Clinical course and risk factors for mortality of adult inpatients with COVID-19 in Wuhan, China: a retrospective cohort study
- et al.
Summary
Background
Methods
Findings
Interpretation
Funding
Introduction
In December, 2019, Wuhan city, the capital of Hubei province in China, became the centre of an outbreak of pneumonia of unknown cause. By Jan 7, 2020, Chinese scientists had isolated a novel coronavirus, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2; previously known as 2019-nCoV), from these patients with virus-infected pneumonia,
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which was later designated coronavirus disease 2019 (COVID-19) in February, 2020, by WHO.
Although the outbreak is likely to have started from a zoonotic transmission event associated with a large seafood market that also traded in live wild animals, it soon became clear that efficient person-to-person transmission was also occurring.
The clinical spectrum of SARS-CoV-2 infection appears to be wide, encompassing asymptomatic infection, mild upper respiratory tract illness, and severe viral pneumonia with respiratory failure and even death, with many patients being hospitalised with pneumonia in Wuhan.
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Although some case series have been published, many patients in these series remained hospitalised at time of publication. To our knowledge, no previous studies have been done among patients with definite outcomes. The estimation of risk factors for severe disease and death in these earlier case series are therefore not very robust. Additionally, details of the clinical and virological course of illness have not yet been well described.
Research in context
Methods
Study design and participants
Before Jan 11, 2020, SARS-CoV-2 RNA detection results were not available in the electronic medical records, from which data for this study were obtained retrospectively; therefore, this study includes 29 of the 41 patients originally reported on.
The study was approved by the Research Ethics Commission of Jinyintan Hospital (KY-2020–01.01) and the requirement for informed consent was waived by the Ethics Commission as described previously.
Data collection
Laboratory procedures
Methods for laboratory confirmation of SARS-CoV-2 infection have been described elsewhere.
Briefly, four institutions—the Chinese Center for Disease Control and Prevention, the Chinese Academy of Medical Science, the Academy of Military Medical Sciences, and the Wuhan Institute of Virology, Chinese Academy of Sciences—were responsible for SARS-CoV-2 detection in respiratory specimens by next-generation sequencing or real-time RT-PCR methods. From Jan 11, 2020, SARS-CoV-2 RNA were detected by local Centers for Disease Control and Prevention, local health institutions, and Jingyintan Hospital and Wuhan Pulmonary Hospital. Throat-swab specimens were obtained for SARS-CoV-2 PCR re-examination every other day after clinical remission of symptoms, including fever, cough, and dyspnoea, but only qualitative data were available. The criteria for discharge were absence of fever for at least 3 days, substantial improvement in both lungs in chest CT, clinical remission of respiratory symptoms, and two throat-swab samples negative for SARS-CoV-2 RNA obtained at least 24 h apart.
Definitions
Fever was defined as axillary temperature of at least 37·3°C. Sepsis and septic shock were defined according to the 2016 Third International Consensus Definition for Sepsis and Septic Shock.
Secondary infection was diagnosed when patients showed clinical symptoms or signs of pneumonia or bacteraemia and a positive culture of a new pathogen was obtained from lower respiratory tract specimens (qualified sputum, endotracheal aspirate, or bronchoalveolar lavage fluid) or blood samples after admission.
Ventilator-associated pneumonia was diagnosed according to the guidelines for treatment of hospital-acquired and ventilator-associated pneumonia.
Acute kidney injury was diagnosed according to the KDIGO clinical practice guidelines
and acute respiratory distress syndrome (ARDS) was diagnosed according to the Berlin Definition.
Acute cardiac injury was diagnosed if serum levels of cardiac biomarkers (eg, high-sensitivity cardiac troponin I) were above the 99th percentile upper reference limit, or if new abnormalities were shown in electrocardiography and echocardiography.
The illness severity of COVID-19 was defined according to the Chinese management guideline for COVID-19 (version 6.0).
Coagulopathy was defined as a 3-second extension of prothrombin time or a 5-second extension of activated partial thromboplastin time. Hypoproteinaemia was defined as blood albumin of less than 25 g/L. Exposure history was defined as exposure to people with confirmed SARS-CoV-2 infection or to the Wuhan seafood market.
Statistical analysis
Continuous and categorical variables were presented as median (IQR) and n (%), respectively. We used the Mann-Whitney U test, χ2 test, or Fisher’s exact test to compare differences between survivors and non-survivors where appropriate. To explore the risk factors associated with in-hospital death, univariable and multivariable logistic regression models were used. Considering the total number of deaths (n=54) in our study and to avoid overfitting in the model, five variables were chosen for multivariable analysis on the basis of previous findings and clinical constraints. Previous studies have shown blood levels of d-dimer and Sequential Organ Failure Assessment (SOFA) scores to be higher in critically ill or fatal cases, whereas lymphopenia and cardiovascular disease have been less commonly observed in non-critical or surviving patients with SARS-COV-2 infection.
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Similar risk factors, including older age, have been reported associated with adverse clinical outcomes in adults with SARS and Middle East respiratory syndrome (MERS).
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Some laboratory findings, including alanine aminotransferase (ALT), lactate dehydrogenase, high-sensitivity cardiac troponin I, creatine kinase, d-dimer, serum ferritin, and IL-6, might be unavailable in emergency circumstances. Therefore, we chose lymphocyte count, d-dimer, SOFA score, coronary heart disease, and age as the five variables for our multivariable logistic regression model.
Role of the funding source
Results
813 adult patients were hospitalised in Jinyintan Hospital or Wuhan Pulmonary Hospital with COVID-19 before Jan 31, 2020. After excluding 613 patients that were still hospitalised or not confirmed by SARS-CoV-2 RNA detection as of Jan 31, 2020, and nine inpatients without available key information in their medical records, we included 191 inpatients (135 from Jinyintan Hospital and 56 from Wuhan Pulmonary Hospital) in the final analysis. 54 patients died during hospitalisation and 137 were discharged. The median age of the 191 patients was 56·0 years (IQR 46·0–67·0), ranging from 18 years to 87 years, and most patients were male (table 1). Comorbidities were present in nearly half of patients, with hypertension being the most common comorbidity, followed by diabetes and coronary heart disease (table 1). The most common symptoms on admission were fever and cough, followed by sputum production and fatigue (table 1). Lymphocytopenia occurred in 77 (40%) patients. 181 (95%) patients received antibiotics and 41 (21%) received antivirals (lopinavir/ritonavir; table 2). Systematic corticosteroid and intravenous immunoglobulin use differed significantly between non-survivors and survivors (table 2). The comparison of characteristics, treatment, and outcomes of patients from the two hospitals are shown in the appendix (pp 2–4).
Total (n=191) | Non-survivor (n=54) | Survivor (n=137) | p value | ||
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Demographics and clinical characteristics | |||||
Age, years | 56·0 (46·0–67·0) | 69·0 (63·0–76·0) | 52·0 (45·0–58·0) | <0·0001 | |
Sex | .. | .. | .. | 0·15 | |
Female | 72 (38%) | 16 (30%) | 56 (41%) | .. | |
Male | 119 (62%) | 38 (70%) | 81 (59%) | .. | |
Exposure history | 73 (38%) | 14 (26%) | 59 (43%) | 0·028 | |
Current smoker | 11 (6%) | 5 (9%) | 6 (4%) | 0·21 | |
Comorbidity | 91 (48%) | 36 (67%) | 55 (40%) | 0·0010 | |
Hypertension | 58 (30%) | 26 (48%) | 32 (23%) | 0·0008 | |
Diabetes | 36 (19%) | 17 (31%) | 19 (14%) | 0·0051 | |
Coronary heart disease | 15 (8%) | 13 (24%) | 2 (1%) | <0·0001 | |
Chronic obstructive lung disease | 6 (3%) | 4 (7%) | 2 (1%) | 0·047 | |
Carcinoma | 2 (1%) | 0 | 2 (1%) | 0·37 | |
Chronic kidney disease | 2 (1%) | 2 (4%) | 0 | 0·024 | |
Other | 22 (12%) | 11 (20%) | 11 (8%) | 0·016 | |
Respiratory rate >24 breaths per min | 56 (29%) | 34 (63%) | 22 (16%) | <0·0001 | |
Pulse ≥125 beats per min | 2 (1%) | 2 (4%) | 0 | 0·024 | |
Systolic blood pressure <90 mm Hg | 1 (1%) | 0 | 1 (1%) | 0·53 | |
Fever (temperature ≥37·3°C) | 180 (94%) | 51 (94%) | 129 (94%) | 0·94 | |
Cough | 151 (79%) | 39 (72%) | 112 (82%) | 0·15 | |
Sputum | 44 (23%) | 14 (26%) | 30 (22%) | 0·55 | |
Myalgia | 29 (15%) | 8 (15%) | 21 (15%) | 0·93 | |
Fatigue | 44 (23%) | 15 (28%) | 29 (21%) | 0·33 | |
Diarrhoea | 9 (5%) | 2 (4%) | 7 (5%) | 0·67 | |
Nausea or vomiting | 7 (4%) | 3 (6%) | 4 (3%) | 0·40 | |
SOFA score | 2·0 (1·0–4·0) | 4·5 (4·0–6·0) | 1·0 (1·0–2·0) | <0·0001 | |
qSOFA score | 1·0 (0·0–1·0) | 1·0 (1·0–1·0) | 0·0 (0·0–1·0) | <0·0001 | |
CURB-65 score | 0·0 (0·0–2·0) | 2·0 (1·0–3·0) | 0·0 (0·0–1·0) | <0·0001 | |
0–1 | 141/188 (75%) | 16 (30%) | 125/134 (93%) | <0·0001 | |
2 | 32/188 (17%) | 23 (43%) | 9/134 (7%) | .. | |
3–5 | 15/188 (8%) | 15 (28%) | 0/134 | .. | |
Disease severity status | .. | .. | .. | <0·0001 | |
General | 72 (38%) | 0 | 72 (53%) | .. | |
Severe | 66 (35%) | 12 (22%) | 54 (39%) | .. | |
Critical | 53 (28%) | 42 (78%) | 11 (8%) | .. | |
Time from illness onset to hospital admission, days | 11·0 (8·0–14·0) | 11·0 (8·0–15·0) | 11·0 (8·0–13·0) | 0·53 | |
Laboratory findings | |||||
White blood cell count, × 109 per L | 6·2 (4·5–9·5) | 9·8 (6·9–13·9) | 5·2 (4·3–7·7) | <0·0001 | |
<4 | 32 (17%) | 5 (9%) | 27 (20%) | <0·0001 | |
4–10 | 119 (62%) | 24 (44%) | 95 (69%) | .. | |
>10 | 40 (21%) | 25 (46%) | 15 (11%) | .. | |
Lymphocyte count, × 109 per L | 1·0 (0·6–1·3) | 0·6 (0·5–0·8) | 1·1 (0·8–1·5) | <0·0001 | |
<0·8 | 77 (40%) | 41 (76%) | 36 (26%) | <0·0001 | |
Haemoglobin, g/L | 128·0 (119·0–140·0) | 126·0 (115·0–138·0) | 128·0 (120·0–140·0) | 0·30 | |
Anaemia | 29 (15%) | 14 (26%) | 15 (11%) | 0·0094 | |
Platelet count, × 109 per L | 206·0 (155·0–262·0) | 165·5 (107·0–229·0) | 220·0 (168·0–271·0) | <0·0001 | |
<100 | 13 (7%) | 11 (20%) | 2 (1%) | <0·0001 | |
Albumin, g/L | 32·3 (29·1–35·8) | 29·1 (26·5–31·3) | 33·6 (30·6–36·4) | <0·0001 | |
ALT, U/L | 30·0 (17·0–46·0) | 40·0 (24·0–51·0) | 27·0 (15·0–40·0) | 0·0050 | |
>40 | 59/189 (31%) | 26 (48%) | 33/135 (24%) | 0·0015 | |
Creatinine >133 μmol/L | 8/186 (4%) | 5 (9%) | 3/132 (2%) | 0·045 | |
Lactate dehydrogenase, U/L | 300·0 (234·0–407·0) | 521·0 (363·0–669·0) | 253·5 (219·0–318·0) | <0·0001 | |
>245 | 123/184 (67%) | 53 (98%) | 70/130 (54%) | <0·0001 | |
Creatine kinase, U/L | 21·5 (13·0–72·4) | 39·0 (19·5–151·0) | 18·0 (12·5–52·1) | 0·0010 | |
>185 | 22/168 (13%) | 11/52 (21%) | 11/116 (9%) | 0·038 | |
High-sensitivity cardiac troponin I, pg/mL | 4·1 (2·0–14·1) | 22·2 (5·6–83·1) | 3·0 (1·1–5·5) | <0·0001 | |
>28 | 24/145 (17%) | 23/50 (46%) | 1/95 (1%) | <0·0001 | |
Prothrombin time, s | 11·6 (10·6–13·0) | 12·1 (11·2–13·7) | 11·4 (10·4–12·6) | 0·0004 | |
<16 | 171/182 (94%) | 47 (87%) | 124/128 (97%) | 0·016 | |
≥16 | 11/182 (6%) | 7 (13%) | 4/128 (3%) | .. | |
D-dimer, μg/mL | 0·8 (0·4–3·2) | 5·2 (1·5–21·1) | 0·6 (0·3–1·0) | <0·0001 | |
≤0·5 | 55/172 (32%) | 4 (7%) | 51/118 (43%) | <0·0001 | |
>0·5 to ≤1 | 45/172 (26%) | 6 (11%) | 39/118 (33%) | .. | |
>1 | 72/172 (42%) | 44 (81%) | 28/118 (24%) | .. | |
Serum ferritin, μg/L | 722·0 (377·2–1435·3) | 1435·3 (728·9–2000·0) | 503·2 (264·0–921·5) | <0·0001 | |
>300 | 102/128 (80%) | 44/46 (96%) | 58/82 (71%) | 0·0008 | |
IL-6, pg/mL | 7·4 (5·3–10·8) | 11·0 (7·5–14·4) | 6·3 (5·0–7·9) | <0·0001 | |
Procalcitonin, ng/mL | 0·1 (0·1–0·1) | 0·1 (0·1–0·5) | 0·1 (0·1–0·1) | <0·0001 | |
<0·1 | 114/164 (70%) | 19/51 (37%) | 95/113 (84%) | <0·0001 | |
≥0·1 to <0·25 | 30/164 (18%) | 16/51 (31%) | 14/113 (12%) | .. | |
≥0·25 to <0·5 | 6/164 (4%) | 3/51 (6%) | 3/113 (3%) | .. | |
≥0·5 | 14/164 (9%) | 13/51 (25%) | 1/113 (1%) | .. | |
Imaging features | |||||
Consolidation | 112 (59%) | 40 (74%) | 72 (53%) | 0·0065 | |
Ground-glass opacity | 136 (71%) | 44 (81%) | 92 (67%) | 0·049 | |
Bilateral pulmonary infiltration | 143 (75%) | 45 (83%) | 98 (72%) | 0·090 |
Total (n=191) | Non-survivor (n=54) | Survivor (n=137) | p value | |
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Treatments | ||||
Antibiotics | 181 (95%) | 53 (98%) | 128 (93%) | 0·15 |
Antiviral treatment | 41 (21%) | 12 (22%) | 29 (21%) | 0·87 |
Corticosteroids | 57 (30%) | 26 (48%) | 31 (23%) | 0·0005 |
Intravenous immunoglobin | 46 (24%) | 36 (67%) | 10 (7%) | <0·0001 |
High-flow nasal cannula oxygen therapy | 41 (21%) | 33 (61%) | 8 (6%) | <0·0001 |
Non-invasive mechanical ventilation | 26 (14%) | 24 (44%) | 2 (1%) | <0·0001 |
Invasive mechanical ventilation | 32 (17%) | 31 (57%) | 1 (1%) | <0·0001 |
ECMO | 3 (2%) | 3 (6%) | 0 | 0·0054 |
Renal replacement therapy | 10 (5%) | 10 (19%) | 0 | <0·0001 |
Outcomes | ||||
Sepsis | 112 (59%) | 54 (100%) | 58 (42%) | <0·0001 |
Respiratory failure | 103 (54%) | 53 (98%) | 50 (36%) | <0·0001 |
ARDS | 59 (31%) | 50 (93%) | 9 (7%) | <0·0001 |
Heart failure | 44 (23%) | 28 (52%) | 16 (12%) | <0·0001 |
Septic shock | 38 (20%) | 38 (70%) | 0 | <0·0001 |
Coagulopathy | 37 (19%) | 27 (50%) | 10 (7%) | <0·0001 |
Acute cardiac injury | 33 (17%) | 32 (59%) | 1 (1%) | <0·0001 |
Acute kidney injury | 28 (15%) | 27 (50%) | 1 (1%) | <0·0001 |
Secondary infection | 28 (15%) | 27 (50%) | 1 (1%) | <0·0001 |
Hypoproteinaemia | 22 (12%) | 20 (37%) | 2 (1%) | <0·0001 |
Acidosis | 17 (9%) | 16 (30%) | 1 (1%) | <0·0001 |
ICU admission | 50 (26%) | 39 (72%) | 11 (8%) | <0·0001 |
ICU length of stay, days | 8·0 (4·0–12·0) | 8·0 (4·0–12·0) | 7·0 (2·0–9·0) | 0·41 |
Hospital length of stay, days | 11·0 (7·0–14·0) | 7·5 (5·0–11·0) | 12·0 (9·0–15·0) | <0·0001 |
Time from illness onset to fever, days | 1·0 (1·0–1·0) | 1·0 (1·0–1·0) | 1·0 (1·0–1·0) | 0·16 |
Time from illness onset to cough, days | 1·0 (1·0–3·0) | 1·0 (1·0–1·0) | 1·0 (1·0–4·0) | 0·30 |
Time from illness onset to dyspnoea, days | 7·0 (4·0–9·0) | 7·0 (4·0–10·0) | 7·0 (4·0–9·0) | 0·51 |
Time from illness onset to sepsis, days | 9·0 (7·0–13·0) | 10·0 (7·0–14·0) | 9·0 (7·0–12·0) | 0·22 |
Time from illness onset to ARDS, days | 12·0 (8·0–15·0) | 12·0 (8·0–15·0) | 10·0 (8·0–13·0) | 0·65 |
Time from illness onset to ICU admission, days | 12·0 (8·0–15·0) | 12·0 (8·0–15·0) | 11·5 (8·0–14·0) | 0·88 |
Time from illness onset to corticosteroids treatment, days | 12·0 (10·0–16·0) | 13·0 (10·0–17·0) | 12·0 (10·0–15·0) | 0·55 |
Time from illness onset to death or discharge, days | 21·0 (17·0–25·0) | 18·5 (15·0–22·0) | 22·0 (18·0–25·0) | 0·0003 |
Duration of viral shedding after COVID-19 onset, days | 20·0 (16·0–23·0) | 18·5 (15·0–22·0) | 20·0 (17·0–24·0) | 0·024 |
In univariable analysis, odds of in-hospital death was higher in patients with diabetes or coronary heart disease (table 3). Age, lymphopenia, leucocytosis, and elevated ALT, lactate dehydrogenase, high-sensitivity cardiac troponin I, creatine kinase, d-dimer, serum ferritin, IL-6, prothrombin time, creatinine, and procalcitonin were also associated with death (table 3).
Univariable OR (95% CI) | p value | Multivariable OR (95% CI) | p value | ||
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Demographics and clinical characteristics | |||||
Age, years | 1·14 (1·09–1·18) | <0·0001 | 1·10 (1·03–1·17) | 0·0043 | |
Female sex (vs male) | 0·61 (0·31–1·20) | 0·15 | .. | .. | |
Current smoker (vs non-smoker) | 2·23 (0·65–7·63) | 0·20 | .. | .. | |
Comorbidity present (vs not present) | |||||
Chronic obstructive lung disease | 5·40 (0·96–30·40) | 0·056 | .. | .. | |
Coronary heart disease | 21·40 (4·64–98·76) | <0·0001 | 2·14 (0·26–17·79) | 0·48 | |
Diabetes | 2·85 (1·35–6·05) | 0·0062 | .. | .. | |
Hypertension | 3·05 (1·57–5·92) | 0·0010 | .. | .. | |
Respiratory rate, breaths per min | |||||
≤24 | 1 (ref) | .. | .. | .. | |
>24 | 8·89 (4·34–18·19) | <0·0001 | .. | .. | |
SOFA score | 6·14 (3·48–10·85) | <0·0001 | 5·65 (2·61–12·23) | <0·0001 | |
qSOFA score | 12·00 (5·06–28·43) | <0·0001 | .. | .. | |
Laboratory findings | |||||
White blood cell count, × 109 per L | |||||
<4 | 0·73 (0·26–2·10) | 0·56 | .. | .. | |
4–10 | 1 (ref) | .. | .. | .. | |
>10 | 6·60 (3·02–14·41) | <0·0001 | .. | .. | |
Lymphocyte count, × 109 per L | 0·02 (0·01–0·08) | <0·0001 | 0·19 (0·02–1·62) | 0·13 | |
ALT, U/L | |||||
≤40 | 1 (ref) | .. | .. | .. | |
>40 | 2·87 (1·48–5·57) | 0·0018 | .. | .. | |
Creatinine, μmol/L | |||||
≤133 | 1 (ref) | .. | .. | .. | |
>133 | 4·39 (1·01–19·06) | 0·048 | .. | .. | |
Lactate dehydrogenase, U/L | |||||
≤245 | 1 (ref) | .. | .. | .. | |
>245 | 45·43 (6·10–338·44) | 0·0002 | .. | .. | |
Creatine kinase, U/L | |||||
≤185 | 1 (ref) | .. | .. | .. | |
>185 | 2·56 (1·03–6·36) | 0·043 | .. | .. | |
High-sensitivity cardiac troponin I, pg/mL | |||||
≤28 | 1 (ref) | .. | .. | .. | |
>28 | 80·07 (10·34–620·36) | <0·0001 | .. | .. | |
D-dimer, μg/mL | |||||
≤0·5 | 1 (ref) | .. | 1 (ref) | .. | |
> 0·5 | 1·96 (0·52–7·43) | 0·32 | 2·14 (0·21–21·39) | 0·52 | |
> 1 | 20·04 (6·52–61·56) | <0·0001 | 18·42 (2·64–128·55) | 0·0033 | |
Prothrombin time, s | |||||
<16 | 1 (ref) | .. | .. | .. | |
≥16 | 4·62 (1·29–16·50) | 0·019 | .. | .. | |
Serum ferritin, μg/L | |||||
≤300 | 1 (ref) | .. | .. | .. | |
>300 | 9·10 (2·04–40·58) | 0·0038 | .. | .. | |
IL-6, pg/mL | 1·12 (1·03–1·23) | 0·0080 | .. | .. | |
Procalcitonin, ng/mL | 13·75 (1·81–104·40) | 0·011 | .. | .. |
For survivors, the median duration of viral shedding was 20·0 days (IQR 17·0–24·0) from illness onset, but the virus was continuously detectable until death in non-survivors (table 2; figure 1). The shortest observed duration of viral shedding among survivors was 8 days, whereas the longest was 37 days. Among 29 patients who received lopinavir/ritonavir and were discharged, the median time from illness onset to initiation of antiviral treatment was 14·0 days (IQR 10·0–17·0) and the median duration of viral shedding was 22·0 days (18·0–24·0). The median duration of viral shedding was 19·0 days (17·0–22·0) in patients with severe disease status and 24·0 days (22·0–30·0) in patients with critical disease status.
Major laboratory markers were tracked from illness onset (figure 2). Baseline lymphocyte count was significantly higher in survivors than non-survivors; in survivors, lymphocyte count was lowest on day 7 after illness onset and improved during hospitalisation, whereas severe lymphopenia was observed until death in non-survivors. Levels of d-dimer, high-sensitivity cardiac troponin I, serum ferritin, lactate dehydrogenase, and IL-6 were clearly elevated in non-survivors compared with survivors throughout the clinical course, and increased with illness deterioration (figure 2). In non-survivors, high-sensitivity cardiac troponin I increased rapidly from day 16 after disease onset, whereas lactate dehydrogenase increased for both survivors and non-survivors in the early stage of illness, but decreased from day 13 for survivors.
Discussion
Previously, older age has been reported as an important independent predictor of mortality in SARS and MERS.
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The current study confirmed that increased age was associated with death in patients with COVID-19. Previous studies in macaques inoculated with SARS-CoV found that older macaques had stronger host innate responses to virus infection than younger adults, with an increase in differential expression of genes associated with inflammation, whereas expression of type I interferon beta was reduced.
The age-dependent defects in T-cell and B-cell function and the excess production of type 2 cytokines could lead to a deficiency in control of viral replication and more prolonged proinflammatory responses, potentially leading to poor outcome.
SOFA score is a good diagnostic marker for sepsis and septic shock, and reflects the state and degree of multi-organ dysfunction.
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Although bacterial infections are usually regarded as a leading cause of sepsis, viral infection can also cause sepsis syndrome. Previously, we determined that sepsis occurred in nearly 40% of adults with community-acquired pneumonia due to viral infection.
In the current study, we found that more than half of patients developed sepsis. Additionally, we found that more than 70% of patients had white blood cell count below 10·0 × 109 per L or procalcitonin below 0·25 ng/mL, and no bacterial pathogens were detected in these patients on admission. Sepsis was a common complication, which might be directly caused by SARS-CoV-2 infection, but further research is needed to investigate the pathogenesis of sepsis in COVID-19 illness.
Cardiac complications, including new or worsening heart failure, new or worsening arrhythmia, or myocardial infarction are common in patients with pneumonia. Cardiac arrest occurs in about 3% of inpatients with pneumonia.
Risk factors of cardiac events after pneumonia include older age, pre-existing cardiovascular diseases, and greater severity of pneumonia at presentation.
Coronary heart disease has also been found to be associated with acute cardiac events and poor outcomes in influenza and other respiratory viral infections.
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In this study, increased high-sensitivity cardiac troponin I during hospitalisation was found in more than half of those who died. The first autopsy of a 53-year-old woman with chronic renal failure in Jinyintan Hospital showed acute myocardial infarction (data not published; personal communication with a pathologist from the Chinese Academy of Science). About 90% of inpatients with pneumonia had increased coagulation activity, marked by increased d-dimer concentrations.
In this study, we found d-dimer greater than 1 μg/mL is associated with fatal outcome of COVID-19. High levels of d-dimer have a reported association with 28-day mortality in patients with infection or sepsis identified in the emergency department.
Contributory mechanisms include systemic pro-inflammatory cytokine responses that are mediators of atherosclerosis directly contributing to plaque rupture through local inflammation, induction of procoagulant factors, and haemodynamic changes, which predispose to ischaemia and thrombosis.
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In addition, angiotensin converting enzyme 2, the receptor for SARS-CoV-2, is expressed on myocytes and vascular endothelial cells,
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so there is at least theoretical potential possibility of direct cardiac involvement by the virus. Of note, interstitial mononuclear inflammatory infiltrates in heart tissue has been documented in fatal cases of COVID-19, although viral detection studies were not reported.
The level and duration of infectious virus replication are important factors in assessing the risk of transmission and guiding decisions regarding isolation of patients. Because coronavirus RNA detection is more sensitive than virus isolation, most studies have used qualitative or quantitative viral RNA tests as a potential marker for infectious coronavirus. For SARS-CoV, viral RNA was detected in respiratory specimens from about a third of patients as long as 4 weeks after disease onset.
Similarly, the duration of MERS-CoV RNA detection in lower respiratory specimans persisted for at least 3 weeks,
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whereas the duration of SARS-CoV-2 RNA detection has not been well characterised. In the current study, we found that the detectable SARS-CoV-2 RNA persisted for a median of 20 days in survivors and that it was sustained until death in non-survivors. This has important implications for both patient isolation decision making and guidance around the length of antiviral treatment. In severe influenza virus infection, prolonged viral shedding was associated with fatal outcome and delayed antiviral treatment was an independent risk factor for prolonged virus detection.
Similarly, effective antiviral treatment might improve outcomes in COVID-19, although we did not observe shortening of viral shedding duration after lopinavir/ritonavir treatment in the current study. Randomised clinical trials for lopinavir/ritonavir (ChiCTR2000029308) and intravenous remdesivir (NCT04257656, NCT04252664) in treatment of COVID-19 are currently in progress.
Our study has some limitations. First, due to the retrospective study design, not all laboratory tests were done in all patients, including lactate dehydrogenase, IL-6, and serum ferritin. Therefore, their role might be underestimated in predicting in-hospital death. Second, patients were sometimes transferred late in their illness to the two included hospitals. Lack of effective antivirals, inadequate adherence to standard supportive therapy, and high-dose corticosteroid use might have also contributed to the poor clinical outcomes in some patients. Third, the estimated duration of viral shedding is limited by the frequency of respiratory specimen collection, lack of quantitative viral RNA detection, and relatively low positive rate of SARS-CoV-2 RNA detection in throat-swabs.
Fourth, by excluding patients still in hospital as of Jan 31, 2020, and thus relatively more severe disease at an earlier stage, the case fatality ratio in our study cannot reflect the true mortality of COVID-19. Last but not least, interpretation of our findings might be limited by the sample size. However, by including all adult patients in the two designated hospitals for COVID-19, we believe our study population is representative of cases diagnosed and treated in Wuhan.
Supplementary Material
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Supplementary appendix
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Figures
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Figure 1Clinical courses of major symptoms and outcomes and duration of viral shedding from illness onset in patients hospitalised with COVID-19
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Figure 2Temporal changes in laboratory markers from illness onset in patients hospitalised with COVID-19
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