American Journal of Respiratory and Critical Care Medicine

To the Editor:

With the dramatic increase of confirmed cases of coronavirus disease (COVID-19) and the increasing death toll in China, timely and effective management of severely and critically ill patients appears to be particularly important. Previous studies on COVID-19 mainly described the general features of patients (1). However, little attention has been paid to clinical characteristics and outcomes of intensive care patients, data on whom are scarce but are of paramount importance to reduce mortality. Some of the results of these studies have been previously reported in the form of an abstract (2).


This study enrolled 344 severely and critically ill patients (intensive care patients) who were diagnosed with COVID-19 according to World Health Organization interim guidance by positive result of an RT-PCR assay of nasal and/or throat-swab specimens, and were hospitalized in eight intensive care wards (totaling approximately 330 beds) in Tongji hospital from January 25, 2020, through February 25, 2020. The intensive care wards staff intensivists and specialist nurses in intensive care and were equipped with continuous vital signs monitoring and respiratory support, including noninvasive and invasive ventilators, high-flow nasal cannula (HFNC) oxygen therapy, and extracorporeal membrane oxygenation. We collected demographic, clinical, laboratory, and radiologic findings, and treatment and outcome data from electronic medical records. The illness severity of COVID-19 was defined according to the Chinese management guideline for COVID-19 (version 6.0) (3). Cytokines were measured by a chemiluminescent immunometric assay (Immulite 1000; Diagnostic Products). Acute respiratory distress syndrome (ARDS) was diagnosed according to the Berlin definition, and septic shock was defined according to the 2016 Third International Consensus definition (4, 5). Disseminated intravascular coagulation was defined per the International Society of Thrombosis and Haemostasis, and acute kidney injury was diagnosed according to the Kidney Disease Improving Global Outcomes clinical practice guidelines (6). Myocardial damage was diagnosed according to the serum levels of cardiac biomarkers or new abnormalities in electrocardiography and echocardiography. Liver injury was diagnosed according to elevation of bilirubin and aminotransferase. Rhabdomyolysis was diagnosed on the basis of the serum level of creatine kinase and myoglobin. Survival endpoint was 28-day mortality after admission to the intensive care ward. The Ethics Commission of Tongji hospital approved this study, with a waiver of informed consent. Continuous variables are presented as median (interquartile range [IQR]), whereas categorical variables were expressed as frequencies (%). Statistical analyses were conducted with R3.6.2 ( using a Fisher’s exact test for categorical data and Mann-Whitney test for continuous data; Kaplan-Meier estimator and Cox regression were used for survival analysis. Correlations were measured by Spearman’s method (ρ). For unadjusted comparisons, a two-sided P less than 0.05 was considered statistically significant.

Characteristics and treatment

Of the 344 intensive care patients (Table 1), nonsurvivors are generally older than survivors, with a higher proportion aged over 60 years, and every 10-year increase in age was associated with a 58% additional risk (hazard ratio [HR], 1.58; 95% confidence interval [CI], 1.38–1.81; P < 0.001). Dyspnea was more common in nonsurvivors, accompanied by a significantly higher respiratory rate and lower SpO 2/FiO 2 (S/F) ratio; S/F was negatively correlated (ρ = −0.68) with the incidence of ARDS, and every 10-U increase in S/F correlated with a 10% decrease in fatality (HR, 0.90; 95% CI, 0.88–0.92; P < 0.001). A total of 128 out of 145 (88.3%) patients who developed ARDS died at or before 28 days. Nonsurvivors were more likely to bear original comorbidities (all P ≤ 0.05). Lymphocytopenia occurred in 237 (69.5%) subjects and was predominant in nonsurvivors (91.6% vs. 55.7%; P < 0.001); higher lymphocyte count was significantly associated with decreasing mortality (HR, 0.1; 95% CI, 0.06–0.18; P < 0.001). A total of 283 (82.3%) patients received antiviral agents, and 266 (77.3%) received antibacterial agents. Other supportive treatments, including γ globulin (156 [45.3%]), muscle relaxant (38 [11.0%]), and glucocorticoids (225 [65.4%]), were given to the patients. Two (0.6%) patients were treated with extracorporeal membrane oxygenation, and nine (2.6%) with continuous renal replacement therapy.

Table 1. Presenting Characteristics of Intensive Care Patients with COVID-19

CharacteristicsAll Patients (N = 344)*Survivors (n = 211)Nonsurvivors (n = 133)P Value
Age, yr64 (52–72)57 (47–69)70 (62–77)<0.001
Age range, yr   <0.001
 ≤60150 (43.6)118 (55.9)32 (24.1) 
 >60194 (56.4)93 (44.1)101 (75.9) 
Sex, M179 (52.0)105 (49.8)74 (55.6)0.341
Signs and symptoms    
 Fever301 (87.5)186 (88.2)115 (86.5)0.770
 Dry cough233 (67.7)137 (64.9)96 (72.2)0.200
 Dyspnea208 (60.5)108 (51.2)100 (75.2)<0.001
 Fatigue167 (48.5)102 (48.3)65 (48.9)1.000
 Expectoration135 (39.2)82 (38.9)53 (39.8)0.945
 Diarrhea92 (26.7)63 (29.9)29 (21.8)0.129
 Anorexia91 (26.5)57 (27.0)34 (25.6)0.864
Original comorbidities or medication history    
 Hypertension141 (41.0)72 (34.1)69 (52.3)0.001
 ACE inhibitors62 (18.0)32 (15.2)30 (22.6)0.083
 Diabetes64 (18.6)34 (16.1)30 (22.9)0.155
 Cardiovascular disease40 (11.6)18 (8.5)22 (16.5)0.030
 COPD16 (4.7)3 (1.4)13 (9.8)0.001
Vital signs    
 Respiratory rate, respirations/min21 (20–25)20 (20–22)24 (20–31)<0.001
 Heart rate, beats/min90 (80–104)90 (80–104)93 (82–108)0.116
 SpO 2/FiO 2279 (157–328)297 (272–448)114 (89–224)<0.001
Laboratory findings at admission    
 Routine blood test    
  White blood cells, ×109/L6.2 (4.5–8.9)5.3 (4.0–6.9)9.1 (6.1–13.3)<0.001
  Lymphocytes, ×109/L0.9 (0.6–1.2)1.0 (0.8–1.4)0.6 (0.4–0.7)<0.001
  Neutrophils, ×109/L4.7 (2.9–7.6)3.7 (2.5–5.3)8.0 (5.5–12.2)<0.001
  Platelets, ×109/L189 (142–257)211 (161–290)159 (112–218)<0.001
  Red cell distribution width12.4 (11.9–13.2)12.3 (11.8–13.0)12.7 (12.2–13.7)<0.001
 Inflammatory marker    
  hs-CRP, mg/L55 (14–106)28 (6–67)101 (61–153)<0.001
  PCT, ng/ml0.09 (0.04–0.23)0.04 (0.03–0.09)0.21 (0.13–0.70)<0.001
  IL-2R, U/ml811 (546–1154)716 (458–954)1098 (721–1512)<0.001
  IL-6, pg/ml27.2 (5.9–60.1)10.8 (2.7–37.4)61.1 (29.9–132.2)<0.001
  IL-8, pg/ml17.2 (9.1–34.0)12.5 (6.9–20.8)28.3 (14.7–59.1)<0.001
  IL-10, pg/ml6.1 (2.5–10.6)2.5 (2.5–7.0)10.5 (5.9–18.5)<0.001
  TNF-α, pg/ml8.8 (6.6–11.7)8.2 (6.1–10.2)10.7 (7.5–15.9)<0.001
 Coagulation index    
  Prothrombin time, s14.3 (13.5–15.4)13.9 (13.3–14.5)15.4 (14.3–17.4)<0.001
  D-Dimer, μg/ml1.3 (0.5–5.0)0.7 (0.4–1.5)5.1 (1.7–31.5)<0.001
  INR1.1 (1.0–1.2)1.1 (1.0–1.1)1.2 (1.1–1.4)<0.001
 Cardiac biomarkers    
  High-sensitivity cardiac troponin I, pg/ml9.7 (2.9–44.4)3.4 (1.4–8.7)46.7 (11.2–801.3)<0.001
  Myo, ng/ml75 (32–199)31 (20–55)179 (103–367)<0.001
  CK-MB, ng/ml1.5 (0.5–3.2)0.4 (0.3–1.2)2.5 (1.2–6.1)<0.001
  ALT (≤41), U/L24 (15–38)21 (14–36)29 (19–42)0.001
  AST (≤41), U/L31 (22–47)27 (20–37)43 (28–66)<0.001
  Albumin (35–52), g/L34 (30–37)36 (33–39)31 (28–34)<0.001
  TBIL (≤26.0), μmol/L10.2 (7.3–14.2)8.5 (6.3–11.3)12.9 (9.8–19.2)<0.001
  Cr (59–104), μmol/L74 (58–93)66 (56.3–86)86 (67–111)<0.001
  BUN (3.6–9.5), mmol/L5.3 (3.8–8.3)4.3 (3.2–5.8)8.3 (5.9–12.1)<0.001
  CK (≤170), U/L109 (60–242)81 (39–139)168 (96–387)<0.001
  LDH (135–225), U/L338 (237–491)271 (205–347)525 (419–676)<0.001
  e-GFR (>90), ml/min/1.73 m287 (70–101)93 (78–107)74 (55–91)<0.001
  Glu (3.9–6.1), mmol/L6.8 (5.7–9.0)6.1 (5.2–7.8)8.2 (6.6–11.4)<0.001
Radiologic manifestation   <0.001
 GGO164 (47.7)101 (50.8)63 (54.8) 
 Local patchy opacities38 (11.0)35 (17.6)3 (2.6) 
 Bilateral patchy opacities110 (32.0)61 (30.7)49 (42.6) 
Organ function injury    
 ARDS145 (42.2)17 (8.1)128 (97.0)<0.001
 Septic shock114 (33.1)2 (0.9)112 (84.2)<0.001
 DIC71 (20.6)1 (0.5)70 (52.6)<0.001
 AKI86 (25.0)6 (2.8)80 (60.2)<0.001
 Myocardial damage111 (32.3)4 (1.9)107 (80.5)<0.001
 Liver injury54 (15.7)9 (4.3)45 (33.8)<0.001
 Rhabdomyolysis9 (2.6)0 (0)9 (6.9)<0.001
Ventilatory support throughout the course    
 HFNC oxygen therapy35 (10.2)7 (3.3)28 (21.1)<0.001
 NIV34 (9.9)7 (3.3)27 (20.3)<0.001
 IV100 (29.1)3 (1.4)97 (72.9)<0.001

Definition of abbreviations: ACE = angiotensin-converting enzyme; AKI = acute kidney injury; ALT = alanine transaminase; ARDS = acute respiratory distress syndrome; AST = aspartate transaminase; BUN = blood urea nitrogen; CK = creatine kinase; CK-MB = creatine kinase, MB form; COPD = chronic obstructive pulmonary disease; COVID-19 = coronavirus disease; Cr = serum creatinine; DIC = disseminated intravascular coagulation; e-GFR = estimated glomerular filtration rate; GGO = ground-glass opacity; Glu = fasting blood glucose; HFNC = high-flow nasal cannula; hs-CRP = high-sensitivity C-reactive protein; INR = international normalized ratio; IV = invasive ventilation; LDH = lactate dehydrogenase; Myo = myoglobin; NIV = noninvasive ventilation; PCT = procalcitonin; SpO 2 = oxygen saturation as measured by pulse oximetry; TBIL = total bilirubin; TNF-α = tumor necrosis factor α.

All records were measured at admission to intensive care wards unless otherwise indicated. Data are shown as n (%) or median (interquartile range).

*The percentages represent the frequency divided by the total cohort size (N = 344), whereas percentages in subgroups were calculated according to contingency table, with missing data removed first.

Normal ranges of listed biochemical parameters are indicated in parentheses.

Ventilatory support

A total of 35 (10.2%) patients were treated with HFNC, of whom 23 (65.7%) also received invasive ventilation. Of the 12 patients who received HFNC only, 7 (58.3%) died at or before 28 days. A total of 134 (40.6%) patients were treated with mechanical ventilation (either noninvasive or invasive), of whom 34 received treatment of noninvasive ventilation only, and 27 (79.4%) died at or before 28 days, whereas invasive ventilation was given to 100 patients, with 97 (97%) deaths at or before 28 days. Median duration from admission to invasive ventilation was 5 (IQR, 1–8) days, and median duration of invasive ventilation was 4 (IQR, 3–8) days. Of the 145 patients who developed ARDS, 100 (69.0%) were treated with invasive ventilation.

Clinical course and outcomes

A total of 133 (38.7%) patients died at or before 28 days, with a median survival of 25 days (Figure 1). For nonsurvivors, median duration from admission to death was 10 (IQR, 6–15) days. Of the 211 survivors, 185 (87.7%) were discharged. Median duration from onset of symptoms to laboratory confirmation of infection by RT-PCR was 8 (IQR, 5–11) days. In survivors, median duration from positive to negative RT-PCR result was 12 (IQR, 9–15) days, whereas, in nonsurvivors, median duration from infection confirmation to death was 15 (IQR, 10–19) days (Figure 1).


This report, to our knowledge, is the largest case series of patients with COVID-19 in intensive care, with informative laboratory characteristics, detailed clinical course, and outcome.

In our cohort, nonsurvivors were older than survivors, which is consistent with an earlier study (7). We did not observe survival differences in regard to sex, but this is inconsistent with the results of a previous study (8). Compared with survivors, nonsurvivors presented more commonly with dyspnea and a higher respiratory rate, indicating that more attention should be paid to changes in vital signs with respect to respiratory rate for intensive care patients. A previous study revealed that original comorbidities were potential risk factors (8), and we observed that hypertension is significantly differentially distributed between nonsurvivors (69 [52.3%]) and survivors (72 [34.1%]), and 62 out of 141 (44.0%) patients with hypertension had a medication history of taking ACE (angiotensin-converting enzyme) inhibitors. Given that ACE2 plays a dual role of vasopeptidase and severe acute respiratory syndrome (SARS) virus receptor, we speculated that patients with hypertension with COVID-19 might be more likely to become critically ill (9). In addition, S/F may be a useful and noninvasive predictive marker, which was defined by the Kigali modification of the Berlin definition and had good correlation with the diagnosis of ARDS (10). Given a large patient flow during epidemic conditions, this indicator could be flexibly used for screening and monitoring.

Lymphocytopenia occurred in almost 70% and was predominant in nonsurvivors, which contradicts a previous study with a relatively small sample size (8). Lymphocytopenia is a prominent feature of critically ill patients with SARS (11) and Middle East respiratory syndrome, which is the result of apoptosis of lymphocytes (12); thus, lymphocyte depletion could be harmful, and lymphocyte count might serve as another prognostic factor for SARS–coronavirus 2 (SARS-CoV-2). In addition, we observed a higher level of hs-CRP (high-sensitivity C-reactive protein), along with other inflammatory markers, which is consistent with relevant reports of SARS and Middle East respiratory syndrome (13). Unexpectedly, however, nonsurvivors showed a higher level of IL-2R. Highly expressed IL-2R initiates autoreactive cytotoxic CD8+ T-cell–mediated autoimmunity. Meanwhile, IL-2 stimulates the proliferation of natural killer cells that highly express IL-2R, promoting the release of cytokines, further inducing the lethal “cytokine storm” (14). We also observed that factors, such as red blood cell distribution width, lactate dehydrogenase, and coagulation index, were upregulated in nonsurvivors, which was probably due to their active participation in inflammatory response. It has been reported that chest computed tomography imaging can be more sensitive diagnostically compared with RT-PCR (15), and we reasoned that computed tomography might even show guiding significance in the critical stage of COVID-19. The high mortality rate of patients who received mechanical ventilation may have been due, in part, to the centralized admission of a large number of intensive care patients in February and the fact that patients were sometimes transferred late to the hospital. These conditions made us question the effectiveness of noninvasive ventilation treatment or HFNC in the first line, and whether the early use of invasive ventilation would improve prognosis. Both questions may be worth further study in a larger cohort.

In summary, in this single-center case series study, older patients with comorbidities are at dramatically increased risk of mortality. Real-time monitoring of S/F and regular measurements of lymphocyte count and inflammatory markers may be essential to disease management.

The authors thank all the hospital staff for their efforts in collecting the information that was used in this study, all the patients who consented to donate their data for analysis, and the medical staff who are on the frontlines of caring for patients.

1. Guan WJ, Ni ZY, Hu Y, Liang WH, Ou CQ, He JX, et al.; China Medical Treatment Expert Group for COVID-19. Clinical characteristics of coronavirus disease 2019 in China. N Engl J Med [online ahead of print] 28 Feb 2020; DOI:
2. Jamil S, Mark N, Carlos G, Dela Cruz CS, Gross JE, Pasnick S. Diagnosis and management of COVID-19 disease [abstract]. Am J Respir Crit Care Med [online ahead of print] 30 Mar 2020; DOI:
3. National Health Commission of the People’s Republic of China. Chinese management guideline for COVID-19 (version 6.0) [in Chinese]. [posted 2020 Feb 18; accessed 2020 Feb 19]. Available from:
4. Singer M, Deutschman CS, Seymour CW, Shankar-Hari M, Annane D, Bauer M, et al. The Third International Consensus definitions for sepsis and septic shock (Sepsis-3). JAMA 2016;315:801810.
5. Ranieri VM, Rubenfeld GD, Thompson BT, Ferguson ND, Caldwell E, Fan E, et al.; ARDS Definition Task Force. Acute respiratory distress syndrome: the Berlin definition. JAMA 2012;307:25262533.
6. Wada H, Thachil J, Di Nisio M, Mathew P, Kurosawa S, Gando S, et al.; The Scientific Standardization Committee on DIC of the International Society on Thrombosis Haemostasis. Guidance for diagnosis and treatment of DIC from harmonization of the recommendations from three guidelines. J Thromb Haemost [online ahead of print] 4 Feb 2013; DOI:
7. Wu Z, McGoogan JM. Characteristics of and important lessons from the coronavirus disease 2019 (COVID-19) outbreak in China: summary of a report of 72 314 cases from the Chinese Center for Disease Control and Prevention. JAMA [online ahead of print] 24 Feb 2020; DOI:
8. Yang X, Yu Y, Xu J, Shu H, Xia J, Liu H, et al. Clinical course and outcomes of critically ill patients with SARS-CoV-2 pneumonia in Wuhan, China: a single-centered, retrospective, observational study. Lancet Respir Med [online ahead of print] 24 Feb 2020; DOI:. [Published erratum appears in Lancet Respir Med 8:e26.]
9. Turner AJ, Hiscox JA, Hooper NM. ACE2: from vasopeptidase to SARS virus receptor. Trends Pharmacol Sci 2004;25:291294.
10. Riviello ED, Kiviri W, Twagirumugabe T, Mueller A, Banner-Goodspeed VM, Officer L, et al. Hospital incidence and outcomes of the acute respiratory distress syndrome using the Kigali modification of the Berlin definition. Am J Respir Crit Care Med 2016;193:5259.
11. Liu J, Li S, Liu J, Liang B, Wang X, Wang H, et al. Longitudinal characteristics of lymphocyte responses and cytokine profiles in the peripheral blood of SARS-CoV-2 infected patients. EBioMedicine 2020:102763.
12. Arabi YM, Arifi AA, Balkhy HH, Najm H, Aldawood AS, Ghabashi A, et al. Clinical course and outcomes of critically ill patients with Middle East respiratory syndrome coronavirus infection. Ann Intern Med 2014;160:389397.
13. Chan JF, Lau SK, To KK, Cheng VC, Woo PC, Yuen KY. Middle East respiratory syndrome coronavirus: another zoonotic betacoronavirus causing SARS-like disease. Clin Microbiol Rev 2015;28:465522.
14. Bachmann MF, Oxenius A. Interleukin 2: from immunostimulation to immunoregulation and back again. EMBO Rep 2007;8:11421148.
15. Ai T, Yang Z, Hou H, Zhan C, Chen C, Lv W, et al. Correlation of chest CT and RT-PCR testing in coronavirus disease 2019 (COVID-19) in China: a report of 1014 cases. Radiology [online ahead of print] 26 Feb 2020; DOI:

*These authors contributed equally to this work.

Corresponding author (e-mail: ; ).

Supported by National Key R&D Program of China grant 2019YFC1711000, National Natural Science Foundation of China grant 81973145, “Double First-Class” University project grant CPU2018GY09, China Postdoctoral Science Foundation grant 2019M651805, Science Foundation of Jiangsu Commission of Health grant H2018117, Emergency Project for the Prevention and Control of the Novel Coronavirus Outbreak in Suzhou grant SYS2020012, Fundamental Research Funds for the Central Universities (HUST: 2017KFYXJJ113; 2020-021414380462), and Wuhan Municipal Science and Technology Bureau (2017060201010173).

Author Contributions: Y.L. and J.W. had full access to all of the data in the study; conceptualization—Y.W., X.L., and T.C.; acquisition, analysis, or interpretation of data—Y.W., X.L., T.C., Y.L., and J.W.; statistical analysis—X.L. and F.Y.; investigation—X.L., H.C., T.C., N.S., F.H., J.Z., and B.Z.; drafting and editing of the manuscript—Y.W., X.L., and T.C.; funding acquisition—Y.W., F.Y., and J.W.; supervision—F.Y. and J.W.

Originally Published in Press as DOI: 10.1164/rccm.202003-0736LE on April 8, 2020

Author disclosures are available with the text of this letter at


No related items
Comments Post a Comment

New User Registration

Not Yet Registered?
Benefits of Registration Include:
 •  A Unique User Profile that will allow you to manage your current subscriptions (including online access)
 •  The ability to create favorites lists down to the article level
 •  The ability to customize email alerts to receive specific notifications about the topics you care most about and special offers
American Journal of Respiratory and Critical Care Medicine

Click to see any corrections or updates and to confirm this is the authentic version of record