[Effect of hypertension on outcomes of patients with COVID-19].

OBJECTIVE: To determine the impact of hypertension on the outcomes of patients with COVID-19. METHODS: This matched cohort study was conducted among a total 442 patients with COVID-19 admitted in Honghu People's Hospital and First Affiliated Hospital of Nanchang University between January 1 to March 18, 2020, including 61 patients with hypertension and 381 normotensive patients. To minimize the effects of the confounding factors including age, gender and other comorbidities, we excluded patients with comorbidities other than hypertension, and matched the patients with and without hypertension for age and gender at a 1:1 ratio. We analyzed the clinical characteristics, laboratory findings and clinical outcomes of in 32 matched pairs of patients with and without hypertension. RESULTS: Compared with the normotensive patients, COVID-19 patients with hypertension were more likely to develop bacterial infections (P=0.002) and had higher neutrophil counts (P=0.007), neutrophil/lymphocyte ratio (P=0.045), and lactate dehydrogenase levels (P=0.035). A greater proportion of patients had bilateral patchy opacities on chest CT (P=0.012) in the hypertension group than in the normotensive group. COVID-19 patients with hypertension group were more likely to receive antibiotics (P=0.035) and corticosteroid therapies (P=0.035). CONCLUSIONS: Hypertension increases the risk of bacterial infection in patients with COVID-19. Hypertensive patients with COVID-19 have higher neutrophil counts and neutrophil/ lymphocyte ratios and are more likely to require treatment with antibiotics. Hypertensive patients with COVID-19 should therefore take cautions to avoid bacterial infections.

Development and Validation of the HNC-LL Score for Predicting the Severity of Coronavirus Disease 2019 (preprint)

Background: The severity of coronavirus disease 2019 (COVID-19) varies widely, ranging from asymptomatic to fatal. However, there is limited information regarding the risk factors associated with severe disease. In this study, we aimed to develop a model for predicting COVID-19 severity. Methods: A total of 690 patients with confirmed COVID-19 were recruited between January 1 and March 18, 2020 from hospitals in Honghu and Nanchang, and finally, 442 patients were analyzed. Data were partitioned into the training set and test sets to develop and validate the model, respectively. Results: A predictive HNC-LL (Hypertension–Neutrophil count–C-reactive protein– Lymphocyte count– Lactate dehydrogenase) score was established based on multivariate logistic regression analysis results. The HNC-LL score accurately predicted disease severity in the Honghu training cohort (area under the curve [AUC] = 0.861, 95% confidence interval [CI]: 0.800–0.922; P <0.001); the Honghu internal validation cohort (AUC = 0.871, 95% CI: 0.769–0.972; P <0.001); and the Nanchang external validation cohort (AUC = 0.826, 95% CI: 0.746–0.907; P <0.001), and outperformed other models including the CURB-65 score model, MuLBSTA score model, and neutrophil-to-lymphocyte ratio model. Moreover, the clinical significance of HNC-LL in accurately predicting patients with severe COVID-19 in the early phase was confirmed. Conclusions: We developed an accurate tool for predicting disease severity in patients with COVID-19. This model can potentially be used to identify patients at risk of developing severe disease in the early stage and therefore, guide treatment decisions.Funding Statement: This work was supported by the National Nature Science Foundation of China (Grant Nos. 81972897) and Guangdong Province Universities and Colleges Pearl River Scholar Funded Scheme (2015).Declaration of Interests: The authors declare that they do not have any conflicts of interest.Ethics Approval Statement: This retrospective analysis was approved by Medical Ethics committee of Nanfang Hospital of Southern Medical University, and the requirement for informed consent was waived by the ethics committee.