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Record W4240255113 · doi:10.21203/rs.3.rs-36416/v1

Physical Frailty and Its Associated Factors Among Elderly Nursing Home Residents in China

2020· preprint· en· W4240255113 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueResearch Square (Research Square) · 2020
Typepreprint
Languageen
FieldMedicine
TopicFrailty in Older Adults
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsChinaNursing homesGerontologyMedicineNursingGeography

Abstract

fetched live from OpenAlex

Abstract Background: Evidence is scarce on the trend in prevalence of physical frailty in China; the primary purpose of this study was to identify the prevalence and correlates of physical frailty among older nursing home residents in China. Methods: Cross-sectional study in 20 nursing homes in Changsha, China. Physical frailty was defined based on the frailty phenotype including weight loss, low grip strength, exhaustion, slow gait speed, and low physical activity. Participants with at least three affected criteria were defined as being frail. Participants with one or two affected criteria were considered as pre-frail, and those with no affected criteria were considered as robust. A total of 1004 nursing home residents aged 60 and over were included in this study. A multinomial logistic regression model was used to analyze the associations of physical frailty with its potential risk factors, including age, sex, education levels, marital status, type of institution, living status, current drinking, current smoking, regular exercise, and self-reported health. Results: The overall prevalence of physical frailty and prefrailty was 55.6%, and 38.5%, respectively. The rate of physical frailty substantially increased with age, and was higher in women than in men (69.5% vs. 30.5%). The multinomial logistic regression analysis showed that older age, being women, living in a private institution, living alone or with unknown person, having no regular exercise (≤ 2 times/week), and poor self-reported health were significantly associated with increased odds of being physically frail. Conclusion: We demonstrated physical frailty is highly prevalent among older residents in nursing homes in China, especially in women. The potential role of those associated factors of physical frailty warrant further investigations to explore their clinical application among elderly nursing home residents.

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.

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)0.022
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Research integrity
Consensus categoriesResearch integrity
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.168
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0080.022
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0040.005
Science and technology studies0.0010.002
Scholarly communication0.0010.001
Open science0.0020.004
Research integrity0.0020.021
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 head0.129
GPT teacher head0.449
Teacher spread0.320 · 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