Dataset Information

Development of a prediction model to estimate the 5-year risk of cardiovascular events and all-cause mortality in haemodialysis patients: a retrospective study.

ABSTRACT:

Background

Cardiovascular disease (CVD) is a major cause of mortality in patients on haemodialysis. The development of a prediction model for CVD risk is necessary to help make clinical decisions for haemodialysis patients. This retrospective study aimed to develop a prediction model for the 5-year risk of CV events and all-cause mortality in haemodialysis patients in China.

Methods

We retrospectively enrolled 398 haemodialysis patients who underwent dialysis at the dialysis facility of the General Hospital of Northern Theater Command in June 2016 and were followed up for 5 years. The composite outcome was defined as CV events and/or all-cause death. Multivariable logistic regression with backwards stepwise selection was used to develop our new prediction model.

Results

Seven predictors were included in the final model: age, male sex, diabetes, history of CV events, no arteriovenous fistula at dialysis initiation, a monocyte/lymphocyte ratio greater than 0.43 and a serum uric acid level less than 436 mmol/L. Discrimination and calibration were satisfactory, with a C-statistic above 0.80. The predictors lay nearly on the 45-degree line for agreement with the outcome in the calibration plot. A simple clinical score was constructed to provide the probability of 5-year CV events or all-cause mortality. Bootstrapping validation showed that the new model also has similar discrimination and calibration. Compared with the Framingham risk score (FRS) and a similar model, our model showed better performance.

Conclusion

This prognostic model can be used to predict the long-term risk of CV events and all-cause mortality in haemodialysis patients. An MLR greater than 0.43 is an important prognostic factor.

SUBMITTER: Zhang A

PROVIDER: S-EPMC9653067 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature

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Publications

Development of a prediction model to estimate the 5-year risk of cardiovascular events and all-cause mortality in haemodialysis patients: a retrospective study.

Zhang Aihong A Qi Lemuge L Zhang Yanping Y Ren Zhuo Z Zhao Chen C Wang Qian Q Ren Kaiming K Bai Jiuxu J Cao Ning N

PeerJ 20221109

<h4>Background</h4>Cardiovascular disease (CVD) is a major cause of mortality in patients on haemodialysis. The development of a prediction model for CVD risk is necessary to help make clinical decisions for haemodialysis patients. This retrospective study aimed to develop a prediction model for the 5-year risk of CV events and all-cause mortality in haemodialysis patients in China.<h4>Methods</h4>We retrospectively enrolled 398 haemodialysis patients who underwent dialysis at the dialysis facil ...[more]

PMID: 36389426

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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.

Project description:BackgroundLow muscle strength is associated with adverse clinical outcomes in patients undergoing haemodialysis (HD). No studies have reported the association between dynapenia, defined by both low handgrip strength (HGS) and quadriceps isometric strength (QIS), and long-term clinical outcomes in patients on HD. We examined the associations between dynapenia, cardiovascular (CV) hospitalizations, and all-cause mortality in the HD population.MethodsThis retrospective study used data from outpatients undergoing HD at two dialysis facilities between October 2002 and March 2020. We defined low muscle strength as an HGS of <28 kg for men and <18 kg for women and a QIS of <40% dry weight. Furthermore, we categorized dynapenia into three groups: robust ('high HGS and high QIS'), either low HGS or low QIS ('low HGS only' or 'low QIS only'), and dynapenia ('low HGS and low QIS'). The outcomes were all-cause mortality and a composite of CV hospitalizations and mortality. Cox proportional hazards and negative binomial models were used to examine these associations.ResultsA total of 616 patients (mean age, 65.4 ± 12.2 years; men, 61%) were included in the analyses. During the follow-up (median, 3.0 years), a total of 163 deaths and 288 CV hospitalizations occurred. Patients with the either low HGS or low QIS [hazard ratio (HR), 1.75; 95% confidence intervals (CIs), 1.46-2.10] and dynapenia (HR, 2.80; 95% CIs, 2.49-3.14) had a higher risk of mortality than those in the robust group. When compared with the robust group, the either low HGS or low QIS [incidence rate ratio (IRR): 1.41, 95% CI: 1.00-1.99] and dynapenia (IRR: 2.04, 95% CI: 1.44-2.89) groups were associated with a significantly higher incident risk of CV hospitalizations.ConclusionsDynapenia (muscle weakness in both upper and lower extremities) was associated with increased risks of all-cause mortality and CV hospitalizations among patients on HD. Screening for dynapenia using both HGS and QIS may be useful for prognostic stratification in the HD population.

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Project description:Purpose: We aimed to assess the associations of handgrip strength (HS) with cardiovascular and all-cause mortality and whether adding data on HS to cardiovascular disease (CVD) risk factors is associated with improvement in CVD mortality prediction.Design: Handgrip strength was assessed in a population-based sample of 861 participants aged 61-74 years at baseline. Relative HS was obtained by dividing the absolute value by body weight.Results: During a median (interquartile range) follow-up of 17.3 (12.6-18.4) years, 116 fatal coronary heart diseases (CHDs), 195 fatal CVDs and 412 all-cause mortality events occurred. On adjustment for several risk factors, the hazard ratios (95% confidence intervals (CIs)) for fatal CHD, fatal CVD and all-cause mortality were 0.59 (0.37-0.95), 0.59 (0.41-0.86) and 0.66 (0.51-0.84), respectively, comparing extreme tertiles of relative HS. Adding relative HS to a CVD mortality risk prediction model containing established risk factors did not improve discrimination or reclassification using Harrell's C-index (C-index change: 0.0034; p = .65), integrated-discrimination-improvement (0.0059; p = .20) and net-reclassification-improvement (-1.31%; p = .74); however, there was a significant difference in -2 log likelihood (p < .001).Conclusions: Relative HS is inversely associated with CHD, CVD and all-cause mortality events. Adding relative HS to conventional risk factors improves CVD risk assessment using sensitive measures of discrimination.KEY MESSAGESHandgrip strength (HS) assessment is simple, inexpensive and it takes only a few minutes to measure in clinical practice; however, its prognostic role for fatal cardiovascular outcomes on top of traditional risk factors in apparently healthy populations is uncertain.In a population-based prospective cohort study, good HS adjusted for body weight was associated with lower risk of fatal cardiovascular outcomes and the associations remained consistent across several clinically relevant subgroups.Handgrip strength may be a useful prognostic tool for fatal CHD and CVD events, in the general population.

Dataset Information

Development of a prediction model to estimate the 5-year risk of cardiovascular events and all-cause mortality in haemodialysis patients: a retrospective study.

Background

Methods

Results

Conclusion

Publications

Development of a prediction model to estimate the 5-year risk of cardiovascular events and all-cause mortality in haemodialysis patients: a retrospective study.

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