Background: Neither a vaccine nor specific therapeutic drugs against 2019 novel coronavirus have been developed. Some studies have shown that Xuebijing injection (XBJ) can exert an anti-inflammatory effect by inhibiting the production of interleukin-6 (IL-6), tumor necrosis factor alpha (TNF-α), and other cytokines.This study aimed to investigate the effect of XBJ on coronavirus disease 2019 (COVID-19) and its effects on IL-6 and tumor necrosis alpha TNF-α.Methods: A total of 42 patients, who were diagnosed with COVID-19 and treated with XBJ combined with routine treatment at Chongqing University Three Gorges Hospital between January 20, 2020, and March 11, 2020, were selected as the observation group. A control group comprising 16 patients who received routine treatment was also established, and cases were matched from the observation group on a 1:1 basis according to age, comorbidities, and mild and severe disease. The clinical symptoms, laboratory test indexes, and changes in computed tomography (CT) scans of patients in the two groups were observed at the time of admission and 7 days after treatment, and the time taken for the patients to produce a negative nucleic acid test was also recorded.Results: There were no significant differences in baseline data between the two groups. After treatment, there were significant improvements in IL-6 levels and body temperature in the observation group as compared with the control group. Particularly in severe patients, the reduction in body temperature in the observation group was greater than that in the control group (P<0.05). A higher number of patients in the observation group showed improved CT imaging results compared with the control group, and the time taken to produce a negative nucleic acid test was shorter in the observation group than in the control group;
Objective Preeclampsia, the main cause of maternal and perinatal deaths, is associated with several maternal complications and adverse perinatal outcomes. Some prediction models are uesd to evaluate adverse pregnancy outcomes. However, some of the current prediction models are mainly carried out in developed countries, and many problems are still exist. We, thus, developed and validated a nomogram to predict the risk of adverse pregnancy outcomes of preeclampsia in Chinese pregnant women. Methods The clinical data of 720 pregnant women with preeclampsia in seven medical institutions in Chongqing from January 1, 2010, to December 31, 2020, were analyzed retrospectively. The patients were divided into two groups: 180 cases (25%) with adverse outcomes and 540 cases (75%) without adverse outcomes. The indicators were identified via univariate analysis. Logistic regression analysis was used to establish the prediction model, which was displayed by a nomogram. The performance of the nomogram was evaluated in terms of the area under the receiver operating characteristic (ROC) curve, calibration, and clinical utility. Results Univariate analysis showed that 24 indicators were significantly different (P < 0.05). Logistic regression analysis showed that gestational age, 24 h urine protein qualitative, and TT were significantly different (P < 0.05). The area under the ROC curve was 0.781 (95% CI 0.737–0.825) in training set and 0.777 (95% CI 0.689–0.865) in test set. The calibration curve of the nomogram showed good agreement between prediction and observation. The analysis of the clinical decision curve showed that the nomogram is of practical significance. Conclusion Our study identified gestational age, 24 h urine protein qualitative, and TT as risk factors for adverse outcomes of preeclampsia in pregnant women, and constructed a nomogram that can easily predict and evaluate the risk of adverse pregnancy outcomes in women with preeclampsia.
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