ORIGINAL RESEARCH article
Front. Med.
Sec. Nephrology
Volume 12 - 2025 | doi: 10.3389/fmed.2025.1481866
A time-dependent predictive model for cardiocerebral vascular events in chronic hemodialysis patients: insights from a prospective study
Provisionally accepted
Haowen Zhong1
Mengbi Zhang1
Yingye Xie1Yuqin Qin2
Na Xie1Yuqiu Ye1
Heng Li3
Hongquan Peng4
Xun Liu5Xiaoyan Su1*Shaohong Li1*- 1Dongguan Tungwah Hospital, Dongguan, China
- 2KingPoint Data Technology Co., Ltd., Guangzhou, China
- 3Dongguan Songshan Lake Tungwah Hospital, Dongguan, China
- 4Kiang Wu Hospital, Macau, Macau, Macao, SAR China
- 5Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, Guangdong Province, China
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Context: The conventional risk factors for cardiocerebral vascular events (CVCs) in non-Hemodialysis (HD) patients cannot be directly applied to HD patients due to the unique characteristics of this population. More accurate information on the risk of progression to CVCs is needed for clinical decisions.Objective: To develop and validate time-dependent predictive models for the progression of CVCs in HD patients.Design, Setting, and Participants: Development and validation of time-dependent predictive models using demographic, clinical, and laboratory data from 3 dialysis centers between 2017 and 2021. These models were developed using time-dependent Cox proportional hazards regression and assessed for discrimination using the concordance index, goodness of fit using the Akaike information criterion and net reclassification improvement.Main Outcome Measures: CVCs included acute heart failure, acute hematencephalon, cardiac or brain-derived death, acute myocardial infarction, acute cerebral infarction, ischemic cardiomyopathy, unstable angina pectoris, and stable angina pectoris.Results: The development and validation cohorts included 233 and 215 patients, respectively. The most accurate model included age, sex, hemoglobin, serum albumin, serum phosphate, white blood cell count, blood flow rate and ultrafiltration volume during HD (C index, 0.704; 95% CI, 0.639-0.768 in the development cohort and 0.775; 95% CI, 0.706-0.843 in the validation cohort). In the validation cohort, this model was more accurate than a model containing variables whose P value in the Cox proportional hazards regression was less than 0.05 (NRI: 0.351, 95% CI: -0.115- 0.565).Conclusion: A time-dependent model using routinely obtained laboratory tests can accurately predict progression to CVCs in HD patients.
Keywords: Time-dependent, predictive model, cardiocerebral vascular events, hemodialysis, Laboratory tests
Received: 19 Aug 2024; Accepted: 22 May 2025.
Copyright: © 2025 Zhong, Zhang, Xie, Qin, Xie, Ye, Li, Peng, Liu, Su and Li. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence:
Xiaoyan Su, Dongguan Tungwah Hospital, Dongguan, China
Shaohong Li, Dongguan Tungwah Hospital, Dongguan, China
Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.