Evidence map›Paper›PMID 42865368›Full record

ArticleFrontiers in endocrinology2026

Pain as a predictor of incident frailty in middle-aged and older adults with metabolic dysfunction-associated steatotic liver disease: a prospective cohort study using machine learning and external validation.

Huifen Hu, Ling Zhang, Xianbing Zhang, Fuhua Li, Wen Liu

Abstract read
In one paragraph

Article in Frontiers in endocrinology, 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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1 · What the graph read from it

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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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4 · The record

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5 · Who and what money

Authors and funding

5 authors.

Huifen HuDepartment of Hepatology, No.2 People's Hospital of Fuyang City, Fuyang Infectious Disease Clinical College of Anhui Medical University, Fuyang, Anhui, China.
Ling ZhangDepartment of Hepatology, No.2 People's Hospital of Fuyang City, Fuyang Infectious Disease Clinical College of Anhui Medical University, Fuyang, Anhui, China.
Xianbing ZhangDepartment of Hepatology, No.2 People's Hospital of Fuyang City, Fuyang Infectious Disease Clinical College of Anhui Medical University, Fuyang, Anhui, China.
Fuhua LiDepartment of Hepatology, No.2 People's Hospital of Fuyang City, Fuyang Infectious Disease Clinical College of Anhui Medical University, Fuyang, Anhui, China.
Wen LiuDepartment of Hepatology, No.2 People's Hospital of Fuyang City, Fuyang Infectious Disease Clinical College of Anhui Medical University, Fuyang, Anhui, China.

Funding

Integrting Information About Aging SurveysR01AG030153 · NIA · UNIVERSITY OF SOUTHERN CALIFORNIA · PI Sara Adar, Alden L. Gross · 2007 to 2026
$41.7M
Mega Meta Data Set of the Health and Retirement Surveys Around the WorldRC2AG036619 · NIA · RAND CORPORATION · PI KAPTEYN, ARIE · 2009 to 2010
$2.0M
Archiving & Creating User Friendly Data: the Longitudinal Aging Survey in IndiaR03AG043052 · NIA · RAND CORPORATION · PI LEE, JINKOOK · 2012 to 2012
$95k
NIA NIH HHS R01 AG030153NIA NIH HHS R03 AG043052NIA NIH HHS RC2 AG036619
6 · The paper itself

Abstract

Background: Metabolic dysfunction-associated steatotic liver disease (MASLD), defined here by the lipid accumulation product (LAP), is common in middle-aged and older adults and linked to frailty, but factors driving frailty progression remain unclear. We examined the role of pain and depressive symptoms in incident frailty. Methods: Data came from two prospective national cohorts: the China Health and Retirement Longitudinal Study (CHARLS, 2011-2018) and the English Longitudinal Study of Ageing (ELSA, 2012-2020). Participants with MASLD and no baseline frailty were followed for 7-8 years. Three feature selection methods (LASSO, Boruta, and recursive feature elimination) identified 14 consensus predictors from 31 candidates. Nine machine learning algorithms were trained in CHARLS (70% training, 30% internal test), with ELSA reserved for external validation. Modified Poisson regression (prespecified four-model framework including baseline frailty index) estimated relative risks (RR); g-computation estimated population attributable fractions (PAF); and mediation by depressive symptoms was assessed. Net reclassification improvement (NRI) and integrated discrimination improvement (IDI) quantified the incremental value of pain. Results: The analysis included 3,622 CHARLS (median 56 years, 70% female) and 2,059 ELSA participants (median 64 years, 53% female). Frailty incidence was 24.49% (CHARLS) and 21.18% (ELSA). Logistic regression performed best (internal test AUC 0.740, 95% CI 0.706-0.774; external validation AUC 0.753, 0.728-0.779). Pain was the strongest predictor (mean absolute SHAP value 0.184). After full adjustment including baseline frailty index, pain remained associated with incident frailty (CHARLS: RR 1.219, 95% CI 1.085-1.368; ELSA: 1.310, 1.114-1.539). Under stated assumptions, the PAF was 8.01% (3.14%-12.66%) in CHARLS and 11.98% (4.76%-19.27%) in ELSA. Adding pain improved reclassification and discrimination (continuous NRI 0.397 and 0.409; IDI 0.024 and 0.023). Depressive symptoms mediated 74.0% (CHARLS) and 46.1% (ELSA) of the total effect; associations were consistent across most subgroups and strongest at baseline FI <0.10 (CHARLS: RR 1.794, 1.289-2.496; ELSA: 1.583, 1.125-2.227). Conclusion: Pain is a strong predictor of incident frailty in MASLD, with depressive symptoms as the principal mediator. Whether pain reduction modifies frailty risk requires interventional evidence. Routine pain screening could facilitate frailty risk assessment; an online calculator is provided for individualized risk prediction (https://baozhadekele.shinyapps.io/MASLD_Frailty/).

Indexed as

Fatty LiverFrailtyMachine LearningMetabolic DiseasesNon-alcoholic Fatty Liver DiseasePainAgedChinaDepressionFemaleHumansIncidenceLongitudinal StudiesMaleMiddle AgedProspective StudiesCHARLSdepressive symptomsELSAfrailtymachine learningMASLDpain

Identifiers

PMID42865368
PMCPMC13654746

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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.