9, with 50 of 56 nonsynonymous mutations characteristic of BA.2.9. The mutations not characteristic of BA.2.9 (Table  6 ) were A5620S in ORF1ab, a 3 bp change to CTC in ORF6, C→T in the intergenic region between ORF7a and ORF8, A→T in the intergenic region between ORF8 and N, a 3 bp change to AAC in N, and a 26 bp deletion in the intergenic region after ORF10. Yet, samples 9 and 10 were missing 5 characteristic mutations of BA.2.9: L24S in S, D61L in ORF6, S84L in ORF8, and R203K and G204R in N.

There were four mutations present in all 11 samples that were identified in 100% of reads: P4715L in ORF1ab and D614G in S (both of which are found in all three of B.1.1.176, BA.1, and BA.2.9), C→T in the intergenic region before ORF1a, and a 3 bp change to AAC in N. The latter two mutations are not characteristic of any of B.1.1.176, BA.1, or BA.2.9.

Several previous studies have identified cancer, and specifically hematologic cancers, as a comorbidity that worsens the health outcomes of those infected with respiratory infections such as COVID-19 [ 24 , 25 , 26 ]. One case report by Yonal-Hindilerden et al. reported on a patient with Hodgkin’s lymphoma who additionally contracted COVID-19. This patient experienced severe respiratory disease, eventually succumbing to COVID-19 10 days after hospital admission [ 27 ]. A second study reported on a patient with Hodgkin’s lymphoma showed reinfection with COVID-19 34 days after clearance of their initial infection [ 28 ]. However, neither of these two studies performed whole genome sequencing to assess any lineage changes in the viral infection present in the patients.

One 2021 study found that 0.47% of COVID-19 patients were incidences of reinfection [ 29 ]. Of these patients that were reinfected, the majority (67%) were reinfected with a different genomic variant than their original infection [ 29 ], as was seen in the present case. The likelihood that the three observed lineages represent within-host evolution is extremely low as B.1.1.176 and BA.1 are evolutionary very distant, with BA.1 and BA.2.9 also being genetically distinct. Another study reported on a chronic SARS-CoV-2 infection lasting over 400 days, with a SARS-CoV-2 mutation rate approximately two-fold higher than the global SARS-CoV-2 evolutionary rate [ 30 ]. This study also reported the presence over time of three genetically distinct genotypes within the patient, representing three different viral populations originating from different physical locations within the patient that continually migrated into the nasopharynx [ 30 ]. This is contrasted with the present study, where mixed infection only appears in sample 9, where the lineages B.1.1.176 and BA.1 appeared to both be present in the nasopharynx. By the next sample in the series, the lineage BA.2.9 appeared to make up 100% of the viral particles sequenced from the nasopharynx.

Immunocompromised patients are at a higher risk of chronic infection, likely due to their B-cell depleted state [ 31 , 32 , 33 ], as B-cells play a large role in protective immunity against SARS-CoV-19 [ 34 ]. The changes in viral lineage over time may have been associated with a poor health outcome in this patient, as Omicron lineages (BA.1 and BA.2) are associated with higher infectivity and immune escape compared to B.1.1.176 (an Alpha lineage) [ 35 , 36 , 37 , 38 ]. Additionally, Omicron lineages are associated with a higher risk of reinfection [ 39 ]. Further complicating the progression from an Alpha COVID-19 infection to two latter Omicron infections was the immunocompromised status of the patient, which has been found to be associated with severe clinical outcomes in COVID-19 infections [ 40 ]. Cancer patients are classified as a population at high-risk for poor health outcomes in COVID-19 infections due to their immunosuppressive state, with COVID-19 symptoms often more severe in this population [ 41 , 42 , 43 ]. Again compounding this risk factor in this patient was the fact that they received SCT, another factor which increases the risk of COVID-19 morbidity and mortality [ 44 , 45 ]. Various studies have shown that due to their immunocompromised state, these patients are at risk for reinfection [ 46 , 47 ], with one study finding that an immunocompromised patient had a higher viral load than a comparable healthy individual [ 48 ].

It has been well characterized that immunocompromised individuals are at a higher risk of developing a chronic SARS-CoV-2 infection [ 49 , 50 , 51 , 52 , 53 , 54 ]. The present study reports a patient that was initially infected with B.1.1.176, which persisted for fifteen months, before subsequent additional infection with BA.1. When resampled one month later, the patient had apparently cleared the B.1.1.176 and BA.1 infections and had been reinfected again, this time with BA.2.9. This case thus represents incidences of chronic infection, mixed infection, as well as independent COVID-19 reinfection. The results of this case study highlight the need to closely monitor those patients that are both infected with COVID-19 and are in an immunocompromised state. To our knowledge, this case study represents one of the longest chronic COVID infections combined with reinfection in an immunocompromised patient.

Abbreviations

Coronavirus disease 2019

Severe acute respiratory syndrome coronavirus 2

Angiotensin converting enzyme 2

Envelope gene

Membrane gene

Nucleocapsid gene

  • Hodgkin’s lymphoma

Doxorubicin, bleomycin, vinblastine, and dacarbazine

Gemcitabine, dexamethasone, and cisplatin

Stem cell transplant

Single-nucleotide polymorphism

Epstein–Barr virus

Post-transplant lymphoproliferative disorder

Graft versus host disease

SARS-CoV-2 Illumina GeNome Assembly Line

Phylogenetic assignment of named global outbreak lineages

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Acknowledgements

We thank all St. Joseph’s Healthcare staff who took part in the care of the patient.

This work was supported by Public Health Ontario, by Genome Canada CanCOGeN funding; by McMaster University’s COVID-19 Research Fund; and a David Braley Chair in Computational Biology to AGM. Computational support was provided by the McMaster Service Lab and Repository computing cluster, supplemented by hardware donations and loans from Cisco Systems Canada; Hewlett Packard Enterprise; and Pure Storage.

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Baker, S.J.C., Nfonsam, L.E., Leto, D. et al. Chronic COVID-19 infection in an immunosuppressed patient shows changes in lineage over time: a case report. Virol J 21 , 8 (2024). https://doi.org/10.1186/s12985-023-02278-7

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Experts say a pneumonia outbreak among children in Ohio and a cluster of pneumonia cases in China are unrelated, despite some social media posts and tabloid articles that have ambiguously linked the two.

The usual respiratory pathogens are making their rounds this cold and flu season, yet the specter of the pandemic has left many on alert for the next novel agent.

“I understand outbreaks in China can make people nervous, but this is not that,” says Paul Offit , an infectious disease physician at Children’s Hospital of Philadelphia. Although another global illness may emerge in the future, the current pneumonia reports are “nothing to worry about,” he adds.

Many pathogens that circulate in the Northern Hemisphere’s winter and year-round—including flu, respiratory syncytial virus (RSV) and now COVID—are far from benign and can lead to pneumonia in some cases. But experts say there is no reason to panic or interpret the current uptick in illnesses as anything other than the typical circulation of respiratory viruses and bacteria.

These are “just everyday pathogens that normally increase during the winter having a somewhat early and very assertive increase at the present time,” says William Schaffner , an infectious disease physician and a professor at Vanderbilt University Medical Center. But people are not helpless against these germs, says Rama Thyagarajan , an infectious disease and internal medicine physician at the University of Texas at Austin Dell Medical School. COVID, the flu and RSV all have vaccines that can reduce the risk of pneumonia, she says.

Schaffner agrees, calling these immunizations “the best present you can give in this holiday season to yourself and to your family and to your neighbors.”

Here’s what to know about the recent reports of pneumonia and the term “white lung pneumonia,” which has been used in some news coverage to describe the uptick in cases.

What clusters of pneumonia cases are being reported?

Warren County, Ohio’s public health department, which serves the northeastern suburbs of Cincinnati, reported a large uptick in the number of typical pneumonia cases in children, with 145 cases in those three to 14 years old recorded as of November 29. Massachusetts has also reported an increase in RSV and “walking pneumonia” among children.

Earlier in November China had reported an increase in respiratory disease cases. Chinese health officials attributed this uptick to the lift of COVID restrictions and the usual rise in known pathogens that can also make people vulnerable to pneumonia, including flu, COVID, RSV and infections caused by the common bacterium  Mycoplasma pneumoniae . The World Health Organization is monitoring those cases, as well as an increase in pediatric respiratory disease cases in northern China.

Meanwhile multiple countries in Europe have also reported a rise in pediatric pneumonia cases, many of which are also caused by Mycoplasma bacteria.

None of these clusters, however, appear to be related to one another or caused by unfamiliar bugs. Initial reports on the increase in Warren County came from school nurses who said that a lot of students were calling in sick, according to Clint Koenig, a family physician and the medical director of Warren County Health District.

“We’re pretty confident that this is way above what we’ve seen this time last year,” he says. But Koenig adds that it’s hard to say how many more cases there are because data on children’s pneumonia cases are not routinely collected. Regardless, the causes of pneumonia are no different than those of past years: mostly RSV, adenovirus and Streptococcus or Mycoplasma infections.

What’s causing the current uptick in pneumonia cases, and how severe are they?

The growing pockets of pneumonia trace back to the usual increase in respiratory illnesses that occurs every winter, Schaffner says. Just as some flu seasons are more intense than others, the spread and severity of other winter diseases can also vary from year to year. Some upticks might be occurring as the usual seasonality of these pathogens continues to settle back into prepandemic patterns after it was disrupted by lockdowns, masking and social distancing, Schaffner says. But the biggest cause is likely that pathogens have more opportunity to spread in the winter.

“These viruses are taking advantage of us now that we are close together in birthday parties, schools, travel, religious services—whatever brings people together indoors,” Schaffner says. “And of course, we anticipate even more of that, given the holiday season. The New Year’s parties, all the travel associated with that and vacations are all wonderful environments that predispose to the spread of all of these respiratory infections, some of which will eventuate in pneumonia.”

What is the difference between pneumonia, “walking pneumonia” and “white lung syndrome”?

Pneumonia is an inflammation of the lungs that can be caused by a wide range of viruses, bacteria and fungi . Most respiratory infections involve the upper respiratory tract—the nose, throat and upper bronchial tubes, Schaffner says.

An infection develops into pneumonia when it reaches the lower respiratory tract and invades the lung tissue. This causes the lung’s white blood cells to trigger an inflammatory response. “If you get a lot of pneumonia, it will materially interfere with your ability to exchange gases. You can get short of breath, and you can have difficulty breathing,” Schaffner says.

Other symptoms include cough, fever, chest pain, fatigue and loss of appetite.

At least a dozen different pathogens can lead to pneumonia—no individual pathogen is responsible for even one in 10 cases . In fact, the pathogen behind any particular case of pneumonia is often never identified. Most pneumonia cases are triggered by a bacterium, but pneumonia is also a possible complication of respiratory viruses, such as COVID, influenza, RSV and even the common cold. These viruses can cause pneumonia by themselves or by making the body more vulnerable to secondary infections.

“Once somebody is infected with a virus, they’re more prone to get a bacterial infection on top of that” because the viral infection reduces their immune defenses, Thyagarajan explains. “The people that are affected are very young—infants and very young children—and very old and people with chronic illness.”

“Walking pneumonia” is a lay term often used to describe mild pneumonia cases, particularly those caused by Mycoplasma bacteria. It also has been called atypical pneumonia, Thyagarajan says, and can cause fevers, a dry cough and sometimes ear infections. According to Offit, “walking pneumonia” is usually not that severe. “Although we treat it with antibiotics, it usually is, for the most part, limited,” he says.

“White lung disease,” or “white lung syndrome,” is nothing but “a scary lay description, not used by medical professionals, of what we see on a routine chest x-ray,” Schaffner says. Healthy lungs full of air appear black in an x-ray because air looks dark in a normal reading. When inflammation and white blood cells fill the area, the lungs become opaque and more white on the reading, Offit explains. “It’s neither a scientific nor a medically acceptable term,” he adds.

How does pneumonia differ between children and adults?

Pneumonia symptoms are similar in children and adults, though young children may also experience nausea and vomiting, and older adults may have confusion. Beyond that, “different bugs are more apt to produce pneumonia in children than adults,” Schaffner says. “The older you get, if you have underlying illnesses, these respiratory viruses are more likely to result in pneumonia.”

Older adults tend to fare worse with pneumonia. Though pneumonia is the number-one cause of hospitalization in children in the U.S., older adults hospitalized with the disease have a greater risk of death than those hospitalized for any of the other top-10 reasons. That’s why it’s particularly important for older adults to get their RSV, flu and COVID vaccines, Thyagarajan says. “The populations who are at higher risk for complications, hospitalizations and dying from respiratory viruses and bacteria are the same populations who will benefit most from these vaccinations,” she says.

How is pneumonia treated?

Most viral pneumonia can only be treated with supportive care, such as providing oxygen; people with severe cases may require ventilators, heart-lung machines and other forms of mechanical ventilation, Offit says. Bacterial pneumonia is treated with antibiotics.

If you are otherwise healthy, there’s no need to contact a health care provider in the first several days of developing a respiratory infection, Thyagarajan says. But if you develop warning symptoms, such as confusion, shortness of breath or a fever that lasts more than three or four days, “it’s prudent to call your health care provider or seek emergency care,” she says.

Antivirals for flu and COVID , such as Paxlovid, can reduce the likelihood of developing pneumonia when taken early in the course of illness. Those in high-risk groups who develop respiratory symptoms, including those who have a chronic illness or are immunocompromised, should call their health care provider even when the symptoms seem mild, Schaffner says. That way they can get tested for flu and COVID to see if they potentially qualify for medications that reduce the severity of those diseases. Diagnosing an infection and treating it early are key to stopping it from turning into pneumonia.

How can you prevent pneumonia?

Though vaccination can’t prevent all cases of pneumonia, five vaccines recommended in the U.S. can substantially reduce risk of it. Two of these are already routinely recommended for children: the pneumococcal conjugate vaccines (PCV15 and PCV20) and the Haemophilus influenzae (Hib) vaccine . Pneumococcal vaccines are also recommended in adults aged 65 and older, as well as adults with certain medical conditions.

The COVID and seasonal flu vaccines , recommended for everyone aged six months and older, greatly reduce the risk of those diseases developing into pneumonia. Protection against RSV by the monoclonal antibody nirsevimab (Beyfortus) and the recently approved RSV vaccines can also reduce pneumonia risk in those eligible, including adults aged 60 and older, pregnant people, babies and some toddlers.

(Pneumonia develops in one out of five cases of pertussis, or whooping cough, so pertussis vaccination can also prevent pneumonia.)

The same behaviors recommended to prevent the spread of COVID, such as masking, staying home when sick and social distancing, will also reduce risk of other respiratory illnesses that can cause pneumonia.

“If you’re in a high-risk group—you’re older, you’re frail, you have underlying illnesses, you’re immune-compromised—you can get out your mask, and you can be more cautious when you travel or go to the supermarket or any indoor gathering of people,” Schaffner says.

Thyagarajan says she wears her mask at large gatherings in the winter season to protect herself and to protect others as well. That’s especially important if you are a caregiver for an older person or young baby, she adds.

Avoiding people who are coughing and showing other symptoms is obviously ideal, too, but it can be difficult to do, Schaffner adds. Stay home if you are sick—it’s ultimately one of the best ways to avoid spreading illness.

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  • Published: 02 January 2024

Construction and evaluation of neonatal respiratory failure risk prediction model for neonatal respiratory distress syndrome

  • Yupeng Lei 1 , 2   na1 ,
  • Xia Qiu 1 , 2   na1 &
  • Ruixi Zhou 1 , 2  

BMC Pulmonary Medicine volume  24 , Article number:  8 ( 2024 ) Cite this article

44 Accesses

Metrics details

Neonatal respiratory distress syndrome (NRDS) is a common respiratory disease in preterm infants, often accompanied by respiratory failure. The aim of this study was to establish and validate a nomogram model for predicting the probability of respiratory failure in NRDS patients.

Patients diagnosed with NRDS were extracted from the MIMIC-iv database. The patients were randomly assigned to a training and a validation cohort. Univariate and stepwise Cox regression analyses were used to determine the prognostic factors of NRDS. A nomogram containing these factors was established to predict the incidence of respiratory failure in NRDS patients. The area under the receiver operating characteristic curve (AUC), receiver operating characteristic curve (ROC), calibration curves and decision curve analysis were used to determine the effectiveness of this model.

The study included 2,705 patients with NRDS. Univariate and multivariate stepwise Cox regression analysis showed that the independent risk factors for respiratory failure in NRDS patients were gestational age, pH, partial pressure of oxygen (PO 2 ), partial pressure of carbon dioxide (PCO 2 ), hemoglobin, blood culture, infection, neonatal intracranial hemorrhage, Pulmonary surfactant (PS), parenteral nutrition and respiratory support. Then, the nomogram was constructed and verified.

Conclusions

This study identified the independent risk factors of respiratory failure in NRDS patients and used them to construct and evaluate respiratory failure risk prediction model for NRDS. The present findings provide clinicians with the judgment of patients with respiratory failure in NRDS and help clinicians to identify and intervene in the early stage.

Peer Review reports

Introduction

Neonatal respiratory distress syndrome (NRDS) is the most common respiratory system disease in premature babies, particularly those born before 28 weeks of gestation [ 1 , 2 ]. It is caused by dysfunction of effective ventilation in neonates due to the lack of pulmonary surfactant (PS), or the immature development of the lung [ 3 , 4 ]. Because of the formation of hyaline membrane in the pathophysiology of this disease, it is also called neonatal pulmonary hyaline membrane disease [ 5 ].The disease causes a progressive worsening of inspiratory dyspnea. NRDS patients may experience rapid breathing, grunting sounds while breathing, and flaring nostrils, they may also have a bluish tint to their skin due to inadequate oxygenation [ 6 ].NRDS has a high morbidity rate, 5% of near-term infants are affected, 30% of infants who had a gestational age of less than 30 weeks are affected, and 60% of premature infants who had a gestational age of less than 28 weeks are affected [ 7 ]. Many premature infants also die because of NRDS [ 8 ]. Severe NRDS can lead to neonatal respiratory failure(NRF), which is defined as decreased oxygen saturation and oxygen partial pressure (PO2), or the need for endotracheal intubation and mechanical ventilation [ 9 ]. NRF is likely to occur after NRDS for a period of time under the induction of various causes, affecting the development of children's circulatory system, nervous system, metabolism and other aspects, and even cause a serious impact on the prognosis of newborns [ 10 ].

At present, prenatal use of dexamethasone to promote fetal lung development and maturation [ 11 ], postpartum PS supplementation [ 12 ], and effective ventilation therapy [ 13 ] have reduced the incidence of NRDS, and also changed its severity and typical manifestations. However, NRDS remains the most common respiratory disease in preterm infants in the neonatal intensive care unit (NICU), and there are many cases of NRDS leading to NRF [ 14 ]. Therefore, being able to identify the cases with a high probability of developing NRF in NRDS patients is helpful for early medical intervention, and is of great significance for improving the prognosis of children.

Predictive models have been previously developed for neonatal respiratory distress syndrome in both preterm and late-preterm infants, as well as for predicting other complications associated with NRDS [ 15 , 16 ]. Nevertheless, a predictive model for respiratory failure within the context of neonatal respiratory distress syndrome has yet to be established. A newborn refers to an infant who is in the initial 28 days of life after birth. during this neonatal period, infants diagnosed with NRDS are at a high risk of developing NRF. As such, this study aims to investigate the likelihood of NRF occurrence among neonates diagnosed with NRDS at both day 1 and day 28 after birth and then establishing a predictive model for the development of NRF in NRDS.

Data source

This study was a restrictive observational study from the Medical Information Mart for Intensive Care IV (MIMIC-IV version 1.0) database ( https://physionet.org/content/mimiciv/1.0/ ), which is a large, freely accessible database of de-identified medical records for patients admitted to the intensive care unit (ICU) at the Beth Israel Deaconess Medical Center in Boston, Massachusetts, USA. It contains data from over 100,000 ICU stays between 2008 and 2019, making it one of the largest publicly available critical care datasets in the world [ 17 ]. The MIMIC-IV database includes information on patient demographics, vital signs, laboratory results, medications, diagnoses, procedures, and other clinical data. It also contains free-text nursing notes and physician progress notes, which can be used for natural language processing and other text-based analyses. The MIMIC-IV database has been used for a wide range of research studies, including machine learning and artificial intelligence approaches for predicting patient outcomes, developing clinical decision support systems, and improving patient care. It has also been used to investigate clinical questions related to sepsis, acute respiratory distress syndrome, cardiac arrest, and other critical care conditions. Individuals who have finished the Collaborative Institutional Training Initiative examination (Certification number 50366200 for YL) can access the database.

Study population

In our study, we included neonatal patients with NRDS, and NRF secondary to the onset of NRDS. NRDS was determined following diagnostic codes from the International Classification of Diseases, 9th revised (ICD-9) and 10th revised (ICD-10) editions [ 18 , 19 ] and we defined cases with a PaO2 level below 50 mmHg as neonatal respiratory failure [ 20 , 21 ]. We extracted these patients’ parameters from the MIMIC-IV, and we collected the following data: basic information including gestational age, gender, ethnic group, admission time, onset time and discharge time. Then, biological variables were collected, including peripheral blood white blood cells (WBC), hemoglobin (Hb), platelets (PLT) from the blood routine examination; bilirubin from the blood biochemistry; pH, PO2, partial pressure of carbon dioxide (PCO2) from the blood gas analysis; blood culture and cerebrospinal fluid (CSF) culture results. All data were collected within 48 h of patient admission, and in cases with multiple measurements, we analyzed only the initial measurements. The clinical variables mainly included intrauterine growth retardation (IUGR), neonatal asphyxia, neonatal apnea, neonatal jaundice, neonatal intracranial hemorrhage, neonatal coagulation disorders, neonatal pneumonia, neonatal anemia and infection. Treatment measures included whether or not to use PS, whether or not to use noninvasive ventilation, whether or not to use caffeine, and whether or not to use parenteral nutrition. The code of data extraction is available on Github ( https://github.com/MIT-LCP/mimic-iv ).

Statistical analysis

For nomogram construction and validation, we randomly divided all the NRDS patients into training and validation cohorts, in a ratio of 7:3 [ 22 ]. The demographic and clinical characteristics of the patients were described in the training and validation datasets. Univariate Cox and stepwise Cox regression analysis were used to screen variables. P values of less than 0.05 ( P  < 0.05) in univariate Cox regression analysis were included in the multivariate Cox proportional hazards regression analysis. To simplify the model and prevent collinearity of variables, multivariate Cox proportional hazards regression analysis was performed to identify variables that significantly affected the onset of NRF, using a significance threshold ( P  < 0.05) [ 23 ]. These eligible variables were included in the final Cox proportional hazards model, and the corresponding nomogram was drawn. The predicted values of the nomogram were calculated, and the actual values observed were compared with the results of the nomogram. The calibration curve [ 24 ], receiver operating characteristic (ROC) curve [ 25 ] and decision curve [ 26 ] were drawn to test the performance of the model. All statistical analyses were conducted using R 4.2.1 ( https://www.r-project.org/ ). In the R software package used, TableOne (0.13.2) was used for data description, survival (3.2.13) was used for feature selection, and RMS (6.2.0) was used for model construction and nomogram drawing. Bilateral P  < 0.05 was considered to indicate statistical significance.

Patient characteristics

A total of 2705 patients diagnosed with NRDS between 2008 and 2019 were included in this study, and NRF was observed in 1194 (44.1%) of them. The training and validation cohorts of NRDS patients consisted of 1899 and 806 cases, respectively. In the total cohort of NRDS patients, the majority of patients were white (30.7%) and male (57.6%). Patients with infection accounted for 16.1% and 17.5% of those in the training and validation cohorts, respectively, while patients with IUGR accounted for 8.1% and 7.0%, and those with neonatal asphyxia accounted for 0.4% and 0.1%. From the laboratory test results, the median pH in both cohorts were 7.29 [7.24, 7.34]. The median WBC in the training and validation cohorts were respectively 10.30 [7.00, 15.20] and 10.40 [6.90, 14.40]. The median PO2 in both cohorts were 47.00 [39.00, 58.00]. Patients with positive blood culture accounted for 5.7% and 4.8% of those in the training and validation cohorts, respectively, and neonatal respiratory failure patients accounted for 44.1% and 44.2%. The remaining baseline characteristics are listed in Table  1 . And there was no significant statistical difference between these variables in the training and validation cohorts ( P  > 0.05).

Screening for pathogenic factors of neonatal respiratory failure.

For NRDS patients, based on univariate and stepwise Cox regression analysis, we identified 11 independent prognostic factors in the training cohort. Gestational age < 28 weeks (hazard ratio (HR) = 6.63(5.59–7.85), P  < 0.0001), pH (HR = 0.05 (0.02–0.13), P  < 0.0001), PO2 (HR = 0.96 (0.95–0.96), P  < 0.0001), PCO2 (HR = 0.99 (0.98–1), P  < 0.05), Hb (HR = 0.91(0.88–0.93), P  < 0.0001), Blood culture (HR = 3.85(1.88–7.89), P  < 0.0001), infection (HR = 1.34(1.11–1.61), P  < 0.05), Neonatal intracranial Hemorrhage (HR = 1.42(1.08–1.86), P < 0.05), PS (HR = 0.76(0.65–0.89), P  < 0.0001), parenteral nutrition (HR = 2.13(1.78–2.54), P  < 0.0001) and noninvasive ventilation (HR = 0.64(0.55–0.73), P  < 0.0001), were all significantly associated with neonatal respiratory failure in NRDS patients (Table  2 ).

Nomogram construction

We developed a nomogram predicting the occurrence of NRF at day 1 and day 28 in patients with NRDS, based on the selected pathogenic factors from the training cohort (Fig.  1 ). Each level of every variable was assigned a score based on the points scale. The total score was obtained by adding the scores of each of the selected variables. The prediction corresponding to this total score then helped in estimating the occurrence of NRF within day 1 and day 28 for each NRDS patients.

figure 1

This nomogram estimates the likelihood of neonatal respiratory failure (NRF) in patients diagnosed with neonatal respiratory distress syndrome (NRDS). When using the nomogram, draw a vertical line from each variable to the points scale, noting the corresponding score, and then sum the scores for all variables to get a total. Finally, refer to the bottom of the nomogram to determine the predicted probability of NRF based on the total score. For comorbidities, 'Yes' indicates the presence and 'No' indicates the absence of the condition. For laboratory test results, 'Neg' stands for negative, and 'Pos' for positive. For treatment measures, 'Yes' indicates the measure was applied, while 'No' means it wasn't. PCO 2 , partial pressure of carbon dioxide; PO 2 , partial pressure of oxygen; Hb, hemoglobin

Nomogram validation

We detected the ability to predict NRF in NRDS patients from the nomogram. Figure  2 indicates that the area under the ROC curve (AUC) values of the nomogram were 0.9343 (Fig.  2 A) and 0.9378 (Fig.  2 B) for the occurrence of disease within day 1- and day 28- in the training cohort, respectively, and in the validation cohort, the AUC values of the nomogram were 0.9237 (Fig.  2 C) and 0.9321 (Fig.  2 D). It shows that our model has good predictive ability in both the training and validation cohorts [ 27 ]. Figure  2 also displays the calibration curves of the nomogram. The calibration curves of the training (Fig.  2 E/F) and validation (Fig.  2 G/H) cohorts indicate that the nomogram provided a good fit to the data, and that our models did not significantly overestimate or underestimate risk [ 28 ]. Finally, we drew a decision curve analysis to illustrate the clinical applicability of the nomogram (Fig.  3 ). It indicated that clinical interventions guided by our nomogram had a high net benefit [ 26 ].

figure 2

ROC and calibration curves for both the training and validation cohorts. A ROC curve representing disease occurrence on day 1 for the training cohort; B ROC curve for disease occurrence on day 28 in the training cohort; C ROC curve for disease occurrence on day 1 in the validation cohort; D ROC curve for disease occurrence on day 28 in the validation cohort. E Calibration curve for disease occurrence on day 1 in the training cohort; F Calibration curve for disease occurrence on day 28 in the training cohort; G Calibration curve for disease occurrence on day 1 in the validation cohort; H Calibration curve for disease occurrence on day 28 in the validation cohort. ROC, receiver operating characteristic; AUC, the area under the ROC curve. TP, true positive; FP, False Positive

figure 3

Decision-curve analysis of the validation cohort and the training cohort. A The occurrence of disease at day 1 in the training cohort; B the occurrence of disease at day 28 in the training cohort; C the occurrence of disease at day 1 in the validation cohort; ( D ) the occurrence of disease at day 28 in the validation cohort

NRF secondary to NRDS is not uncommon, it may occur after NRDS for a period of time after the onset of NRDS, especially when combined with multiple risk factors. We performed a large sample multi-risk factor analysis, and indicated Gestational age < 28 weeks, pH, PO2, PCO2, Hb, Blood culture, infection, Neonatal intracranial Hemorrhage, PS, parenteral nutrition and respiratory support as independent risk factors for NRF in NRDS patients. These results were used to construct a nomogram for estimating the NRF risk in NRDS patients within day 1 and day 28 during hospitalization. The validity of our nomogram model was determined using multiple indicators, including AUC, calibration curves and decision-curve analysis. In this study, we constructed a more comprehensive model based on a combination of various risk factors, to better predict the risk of NRF in patients with NRDS.

We found that most of the secondary NRF in NRDS patients occurred within one day [ 29 ]. This is also consistent with the clinical features of NRDS, which is a progressive worsening of dyspnea that develops gradually after birth, therefore most NRDS patients typically develop respiratory failure within 1 day. Premature infants with a gestational age of less than 28 weeks are at an increased risk of developing NRF following NRDS. This is primarily due to the fact that premature infants exhibit underdeveloped lungs, insufficient production of surface-active substances, and compromised immunity, which collectively increase the likelihood of disease progression and exacerbation2. In addition, we found that infection-related factors were also closely related to neonatal respiratory failure secondary to NRDS, including clear presence of infection-related symptoms, or positive microbial tests such as blood culture and CSF culture, which may be due to the decreased activity and increased degradation of PS caused by inflammatory mediators [ 30 ]. At the same time, inflammation can cause mechanical damage to type II alveolar epithelial cells, and further reduce the secretion of PS [ 31 ]. Thus, patients with pathogen cultures detected during the first time should receive clinical attention. Antimicrobial agents should include all possibly present pathogenic bacteria in the initial stage of anti-infective therapy.

In terms of treatment, parenteral nutrition increases the risk of NRF, which may be associated with infection due to parenteral nutrition, or increased pulmonary circulation due to excessive fluid intake [ 32 ]. Therefore, rational parenteral nutrition and fluid management are critical in patients with NRDS. At the same time, the use of noninvasive ventilation and Surfactant replacement can effectively reduce the occurrence of NRF. Noninvasive ventilation techniques, like nasal Continuous Positive Airway Pressure (nCPAP), offer positive end-expiratory pressure to NRDS patients. This aids in consistently expanding the alveoli, enhancing gas exchange, and subsequently mitigating the risk of NRF. As the respiratory distress in NRDS patients stems from a PS deficiency, replenishing PS further reduces the likelihood of NRF [ 33 ].

Blood gas analysis is an important laboratory test index in neonatal respiratory management. Our study found that pH, PO2 and PCO2 are of great importance to NRF [ 10 ]. These indicators can not only reflect the occurrence of NRF, but also be used as risk factors to early judge NRF secondary to NRDS, and remind us to carry out early intervention. Our findings revealed a significant association between reduced hemoglobin levels and disease development, potentially attributed to inadequate oxygenation among anemic children. Furthermore, the impact of intracranial hemorrhage on disease onset may be related to the central nervous system's role in respiratory regulation.

Clinical predictive models can be used to study the relationship between future outcome events and baseline status in patients [ 34 ]. They can integrate the results of traditional analyses, simplify them with more intuitive and convincing presentations, and predict the probability of certain outcome events with a scoring system [ 35 ]. NRDS is the most common respiratory disease in preterm infants. NRF caused by NRDS can be followed by multiple organ dysfunctions, which has a great impact on the prognosis of preterm infants. At present, the risk factors of respiratory failure secondary to NRDS have not been well studied. Therefore, the establishment of this prediction model has important clinical significance for early identification of NRF in patients with NRDS. Our doctors can use the scoring results of the model to communicate with the family members of the neonate, help them understand the severity of the child's condition, work out a treatment plan together, improve the degree of cooperation, and prevent the occurrence of NRF to the greatest extent. However, the predictive ability of this nomogram may be improved by considering other potential important factors that we were not able to obtain from the MIMIC-IV database, such as maternal factors during pregnancy, perinatal medication and detailed insights into the parameters associated with non-invasive ventilation. And although the number of patients included was large, this study is a single-center study, and lacks external validation.

Availability of data and materials

The datasets analyzed during the current study are available in the MIMIC-IV repository, https://physionet.org/content/mimiciv/1.0/ .

Abbreviations

Area under the ROC curve

Cerebrospinal fluid

Intrauterine growth retardation

International Classification of Diseases

Medical Information Mart for Intensive Care

Nasal Continuous Positive Airway Pressure

Neonatal intensive care unit

Neonatal respiratory distress syndrome

Neonatal respiratory failure

Partial pressure of carbon dioxide

Partial pressure of oxygen

Pulmonary surfactant

Receiver operating characteristic curve

White blood cells

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Acknowledgements

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Yupeng Lei and Xia Qiu contributed equally to this work.

Authors and Affiliations

Department of Pediatrics, West China Second University Hospital, Sichuan University, Chengdu, 610041, Sichuan, China

Yupeng Lei, Xia Qiu & Ruixi Zhou

Key Laboratory of Birth Defects and Related Diseases of Women and Children, Sichuan University, Ministry of Education, Chengdu, 610041, China

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Contributions

L and XQ contributed to the collection and analysis of data, and the writing and editing of the manuscript. RZ contributed to the conception and design of the work, editing and writing assistance. All authors contributed to the article and approved the submitted version.

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Correspondence to Ruixi Zhou .

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Lei, Y., Qiu, X. & Zhou, R. Construction and evaluation of neonatal respiratory failure risk prediction model for neonatal respiratory distress syndrome. BMC Pulm Med 24 , 8 (2024). https://doi.org/10.1186/s12890-023-02819-4

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DOI : https://doi.org/10.1186/s12890-023-02819-4

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BMC Pulmonary Medicine

ISSN: 1471-2466

case study of respiratory failure

A new coronavirus variant is taking over, but its symptoms don't seem any worse

Nurse Sandra Lindsay receives the latest Covid vaccine.

Covid cases appear to be climbing , according to Dr. Mandy Cohen, the director of the Centers for Disease Control and Prevention — and one particular variant seems to be fueling the virus' spread .

JN.1, as the variant is known, now accounts for around 44% of Covid cases  in the U.S., up from 8% just four weeks ago, according to the CDC.

“We are seeing JN.1 quickly become the dominant version of the Covid virus, which tells us it is more transmissible,” Cohen said in a phone interview. “The good news is we don’t see an increase in severity.”

The variant is also picking up steam globally. It accounted for 27% of genetic sequences submitted to a global virus database called GISAID in the week that ended Dec. 3, up from 10% in the week that ended Nov. 19.

The World Health Organization declared JN.1 a "variant of interest" Tuesday — a designation that applies to variants that are driving new cases and have genetic changes that could help them spread or evade immunity.

But so far, the illness caused by JN.1 — which, like all other variants that have gained dominance since early 2022, is a descendant of omicron — doesn't seem any more severe than earlier Covid cases.

Neither the WHO nor the CDC collects regular data on how Covid symptoms are evolving over time, so it's hard to assess whether infections are presenting differently. However, doctors say they haven't noticed a new trend.

“The symptoms of JN.1 seem to be very similar, if not the same, as others,” said Dr. Molly Fleece, a hospital epidemiologist at University of Alabama at Birmingham Medicine.

Many recent Covid patients have reported sore throats as their first symptoms, often followed by congestion. The illness’ past hallmarks, such as a dry cough or the loss of taste or smell, have become less common, according to doctors .

Severe cases, meanwhile, are still characterized by shortness of breath, chest pain or pale, gray or blue skin, lips or nail beds — an indicator of a lack of oxygen.

But on the whole, Covid symptoms are milder than they were early in the pandemic.

Fleece said JN.1 is spreading at an unfortunate time as people travel and gather indoors.

“If we have a variant that is extremely easy to spread among people, that’s extremely important to think about going into the holidays,” she said. “Just the ease of transmissibility, especially being an omicron descendant — we saw how easily omicron spread throughout communities — should make everyone concerned.”

The WHO has warned that JN.1 could cause an uptick in Covid cases this winter and “increase the burden of respiratory infections in many countries.”

The variant's parent lineage, BA.2.86, has a large number of mutations compared to the original version of omicron — and those changes have enabled the virus to sidestep existing immunity . Compared to BA.2.86, the JN.1 variant has an additional mutation in the spike protein that could make it even easier for the virus to invade cells.

However, the WHO said JN.1 isn’t likely to pose an added public health risk compared with other circulating variants. And although the newest vaccines target a different variant — called XBB.1.5 — they seem to be effective against JN.1, as well.

A  preprint study found that updated mRNA shots from Moderna and Pfizer boosted antibody protection against JN.1 up to 13 times, depending on a person's history of vaccination and infection. The study hasn’t been peer-reviewed, however.

The participants in that study had received four or five Covid shots before the updated vaccine, and some had recently gotten Covid. But the researchers found that antibody protection against JN.1 was still relatively low before the new vaccine was administered.

“It would suggest that those people who were not recently boosted probably would not be all that well-protected against JN.1," said an author of the study, Dr. David Ho, a professor of microbiology and immunology at Columbia University.

Antibody levels against JN.1 from the updated vaccine are "quite decent," Ho added, "and should confer some degree of protection."

Just 18% of adults and 8% of children ages 6 months and up have received the new Covid vaccine since it became available in September. So Cohen urged people to stay up to date on their shots.

“That’s exactly why we want folks to get the updated Covid vaccine, because it does map to the changes that we’re seeing in the virus," she said.

Ho acknowledged, however, that scientists expect to continue playing cat and mouse with Covid in the near future.

"We do something, and then the virus finds a solution to go elsewhere, away from our countermeasures," he said. “We’re chasing it the best we can, but we’re always a little behind.”

case study of respiratory failure

Aria Bendix is the breaking health reporter for NBC News Digital.

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