Dataset Information

A meta-analysis of the effects of statin treatment on cardiovascular events and all-cause mortality in diabetic dialysis patients.

ABSTRACT:

Objectives

Diabetic dialysis patients have higher risk of cardiovascular disease (CVD) than general population. While statin treatment is effective in prevention of CVD and all-cause mortality in general population, the use of statin in diabetic dialysis patients remains controversial. Thus, we aimed to assess the effects of statin treatment on prevention of CVD and all-cause mortality in diabetic dialysis patients by meta-analysis.

Materials and methods

Pubmed, Embase and Cochrane Library were searched between each database's inception and July, 2014. Hazard ratio (HR) with 95% confidence interval (CI) for CVD and all-cause mortality was extracted from each study. The pooled analysis was performed using random-effects models by Stata 12.0.

Results

Our search yielded five eligible articles including two RCTs and three observational studies. By pooled estimate, statin treatment was associated with a decreased risk of the cardiac endpoint which included cardiac death and nonfatal MI (HR=0.84, 95% CI: 0.78-0.90) and all cardiac events combined (HR=0.89, 95% CI: 0.82-0.96). There was no difference in the overall incidence of fatal or nonfatal stroke (HR=1.24, 95% CI: 0.99-1.53) and all cerebrovascular events combined (HR=1.14, 95% CI: 0.98-1.33) between statin treatment and control group. Finally, statin treatment was associated with a decreased risk of all-cause mortality (HR=0.81, 95% CI: 0.71-0.92).

Conclusions

Statin treatment may be beneficial for reducing the risk of cardiac events and all-cause mortality while have no effect on overall cerebrovascular events in diabetic dialysis patients. More RCTs were needed to validate the results.

SUBMITTER: Yang M

PROVIDER: S-EPMC4538050 | biostudies-literature | 2015

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

A meta-analysis of the effects of statin treatment on cardiovascular events and all-cause mortality in diabetic dialysis patients.

Yang Man M Xie Xi-Sheng XS Yuan Wei-Jie WJ

International journal of clinical and experimental medicine 20150615 6

<h4>Objectives</h4>Diabetic dialysis patients have higher risk of cardiovascular disease (CVD) than general population. While statin treatment is effective in prevention of CVD and all-cause mortality in general population, the use of statin in diabetic dialysis patients remains controversial. Thus, we aimed to assess the effects of statin treatment on prevention of CVD and all-cause mortality in diabetic dialysis patients by meta-analysis.<h4>Materials and methods</h4>Pubmed, Embase and Cochran ...[more]

PMID: 26309494

Similar Datasets

Project description:Some variables including age, comorbidity of diabetes, and so on at dialysis initiation are associated with patient prognosis. Cardiovascular (CV) events are a major cause of death, and adequate models that predict prognosis in dialysis patients are warranted. Therefore, we created models using some variables at dialysis initiation. We used a database of 1,520 consecutive dialysis patients (median age, 70 years; 492 women [32.4%]) from a multicenter prospective cohort study. We established the primary endpoint as a composite of the incidence of first CV events or all-cause death. A multivariable Cox proportional hazard regression model was used to construct a model. We considered a complex and a simple model. We used area under the receiver operating characteristic curve (AUROC) to assess and compare the predictive performances of the prediction models and evaluated the improvement in discrimination using the complex model versus the simple model using net reclassification improvement (NRI). We then assessed integrated discrimination improvement (IDI) to evaluate improvements in average sensitivity and specificity. Of 392 deaths, 152 were CV-related. Totally, 506 CV events occurred during the follow-up period (median 1,285 days). Finally, 692 patients reached the primary endpoint. Baseline data were set at dialysis initiation. AUROC for the primary endpoint was 0.737 (95% confidence interval [CI], 0.712-0.761) in the simple model and 0.765 (95% CI, 0.741-0.788) in the complex model. There were significant intergroup differences in NRI (0.44; 95% CI, 0.34-0.53; p < 0.001) and IDI (0.02; 95% CI, 0.02-0.03; p < 0.001). We prepared a Shiny R application for each model to automatically calculate the predicted occurrence probability (https://statacademy.shinyapps.io/App_inaguma_20190717/). The complex model made more accurate predictions than the simple model. However, the intergroup difference was not significant. Hence, the simple model was more useful than the complex model. The tool was useful in a real-world clinical setting because it required only routinely available variables. Moreover, we emphasized that the tool could predict the incidence of CV events or all-cause mortality for individual patients. In the future, we must confirm its external validity in other prospective cohorts.

Project description:BackgroundBased on the International Society for peritoneal dialysis (PD) recommendations, blockade of renin-angiotensin systems with an angiotensin-converting enzyme inhibitors (ACEI) and angiotensin receptor blockers (ARB) improves residual kidney function in PD patients. However, the long-term effectiveness of ACEI/ARB use in PD patients has not been fully elucidated. We, therefore, intend to perform a systematic review and meta-analysis to summarize the effects of ACEI/ARB use on long-term mortality, cardiovascular outcomes, and adverse events among PD patients.MethodsThis systematic review will include both randomized controlled trials and non-randomized studies in adult PD patients. We also plan to incorporate data from our cohort study in Thai PD population into this review. We will search PubMed, Medline, EMBASE, Cochrane Library, Web of Science, Scopus, CINAHL, and grey literature from inception to February 29, 2019, with no language restrictions. The process of study screening, selection, data extraction, risk of bias assessment, and grading the strength of evidence will be performed independently by a pair of reviewers. Any discrepancy will be resolved through a team discussion and/or consultation with the third reviewer. The pooled effects estimate and 95% confidence intervals will be estimated using DerSimonian-Laird random-effects models. Heterogeneity will be assessed by the Cochran Q test, I index and tau-squared statistics. The funnel plots along with the Begg and Egger test and trim and fill method will be performed to investigate any evidence of publication bias. Preplanned subgroup analyses and random-effects univariate meta-regressions will be performed to quantify the potential sources of heterogeneity based on studies- and patient-characteristics.ResultsThis will be the first systematic review and meta-analysis to summarize the long-term effectiveness of renin-angiotensin system inhibitors in PD populations.ConclusionIn summary, this systematic review and meta-analysis will summarize the effectiveness of ACEI/ARB on long-term mortality, cardiovascular outcomes, and adverse events among adult PD patients by integrated all available evidences.Ethics and disseminationBased on the existing published data, an ethical approval is not required. The findings will be disseminated through scientific meetings and publications in peer-reviewed journals.PROSPERO registration number: CRD42019129492.

Dataset Information

A meta-analysis of the effects of statin treatment on cardiovascular events and all-cause mortality in diabetic dialysis patients.

Objectives

Materials and methods

Results

Conclusions

Publications

A meta-analysis of the effects of statin treatment on cardiovascular events and all-cause mortality in diabetic dialysis patients.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets