95 Associated Factors and Outcomes of Falls in Acute Elderly Inpatients
Bibliographic record
Abstract
Abstract Introduction It is thought that more than 1:3 individuals ≥65 years old fall at least once per year. With an increasing number of elderly inpatients in an ageing Australian population, falls prevention is now part of patient safety. We aimed to characterise associated factors of inpatient falls and patient outcomes in an acute medical ward in a regional hospital. Methodology Inpatient falls for a 12-month duration (January-December 2018) were identified through a mandatory incident reporting system. Identifiable cases were included in the study with medical records reviewed retrospectively to ascertain active medical issues. Individuals with recurrent falls in the same admission were only counted once. Statistical analyses were performed in cases which completed an Ontario Modified Stratify (Sydney Scoring) Falls Risk Screen (OMS) during admission. An OMS score of ≥9 was indicative of high falls risk (HFR). Active issues were categorised based on major diagnostic categories. Results A total of 77 falls occurred during the 12-month period. Fifty three events fulfilled criteria for further analyses. This comprised of 24 (45.3%) males and 29 (54.7%) females once recurrent fallers were accounted. The mean cohort age was 80.2 years (SD 13.6) with a mean OMS score of 14.3 (SD 8.6) whereby 63.0% were deemed HFR. The top six categories of active issues experienced in this group were history of fall(s) contributing to admission (47.2%), cognitive impairment/ delirium/ dementia (43.4%), infection (43.4%), significant orthopaedic/ rheumatological disorders (39.6%), ischaemic heart disease/ heart failure/ valvulopathy (34%) and hypertension (34%). Medical admission outcomes for inpatient fallers were as follows; 58.5% discharged, 22.6% transferred to subacute care, 3.8% interhospital transfer and 15.1% death. Conclusion Recommended cut-off scores for the OMS are likely suboptimal in multimorbid elderly acute medical inpatients. Based on the limited sample size, elderly inpatients who experienced in-hospital falls are at higher risk of mortality.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".