Evidence map›Paper›PMID 41527045›Full record

ArticleBMC geriatrics2026

Construction and validation of a predictive model for reversible cognitive frailty in elderly people in nursing homes.

Yi Zhao, Ruiyang Guo, Jiajun Sai, Yaqi Wang, Xinyi Meng, Jianwen Lu, Bolun Zhao

Abstract readValidation Study
In one paragraph

Article in BMC geriatrics, 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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0citing papers in PubMed
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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

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3 · Its place in the literature

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No citing paper in PubMed yet.

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

7 authors.

Yi ZhaoSchool of Nursing, Dalian Medical University, Liaoning, 116044, China.
Ruiyang GuoSchool of Nursing, Dalian Medical University, Liaoning, 116044, China.
Jiajun SaiSchool of Nursing, Dalian Medical University, Liaoning, 116044, China.
Yaqi WangSchool of Nursing, Dalian Medical University, Liaoning, 116044, China.
Xinyi MengSchool of Nursing, Dalian Medical University, Liaoning, 116044, China.
Jianwen LuSchool of Nursing, Dalian Medical University, Liaoning, 116044, China. lujianwen0828@163.com.
Bolun ZhaoSchool of Nursing, Dalian Medical University, Liaoning, 116044, China. babylover021@126.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

aimTo investigate the factors affecting reversible cognitive frailty in older adults in nursing homes, to construct a risk prediction model, and to validate its prediction performance.

methodOlder adults from five nursing homes in Liaoning Province, China, were selected as the study subjects from April to October 2024, and the data were randomly divided into a training set and a validation set according to 8:2. Logistic regression analysis was used to analyze the factors affecting reversible cognitive frailty in older adults in nursing homes, and a column-line graph model was constructed using R software (4.4.1).

resultA total of 311 cases of older adults were included, of which 86 cases (27.7%) had reversible cognitive frailty. The AUCs of the training and validation sets were 0.852 and 0.805, respectively. The Hosmer-Lemeshow goodness-of-fit test values were P = 0.513 and 0.796 (both > 0.05).

conclusionThe risk prediction model constructed in this study has good predictive performance, which is beneficial for institutional workers in providing early warning of the risk of reversible cognitive frailty for older adults and intervention.

Indexed as

CognitionFrail ElderlyFrailtyNursing HomesAgedAged, 80 and overChinaFemaleHumansMaleNursing Home ResidentsPrediction AlgorithmsNursing homePredictive modelReversible cognitive frailty

Identifiers

PMID41527045
PMCPMC12983629

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.