Prediction of geriatric rehabilitation outcomes: Comparison between three cognitive screening tools
Bibliographic record
Abstract
AIM: Comparison between the predictions of functional rehabilitation outcomes at a department of geriatric rehabilitation using three cognitive screening tools - Mini Mental State Examination (MMSE), Montreal Cognitive Assessment (MoCA), and Informant Questionnaire on Cognitive Decline in the Elderly (IQCODE). METHODS: This study is a prospective study. The study participants were 212 patients aged 65 and older admitted to rehabilitation departments at a geriatric facility in central Israel, from April 2016 to October 2016. The cognitive functioning of each patient was assessed using the MMSE, MoCA, and IQCODE. Upon discharge, rehabilitation outcomes were examined using the Functional Independence Measure (FIM), cognitive FIM, delta FIM (Δ FIM), and ADL. RESULTS: Cognitive impairment was found to interfere with the rehabilitation process. The MMSE was the best predictor of functional rehabilitation outcomes at discharge, compared to the IQCODE, while the MoCA did not predict these measures. In addition, when distinguishing between patients by ethnicity (Jewish versus Arab), the MMSE and the IQCODE predicted FIM upon discharge among Jewish patients, while only the IQCODE predicted FIM upon discharge among Arab patients. CONCLUSIONS: The research findings show that cognitive assessment upon admission for rehabilitation - MMSE among Jewish patients and IQCODE among Arab patients - can help predict functional rehabilitation outcomes and make the appropriate adaptations in the rehabilitation program. Geriatr Gerontol Int 2017; 17: 2507-2513.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 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 teacher head, 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".