The development of multidimensional screening model of geriatric syndrome for community-dwelling older adults: results of the Taiwan Integration Health and Welfare (TIHW) Study
Bibliographic record
Abstract
Abstract Background: Comprehensive geriatric assessment (CGA) is a multidimensional and multidisciplinary diagnostic and treatment process that identifies geriatric syndrome in older adults. However, CGA program is not appropriate in community screening. To the best of our knowledge, there is no applicable multidimensional screening model to evaluate geriatric syndrome in community-dwelling older adults. This study aimed to identify the risk factors of geriatric syndrome among physical function tests, socioeconomic status, medical history, and healthy behaviours in community-dwelling older adults and develop a multidimensional prediction model for community screening. Methods: A total of 1313 community-dwelling older adults aged 60 years or above were recruited from 58 communities in four aging cities in Taiwan. Geriatric syndrome was defined by disability using Instrumental Activities of Daily Livings, cognitive impairment using Short Portable Mental Status Questionnaire, depression using Geriatric Depression Scale, or by receiving mild disability card. The cutoff values of the physical function tests were calculated using receiver operating characteristic analysis. Multivariate logistic regression was used to evaluate the risk factors of geriatric syndrome, and the risk model was developed using stepwise logistic regression. Results: We developed the new cutoff values in predicting geriatric syndrome for dominant handgrip strength test, 6-meter walk, and timed up-and-go tests, which were significantly associated with geriatric syndrome. Moreover, male sex, obesity, absence of labour activities, and participants who cannot report personal information, had depressive mood for the past 2 weeks, and a history of heart disease were associated with geriatric syndrome. Finally, we developed Taiwan Risk Scores for Geriatric Syndrome (TRSGS) with the cutoff value of 6 (sensitivity, 77.2%; specificity, 75.5%). Conclusions: Most of the screening tools focus on specific problems such as sarcopenia, dementia, or frailty. The TRSGS model demonstrated a multidimensional prediction model, which could be applied in community screening for geriatric syndrome. Management of risk factors to prevent geriatric syndrome in the community is important.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.011 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".