Development and Validation of a Nomogram for Predicting the Disease Progression of Nonsevere Coronavirus Disease 2019.

BACKGROUND AND OBJECTIVES: The majority of coronavirus disease 2019 (COVID-19) cases are nonsevere, but severe cases have high mortality and need early detection and treatment. We aimed to develop a nomogram to predict the disease progression of nonsevere COVID-19 based on simple data that can be easily obtained even in primary medical institutions. METHODS: In this retrospective, multicenter cohort study, we extracted data from initial simple medical evaluations of 495 COVID-19 patients randomized (2:1) into a development cohort and a validation cohort. The progression of nonsevere COVID-19 was recorded as the primary outcome. We built a nomogram with the development cohort and tested its performance in the validation cohort. RESULTS: The nomogram was developed with the nine factors included in the final model. The area under the curve (AUC) of the nomogram scoring system for predicting the progression of nonsevere COVID-19 into severe COVID-19 was 0.875 and 0.821 in the development cohort and validation cohort, respectively. The nomogram achieved a good concordance index for predicting the progression of nonsevere COVID-19 cases in the development and validation cohorts (concordance index of 0.875 in the development cohort and 0.821 in the validation cohort) and had well-fitted calibration curves showing good agreement between the estimates and the actual endpoint events. CONCLUSIONS: The proposed nomogram built with a simplified index might help to predict the progression of nonsevere COVID-19; thus, COVID-19 with a high risk of disease progression could be identified in time, allowing an appropriate therapeutic choice according to the potential disease severity.

Hyperglycemia and Correlated High Levels of Inflammation Have a Positive Relationship with the Severity of Coronavirus Disease 2019.

OBJECTIVE: Coronavirus disease 2019 (COVID-19) is a considerable global public health threat. This study sought to investigate whether blood glucose (BG) levels or comorbid diabetes are associated with inflammatory status and disease severity in patients with COVID-19. METHODS: In this retrospective cohort study, the clinical and biochemical characteristics of COVID-19 patients with or without diabetes were compared. The relationship among severity of COVID-19, inflammatory status, and diabetes or hyperglycemia was analyzed. The severity of COVID-19 in all patients was determined according to the diagnostic and treatment guidelines issued by the Chinese National Health Committee (7th edition). RESULTS: Four hundred and sixty-one patients were enrolled in our study, and 71.58% of patients with diabetes and 13.03% of patients without diabetes had hyperglycemia. Compared with patients without diabetes (n = 366), patients with diabetes (n = 95) had a higher leucocyte count, neutrophil count, neutrophil to lymphocyte ratio (NLR), and erythrocyte sedimentation rate (ESR). There was no association between severity of COVID-19 and known diabetes adjusted for age, sex, body mass index (BMI), known hypertension, and coronary heart disease. The leucocyte count, NLR, and C-reactive protein (CRP) level increased with increasing BG level. Hyperglycemia was an independent predictor of critical (OR 4.00, 95% CI 1.72-9.30) or severe (OR 3.55, 95% CI 1.47-8.58) COVID-19, and of increased inflammatory levels (high leucocyte count (OR 4.26, 95% CI 1.65-10.97), NLR (OR 2.76, 95% CI 1.24-6.10), and CRP level (OR 2.49, 95% CI 1.19-5.23)), after adjustment for age, sex, BMI, severity of illness, and known diabetes. CONCLUSION: Hyperglycemia was positively correlated with higher inflammation levels and more severe illness, and it is a risk factor for the increased severity of COVID-19. The initial measurement of plasma glucose levels after hospitalization may help identify a subset of patients who are predisposed to a worse clinical course.

Distinct effects of asthma and COPD comorbidity on disease expression and outcome in patients with COVID-19.

BACKGROUND: The impacts of chronic airway diseases on coronavirus disease 2019 (COVID-19) are far from understood. OBJECTIVE: To explore the influence of asthma and chronic obstructive pulmonary disease (COPD) comorbidity on disease expression and outcomes, and the potential underlying mechanisms in COVID-19 patients. METHODS: A total of 961 hospitalized COVID-19 patients with a definite clinical outcome (death or discharge) were retrospectively enrolled. Demographic and clinical information were extracted from the medical records. Lung tissue sections from patients suffering from lung cancer were used for immunohistochemistry study of angiotensin-converting enzyme II (ACE2) expression. BEAS-2B cell line was stimulated with various cytokines. RESULTS: In this cohort, 21 subjects (2.2%) had COPD and 22 (2.3%) had asthma. After adjusting for confounding factors, COPD patients had higher risk of developing severe illness (OR: 23.433; 95% CI 1.525-360.135; P < .01) and acute respiratory distress syndrome (OR: 19.762; 95% CI 1.461-267.369; P = .025) than asthmatics. COPD patients, particularly those with severe COVID-19, had lower counts of CD4+ T and CD8+ T cells and B cells and higher levels of TNF-α, IL-2 receptor, IL-10, IL-8, and IL-6 than asthmatics. COPD patients had increased, whereas asthmatics had decreased ACE2 protein expression in lower airways, compared with that in control subjects without asthma and COPD. IL-4 and IL-13 downregulated, but TNF-α, IL-12, and IL-17A upregulated ACE2 expression in BEAS-2B cells. CONCLUSION: Patients with asthma and COPD likely have different risk of severe COVID-19, which may be associated with different ACE2 expression.

Efficacy of corticosteroid in patients with COVID-19: A multi-center retrospective study and meta-analysis.

To evaluate the efficacy of corticosteroids on coronavirus disease 2019 (COVID-19) patients with different levels of disease severity. In our multicenter study, 543 patients with confirmed COVID-19 were classified as non-severe group and severe group, and then were compared respectively for all-cause mortality and length of hospital stay between those who received corticosteroids and not. By searching in PubMed, Web of Science, Embase, and CNKI, we identified 13 retrospective studies and 6 random control trials eligible for criteria of inclusion, and conducted comprehensive meta-analyses assessing the impacts of corticosteroids on mortality, length of stay, duration of RNA clearance and duration of fever. Our multicenter study demonstrated that low-dose corticosteroids can reduce mortality in the multivariable Cox regression analysis for severe patients (p = .03), while presented no influence in univariable analysis for non-severe patients (p = .14). From multivariable analyses, patients with corticosteroids in non-severe group had longer duration of hospitalization (p = .003), but did not in severe group (p = .18). Moreover, for severe patients, corticosteroids can evidently shorten duration of fever. The same results were summarized in the meta-analyses supplemented with the result that corticosteroids delayed viral clearing in non-severe patients. Corticosteroids should be considered based on patient's condition. For patients with non-severe COVID-19, corticosteroid was not recommended as a routine therapeutic initiative as that presented prolonged duration of hospitalization and delayed viral clearing, as well as no positive impact on prognosis. While low-dose corticosteroids may benefit patients with severe COVID-19 for it can manifestly lower risk of death and improve the clinical status to some extent.

Clinical characteristics and predictors of mortality in young adults with severe COVID-19: a retrospective observational study.

BACKGROUND AND OBJECTIVE: Little is yet known whether pathogenesis of COVID-19 is different between young and elder patients. Our study aimed to investigate the clinical characteristics and provide predictors of mortality for young adults with severe COVID-19. METHODS: A total of 77 young adults with confirmed severe COVID-19 were recruited retrospectively at Tongji Hospital. Clinical characteristics, laboratory findings, treatment and outcomes were obtained from electronic medical records. The prognostic effects of variables were analyzed using logistic regression model. RESULTS: In this retrospective cohort, non-survivors showed higher incidence of dyspnea and co-existing laboratory abnormalities, compared with young survivals in severe COVID-19. Multivariate logistic regression analysis showed that lymphopenia, elevated level of d-dimer, hypersensitive cardiac troponin I (hs-CTnI) and high sensitivity C-reactive protein (hs-CRP) were independent predictors of mortality in young adults with severe COVID-19. Further analysis showed that severely young adults with two or more factors abnormalities above would be more prone to death. The similar predictive effect of above four factors had been observed in all-age patients with severe COVID-19. CONCLUSION: Lymphopenia, elevated level of d-dimer, hs-CTnI and hs-CRP predicted clinical outcomes of young adults with severe COVID-19.

High-Flow Nasal Oxygen in Coronavirus Disease 2019 Patients With Acute Hypoxemic Respiratory Failure: A Multicenter, Retrospective Cohort Study.

OBJECTIVES: An ongoing outbreak of coronavirus disease 2019 is spreading globally. Acute hypoxemic respiratory failure is the most common complication of coronavirus disease 2019. However, the clinical effectiveness of early high-flow nasal oxygen treatment in patients with coronavirus disease 2019 with acute hypoxemic respiratory failure has not been explored. This study aimed to analyze the effectiveness of high-flow nasal oxygen treatment and to identify the variables predicting high-flow nasal oxygen treatment failure in coronavirus disease 2019 patients with acute hypoxemic respiratory failure. DESIGN: A multicenter, retrospective cohort study. SETTING: Three tertiary hospitals in Wuhan, China. PATIENTS: Forty-three confirmed coronavirus disease 2019 adult patients with acute hypoxemic respiratory failure treated with high-flow nasal oxygen. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: Mean age of the enrolled patients was 63.0 ± 9.7 years; female patients accounted for 41.9%. High-flow nasal oxygen failure (defined as upgrading respiratory support to positive pressure ventilation or death) was observed in 20 patients (46.5%), of which 13 (30.2%) required endotracheal intubation. Patients with high-flow nasal oxygen success had a higher median oxygen saturation (96.0% vs 93.0%; p < 0.001) at admission than those with high-flow nasal oxygen failure. High-flow nasal oxygen failure was more likely in patients who were older (p = 0.030) and male (p = 0.037), had a significant increase in respiratory rate and a significant decrease in the ratio of oxygen saturation/FIO2 to respiratory rate index within 3 days of high-flow nasal oxygen treatment. In a multivariate logistic regression analysis model, male and lower oxygen saturation at admission remained independent predictors of high-flow nasal oxygen failure. The hospital mortality rate of the cohort was 32.5%; however, the hospital mortality rate in patients with high-flow nasal oxygen failure was 65%. CONCLUSIONS: High-flow nasal oxygen may be effective for treating coronavirus disease 2019 patients with mild to moderate acute hypoxemic respiratory failure. However, high-flow nasal oxygen failure was associated with a poor prognosis. Male and lower oxygenation at admission were the two strong predictors of high-flow nasal oxygen failure.

Ruxolitinib in treatment of severe coronavirus disease 2019 (COVID-19): A multicenter, single-blind, randomized controlled trial.

BACKGROUND: Accumulating evidence proposed Janus-associated kinase (JAK) inhibitors as therapeutic targets warranting rapid investigation. OBJECTIVE: This study evaluated the efficacy and safety of ruxolitinib, a JAK1/2 inhibitor, for coronavirus disease 2019. METHODS: We conducted a prospective, multicenter, single-blind, randomized controlled phase II trial involving patients with severe coronavirus disease 2019. RESULTS: Forty-three patients were randomly assigned (1:1) to receive ruxolitinib plus standard-of-care treatment (22 patients) or placebo based on standard-of-care treatment (21 patients). After exclusion of 2 patients (1 ineligible, 1 consent withdrawn) from the ruxolitinib group, 20 patients in the intervention group and 21 patients in the control group were included in the study. Treatment with ruxolitinib plus standard-of-care was not associated with significantly accelerated clinical improvement in severe patients with coronavirus disease 2019, although ruxolitinib recipients had a numerically faster clinical improvement. Eighteen (90%) patients from the ruxolitinib group showed computed tomography improvement at day 14 compared with 13 (61.9%) patients from the control group (P = .0495). Three patients in the control group died of respiratory failure, with 14.3% overall mortality at day 28; no patients died in the ruxolitinib group. Ruxolitinib was well tolerated with low toxicities and no new safety signals. Levels of 7 cytokines were significantly decreased in the ruxolitinib group in comparison to the control group. CONCLUSIONS: Although no statistical difference was observed, ruxolitinib recipients had a numerically faster clinical improvement. Significant chest computed tomography improvement, a faster recovery from lymphopenia, and favorable side-effect profile in the ruxolitinib group were encouraging and informative to future trials to test efficacy of ruxolitinib in a larger population.

Risk factors for severity and mortality in adult COVID-19 inpatients in Wuhan.

BACKGROUND: In December 2019, the coronavirus disease 2019 (COVID-19) outbreak occurred in Wuhan. Data on the clinical characteristics and outcomes of patients with severe COVID-19 are limited. OBJECTIVE: We sought to evaluate the severity on admission, complications, treatment, and outcomes of patients with COVID-19. METHODS: Patients with COVID-19 admitted to Tongji Hospital from January 26, 2020, to February 5, 2020, were retrospectively enrolled and followed-up until March 3, 2020. Potential risk factors for severe COVID-19 were analyzed by a multivariable binary logistic model. Cox proportional hazard regression model was used for survival analysis in severe patients. RESULTS: We identified 269 (49.1%) of 548 patients as severe cases on admission. Older age, underlying hypertension, high cytokine levels (IL-2R, IL-6, IL-10, and TNF-α), and high lactate dehydrogenase level were significantly associated with severe COVID-19 on admission. The prevalence of asthma in patients with COVID-19 was 0.9%, markedly lower than that in the adult population of Wuhan. The estimated mortality was 1.1% in nonsevere patients and 32.5% in severe cases during the average 32 days of follow-up period. Survival analysis revealed that male sex, older age, leukocytosis, high lactate dehydrogenase level, cardiac injury, hyperglycemia, and high-dose corticosteroid use were associated with death in patients with severe COVID-19. CONCLUSIONS: Patients with older age, hypertension, and high lactate dehydrogenase level need careful observation and early intervention to prevent the potential development of severe COVID-19. Severe male patients with heart injury, hyperglycemia, and high-dose corticosteroid use may have a high risk of death.

Clinical features of patients infected with 2019 novel coronavirus in Wuhan, China.

BACKGROUND: A recent cluster of pneumonia cases in Wuhan, China, was caused by a novel betacoronavirus, the 2019 novel coronavirus (2019-nCoV). We report the epidemiological, clinical, laboratory, and radiological characteristics and treatment and clinical outcomes of these patients. METHODS: All patients with suspected 2019-nCoV were admitted to a designated hospital in Wuhan. We prospectively collected and analysed data on patients with laboratory-confirmed 2019-nCoV infection by real-time RT-PCR and next-generation sequencing. Data were obtained with standardised data collection forms shared by WHO and the International Severe Acute Respiratory and Emerging Infection Consortium from electronic medical records. Researchers also directly communicated with patients or their families to ascertain epidemiological and symptom data. Outcomes were also compared between patients who had been admitted to the intensive care unit (ICU) and those who had not. FINDINGS: By Jan 2, 2020, 41 admitted hospital patients had been identified as having laboratory-confirmed 2019-nCoV infection. Most of the infected patients were men (30 [73%] of 41); less than half had underlying diseases (13 [32%]), including diabetes (eight [20%]), hypertension (six [15%]), and cardiovascular disease (six [15%]). Median age was 49·0 years (IQR 41·0-58·0). 27 (66%) of 41 patients had been exposed to Huanan seafood market. One family cluster was found. Common symptoms at onset of illness were fever (40 [98%] of 41 patients), cough (31 [76%]), and myalgia or fatigue (18 [44%]); less common symptoms were sputum production (11 [28%] of 39), headache (three [8%] of 38), haemoptysis (two [5%] of 39), and diarrhoea (one [3%] of 38). Dyspnoea developed in 22 (55%) of 40 patients (median time from illness onset to dyspnoea 8·0 days [IQR 5·0-13·0]). 26 (63%) of 41 patients had lymphopenia. All 41 patients had pneumonia with abnormal findings on chest CT. Complications included acute respiratory distress syndrome (12 [29%]), RNAaemia (six [15%]), acute cardiac injury (five [12%]) and secondary infection (four [10%]). 13 (32%) patients were admitted to an ICU and six (15%) died. Compared with non-ICU patients, ICU patients had higher plasma levels of IL2, IL7, IL10, GSCF, IP10, MCP1, MIP1A, and TNFα. INTERPRETATION: The 2019-nCoV infection caused clusters of severe respiratory illness similar to severe acute respiratory syndrome coronavirus and was associated with ICU admission and high mortality. Major gaps in our knowledge of the origin, epidemiology, duration of human transmission, and clinical spectrum of disease need fulfilment by future studies. FUNDING: Ministry of Science and Technology, Chinese Academy of Medical Sciences, National Natural Science Foundation of China, and Beijing Municipal Science and Technology Commission.