Evidence map›Paper›PMID 41549278›Full record

ArticleEuropean journal of medical research2026

Prediction of cardiovascular mortality based on iron metabolism in patients with cardiovascular-kidney-metabolic syndrome: development and validation of clinical predictive model.

Ailifeire Aihaiti, Abulajiang Saidaming, Hasiyeti Tuerxun, Nan Li, Muyesai Nijiati

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Article in European journal of medical research, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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5 · Who and what money

Authors and funding

5 authors.

Ailifeire AihaitiXinjiang Emergency Center, People's Hospital of Xinjiang Uygur Autonomous Region, No.91 Tianchi Road, Tianshan District, Urumqi City, Xinjiang Uygur Autonomous Region, China.
Abulajiang SaidamingHospital of Xinjiang Traditional Uygur Medicine, Urumqi, Xinjiang, China.
Hasiyeti TuerxunXinjiang Emergency Center, People's Hospital of Xinjiang Uygur Autonomous Region, No.91 Tianchi Road, Tianshan District, Urumqi City, Xinjiang Uygur Autonomous Region, China.
Nan LiXinjiang Emergency Center, People's Hospital of Xinjiang Uygur Autonomous Region, No.91 Tianchi Road, Tianshan District, Urumqi City, Xinjiang Uygur Autonomous Region, China.
Muyesai NijiatiXinjiang Emergency Center, People's Hospital of Xinjiang Uygur Autonomous Region, No.91 Tianchi Road, Tianshan District, Urumqi City, Xinjiang Uygur Autonomous Region, China. muyassar11@aliyun.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundIron metabolism is associated with cardiovascular disease (CVD) mortality in patients with cardiovascular-kidney-metabolic (CKM) syndrome. However, its prognostic significance remains unclear. This study was aimed at evaluating incorporation of iron metabolism indicators as a predicting tool for CVD mortality in CKM.

methodsThis study was conducted on data of CKM patients collected from the NHANES between 1999 and 2018. The outcome was CVD mortality. Predictors included iron metabolism indicators and traditional risk factors. Cox proportional hazard models were performed to construct the model. The performance of model was assessed through Harrell's C, NIR, IDI, AIC, BIC and decision curve analysis curves. The nomogram was depicted to predict CVD mortality risk.

resultsTotal of 26,609 patients were included, among which 12,808 (48.1%) were male, and the mean age was 51 years. Over a median follow-up of 9.7 years, there were 911 (3.4%) CVD deaths. Among the iron metabolism indicators, iron and ferritin were associated with CVD mortality, and the performance of model improved after adding to the basic model (Harrell's C, 0.8353 vs 0.8880; NRI, < 0.001; IDI, < 0.001; AIC, 1667.7860 vs 324.8295; BIC, 1740.5520 vs 390.4293) in the training set. These were confirmed in the validation set. The model also demonstrated improved reclassification and discrimination (Harrell's C, 0.8332 vs 0.8946; NRI, < 0.001; IDI, 1.333; AIC, 769.3590 vs 195.0582; BIC, 834.3515 vs 250.9120).

conclusionsThe incorporation of serum iron and ferritin levels enhanced the predictive value for CVD mortality in CKM patients without pre-existing CVD.

Indexed as

Cardiovascular disease mortalityCardiovascular–kidney–metabolic syndromeIron metabolismNational Health and Nutrition Examination SurveyPrediction model

Identifiers

PMID41549278
PMCPMC12817717

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