Edited by: Rukhsana Ahmed, University at Albany, United States
Reviewed by: Meghan Starolis, Quest Diagnostics, United States; Jing Yuan, Children’s Hospital of Capital Institute of Pediatrics, China
*Correspondence: Wandong Hong,
This article was submitted to Clinical Microbiology, a section of the journal Frontiers in Cellular and Infection Microbiology
†These authors have contributed equally to this work
This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
The objective of this study was to investigate the clinical features and laboratory findings of patients with and without critical COVID-19 pneumonia and identify predictors for the critical form of the disease.
Demographic, clinical, and laboratory data of 63 COVID-19 pneumonia patients were retrospectively reviewed. Laboratory parameters were also collected within 3–5 days, 7–9 days, and 11–14 days of hospitalization. Outcomes were followed up until March 12, 2020.
Twenty-two patients developed critically ill pneumonia; one of them died. Upon admission, older patients with critical illness were more likely to report cough and dyspnoea with higher respiration rates and had a greater possibility of abnormal laboratory parameters than patients without critical illness. When compared with the non-critically ill patients, patients with serious illness had a lower discharge rate and longer hospital stays, with a trend towards higher mortality. The interleukin-6 level in patients upon hospital admission was important in predicting disease severity and was associated with the length of hospitalization.
Many differences in clinical features and laboratory findings were observed between patients exhibiting non-critically ill and critically ill COVID-19 pneumonia. Non-critically ill COVID-19 pneumonia also needs aggressive treatments. Interleukin-6 was a superior predictor of disease severity.
香京julia种子在线播放
The mortality rate in critically ill patients is low.
Different severity of diseases has different clinical and laboratory results.
Non-critically ill COVID-19 pneumonia also needs aggressive treatments.
Interleukin-6 is a good predictor of critically ill COVID-19 pneumonia.
Interleukin-6 is associated with length of hospitalization
Novel coronavirus (COVID-19) pneumonia is a newly recognized disease that has spread rapidly throughout China, originating from Wuhan (Hubei province) and expanding to other provinces within the country and around the world (
Therefore, our study aimed to investigate the clinical features of COVID-19 pneumonia in patients who were critically ill
We conducted a retrospective cohort study in the First Affiliated Hospital of Wenzhou Medical University in mainland China. All patients with confirmed COVID-19 pneumonia between January 29, 2020 and March 12, 2020 were eligible for inclusion in this study. A confirmed case of COVID-19 was defined as exhibiting a positive result on high-throughput sequencing or real-time reverse-transcriptase–polymerase chain reaction (RT-PCR) assay of nasal and pharyngeal swab specimens (
According to the China Guidelines for the Diagnosis and Treatment Plan of COVID-19 Infection (
For comparative analysis, we also defined the degree of severity of critically ill
The epidemiological, clinical, laboratory, radiologic, and treatment and outcomes data during the course of hospitalization were obtained with data collection forms from electronic medical records. The date of disease onset was defined as the day when the symptoms were noticed (
This study protocol was approved by the Ethics Committee of the First Affiliated Hospital of Wenzhou Medical University. It was performed according to the principles expressed in the Declaration of Helsinki, and informed consent was obtained from all the subjects.
The Shapiro-Wilk test was used to determine if the continuous data follow a normal distribution (
The area under the receiver operating characteristic (ROC) curve (AUC) was used to evaluate the performance of the predictors. A larger AUC value is indicative of greater diagnostic accuracy of a variable (
Pearson correlation and linear regression analysis were used to investigate the relationship between predictor and length of hospitalization. The variables with skewed distribution were log-transformed for correlation analysis when necessary. Differences were considered to be statistically significant if the two-tailed P value was less than 0.05.
A total of 63 hospitalized patients confirmed to have COVID-19 pneumonia were enrolled in our study. Twenty-eight patients were imported cases who had traveled from Wuhan City (
Baseline characteristics of 63 patients infected with COVID-19 pneumonia on admission.
Characteristic | Total number (N=63) | Non- Critically ill (N=41) | Critically ill (N=22) | P-value |
---|---|---|---|---|
Median age, years (IQR) | 56 ± 15 | 52·9 ± 14·9 | 61·5 ± 14·7 | 0·034 |
Male sex, N (%) | 41 (65·1) | 26 (63·4) | 15 (68·2) | 0·705 |
Time from symptoms to admission, days | 6·9 ± 3·7 | 6·9 ± 4·0 | 6·8 ± 2·8 | 0·939 |
|
0.847 | |||
Travelled from Wuhan, N (%) | 25 (38·1) | 16 (39·0) | 9 (40·9) | |
Contacted to case, N (%) | 14 (22·2) | 10 (24·4) | 4 (18·2) | |
Occult history, N (%) | 24 (39·7) | 15 (36·6) | 9 (40·9) | |
Median BMI | 25·2 (22·3–26·9) (N=40) | 24·5 (22.1–26.4) (N=28) | 25·9 (24·5–29·0) (N=12) | 0·165 |
Smoking, N (%) | 11 (17·5) | 6 (14·6) | 5 (22·7) | 0·420 |
Alcohol, N (%) | 10 (16·0) | 6 (14·6) | 4 (18·2) | 0·713 |
|
27 (42·9) | 15 (36·6) | 12 (54·6) | 0·170 |
Hypertension, N (%) | 21 (33·3) | 12 (29·3) | 9 (40·9) | 0·407 |
Diabetes mellitus, N (%) | 9 (14·3) | 4 (9·8) | 5 (22·7) | 0·256 |
Malignancy, N (%) | 2 (3·2) | 0 (0) | 2 (9·1) | 0·118 |
Cardiovascular, N (%) | 2 (3·2) | 2 (4·9) | 0 (0) | 0·538 |
Neurologic, N (%) | 1 (1·6) | 1 (2·4) | 0 (0) | 1·000 |
Pulmonary, N (%) | 1 (1·6) | 0 (0) | 1 (4·5) | 0·349 |
Hepatitis virus carrier, N (%) | 1 (1·6) | 1 (2·4) | 0 (0) | 1·000 |
|
||||
Fever, N (%) | 62 (98·4) | 40 (97·6) | 22 (100) | 1·000 |
Cough, N (%) | 39 (61·9) | 21 (51·2) | 18 (81·8) | 0·028 |
Sputum, N (%) | 22 (34·9) | 12 (29·3) | 10 (45·5) | 0·269 |
Dyspnoea, N (%) | 17 (27·0) | 4 (9·8) | 13 (59·1) | <0·001 |
Chills, N (%) | 15 (23·8) | 12 (29·3) | 3 (13·6) | 0·222 |
Fatigue, N (%) | 8 (12·7) | 4 (9·8) | 4 (18·2) | 0·434 |
Sore throat, N (%) | 7 (11·1) | 6 (14·6) | 1 (4·6) | 0·405 |
Headache, N (%) | 3 (4·8) | 3 (7·3) | 0 (0) | 0·546 |
Myalgia, N (%) | 4 (6·4) | 2 (4·9) | 2 (9·1) | 0·606 |
Diarrhea, N (%) | 3 (4·8) | 2 (4·9) | 1 (4·6) | 1·000 |
|
||||
Distribution of temperature | 0.128 | |||
<37·0, N (%) | 16 (25·4) | 14 (34·1) | 2 (9·1) | |
37·0-37·4, N (%) | 17 (27·0) | 9 (22·0) | 8 (36·4) | |
37·5-38·0, N (%) | 15 (23·8) | 10 (24·4) | 5 (22·7) | |
38·1-39, N (%) | 14 (22·2) | 7 (17·1) | 7 (31·8) | |
>39, N (%) | 1 (1·6) | 1 (2·4) | 0 (0) | |
Mean arterial pressure (IQR), mmHg | 99·0 ± 11·5 | 98·6 ± 11·4 | 99·6 ± 11·9 | 0·741 |
Heart rate, bpm | 87·1 ± 16·0 | 88·2 ± 16·7 | 84·9 ± 14·7 | 0·438 |
Respiratory rate | 20 (20–23) | 20 (20–20) | 23·5 (20–28) | 0·004 |
|
0·538 | |||
Unilateral pneumonia | 2 (3·2) | 2 (4·9) | 0 (0) | |
Bilateral pneumonia | 61 (96·8) | 39 (95·1) | 22 (100) |
Data are shown either as the number of observations, percentage, or median and interquartile range.
As shown in
Classifications of the severity of COVID-19-related pneumonia on admission, types of oxygen inhalation, and clinical outcomes. Light yellow indicates COVID-19 pneumonia patients with non-critical illness; light red indicated patients with critical illness.
As shown in
Upon admission, data regarding levels of D-dimer (full data available for 58 patients), B-type natriuretic peptide (full data available for 62 patients), and interleukin-6 (IL-6) (full data available for 46 patients) were obtained. As shown in
Comparison of laboratory findings, treatment measures and clinical outcomes between critically and non-critically ill COVID-19 pneumonia patient groups.
Characteristic | Normal range | Non-Critically ill (N=41) | Critically ill(N=22) | P-value |
---|---|---|---|---|
|
||||
Leukocyte (109/L) | 3.5–9.5 | 5·1 (4·3–7.2) | 9·5 (7·8–12·4) | 0·001 |
Lymphocyte (109/L) | 1.1–3.2 | 0·9 (0·72–1·17) | 0·67 (0·44–1·07) | 0·059 |
Neutrophil (109/L) | 1.80–6.3 | 3·69 (2·81–5·45) | 8·06 (5·13–9·84) | 0·002 |
Platelet (109/L) | 125–350 | 219 (168–296) | 196 (155–231) | 0·056 |
Total bilirubin, mmol/L | 0–20 | 11 (8–15) | 12·5 (8–17) | 0·406 |
Alanine aminotransferase, U/L | 9–50 | 24 (20–42) | 38·5 (21–69) | 0·217 |
Aspartate transaminase, U/L | 15–40 | 28 (23–38) | 50 (35–83) | 0·001 |
Albumin, (mg/dL) | 40.0–55.0 | 34·4 ± 4·6 | 30·8 ± 3·7 | 0·002 |
Blood urea nitrogen, mmol/L | 2.8–7.2 | 4·7 (3·4–5·9 | 5·5 (4·9–6·9) | 0·014 |
Creatinine, μmol/L | 44–97 | 60 (55–67) | 68·5 (58–83) | 0·030 |
Glucose, mmol/L | 3.9–6.1 | 7·4 (5·7–10·7) | 9·3 (8–9·6) | 0·121 |
Prothrombin time | 11.5–14.6 | 15·9 (15·3–16·8) | 16·2 (15·7–16·8) | 0·829 |
Fibrinogen (N=57), g/L | 2.00–4.00 | 5·35 (4·65–6·35) (N=38) | 6·05 (5·16–6·84) (N=19) | 0·101 |
D-dimer (N=58), mg/L | 0.00–0.50 | 0·68 (0·48–0·98) (N=36) | 1·14 (0·68–1·47) (N=22) | 0·009 |
Creatine kinase, U/L | 0.00–4.87 | 69 (52–90) | 147·5 (64–283) | 0·014 |
B-type natriuretic peptide (N=62), pg/ml | 0.00–125.0 | 18·5 (10–53·5) (N=40) | 64·5 (19–152) (N=22) | 0·002 |
C-reactive protein, mg/L | 0.0–6.0 | 20·4 (14·9–47·6) | 54 (24·1–90) | 0·021 |
Procalcitonin, ng/mL | 0-0.5 | 0·06 (0·04–0·08) | 0·12 (0·06–0·20) | 0·001 |
Interleukin-6 (N=46), pg/ml | <3 | 8·4 (4·0–32·2) (N=30) | 76·1 (32·2–103·1) (N=16) | <0·001 |
|
||||
High flow nasal cannula, N (%) | 0 | 18 (81·8) | <0·001 | |
Mechanical ventilation, N (%) | 0 | 16 (72·7) | <0·001 | |
Non-invasive, N (%) | 0 | 14 (63·6) | <0·001 | |
invasive, N (%) | 0 | 10 (45·5) | <0·001 | |
Extracorporeal membrane oxygenation, N (%) | 0 | 6 (27·3) | <0·001 | |
Antibiotics, N (%) | 31 (75·6) | 21 (95·5) | 0·079 | |
Antiviral, N (%) | ||||
Kaletra, N (%) | 33 (80·5) | 19 (86·4) | 0·733 | |
Arbidol, N (%) | 39 (95·1) | 21 (95·5) | 1·000 | |
methylprednisolone, N (%) | 8 (19·5) | 19 (86·4) | 0·001 | |
thymosin alpha 1, N (%) | 10 (24·4) | 16 (72·7) | <0·001 | |
Intravenous immunoglobulin, N (%) | 8 (19·5) | 13 (59·1) | <0·001 | |
blood plasma transfusion, N (%) | 1 (2·4) | 11 (50·0) | <0·001 | |
Intravenous albumin, N (%) | 22 (53·7) | 21 (95·5) | 0·001 | |
|
||||
Hospitalization, N (%) | 0 (0) | 5 (22·7) | 0·004 | |
Discharge, N (%) | 41 (100) | 15 (68·2) | <0·001 | |
Hospital days, N (%) | 17·2 ± 6·7 | 24·1 ± 5·5 | <0·001 | |
Death, N (%) | 0 (0) | 1 (4.5) | 0·118 |
*Patients may receive more than one treatment item.
As shown in
Longitudinal analysis of twelve laboratory parameters altered during the hospitalization in critically and non-critically ill patients.
A high flow nasal cannula was initially used in the treatment of 18 patients, of which 6 belonged to the critically ill group and strictly required a high flow nasal cannula, while the rest (12 patients) were switched to mechanical ventilation or extracorporeal membrane oxygenation (ECMO) (
A total of 52 (82·5%) patients received empirical antibiotic therapy (moxifloxacin, 33 [52·4%]; tazocin, 18 [18·6%]; ceftazidime, 6 [9·5%]; and Piperacillin, 6 [9·5%]) and antiviral therapy (Kaletra, 52 [82·5%] and Arbidol, 60 [95·2%]). Twenty-seven (42·9%) patients were given systematic methylprednisolone, while 26 (41·3%) patients received thymosin alpha 1. Additionally, intravenous immunoglobulin, blood plasma transfusion, and intravenous albumin were administered in 21 (33·3%), 12 (19·1%), and 43 (68·3%) patients, respectively. When compared to the non-critically ill group of patients, critically ill patients were given a higher dose of methylprednisolone, thymosin alpha 1, intravenous immunoglobulin, blood plasma transfusion, and intravenous albumin therapy (
As of March 12, 2020, six critically ill patients were still hospitalized. Among these, four had been transferred to the general wards because of improved condition, while the remaining two patients, who are 79 and 92 years old, respectively, and are both supported by ECMO, are still in the ICU. A total of 56 patients (88.9%) have been discharged, and one patient (1·6%) died. The patient who died was 79 years old and underwent ECMO therapy before death. When compared with the non-critically ill patient group, critically ill patients had a lower discharge rate (68·2%
Upon admission, the parameters that reached a statistically significant difference between patients with and without critical illness include age, presence of cough and dyspnoea, respiratory rate, white blood cell counts, neutrophil counts, and levels of aspartate transaminase, albumin, blood urea nitrogen, creatine, D-dimer, creatine kinase, B-type natriuretic peptide, C-reactive protein, procalcitonin, and interleukin-6. These were evaluated as potential predictors of severe COVID-19 pneumonia. Based on the ROC curve analysis, among single predictors, interleukin-6 has the highest AUC (0·85), indicative of excellent diagnostic accuracy (
Forest plot for accuracy of various markers in predicting critical COVID-19-related pneumonia. Each marker is plotted as an area under the curve of the receiver operating characteristic curve (AUC) with a 95% confidence interval.
Relationship between IL-6 levels and length of hospitalization of COVID-19-related pneumonia patients (data were available for 46 patients).
It was also inferred from the ROC curve analysis that the optimum cut-off value for interleukin-6 was 77·5 pg/mol. The sensitivity, specificity, positive likelihood ratio, negative likelihood ratio, positive predictive value, negative predictive value, and diagnostic accuracy were 50, 96·7, 15, 0·52, 88·9, 78·4, and 80·4%, respectively.
Using a cut-off value of 77·5 and the incidence of severe pneumonia (34·8% in this study) as the pre-test probability, the resulting Fagan plot (
Fagan plot of IL-6 for the hospital stay prediction of critically ill COVID-19 patients (data were available for 46 patients).
The earliest patient was an imported case who had a history of travel from Wuhan City, and the latest patient had an occult epidemic history (
On average, critically ill patients were shown to be older than non-critically ill patients (61·5
Patients belonging to the critically ill group had higher white blood cell counts, neutrophil counts, and D-dimer levels than patients in the non-critically ill group. This indicated that severely ill patients get a stronger inflammatory response, as well as activation of coagulation induced by viral infection. Lymphocytopenia may be associated with cellular immune deficiency. Yang et al. suggested that the severity of lymphocytopenia may reflect the severity of COVID-2019 infection (
Rapid production of IL-6 contributes to host defense during infection and tissue injury, but excessive IL-6 production causes severe inflammatory diseases (
Yang et al. suggested that for non-critically ill patients, close follow-up is likely to be sufficient to manage the disease (
Until now, no specific treatment has been recommended for coronavirus infections, except for meticulous supportive care (
When compared with the non-critically ill patients in our study, the critically ill ones received higher levels of methylprednisolone (86·4%
When compared with the non-critically ill patients, critically ill ones had a lower discharge rate (68·2%
The limitation of this study is that it is a retrospective study from a single center, and the sample size was small. Patients had a variety of different treatments (for example: antivirals, antibiotics, intravenous immunoglobulin, blood plasma transfusion, and intravenous albumin). This made it very difficult to interpret any other outcome data objectively. Therefore, it would be interesting to conduct a randomized clinical trial to assess the effect of different therapeutic strategies for patients with or without COVID-19 pneumonia in future studies. Additionally, only patients with pneumonia were enrolled, so our results may be not applicable to patients without pneumonia.
In conclusion, both critically ill and non-critically ill COVID-19 pneumonia patients need close monitoring and aggressive treatments. There was a statistically significant difference between critically ill and non-critically ill COVID-19 pneumonia patients in terms of age, some symptoms, laboratory findings, treatments, and outcomes. Interleukin-6 levels upon admission is a good predictor of the disease, and it is associated with the length of hospitalization.
The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.
This study protocol was approved by the Ethics Committee of the First Affiliated Hospital of Wenzhou Medical University. The committee decided to waive the need for written informed consent from the participants studied in this analysis as the data were analyzed retrospectively and anonymously.
WH conceived the study and carried out the majority of the work. WH, QC, SQ, YW, and JP participated in data collection. WH conducted data analysis and drafted the manuscript. ZB, VZ, MZ, and JP helped to finalize the manuscript. All authors contributed to the article and approved the submitted version.
This work was supported by Wenzhou Science and Technology Bureau (Number: Y2020010) and Wenzhou Key Technology Breakthrough Program on Prevention and Treatment for COVID-19 Epidemic, No. ZG2020012.
The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
The Supplementary Material for this article can be found online at:
Bar graph depicting travel history of patients with COVID-19-related pneumonia.
Representative computed tomography images from a patient with COVID-19-related pneumonia.