Evidence map›Paper›PMID 41618949›Full record

ArticleJACC. Asia2026

Biological Age Acceleration and All-Cause Mortality in Moderate to Severe Aortic Valve Stenosis: A Prospective Cohort Study.

Yiqi Zheng, Xinghao Xu, Zhenyu Xiong, Bingzhen Li, Han Wen, Yue Guo, Menghui Liu, Huimin Zhou, Xingfeng Xu, Shaozhao Zhang and 3 more

Abstract read
In one paragraph

Article in JACC. Asia, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

13 authors.

Yiqi ZhengDepartment of Cardiology, First Affiliated Hospital of Sun Yat-Sen University, Guangzhou, China; NHC Key Laboratory of Assisted Circulation (Sun Yat-Sen University), Guangzhou, China; Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, China.
Xinghao XuDepartment of Cardiology, First Affiliated Hospital of Sun Yat-Sen University, Guangzhou, China; NHC Key Laboratory of Assisted Circulation (Sun Yat-Sen University), Guangzhou, China.
Zhenyu XiongDepartment of Cardiology, First Affiliated Hospital of Sun Yat-Sen University, Guangzhou, China; NHC Key Laboratory of Assisted Circulation (Sun Yat-Sen University), Guangzhou, China.
Bingzhen LiDepartment of Cardiology, First Affiliated Hospital of Sun Yat-Sen University, Guangzhou, China; NHC Key Laboratory of Assisted Circulation (Sun Yat-Sen University), Guangzhou, China.
Han WenDepartment of Cardiology, First Affiliated Hospital of Sun Yat-Sen University, Guangzhou, China; NHC Key Laboratory of Assisted Circulation (Sun Yat-Sen University), Guangzhou, China.
Yue GuoDepartment of Cardiology, First Affiliated Hospital of Sun Yat-Sen University, Guangzhou, China; NHC Key Laboratory of Assisted Circulation (Sun Yat-Sen University), Guangzhou, China.
Menghui LiuDepartment of Cardiology, First Affiliated Hospital of Sun Yat-Sen University, Guangzhou, China; NHC Key Laboratory of Assisted Circulation (Sun Yat-Sen University), Guangzhou, China.
Huimin ZhouDepartment of Cardiology, First Affiliated Hospital of Sun Yat-Sen University, Guangzhou, China; NHC Key Laboratory of Assisted Circulation (Sun Yat-Sen University), Guangzhou, China.
Xingfeng XuDepartment of Cardiology, First Affiliated Hospital of Sun Yat-Sen University, Guangzhou, China; NHC Key Laboratory of Assisted Circulation (Sun Yat-Sen University), Guangzhou, China.
Shaozhao ZhangDepartment of Cardiology, First Affiliated Hospital of Sun Yat-Sen University, Guangzhou, China; NHC Key Laboratory of Assisted Circulation (Sun Yat-Sen University), Guangzhou, China.
Rihua HuangDepartment of Cardiology, First Affiliated Hospital of Sun Yat-Sen University, Guangzhou, China; NHC Key Laboratory of Assisted Circulation (Sun Yat-Sen University), Guangzhou, China.
Xiaodong ZhuangDepartment of Cardiology, First Affiliated Hospital of Sun Yat-Sen University, Guangzhou, China; NHC Key Laboratory of Assisted Circulation (Sun Yat-Sen University), Guangzhou, China. Electronic address: zhuangxd3@mail.sysu.edu.cn.
Xinxue LiaoDepartment of Cardiology, First Affiliated Hospital of Sun Yat-Sen University, Guangzhou, China; NHC Key Laboratory of Assisted Circulation (Sun Yat-Sen University), Guangzhou, China. Electronic address: liaoxinx@mail.sysu.edu.cn.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundBiological age acceleration (BAA) is a promising aging surrogate, but its prognostic value in moderate to severe aortic valve stenosis (AVS) remains undetermined.

objectivesIn this study, the authors sought to explore the association between BAA and all-cause mortality in patients with moderate to severe AVS.

methodsA total of 559 patients were selected in the ARISTOTLE (Aortic Valve Diseases Risk Factor Assessment and Prognosis Model Construction) study. BAA was measured with the use of clinical biomarkers based on the KDM-BA and PhenoAge algorithms. Cox regression, restricted cubic spline (RCS) regression, and incremental predictive value analyses were used to evaluate the association between BAA and mortality.

resultsAmong 559 patients (mean age 64.80 years, 315 [56.4%] male), there were 153 cases (27.4%) of all-cause mortality during median 35.50 months of follow-up (range: 18.47-57.03 months). Kaplan-Meier curves revealed significantly elevated mortality in the highest quartile of BAA for both measures (KDM-BA: 38.8% [HR: 2.72; 95% CI: 1.73-4.29]; PhenoAge: 41.1% [HR: 3.26; 95% CI: 2.01-5.27]; both log-rank P < 0.0001). After fully adjusting for confounders, each SD increase in BAA was significantly associated with higher mortality (KDM-BA acceleration: HR: 1.36 [95% CI: 1.15-1.61]; PhenoAge acceleration: HR: 1.35 [95% CI: 1.17-1.56]). RCS regression revealed a significant linear BAA-mortality relationship. The addition of BAA into the basic model for all-cause mortality improved C-statistics (both P < 0.001), continuous-free net reclassification improvement value (both P = 0.013), and integrated discrimination improvement value (both P < 0.05).

conclusionsBiomarker-derived BAA is independently associated with increased all-cause mortality in moderate to severe AVS patients, highlighting its potential as a prognostic indicator.

Indexed as

aortic valve stenosisbiological age accelerationmortality

Identifiers

PMID41618949
PMCPMC13080748

What Socratic holds

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LicenceCC BY-NC-ND
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Registered trials

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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 Socratic graph.