Return to the ED and hospitalisation following minor injuries among older persons treated in the emergency department: predictors among independent seniors within 6 months
Bibliographic record
Abstract
BACKGROUND: minor traumatic injuries among independent older people have received little attention to date, but increasingly the impact of such injuries is being recognised. OBJECTIVES: we assessed the frequency and predictors of acute health care use, defined as return to the emergency department (ED) or hospitalisation. STUDY DESIGN: national multicentre prospective observational study. SETTING: eight Canadian teaching EDs between April 2009 and April 2013. PARTICIPANTS: a total of 1,568 patients aged 65-100 years, independent in basic activities of daily living, discharged from ED following a minor traumatic injury. METHODS: trained assessors measured baseline data including demographics, functional status, cognition, comorbidities, frailty and injury severity. We then conducted follow-up telephone interviews at 6 months to assess subsequent acute health care use. We used log-binomial regression analyses to identify predictors of acute health care use, and reported relative risks and 95% CIs. RESULTS: participants' mean age was 77.0, 66.4% female, and their injuries included contusions (43.5%), lacerations (25.1%) and fractures (25.4%). The cumulative rate of acute health care use by 6 months post-injury was 21.5% (95% CI: 19.0-24.3%). The strongest predictors of acute health care use within 6 months were cognitive impairment, RR = 1.6 (95% IC: 1.2-2.1) and the mechanism of injury including pedestrian struck or recreational injuries, RR = 1.6 (95% CI 1.2-2.2). CONCLUSIONS: among independent community living older persons with a minor injury, cognitive impairment and mechanism of injury were independent risk factors for acute healthcare use. Future studies should look at whether tailored discharge planning can reduce the need for acute health care use.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".