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Acceleration of health deficit accumulation in late-life: evidence of terminal decline in frailty index three years before death in the US Health and Retirement Study

2021· article· en· W3139624997 on OpenAlexaff
Erwin Stolz, Hannes Mayerl, Emiel O. Hoogendijk, Joshua Armstrong, Regina Roller‐Wirnsberger, Wolfgang Freidl

Bibliographic record

VenueAnnals of Epidemiology · 2021
Typearticle
Languageen
FieldMedicine
TopicFrailty in Older Adults
Canadian institutionsLakehead University
Fundersnot available
KeywordsMedicineFrailty IndexDemographyGerontologyProxy (statistics)CohortInternal medicineStatistics

Abstract

fetched live from OpenAlex

BACKGROUND: Little is known about within-person frailty index (FI) changes during the last years of life. In this study, we assess whether there is a phase of accelerated health deficit accumulation (terminal health decline) in late-life. MATERIAL AND METHODS: A total of 23,393 observations from up to the last 21 years of life of 5713 deceased participants of the AHEAD cohort in the Health and Retirement Study were assessed. A FI with 32 health deficits was calculated for up to 10 successive biannual, self- and proxy-reported assessments (1995-2014), and FI changes according to time-to-death were analyzed with a piecewise linear mixed model with random change points. RESULTS: The average normal (preterminal) health deficit accumulation rate was 0.01 per year, which increased to 0.05 per year at approximately 3 years before death. Terminal decline began earlier in women and was steeper among men. The accelerated (terminal) rate of health deficit accumulation began at a FI-value of 0.29 in the total sample, 0.27 for men, and 0.30 for women. CONCLUSION: We found evidence for an observable terminal health decline in the FI following declining physiological reserves and failing repair mechanisms. Our results suggest a conceptually meaningful cut-off value for the continuous FI around 0.30.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.008
metaresearch head score (Gemma)0.008
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.034
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0080.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.467
GPT teacher head0.515
Teacher spread0.047 · 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 teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

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

Citations40
Published2021
Admission routes1
Has abstractyes

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