Correlation between clinical course and radiographic development on CT scan in patients with COVID-19.

Background: To analyze the correlation between clinical course and radiographic development on computed tomography (CT) in patients with confirmed coronavirus disease 2019 (COVID-19) and to provide more evidence for treatment. Methods: This retrospective, observational, cohort study enrolled 49 patients with Reverse transcription-polymerase chain reaction (RT-PCR)-confirmed COVID-19, which included 30 patients admitted to the intensive care unit (ICU) of Wuhan Third Hospital and 19 patients either admitted to or receiving telemedicine consultation from Shanghai General Hospital, Shanghai Xuhui Dahua Hospital, and hospitals in other provinces. CT scans were performed in all enrolled patients and the radiographic features including simple ground-glass opacities (GGOs), GGO with interlobular septal thickening, consolidations with GGO, and consolidations only were monitored by repeating the CT. The progression of these radiographic features was analyzed in combination with their clinical staging and the time interval between onset of symptoms to CT. Results: Based on illness severity, the 49 patients were classified into four stages: mild (n = 6), moderate (n = 12), severe (n = 16), and critically ill (n = 15). The CT findings were classified into three phases: early (n = 5), progression (n = 39), and recovery (n = 5). Among the 49 patients, 9 had bilateral diffuse GGO or diffuse consolidations (white lungs) and were counted as 18 lesions. Three patients had no abnormal findings on initial CT, but their repeat CT showed new lesions. In all, we identified 892 lesions including simple GGO, GGO with interlobular septal thickening, consolidations with GGO, and consolidations only. Conclusions: Most patients had pulmonary lesions on the posterior, inferior, and peripheral lung fields on CT. The development of GGO with interlobular septal thickening, GGO with consolidations, and consolidations only happened mainly between day 8 and 14. The emergence of consolidations may suggest the progression to the severe phase of the illness, whereas simple consolidations or "white lung" may suggest a critically ill phase.

[Thymosin alpha 1 for the adjuvant treatment of coronavirus disease 2019: a retrospective cohort study].

OBJECTIVE: To evaluate the effect of thymosin alpha 1 on the prognosis of patients with coronavirus disease 2019 (COVID-19). METHODS: A retrospective cohort study was performed to collect clinical data of 95 patients treated by Shanghai Aid Medical Team in Wuhan Third Hospital during January 31, 2020 and March 4, 2020, who were confirmed COVID-19. They were divided into two groups according to whether they were treated with thymosin alpha 1 after admission. The 28-day mortality (primary outcome), and 28-ventilator-free-day, lymphocyte count (LYM) level, C-reactive protein (CRP) level (secondary outcomes) were compared between two groups. Survival analysis was performed using the Kaplan-Meier curve. The effect of thymosin alpha 1 on 28-day survival was evaluated with Cox regression model. RESULTS: Among the 95 patients, there were 31 cases in thymosin group and 64 cases in non-thymosin group; 29 patients died 28 days after admission, including 11 cases (35.5%) in thymosin group and 18 cases (28.1%) in non-thymosin group. Kaplan-Meier survival curve showed that thymosin alpha 1 could improve the 28-day survival of patients with COVID-19, but the univariate Cox model analysis showed that the difference was not statistically significant [hazard ratio (HR) = 0.48, 95% confidence interval (95%CI) was 0.20-1.14, P = 0.098]; multivariate Cox model analysis showed that thymosin alpha 1 was the factor to improve the 28-day mortality (HR = 0.15, 95%CI was 0.04-0.55, P = 0.004), old age (HR = 1.10, 95%CI was 1.05-1.15, P < 0.001), accompanied by chronic renal dysfunction (HR = 42.35, 95%CI was 2.77-648.64, P = 0.007), decrease of LYM at admission (HR = 0.15, 95%CI was 0.04-0.60, P = 0.007) and the use of methylprednisolone (HR = 4.59, 95%CI was 1.26-16.67, P = 0.021) were also risk factors for the increase of 28-day mortality. The use of immunoglobulin and antiviral drugs abidol and ganciclovir did not affect the 28-day mortality. After adjustment for age, gender, LYM and other factors, weighted multivariate Cox analysis model showed thymosin alpha 1 could significantly improve the 28-day survival of COVID-19 patients (HR = 0.45, 95%CI was 0.25-0.84, P = 0.012). In terms of secondary outcomes, no statistical difference (all P > 0.05) was found between two groups in days without ventilator at 28 days after admission (days: 17.97±13.56 vs. 20.09±12.67) and the increase of LYM at 7 days after admission [×109/L: -0.07 (-0.23, 0.43) vs. 0.12 (-0.54, 0.41)]. But the decrease of CRP at 7 days after admission in thymosin alpha group was significantly greater than that in non-thymosin group [mg/L: 39.99 (8.44, 82.22) vs. 0.53 (-7.78, 22.93), P < 0.05]. CONCLUSION: Thymosin alpha 1 may improve 28-day mortality and inflammation state in COVID-19 patients.

[Comparative analysis of clinical features between severe coronavirus disease 2019 and severe community acquired pneumonia].

OBJECTIVE: To compare and analyze the clinical features of patients with severe coronavirus disease 2019 (sCOVID-19) and severe community acquired pneumonia (sCAP) who meet the diagnostic criteria for severe pneumonia of the Infectious Diseases Society of America/American Thoracic Society (IDSA/ATS). METHODS: A retrospective comparative analysis of the clinical records of 116 patients with sCOVID-19 admitted to the department of critical care medicine of Wuhan Third Hospital from January 1, 2020 to March 31, 2020 and 135 patients with sCAP admitted to the department of critical care medicine of Shanghai First People's Hospital from January 1, 2010 to December 31, 2017 was conducted. The basic information, diagnosis and comorbidities, laboratory data, etiology and imaging results, treatment, prognosis and outcome of the patients were collected. The differences in clinical data between sCOVID-19 and sCAP patients were compared, and the risk factors of death were analyzed. RESULTS: The 28-day mortality of sCOVID-19 and sCAP patients were 50.9% (59/116) and 37.0% (50/135), respectively. The proportion of arterial partial pressure of oxygen/fraction of inspired oxygen (PaO2/FiO2) ≤ 250 mmHg (1 mmHg ≈ 0.133 kPa) in sCOVID-19 patients was significantly higher than that of sCAP [62.1% (72/116) vs. 34.8% (47/135), P < 0.01]. The possible reason was that the proportion of multiple lung lobe infiltration in sCOVID-19 was significantly higher than that caused by sCAP [94.0% (109/116) vs. 40.0% (54/135), P < 0.01], but the proportion of sCOVID-19 patients requiring mechanical ventilation was significantly lower than that of sCAP [45.7% (53/116) vs. 60.0% (81/135), P < 0.05]. Further analysis of clinical indicators related to patient death found that for sCOVID-19 patients PaO2/FiO2, white blood cell count (WBC), neutrophils (NEU), neutrophil percentage (NEU%), neutrophil/lymphocyte ratio (NLR), total bilirubin (TBil), blood urea nitrogen (BUN), albumin (ALB), Ca2+, prothrombin time (PT), D-dimer, C-reactive protein (CRP) and other indicators were significantly different between the death group and the survival group, in addition, the proportion of receiving mechanical ventilation, gamma globulin, steroid hormones and fluid resuscitation in death group were higher than survival group. Logistic regression analysis showed that the need for mechanical ventilation, NLR > 10, TBil > 10 µmol/L, lactate dehydrogenase (LDH) > 250 U/L were risk factors for death at 28 days. For sCAP patients, there were significant differences in age, BUN, ALB, blood glucose (GLU), Ca2+ and D-dimer between the death group and the survival group, but there was no significant difference in treatment. Logistic regression analysis showed that BUN > 7.14 mmol/L and ALB < 30 g/L were risk factors for 28-day death of sCAP patients. CONCLUSIONS: The sCOVID-19 patients in this cohort have worse oxygen condition and symptoms than sCAP patients, which may be due to the high proportion of lesions involving the lungs. The indicators of the difference between the death group and the survival group were similar in sCOVID-19 and sCAP patients. It is suggested that the two diseases have similar effects on renal function, nutritional status and coagulation function. But there were still differences in risk factors affecting survival. It may be that sCOVID-19 has a greater impact on lung oxygenation function, inflammatory cascade response, and liver function, while sCAP has a greater impact on renal function and nutritional status.

Validated tool for early prediction of intensive care unit admission in COVID-19 patients.

BACKGROUND: The novel coronavirus disease 2019 (COVID-19) pandemic is a global threat caused by the severe acute respiratory syndrome coronavirus-2. AIM: To develop and validate a risk stratification tool for the early prediction of intensive care unit (ICU) admission among COVID-19 patients at hospital admission. METHODS: The training cohort included COVID-19 patients admitted to the Wuhan Third Hospital. We selected 13 of 65 baseline laboratory results to assess ICU admission risk, which were used to develop a risk prediction model with the random forest (RF) algorithm. A nomogram for the logistic regression model was built based on six selected variables. The predicted models were carefully calibrated, and the predictive performance was evaluated and compared with two previously published models. RESULTS: There were 681 and 296 patients in the training and validation cohorts, respectively. The patients in the training cohort were older than those in the validation cohort (median age: 63.0 vs 49.0 years, P < 0.001), and the percentages of male gender were similar (49.6% vs 49.3%, P = 0.958). The top predictors selected in the RF model were neutrophil-to-lymphocyte ratio, age, lactate dehydrogenase, C-reactive protein, creatinine, D-dimer, albumin, procalcitonin, glucose, platelet, total bilirubin, lactate and creatine kinase. The accuracy, sensitivity and specificity for the RF model were 91%, 88% and 93%, respectively, higher than those for the logistic regression model. The area under the receiver operating characteristic curve of our model was much better than those of two other published methods (0.90 vs 0.82 and 0.75). Model A underestimated risk of ICU admission in patients with a predicted risk less than 30%, whereas the RF risk score demonstrated excellent ability to categorize patients into different risk strata. Our predictive model provided a larger standardized net benefit across the major high-risk range compared with model A. CONCLUSION: Our model can identify ICU admission risk in COVID-19 patients at admission, who can then receive prompt care, thus improving medical resource allocation.

Clinical characteristics and outcomes of critically ill patients with acute COVID-19 with Epstein-Barr virus reactivation.

BACKGROUND: Our goal is to further elucidate the clinical condition and prognosis of patients with severe acute COVID-19 with EBV reactivation. METHOD: This is a retrospective single-center study of COVID-19 patients admitted to the intensive care unit of Wuhan No. 3 Hospital (January 31 to March 27, 2020). According to whether Epstein-Barr virus reactivation was detected, the patients were divided into an EBV group and a Non-EBV group. Baseline data were collected including epidemiological, larithmics, clinical and imaging characteristics, and laboratory examination data. RESULTS: Of the 128 patients with COVID-19, 17 (13.3%) were infected with Epstein-Barr virus reactivation. In the symptoms,the rate of tachypnoea in the EBV group was apparently higher than that in the Non-EBV group. In lab tests, the lymphocyte and albumin of EBV group decreased more significantly than Non-EBV group, and the D-dimer and serum calcium of EBV group was higher than Non-EBV group. Regarding the infection index, CRP of EBV group was apparently above the Non-EBV group, and no significant difference was found in procalcitonin of the two groups. The incidence of respiratory failure, ARDS, and hypoproteinaemia of EBV group had more incidence than Non-EBV group. The 28-day and 14-day mortality rates of EBV group was significantly higher than that of Non-EBV group. CONCLUSIONS: In the COVID-19 patients, patients with EBV reactivation had higher 28-day and 14-day mortality rates and received more immuno-supportive treatment than patients of Non-EBV group.

[The Clinical Characteristics and Influencing Factors of Patients with Severe COVID-19].

OBJECTIVE: To investigate the clinical characteristic of coagulation, possible causes and countermeasures of patients with severe corona virus disease 2019 (COVID-19). METHODS: The clinical data of the 142 patients diagnosed as COVID-19 at Wuhan Third Hospital in Wuhan, China, from February 10 to February 16, 2020 were collected and analyzed retrospective. Among the patients, 17 cases of dead patients were divided into observe group, and 125 cases of cured patients were divided into control group. The clinical characteristics, laboratory tests, influencing factors, anticoagulant therapy, embolization and bleeding events of the two groups were observed. RESULTS: The average hospital stay time in 142 patients was 22 d. For the 17 dead patients in the observe group, the average hospital stay time was 9.9 d, and the D-dimer, prothrombin time, WBC count and Padua score of the patients in the observe group were significantly higher as compared with the patients in the control group. PT(OR=1.064, 95%CI 1.012-1.119) and D-D(OR=1.045, 95%CI 1.027-1.064) were the independent risk factors that causing the death of COVID-19 patients. Among the patients, 36(25.4%) patients received low-molecular-weight heparin for anticoagulant therapy, with the average course of 9.6 d. The cumulative incidence of the embolism of the patients in the observe group was 7（41.2%）, while 2(11.8%) patients developed to deep vein thrombosis (DVT) and pulmonary embolism (PE), 3 (17.6%) patients occurred acute cerebral infarction and 2 (11.8%) patients occurred acute myocardial infarction. 3 (17.6%) dead patients revealed dominant disseminated intravascular coagulation (DIC). CONCLUSION: Most patients with severe COVID-19 shows a variety of risk factors for thrombus, and those with coagulation dysfunction shows a high dead rate and rapid disease progression. Therefore, coagulation indicators should be dynamically monitored, and mechanical and drug prevention should be actively carried out.

Arbidol is associated with increased in-hospital mortality among 109 patients with severe COVID-19: A multicenter, retrospective study.

BACKGROUND: The antiviral therapy has been considered as an ordinary intervention for COVID-19 patients. However, the effectiveness of antiviral therapy is uncertain. This study was designed to determine the association between the antiviral therapy and in-hospital mortality among severe COVID-19 patients. METHODS: This study enrolled severe COVID-19 patients admitted to four designated hospitals in Wuhan, China. The use of antiviral treatments, demographics, laboratory variables, co-morbidities, complications, and other treatments were compared between survival and fatal cases. The association between antiviral agents and in-hospital mortality were analyzed. RESULTS: In total, 109 severe COVID-19 patients (mean age 65.43) were enrolled for analysis, among which, 61 (56.0%) patients were discharged alive, and 48 (44.0%) died during hospitalization. We found no association between lopinavir/ritonavir (LPV/r) treatment and the in-hospital mortality (odds ratio (OR) = 0.195, 95% confidence interval (CI) = 0.023-1.679). Besides, ribavirin (OR = 0.738, 95% CI = 0.344-1.582), oseltamivir (OR = 0.765, 95% CI = 0.349-1.636), and interferon-alpha (IFN-α) (OR = 0.371, 95% CI = 0.112-1.236) were not associated with the in-hospital mortality. However, arbidol monotherapy (OR = 5.027, 95% CI = 1.795-14.074) or the combination of arbidol and oseltamivir (OR = 5.900, 95% CI = 1.190-29.247) was associated with an increased in-hospital mortality. In addition, the multiple logistic regression identified a significant association between the use of arbidol and the in-hospital mortality (adjusted OR = 4.195, 95% CI = 1.221-14.408). CONCLUSIONS: Our findings indicated that LPV/r, IFN-α, ribavirin, or oseltamivir have no beneficial effects on the prognosis of severe COVID-19 patients, whereas the use of arbidol is associated with increased in-hospital mortality.

Determinants of mortality of patients with COVID-19 in Wuhan, China: a case-control study.

BACKGROUND: Coronavirus disease 2019 (COVID-19) has resulted in an overwhelmed challenge to the healthcare system worldwide. METHODS: A case-control study of COVID-19 patients in Wuhan Third Hospital was conducted. 96 deceased COVID-19 patients and 230 discharged patients were included as the case group and control group, respectively. Demographic, epidemiological, clinical and laboratory variables on admission were collected from electronic medical records. Univariate and multivariate logistic regression were adopted to investigate the independent predictors of mortality. A nomogram was formed for predicting the mortality risk. RESULTS: The multivariate stepwise logistic model demonstrated that age of 60+ years (OR =4.426, 95% CI: 1.955-10.019), comorbidity of cerebrovascular disease (OR =7.084, 95% CI: 1.545-32.471), white blood cell (WBC) count >9.5×109/L (OR =7.308, 95% CI: 1.650-32.358), platelet count <125×109/L (OR =5.128, 95% CI: 2.157-12.191), aspartate aminotransferase (AST) >40 U/L (OR =2.554, 95% CI: 1.253-5.206), cystatin C >1.1 mg/L (OR =4.132, 95% CI: 2.118-8.059), C reactive protein (CRP) ≥100 mg/L (OR =2.830, 95% CI: 1.311-6.109), creatine kinase isoenzymes (CK-MB) >24 U/L (OR =6.015, 95% CI: 2.119-17.07) and D-dimer >5 µg/L (OR =4.917, 95% CI: 1.619-14.933) were independent predictors of mortality of COVID-19 patients. The nomogram demonstrated a well discriminatory accuracy for mortality prediction with a C-index of 0.903. CONCLUSIONS: The determinants identified may help to determine patients at high risk of death at an early stage and guide the optimal treatment.

A Novel Risk-Stratification Models of the High-Flow Nasal Cannula Therapy in COVID-19 Patients With Hypoxemic Respiratory Failure.

Background: High-flow nasal cannula (HFNC) has been recommended as a suitable choice for the management of coronavirus disease 2019 (COVID-19) patients with acute hypoxemic respiratory failure before mechanical ventilation (MV); however, delaying MV with HFNC therapy is still a dilemma between the technique and clinical management during the ongoing pandemic. Methods: Retrospective analysis of COVID-19 patients treated with HFNC therapy from four hospitals of Wuhan, China. Demographic information and clinical variables before, at, and shortly after HFNC initiation were collected and analyzed. A risk-stratification model of HFNC failure (the need for MV) was developed with the 324 patients of Jin Yin-tan Hospital and validated its accuracy with 69 patients of other hospitals. Results: Among the training cohort, the median duration of HFNC therapy was 6 (range, 3-11), and 147 experienced HFNC failure within 7 days of HFNC initiation. Early predictors of HFNC failure on the basis of a multivariate regression analysis included age older than 60 years [odds ratio (OR), 1.93; 95% confidence interval (CI), 1.08-3.44; p = 0.027; 2 points], respiratory rate-oxygenation index (ROX) <5.31 (OR, 5.22; 95% CI, 2.96-9.20; p < 0.001; 5 points) within the first 4 h of HFNC initiation, platelets < 125 × 109/L (OR, 3.04; 95% CI, 1.46-6.35; p = 0.003; 3 points), and interleukin 6 (IL-6) >7.0 pg/mL (OR, 3.34; 95% CI, 1.79-6.23; p < 0.001; 3 points) at HFNC initiation. A weighted risk-stratification model of these predictors showed sensitivity of 80.3%, specificity of 71.2% and a better predictive ability than ROX index alone [area under the curve (AUC) = 0.807 vs. 0.779, p < 0.001]. Six points were used as a cutoff value for the risk of HFNC failure stratification. The HFNC success probability of patients in low-risk group (84.2%) was 9.84 times that in the high-risk group (34.8%). In the subsequent validation cohort, the AUC of the model was 0.815 (0.71-0.92). Conclusions: Aged patients with lower ROX index, thrombocytopenia, and elevated IL-6 values are at increased risk of HFNC failure. The risk-stratification models accurately predicted the HFNC failure and early stratified COVID-19 patients with HFNC therapy into relevant risk categories.

Identification of risk factors for mortality associated with COVID-19.

OBJECTIVES: Coronavirus Disease 2019 (COVID-19) has become a pandemic outbreak. Risk stratification at hospital admission is of vital importance for medical decision making and resource allocation. There is no sophisticated tool for this purpose. This study aimed to develop neural network models with predictors selected by genetic algorithms (GA). METHODS: This study was conducted in Wuhan Third Hospital from January 2020 to March 2020. Predictors were collected on day 1 of hospital admission. The primary outcome was the vital status at hospital discharge. Predictors were selected by using GA, and neural network models were built with the cross-validation method. The final neural network models were compared with conventional logistic regression models. RESULTS: A total of 246 patients with COVID-19 were included for analysis. The mortality rate was 17.1% (42/246). Non-survivors were significantly older (median (IQR): 69 (57, 77) vs. 55 (41, 63) years; p < 0.001), had higher high-sensitive troponin I (0.03 (0, 0.06) vs. 0 (0, 0.01) ng/L; p < 0.001), C-reactive protein (85.75 (57.39, 164.65) vs. 23.49 (10.1, 53.59) mg/L; p < 0.001), D-dimer (0.99 (0.44, 2.96) vs. 0.52 (0.26, 0.96) mg/L; p < 0.001), and α-hydroxybutyrate dehydrogenase (306.5 (268.75, 377.25) vs. 194.5 (160.75, 247.5); p < 0.001) and a lower level of lymphocyte count (0.74 (0.41, 0.96) vs. 0.98 (0.77, 1.26) × 109/L; p < 0.001) than survivors. The GA identified a 9-variable (NNet1) and a 32-variable model (NNet2). The NNet1 model was parsimonious with a cost on accuracy; the NNet2 model had the maximum accuracy. NNet1 (AUC: 0.806; 95% CI [0.693-0.919]) and NNet2 (AUC: 0.922; 95% CI [0.859-0.985]) outperformed the linear regression models. CONCLUSIONS: Our study included a cohort of COVID-19 patients. Several risk factors were identified considering both clinical and statistical significance. We further developed two neural network models, with the variables selected by using GA. The model performs much better than the conventional generalized linear models.

A bibliometric analysis using VOSviewer of publications on COVID-19.

BACKGROUND: As a global pandemic, COVID-19 has aroused great concern in the last few months and a growing number of related researches have been published. Therefore, a bibliometric analysis of these publications may provide a direction of hot topics and future research trends. METHODS: The global literatures about COVID-19 published between 2019 and 2020 were scanned in the Web of Science collection database. "COVID-19" "Novel Coronavirus" "2019-nCoV" and "SARS-CoV-2" were used as the keywords to reach the relevant publications. VOSviewer was applied to perform the bibliometric analysis of these articles. RESULTS: Totally 3,626 publications on the topic of COVID-19 were identified and "COVID-19" with a total link strength of 2,649 appeared as the most frequent keyword, which had a strong link to "pneumonia" and "epidemiology". The mean citation count of the top 100 most cited articles was 96 (range, 26-883). Most of them were descriptive studies and concentrated on the clinical features. The highest-ranking journal was British medical journal with 211 publications and the most cited journal was Lancet with 2,485 citation counts. Eleven articles written by Christian Drosten from Berlin Institute of Virology have been cited for 389 times and 40 articles from Chinese Academy of Sciences have been cited for 1,597 times which are the most cited author and organization. The number of collaborators with China is 44 and the total link strength is 487. The main partners of China are USA, England and Germany. The published literatures have focused on three topics: disease management, clinical features and pathogenesis. CONCLUSIONS: The current growth trends predict a large increase in the number of global publications on COVID-19. China made the most outstanding contribution within this important field. Disease treatment, spike protein and vaccine may be hotspots in the future.

Clinical course and predictors of 60-day mortality in 239 critically ill patients with COVID-19: a multicenter retrospective study from Wuhan, China.

BACKGROUND: The global numbers of confirmed cases and deceased critically ill patients with COVID-19 are increasing. However, the clinical course, and the 60-day mortality and its predictors in critically ill patients have not been fully elucidated. The aim of this study is to identify the clinical course, and 60-day mortality and its predictors in critically ill patients with COVID-19. METHODS: Critically ill adult patients admitted to intensive care units (ICUs) from 3 hospitals in Wuhan, China, were included. Data on demographic information, preexisting comorbidities, laboratory findings at ICU admission, treatments, clinical outcomes, and results of SARS-CoV-2 RNA tests and of serum SARS-CoV-2 IgM were collected including the duration between symptom onset and negative conversion of SARS-CoV-2 RNA. RESULTS: Of 1748 patients with COVID-19, 239 (13.7%) critically ill patients were included. Complications included acute respiratory distress syndrome (ARDS) in 164 (68.6%) patients, coagulopathy in 150 (62.7%) patients, acute cardiac injury in 103 (43.1%) patients, and acute kidney injury (AKI) in 119 (49.8%) patients, which occurred 15.5 days, 17 days, 18.5 days, and 19 days after the symptom onset, respectively. The median duration of the negative conversion of SARS-CoV-2 RNA was 30 (range 6-81) days in 49 critically ill survivors that were identified. A total of 147 (61.5%) patients deceased by 60 days after ICU admission. The median duration between ICU admission and decease was 12 (range 3-36). Cox proportional-hazards regression analysis revealed that age older than 65 years, thrombocytopenia at ICU admission, ARDS, and AKI independently predicted the 60-day mortality. CONCLUSIONS: Severe complications are common and the 60-day mortality of critically ill patients with COVID-19 is considerably high. The duration of the negative conversion of SARS-CoV-2 RNA and its association with the severity of critically ill patients with COVID-19 should be seriously considered and further studied.

In-Hospital Use of Statins Is Associated with a Reduced Risk of Mortality among Individuals with COVID-19.

Statins are lipid-lowering therapeutics with favorable anti-inflammatory profiles and have been proposed as an adjunct therapy for COVID-19. However, statins may increase the risk of SARS-CoV-2 viral entry by inducing ACE2 expression. Here, we performed a retrospective study on 13,981 patients with COVID-19 in Hubei Province, China, among which 1,219 received statins. Based on a mixed-effect Cox model after propensity score-matching, we found that the risk for 28-day all-cause mortality was 5.2% and 9.4% in the matched statin and non-statin groups, respectively, with an adjusted hazard ratio of 0.58. The statin use-associated lower risk of mortality was also observed in the Cox time-varying model and marginal structural model analysis. These results give support for the completion of ongoing prospective studies and randomized controlled trials involving statin treatment for COVID-19, which are needed to further validate the utility of this class of drugs to combat the mortality of this pandemic.