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Record W3194672567 · doi:10.1002/alz.054751

Association between patterns of multiple chronic conditions and cognitive impairment in community‐dwelling older adults in Taiwan

2021· article· en· W3194672567 on OpenAlexaboutno aff
Yen‐Ching Chen, Jeng‐Min Chiou, Ta‐Fu Chen, Su‐Ling Yeh, Jen‐Hau Chen

Bibliographic record

VenueAlzheimer s & Dementia · 2021
Typearticle
Languageen
FieldMedicine
TopicChronic Disease Management Strategies
Canadian institutionsnot available
Fundersnot available
KeywordsAssociation (psychology)Cognitive impairmentGerontologyCognitionDemographyPsychologyMedicinePsychiatrySociology

Abstract

fetched live from OpenAlex

Abstract Background Previous studies mainly explored the effect of single chronic disease on cognition. However, limited focuses have been put on the co‐existence of diseases, symptoms, and functional impairments and how their combinations affect older adults. This study aimed to identify sex‐specific patterns of multiple chronic conditions (MCC) and to relate them with cognitive impairment in a six‐year cohort study. Method We included 516 non‐demented older adults at baseline (2011‐2013) from the ongoing Taiwan Initiative for Geriatric Epidemiological Research, with three biennially follow‐ups. The global and domain‐specific (memory, attention, executive function, and language) cognition were assessed using the Taiwanese version of Montreal Cognitive Assessment and a battery of neuropsychological tests. Exploratory factor analysis was utilized to identify patterns of 33 self‐reported chronic conditions. For each pattern, the factor score of each participant was calculated by summing up the product of the status of a specific condition and its corresponding factor loadings. The generalized linear mixed model was utilized to examine the association between MCC patterns and cognitive performance adjusted for age, years of education, apolipoprotein E ε4 status, cigarette smoking, alcohol consumption, and years of follow‐up. Result Three MCC patterns were identified for each sex, which included (1) Mental‐Exhaustion, (2) Cancer‐Thyroid, and (3) Frailty‐Cardiometabolic patterns in females; and (1) Mental‐Skeletal, (2) Cardiometabolic‐Renal, and (3) Thyroid‐Prostate patterns in males. Among females, higher factor scores of the Mental‐Exhaustion and Frailty‐Cardiometabolic patterns were significantly associated with poor performance of global cognition (β: ‐0.16), logical memory (β:‐0.11 to ‐0.07) and executive function (β:‐0.32). Among males, higher factor scores of the Mental‐Skeletal and Thyroid‐Prostate patterns were significantly associated with poor performance of memory (β:‐0.11) and attention (β:‐0.13). In contrast, a protective effect was observed between Cancer‐Thyroid pattern and memory (β:0.12 to 0.13) or attention (β:0.16), as well as between Cardiometabolic‐Renal pattern and verbal fluency (β:0.15). Conclusion MCC patterns identified in this Asian population were different from those observed in western countries, and these patterns were associated with poor global or domain‐specific cognition. Further research was required to validate our findings and to clarify the underlying mechanism between MCC and cognitive impairment.

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)0.000
metaresearch head score (Gemma)0.001
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 score0.020
Threshold uncertainty score0.040

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
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 head0.025
GPT teacher head0.300
Teacher spread0.276 · 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
Published2021
Admission routes1
Has abstractyes

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