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Sökning: WFRF:(Chen ZH)

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  • Mao, W, et al. (författare)
  • Bupi Yishen Formula Versus Losartan for Non-Diabetic Stage 4 Chronic Kidney Disease: A Randomized Controlled Trial
  • 2021
  • Ingår i: Frontiers in pharmacology. - : Frontiers Media SA. - 1663-9812. ; 11, s. 627185-
  • Tidskriftsartikel (refereegranskat)abstract
    • Chinese herbal medicine (CHM) might have benefits in patients with non-diabetic chronic kidney disease (CKD), but there is a lack of high-quality evidence, especially in CKD4. This study aimed to assess the efficacy and safety of Bupi Yishen Formula (BYF) vs. losartan in patients with non-diabetic CKD4. This trial was a multicenter, double-blind, double-dummy, randomized controlled trial that was carried out from 11-08-2011 to 07-20-2015. Patients were assigned (1:1) to receive either BYF or losartan for 48 weeks. The primary outcome was the change in the slope of the estimated glomerular filtration rate (eGFR) over 48 weeks. The secondary outcomes were the composite of end-stage kidney disease, death, doubling of serum creatinine, stroke, and cardiovascular events. A total of 567 patients were randomized to BYF (n = 283) or losartan (n = 284); of these, 549 (97%) patients were included in the final analysis. The BYF group had a slower renal function decline particularly prior to 12 weeks over the 48-week duration (between-group mean difference of eGFR slopes: −2.25 ml/min/1.73 m2/year, 95% confidence interval [CI]: −4.03,−0.47), and a lower risk of composite outcome of death from any cause, doubling of serum creatinine level, end-stage kidney disease (ESKD), stroke, or cardiovascular events (adjusted hazard ratio = 0.61, 95%CI: 0.44,0.85). No significant between-group differences were observed in the incidence of adverse events. We conclude that BYF might have renoprotective effects among non-diabetic patients with CKD4 in the first 12 weeks and over 48 weeks, but longer follow-up is required to evaluate the long-term effects.Clinical Trial Registration:http://www.chictr.org.cn, identifier ChiCTR-TRC-10001518.
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  • Mei, J, et al. (författare)
  • Development and external validation of a COVID-19 mortality risk prediction algorithm: a multicentre retrospective cohort study
  • 2020
  • Ingår i: BMJ open. - : BMJ. - 2044-6055. ; 10:12, s. e044028-
  • Tidskriftsartikel (refereegranskat)abstract
    • This study aimed to develop and externally validate a COVID-19 mortality risk prediction algorithm.DesignRetrospective cohort study.SettingFive designated tertiary hospitals for COVID-19 in Hubei province, China.ParticipantsWe routinely collected medical data of 1364 confirmed adult patients with COVID-19 between 8 January and 19 March 2020. Among them, 1088 patients from two designated hospitals in Wuhan were used to develop the prognostic model, and 276 patients from three hospitals outside Wuhan were used for external validation. All patients were followed up for a maximal of 60 days after the diagnosis of COVID-19.MethodsThe model discrimination was assessed by the area under the receiver operating characteristic curve (AUC) and Somers’ D test, and calibration was examined by the calibration plot. Decision curve analysis was conducted.Main outcome measuresThe primary outcome was all-cause mortality within 60 days after the diagnosis of COVID-19.ResultsThe full model included seven predictors of age, respiratory failure, white cell count, lymphocytes, platelets, D-dimer and lactate dehydrogenase. The simple model contained five indicators of age, respiratory failure, coronary heart disease, renal failure and heart failure. After cross-validation, the AUC statistics based on derivation cohort were 0.96 (95% CI, 0.96 to 0.97) for the full model and 0.92 (95% CI, 0.89 to 0.95) for the simple model. The AUC statistics based on the external validation cohort were 0.97 (95% CI, 0.96 to 0.98) for the full model and 0.88 (95% CI, 0.80 to 0.96) for the simple model. Good calibration accuracy of these two models was found in the derivation and validation cohort.ConclusionThe prediction models showed good model performance in identifying patients with COVID-19 with a high risk of death in 60 days. It may be useful for acute risk classification.
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