Severity of COVID-19 in Cancer patients versus patients without Cancer: A Propensity Score Matching Analysis.

Purpose: Data are extremely limited with regards to the impact of COVID-19 on cancer patients. Our study explored the distinct clinical features of COVID-19 patients with cancer. Experimental Design: 189 COVID-19 patients, including 16 cancer patients and 173 patients without cancer, were recruited. Propensity score 1:4 matching (PSM) was performed between cancer patients and patients without cancer based on age, gender and comorbidities. Survival was calculated by the Kaplan-Meier method and the difference was compared by the log-rank test. Results: PSM analysis yielded 16 cancer patients and 64 propensity score-matched patients without cancer. Compared to patients without cancer, cancer patients tended to have leukopenia and elevated high-sensitivity C-reactive protein (hs-CRP) and procalcitonin. For those with critical COVID-19, cancer patients had an inferior survival than those without cancer. Also, cancer patients with severe/critical COVID-19 tended to be male and present with low SPO2 and albumin, and high hs-CRP, lactate dehydrogenase and blood urea nitrogen on admission compared to those with mild COVID-19. In terms of risk factors, recent cancer diagnosis (within 1 year of onset of COVID-19) and anti-tumor treatment within 3 months of COVID-19 diagnosis were associated with inferior survival. Conclusions: We found COVID-19 patients with cancer have distinct clinical features as compared to patients without cancer. Importantly, cancer patients with critical COVID-19 were found to have poorer outcomes compared to those without cancer. In the cancer cohort, patients with severe/critical COVID-19 presented with a distinct clinical profile from those with mild COVID-19; short cancer history and recent anti-cancer treatment were associated with inferior survival.

The interval between onset and admission predicts disease progression in COVID-19 patients.

BACKGROUND: The prognostic role of the interval between disease onset and hospital admission (O-A interval) was undetermined in patients with the coronavirus disease 2019 (COVID-19). METHODS: A total of 205 laboratory-confirmed inpatients admitted to Hankou hospital of Wuhan from January 11 to March 8, 2020 were consecutively included in this retrospective observational study. Demographic data, medical history, laboratory testing results were collected from medical records. Univariate and multivariate logistic regression models were used to evaluate the prognostic effect of the O-A interval (≤7 versus >7 days) on disease progression in mild-to-moderate patients. For severe-to-critical patients, the in-hospital mortality and the length of hospital stay were compared between the O-A interval subgroups using log-rank test and Mann-Whitney U test, respectively. RESULTS: Mild-to-moderate patients with a short O-A interval (≤7 days) are more likely to deteriorate to severe-to-critical stage compared to those with a long O-A interval (>7 days) [unadjusted odds ratio =2.93, 95% confidence interval (CI), 1.32-6.55; adjusted odds ratio =3.44, 95% CI, 1.20-9.83]. No association was identified between the O-A interval and the mortality or the length of hospital stay of severe-to-critical patients. CONCLUSIONS: The O-A interval has predictive values for the disease progression in mild-to-moderate COVID-19 patients. Under circumstances of the specific health system in Wuhan, China, the spontaneous healthcare-seeking behavior is usually determined by patients' own heath conditions. Hence, the O-A interval can be reflective of the natural course of COVID-19 to some extent. However, our findings should be validated further in other cohorts and in other health systems.

Early triage of critically ill COVID-19 patients using deep learning.

The sudden deterioration of patients with novel coronavirus disease 2019 (COVID-19) into critical illness is of major concern. It is imperative to identify these patients early. We show that a deep learning-based survival model can predict the risk of COVID-19 patients developing critical illness based on clinical characteristics at admission. We develop this model using a cohort of 1590 patients from 575 medical centers, with internal validation performance of concordance index 0.894 We further validate the model on three separate cohorts from Wuhan, Hubei and Guangdong provinces consisting of 1393 patients with concordance indexes of 0.890, 0.852 and 0.967 respectively. This model is used to create an online calculation tool designed for patient triage at admission to identify patients at risk of severe illness, ensuring that patients at greatest risk of severe illness receive appropriate care as early as possible and allow for effective allocation of health resources.

Effect and safety of Chinese herbal medicine granules in patients with severe coronavirus disease 2019 in Wuhan, China: a retrospective, single-center study with propensity score matching.

BACKGROUND: Chinese herbal medicine (CHM) has been used for severe illness caused by coronavirus disease 2019 (COVID-19), but its treatment effects and safety are unclear. PURPOSE: This study reviews the effect and safety of CHM granules in the treatment of patients with severe COVID-19. METHODS: We conducteda single-center, retrospective study on patients with severe COVID-19 in a designated hospital in Wuhan from January 15, 2020 to March 30, 2020. The propensity score matching (PSM) was used to assess the effect and safety of the treatment using CHM granules. The ratio of patients who received treatment with CHM granules combined with usual care and those who received usual care alone was 1:1. The primary outcome was the time to clinical improvement within 28 days, defined as the time taken for the patients' health to show improvement by decline of two categories (from the baseline) on a modified six-category ordinal scale, or to be dischargedfrom the hospital before Day 28. RESULTS: Using PSM, 43 patients (45% male) aged 65.6 (57-70) yearsfrom each group were exactly matched. No significant difference was observed in clinical improvement of patients treated with CHM granules compared with those who received usual (p = 0.851). However, the use of CHM granules reduced the 28-day mortality (p = 0.049) and shortened the duration of fever (4 days vs. 7 days, p = 0.002). The differences in the duration of cough and dyspnea and the difference in lung lesion ratio on computerized tomography scans were not significant.Commonly,patients in the CHM group had an increased D-dimer level (p = 0.036). CONCLUSION: Forpatients with severe COVID-19, CHM granules, combined with usual care, showed no improvement beyond usual care alone. However, the use of CHM granules reduced the 28-day mortality rate and the time to fever alleviation. Nevertheless, CHM granules may be associated with high risk of fibrinolysis.

The utility of MEWS for predicting the mortality in the elderly adults with COVID-19: a retrospective cohort study with comparison to other predictive clinical scores.

BACKGROUND: Older adults have been reported to be a population with high-risk of death in the COVID-19 outbreak. Rapid detection of high-risk patients is crucial to reduce mortality in this population. The aim of this study was to evaluate the prognositc accuracy of the Modified Early Warning Score (MEWS) for in-hospital mortality in older adults with COVID-19. METHODS: A retrospective cohort study was conducted in Wuhan Hankou Hospital in China from 1 January 2020 to 29 February 2020. Receiver operating characteristic (ROC) analysis was used to evaluate the predictive value of MEWS, Acute Physiology and Chronic Health Evaluation II (APACHE II), Sequential Organ Function Assessment (SOFA), quick Sequential Organ Function Assessment (qSOFA), Pneumonia Severity Index (PSI), Combination of Confusion, Urea, Respiratory Rate, Blood Pressure, and Age ≥65 (CURB-65), and the Systemic Inflammatory Response Syndrome Criteria (SIRS) for in-hospital mortality. Logistic regression models were performed to detect the high-risk older adults with COVID-19. RESULTS: Among the 235 patients included in this study, 37 (15.74%) died and 131 (55.74%) were male, with an average age of 70.61 years (SD 8.02). ROC analysis suggested that the capacity of MEWS in predicting in-hospital mortality was as good as the APACHE II, SOFA, PSI and qSOFA (Difference in AUROC: MEWS vs. APACHE II, -0.025 (95% CI [-0.075 to 0.026]); MEWS vs. SOFA, -0.013 (95% CI [-0.049 to 0.024]); MEWS vs. PSI, -0.015 (95% CI [-0.065 to 0.035]); MEWS vs. qSOFA, 0.024 (95% CI [-0.029 to 0.076]), all P > 0.05), but was significantly higher than SIRS and CURB-65 (Difference in AUROC: MEWS vs. SIRS, 0.218 (95% CI [0.156-0.279]); MEWS vs. CURB-65, 0.064 (95% CI [0.002-0.125]), all P < 0.05). Logistic regression models implied that the male patients (≥75 years) had higher risk of death than the other older adults (estimated coefficients: 1.16, P = 0.044). Our analysis further suggests that the cut-off points of the MEWS score for the male patients (≥75 years) subpopulation and the other elderly patients should be 2.5 and 3.5, respectively. CONCLUSIONS: MEWS is an efficient tool for rapid assessment of elderly COVID-19 patients. MEWS has promising performance in predicting in-hospital mortality and identifying the high-risk group in elderly patients with COVID-19.

Systemic Corticosteroids and Mortality in Severe and Critical COVID-19 Patients in Wuhan, China.

BACKGROUND: Systemic corticosteroids are now recommended in many treatment guidelines, although supporting evidence is limited to 1 randomized controlled clinical trial (RECOVERY). OBJECTIVE: To identify whether corticosteroids were beneficial to COVID-19 patients. METHODS: A total of 1514 severe and 249 critical hospitalized COVID-19 patients from 2 medical centers in Wuhan, China. Multivariable Cox models, Cox model with time-varying exposure and propensity score analysis (inverse-probability-of-treatment-weighting [IPTW] and propensity score matching [PSM]) were used to estimate the association of corticosteroid use with risk of in-hospital mortality in severe and critical cases. RESULTS: Corticosteroids were administered in 531 (35.1%) severe and 159 (63.9%) critical patients. Compared to the non-corticosteroid group, systemic corticosteroid use was not associated with beneficial effect in reducing in-hospital mortality in either severe cases (HR = 1.77; 95% CI, 1.08-2.89; P = 0.023), or critical cases (HR = 2.07; 95% CI, 1.08-3.98; P = 0.028). Findings were similar in time-varying Cox analysis. For patients with severe COVID-19 at admission, corticosteroid use was not associated with improved or harmful outcome in either PSM or IPTW analysis. For critical COVID-19 patients at admission, results were consistent with multivariable Cox model analysis. CONCLUSION: Corticosteroid use was not associated with beneficial effect in reducing in-hospital mortality for severe or critical cases in Wuhan. Absence of the beneficial effect in our study in contrast to that observed in the RECOVERY clinical trial may be due to biases in observational data, in particular prescription by indication bias, differences in clinical characteristics of patients, choice of corticosteroid used, timing of initiation of treatment, and duration of treatment.

Elevation of blood glucose level predicts worse outcomes in hospitalized patients with COVID-19: a retrospective cohort study.

INTRODUCTION: With intense deficiency of medical resources during COVID-19 pandemic, risk stratification is of strategic importance. Blood glucose level is an important risk factor for the prognosis of infection and critically ill patients. We aimed to investigate the prognostic value of blood glucose level in patients with COVID-19. RESEARCH DESIGN AND METHODS: We collected clinical and survival information of 2041 consecutive hospitalized patients with COVID-19 from two medical centers in Wuhan. Patients without available blood glucose level were excluded. We performed multivariable Cox regression to calculate HRs of blood glucose-associated indexes for the risk of progression to critical cases/mortality among non-critical cases, as well as in-hospital mortality in critical cases. Sensitivity analysis were conducted in patient without diabetes. RESULTS: Elevation of admission blood glucose level was an independent risk factor for progression to critical cases/death among non-critical cases (HR=1.30, 95% CI 1.03 to 1.63, p=0.026). Elevation of initial blood glucose level of critical diagnosis was an independent risk factor for in-hospital mortality in critical cases (HR=1.84, 95% CI 1.14 to 2.98, p=0.013). Higher median glucose level during hospital stay or after critical diagnosis (≥6.1 mmol/L) was independently associated with increased risks of progression to critical cases/death among non-critical cases, as well as in-hospital mortality in critical cases. Above results were consistent in the sensitivity analysis in patients without diabetes. CONCLUSIONS: Elevation of blood glucose level predicted worse outcomes in hospitalized patients with COVID-19. Our findings may provide a simple and practical way to risk stratify COVID-19 inpatients for hierarchical management, particularly where medical resources are in severe shortage during the pandemic.