ArticleBMC cardiovascular disorders2026
Association of frailty-risk indicators with cardiovascular diseases: evidence from the CHARLS.
Article in BMC cardiovascular disorders, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
Abstract
Cardiovascular diseases (CVDs) impose a heavy global disease burden, and China faces increasing healthcare costs and socioeconomic losses. Frailty is an age-related clinical state characterized by reduced physiological reserve and multisystem dysfunction. Because a complete Fried frailty phenotype could not be reconstructed from the available CHARLS variables, this study used "frailty risk factors" to refer to available physical performance and biomarker indicators related to frailty or high frailty risk, including handgrip strength (HGS)-derived variables and cystatin C (Cys C). This study explored the association between these indicators and CVDs.Methods Data from the 2015 China Health and Retirement Longitudinal Study (CHARLS) were analyzed. Participants were grouped by prevalent CVDs, defined as self-reported physician-diagnosed hypertension, heart disease, or stroke. LASSO regression followed by simple and multiple logistic regression was used to screen variables. The dataset was randomly split 6:2:2 into training, testing, and validation sets to develop six models (LR, XGBoost, LightGBM, SVM, RF, and DT), and model performance was evaluated by discrimination, calibration, decision curve analysis, and SHAP interpretability analyses.Results A total of 10,657 participants were included (76% female), of whom 2,650 had CVDs (84% female). The XGBoost model showed the best overall performance. SHAP analysis identified age, HbA1c, UA, and Cys C as variables increasing the predicted risk of CVDs, whereas higher left HGS/weight ratio and lower blood pressure values were associated with lower predicted risk.Conclusion These findings suggest that frailty risk factors, especially HGS/weight ratio and Cys C, may provide additional information for CVD risk stratification beyond conventional factors. The results support incorporating simple physical performance assessment and frailty-risk evaluation into CVD prevention strategies.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.