Comparison of the prophylactic antithrombotic effect of indobufen and warfarin in patients with nephrotic syndrome: a randomized controlled trial.

PURPOSE: The risk of thromboembolic events is elevated in patients with nephrotic syndrome, and warfarin use has been associated with an increased risk of bleeding. Indobufen, a selective cyclooxygenase-1 inhibitor, is currently being evaluated for the prevention of thromboembolic events in nephrotic syndrome. This study aimed to compare the efficacy and safety of indobufen with that of warfarin in patients with nephrotic syndrome. MATERIALS AND METHODS: This multicenter, randomized, three-arm, open-label, parallel controlled trial involved a total of 180 adult patients with nephrotic syndrome from four centers in China. Patients were randomly assigned to receive 100 mg indobufen (bid), 200 mg indobufen (bid), and 3 mg warfarin (qd) daily for 12 weeks. The primary endpoints included thromboembolic and bleeding events, while laboratory results and adverse events constituted secondary endpoints. RESULTS: No thromboembolic events occurred in the high-/low-dose indobufen and warfarin groups. Moreover, the use of a low dose of indobufen significantly reduced the risk of minor bleeding events compared with warfarin use (2% versus 18%, p < .05). Finally, adverse events were more frequent in warfarin-treated patients. CONCLUSIONS: This study found that indobufen therapy provided equivalent effects in preventing thromboembolic events compared with warfarin therapy, while low dose of indobufen was associated with a reduced risk of bleeding events, thus it should be recommended for the prevention of thromboembolic events in clinical practice in patients with nephrotic syndrome. TRIAL REGISTRATION NUMBER: ChiCTR-IPR-17013428.

Development of an Early Warning Model for Predicting the Death Risk of Coronavirus Disease 2019 Based on Data Immediately Available on Admission.

Introduction: COVID-19 has overloaded worldwide medical facilities, leaving some potentially high-risk patients trapped in outpatient clinics without sufficient treatment. However, there is still a lack of a simple and effective tool to identify these patients early. Methods: A retrospective cohort study was conducted to develop an early warning model for predicting the death risk of COVID-19. Seventy-five percent of the cases were used to construct the prediction model, and the remaining 25% were used to verify the prediction model based on data immediately available on admission. Results: From March 1, 2020, to April 16, 2020, a total of 4,711 COVID-19 patients were included in our study. The average age was 63.37 ± 16.70 years, of which 1,148 (24.37%) died. Finally, age, SpO2, body temperature (T), and mean arterial pressure (MAP) were selected for constructing the model by univariate analysis, multivariate analysis, and a review of the literature. We used five common methods for constructing the model and finally found that the full model had the best specificity and higher accuracy. The area under the ROC curve (AUC), specificity, sensitivity, and accuracy of full model in train cohort were, respectively, 0.798 (0.779, 0.816), 0.804, 0.656, and 0.768, and in the validation cohort were, respectively, 0.783 (0.751, 0.815), 0.800, 0.616, and 0.755. Visualization tools of the prediction model included a nomogram and an online dynamic nomogram (https://wanghai.shinyapps.io/dynnomapp/). Conclusion: We developed a prediction model that might aid in the early identification of COVID-19 patients with a high probability of mortality on admission. However, further research is required to determine whether this tool can be applied for outpatient or home-based COVID-19 patients.