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Record W4390194264 · doi:10.1002/alz.073965

The Relationship Between Inner Retinal Thickness, Cognition, and Frailty in Community‐dwelling Older Adults: findings from a 6‐year follow‐up study

2023· article· en· W4390194264 on OpenAlexaboutno aff
Yung‐Sung Lee, Yi‐Ting Hsieh, Jen‐Ming Chiou, Jen‐Hau Chen, Yen‐Ching Chen

Bibliographic record

VenueAlzheimer s & Dementia · 2023
Typearticle
Languageen
FieldMedicine
TopicDementia and Cognitive Impairment Research
Canadian institutionsnot available
Fundersnot available
KeywordsCognitionMedicineCognitive declineNeuropsychologyCohortPsychologyGerontologyDementiaPsychiatryInternal medicine

Abstract

fetched live from OpenAlex

Abstract Background Thinning of the inner retinal thickness, including ganglion cell‐inner plexiform layer (GC‐IPL) and retinal nerve fiber layer (RNFL), has been related to cognitive decline. However, the relationship between GC‐IPL/RNFL thickness, physical frailty, and cognitive frailty remains unclear. Therefore, this longitudinal study aims to investigate the association of these retinal markers with cognition, frailty, and cognitive frailty. Method This is a 7‐year cohort study including 221 community‐dwelling elders in the ongoing Taiwan Initiate for Geriatric Epidemiological Research (TIGER) between 2015 and 2017 and received biennial assessments for cognition and physical frailty three consecutive times. The global and domain‐specific (memory, attention, executive function, and language) cognition were assessed using the Taiwanese version of the Montreal Cognitive Assessment and a series of neuropsychological tests. Physical frailty was assessed by modified Fried frailty phenotypes. The generalized linear mixed model was used to analyze the association between GC‐IPL/RNFL thickness and global/domain‐specific cognitive frailty adjusted for age, sex, years of education, apolipoprotein E ε4 status carriers, cigarette smoking status, presence of depressive symptoms, hypertension or diabetes mellitus, years of follow‐up, and practice effect. Result The performance of global cognition decreased as the mean GC‐IPL thickness of bilateral eyes deviated from the sample mean (76.6 µm) (quadratic GC‐IPL: β = ‐0.4×10−2; 95% confidence interval: ‐0.7×10−2 to ‐0.2×10−2). Similar associations were also found for logical memory with RNFL/GC‐IPL thickness. No significant association was observed between RNFL/GC‐IPL thickness and physical frailty. An increased odds of impaired logical memory‐physical frailty was found for GC‐IPL (quadratic GC‐IPL: adjusted odds ratio = 1.005; 95% confidence interval: 1.001 to 1.005), but no significant association was found between cognitive frailty and RNFL thickness. Conclusion Change in the GC‐IPL thickness was associated with impaired cognition and poor logical memory‐frailty performance. The inner retinal thickness may serve as a biomarker for cognition or cognitive frailty in non‐demented elders.

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)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.012
Threshold uncertainty score0.024

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.070
GPT teacher head0.342
Teacher spread0.273 · 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 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

Citations0
Published2023
Admission routes1
Has abstractyes

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