Evidence map›Paper›PMID 40414902›Full record

ArticleEuropean journal of medical research2025

Comparison of the long-term prognostic value of different frailty instruments in older inpatients: a 5-year prospective cohort study.

Min Zeng, Yu-Hao Wan, Yao-Dan Liang, Jing Shi, Zhi-Kai Yang, Ting Wang, Chen Ji, Wei He, Ning Sun, Di Guo and 4 more

Abstract readComparative Study
In one paragraph

Article in European journal of medical research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed, 1 pooled it
–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

4 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. [Frailty in intensive care medicine].Medizinische Klinik, Intensivmedizin und Notfallmedizin · 2026
    Pooled it
  2. FI-CGA and eFI-CGA in Frailty Care: a Scoping Review.Canadian geriatrics journal : CGJ · 2026
    Review
  3. Article
  4. 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

14 authors.

Min Zeng *Department of Cardiology, Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing, People's Republic of China.
Yu-Hao Wan *Department of Cardiology, Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing, People's Republic of China.
Yao-Dan LiangDepartment of Pulmonary and Critical Care Medicine, Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing, People's Republic of China.
Jing ShiThe Key Laboratory of Geriatrics, Beijing Institute of Geriatrics, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing Hospital/National Center of Gerontology of National Health Commission, Beijing, 100730, China.
Zhi-Kai YangDepartment of Cardiology, Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing, People's Republic of China.
Ting WangDepartment of Cardiology, Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing, People's Republic of China.
Chen JiDepartment of Cardiology, Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing, People's Republic of China.
Wei HeDepartment of Cardiology, Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing, People's Republic of China.
Ning SunDepartment of Cardiology, Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing, People's Republic of China.
Di GuoDepartment of Cardiology, Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing, People's Republic of China.
Ling-Ling CuiDepartment of Cardiology, Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing, People's Republic of China.
Lin YangDepartment of Cardiology, Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing, People's Republic of China.
Jie-Fu Yang *Department of Cardiology, Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing, People's Republic of China. yangjiefu2011@126.com.
Hua Wang *Department of Cardiology, Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing, People's Republic of China. wh74220@aliyun.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundFrailty is associated with increased mortality in older adults, but limited studies compare frailty instruments among inpatients with long-term follow-up.

aimsTo evaluate five frailty scales for predicting 5-year all-cause mortality in older inpatients.

methodsThis prospective cohort study enrolled 917 inpatients aged ≥ 65 years. We used five commonly used scales [Clinical Frailty Scale (CFS), FRAIL, Fried, Edmonton, and the comprehensive geriatric assessment-frailty index (CGA-FI)] to screen or assess frailty and then conducted a 5-year telephone follow-up. The primary endpoint was 5-year all-cause mortality. The predictive value of different frailty scales was compared using Kaplan-Meier (K-M) survival analysis, COX regression models, and the receiver operating characteristic (ROC) curves.

resultsThe prevalence of frailty ranged from 19.5 to 36.5%. Both K-M survival curves and Cox regression confirmed that frailty patients had higher mortality risk across all scales. After multivariate adjustment, the hazard ratios from highest to lowest, were: CGA-FI, FRAIL, Fried, CFS, and Edmonton (all p < 0.05). Frailty demonstrated moderate performance, with area under the curves (AUCs) ranging from 0.70 to 0.75 (all p < 0.001). CGA-FI had the largest AUC of 0.724, revealing the best predictive value, while FRAIL had the smallest AUC of 0.666. The AUCs of Fried, Edmonton, and CFS gradually decreased, with no statistical differences. Furthermore, CFS has the highest sensitivity (77.5%).

conclusionsFrailty identified by all scales is associated with an increased risk of long-term mortality. CFS is the preferred frailty screening scale, while CGA-FI is the most accurate assessment scale. Trial registration ChiCTR1800017204 (07/18/2018).

Indexed as

Frail ElderlyFrailtyGeriatric AssessmentAgedAged, 80 and overFemaleFollow-Up StudiesHumansInpatientsKaplan-Meier EstimateMalePrognosisProspective StudiesROC CurveAll-cause mortalityFatigueFrailty scaleLong-term prognosisOlder hospitalized patients

Identifiers

PMID40414902
PMCPMC12105130

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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 OpenQuestion graph.