Dataset Information

Observational Evidence for Unintentional Weight Loss in All-Cause Mortality and Major Cardiovascular Events: A Systematic Review and Meta-Analysis.

ABSTRACT: The obesity paradox has been described in several observational cohorts and meta-analysis. However, evidence of the intentionality of weight loss in all-cause deaths and major cardiovascular events (MACE) in prospective cohorts is unclear. We analysed whether involuntary weight loss is associated with increased cardiovascular events and mortality. In a systematic review, we searched multiple electronic databases for observational studies published up to October 2016. Studies reporting risk estimates for unintentional weight loss compared with stable weight in MACE and mortality were included. Fifteen studies met the selection criteria, with a total of 178,644 participants. For unintentional weight loss, we found adjusted risk ratios (RRs) with confidence intervals (CIs) of 1.38 (95% CI: 1.23, 1.53) and 1.17 (95% CI: 0.98, 1.37) for all-cause mortality and MACE, respectively. Participants with comorbidities, overweight and obese populations, and older adults yielded RRs (95% CI) of 1.49 (1.30, 1.68), 1.11 (1.04, 1.18), and 1.81 (1.59, 2.03), respectively. Unintentional weight loss had a significant impact on all-cause mortality. We found no protective effect of being overweight or obese for unintentional weight loss and MACE.

SUBMITTER: De Stefani FDC

PROVIDER: S-EPMC6194006 | biostudies-literature | 2018 Oct

REPOSITORIES: biostudies-literature

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Publications

Observational Evidence for Unintentional Weight Loss in All-Cause Mortality and Major Cardiovascular Events: A Systematic Review and Meta-Analysis.

De Stefani Fernanda do Carmo FDC Pietraroia Priscila Saia PS Fernandes-Silva Miguel Morita MM Faria-Neto José J Baena Cristina Pellegrino CP

Scientific reports 20181018 1

The obesity paradox has been described in several observational cohorts and meta-analysis. However, evidence of the intentionality of weight loss in all-cause deaths and major cardiovascular events (MACE) in prospective cohorts is unclear. We analysed whether involuntary weight loss is associated with increased cardiovascular events and mortality. In a systematic review, we searched multiple electronic databases for observational studies published up to October 2016. Studies reporting risk estim ...[more]

PMID: 30337578

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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.

Dataset Information

Observational Evidence for Unintentional Weight Loss in All-Cause Mortality and Major Cardiovascular Events: A Systematic Review and Meta-Analysis.

Publications

Observational Evidence for Unintentional Weight Loss in All-Cause Mortality and Major Cardiovascular Events: A Systematic Review and Meta-Analysis.

Similar Datasets

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