933 FACTORS ASSOCIATED WITH LENGTH OF STAY ON OLDER PEOPLE’S MEDICINE WARDS
Bibliographic record
Abstract
Abstract Introduction The Newcastle upon Tyne Hospitals NHS Foundation Trust’s Older People’s Medicine (OPM) department includes six inpatient wards. It was hypothesized that an increasing prevalence of inpatient frailty would be associated with increased length of stay. Method Data were collected on OPM wards, on a single day of February 2020 and July 2021. Demographic details, mobility, presence of delirium, resuscitation status, length of stay (LOS), and Clinical Frailty Scale (CFS) status was recorded (frailty defined as CFS score ≥ 5). Descriptive statistics and tests of significance comparing 2020 with 2021 data were performed. Independent associations with above-median LOS were analysed using binary logistic regression. Results There were 172 inpatients in 2020, and 160 in 2021. Median age was 84 (range 66–98 years) in 2020, and 85 (range 64–99 years) in 2021. 87 (54.4%) in 2021, and 102 (59.3%) in 2020 were female. Prevalence of pre-admission frailty was higher in 2021 (n = 143, 89.4%) compared to 2020 (n = 125, 72.7%, p < 0.0001). The prevalence of delirium was higher (n = 60, 37.5%, p < 0.0001) and fewer were independently mobile (n = 53, 33.1%, p = 0.013) in 2021 than in 2020. Nevertheless, median LOS was shorter in 2021, 9 days (range 1.0–106.9) versus 15 days (range 0.7–87.0) in 2020, p = 0.006. Being admitted from home and having a DNACPR were independent predictors of increased LOS (OR 2.4 [95% CI 1.4 to 4.0] for both), controlling for age, sex, frailty, delirium, and reduced mobility. Conclusion Despite the increased prevalence of frailty, delirium and reduced mobility, these factors were not associated with increased LOS. Residence at home and DNACPR were associated with above-median LOS, irrespective of the patient’s frailty, delirium or mobility status. Overall, this suggest appropriate high quality care is being delivered, despite increased pressures due to shorter LOS and higher frailty prevalence.
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.008 | 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".