334 GEMS: Geriatric Emergency Service - Rockwood’s Clinical Frailty Scale and Outcomes
Bibliographic record
Abstract
Abstract Background Rockwood’s Clinical Frailty Scale (CFS), which uses clinical descriptors and pictographs, was developed to provide clinicians with an easily applicable tool to stratify older adults according to level of vulnerability. The CFS was validated in a sample of 2305 older participants from the Canadian Study of Health and Aging and was shown to be a strong predictor of institutionalisation and mortality (Rockwood K, 2005). Methods The aim of GEMS is to improve care, outcomes and the patient experience for older people living with Frailty. All people aged 75 years and older who attend as an emergency are screened on triage using the Variable Indicative of Placement Tool (VIP). The GEMS Acute Floor Team respond early to those who screen positive by starting a CGA. At the end of CGA all patients have a score 1 to 9 assigned from the Clinical Frailty Scale (CFS). Results 10,037 patients were triaged in the first two years of the service. 43% screened positive for Frailty. 66% had a CGA. 10% were vulnerable CFS 4, 32% mildly frail CFS 5, 32% moderately frail CFS 6 and 31% severely frail CFS 7. Increasing score on the CFS correlated with increased length of stay, death and institutionalisation. Conclusion The CFS correlates with Length of stay (LOS), mortality and institutionalisation in people aged 75 years and older who attend as an emegency and screen positive for Frailty.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".