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Record W4400066866 · doi:10.1016/s2666-7568(24)00092-8

Association of intrinsic capacity with functional decline and mortality in older adults: a systematic review and meta-analysis of longitudinal studies

2024· review· en· W4400066866 on OpenAlexaboutno aff
Juan Luis Sánchez‐Sánchez, Wan‐Hsuan Lu, Daniel Gallardo‐Gómez, Borja del Pozo Cruz, Philipe de Souto Barreto, Alejandro Lucía, Pedro L. Valenzuela

Bibliographic record

VenueThe Lancet Healthy Longevity · 2024
Typereview
Languageen
FieldMedicine
TopicFrailty in Older Adults
Canadian institutionsnot available
FundersAgence Nationale de la RechercheUniversidad Pública de NavarraEuropean CommissionInstituto de Salud Carlos IIIUniversidad de Sevilla
KeywordsMeta-analysisAssociation (psychology)GerontologyDemographyPsychologyMedicineSociologyInternal medicine

Abstract

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Background Together with environmental factors, intrinsic capacity (the composite of all the physical and mental capacities of an individual) has been proposed as a marker of healthy ageing.However, whether intrinsic capacity predicts major clinical outcomes is unclear.We aimed to explore the association of intrinsic capacity with functional decline and mortality in older adults.Methods In this systematic review and meta-analysis, we conducted a systematic search in MEDLINE (via PubMed), Scopus, and Web of Science from database inception to Feb 14, 2024, of observational longitudinal studies conducted in older adults (age ≥60 years) assessing the association of intrinsic capacity with impairment in basic activities of daily living (BADL) or instrumental activities of daily living (IADL) or risk of mortality.Estimates were extracted by two reviewers (JLS-S and W-HL) and were pooled using three-level meta-analytic models.The quality of each study was independently assessed by two authors (JLS-S and PLV) using the Newcastle-Ottawa Scale for longitudinal studies.Heterogeneity was evaluated using the I² indicator at two levels: within-study (level 2) and between-study (level 3) variation.For associations between intrinsic capacity and IADL and BADL, we transformed data (standardised β coefficients and odds ratios [ORs]) into Pearson product moment correlation coefficients (r) using Pearson and Digby formulas to allow comparability across studies.For associations between intrinsic capacity and risk of mortality, hazard ratios (HRs) with 95% CIs were extracted from survival analyses.This study is registered with PROSPERO, CRD42023460482.Findings We included 37 studies (206 693 participants; average age range 65•3-85•9 years) in the systematic review, of which 31 were included in the meta-analysis on the association between intrinsic capacity and outcomes; three studies (2935 participants) were included in the meta-analysis on the association between intrinsic capacity trajectories and longitudinal changes in BADL or IADL.Intrinsic capacity was inversely associated with longitudinal impairments in BADL (Pearson's r -0•12 [95% CI -0•19 to -0•04]) and IADL (-0•24 [-0•35 to -0•13]), as well as with mortality risk (hazard ratio 0•57 [95% CI 0•51 to 0•63]).An association was also found between intrinsic capacity trajectories and impairment in IADL (but not in BADL), with maintained or improved intrinsic capacity over time associated with a lower impairment in IADL (odds ratio 0•37 [95% CI 0•19 to 0•71]).There was no evidence of publication bias (Egger's test p>0•05) and there was low between-study heterogeneity (I²=18•4%), though withinstudy (I²=63•2%) heterogeneity was substantial.Interpretation Intrinsic capacity is inversely associated with functional decline and mortality risk in older adults.These findings could support the use of intrinsic capacity as a marker of healthy ageing, although further research is needed to refine the structure and operationalisation of this construct across settings and populations.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.021
metaresearch head score (Gemma)0.049
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.021
Threshold uncertainty score0.110

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0210.049
Meta-epidemiology (narrow)0.0030.001
Meta-epidemiology (broad)0.0170.038
Bibliometrics0.0090.009
Science and technology studies0.0010.001
Scholarly communication0.0040.002
Open science0.0020.002
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0030.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.208
GPT teacher head0.418
Teacher spread0.211 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designMeta-analysis
Domainnot available
GenreReview

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations123
Published2024
Admission routes1
Has abstractyes

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