PATIENT MANAGEMENT AFTER EMERGENCY DEPARTMENT FALL RELATED INJURY
Bibliographic record
Abstract
Falls and fall related injuries are a major health problem in aging populations. Women who present to the emergency department (ED) with falls are at increased risk of further falls and injuries. Although the American Geriatrics Society Guidelines suggest that exercise should be prescribed our clinical impression is that frequently, exercise is not prescribed. PURPOSE To describe the management of older women who present with a fall to the ED 18 months after presentation; and, to identify if a care gap exists between actual treatment and recommended management according to the literature. METHODS We examined 55 consecutive computerized patient records of a tertiary care hospital ED. Patient management, current health status and functional status were assessed from the records and by investigator-administered questionnaire. RESULTS Patient management consisted of fall complication treatment (laceration, fracture) alone in 75% of subject—there was not documented fall risk screening or fall prevention intervention implemented. 15% of patients were referred to their GP for follow-up. Only 3% received any form of exercise prescription or referral to physiotherapy. Most patients (44%) did not recall being provided with any fall prevention intervention such as physiotherapy assessment or medication reduction. At 18 months follow-up, most patients reported significantly less function than they had had prior to the fall. CONCLUSION The ED is a well-recognized site that has potential for secondary fall prevention. However, there is a substantial care gap between the ‘standard of care’ and the treatment that is being meted out. This applies particularly to exercise prescription. These data provide leverage for the ACSM to call for implementation of specific interventions to address this care gap. Supported by the BC Sports Medicine Foundation, The Canadian Institutes of Health Research (IMHA) and NSERC.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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) | 0.004 | 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".