Associations Between Patient Characteristics and Unplanned or Delayed Discharges From Geriatric Rehabilitation
Bibliographic record
Abstract
ABSTRACT: Returning home is considered an indicator of successful rehabilitation for community-dwelling older adults. However, the factors associated with unplanned discharge remain uncertain. This retrospective chart review included patients 65 yrs and older admitted to a geriatric rehabilitation unit from medical and surgical wards in an academic hospital. Patient characteristics and outcomes were abstracted from the electronic medical record. The primary outcome was unplanned discharge destination defined as anything other than return to patients' preexisting residence. The associations between patient variables and unplanned discharge destination were analyzed using Pearson χ 2 and univariate logistic regression. Of the 251 charts screened, 25 patients (10.0%) had an unplanned discharge destination, and 74 of the remaining 226 (32.7%) experienced a delayed discharge (beyond 20 days). Requiring assistance for activities of daily living (odds ratio [OR], 2.80; 95% confidence interval [CI], 1.17-7.47), a diagnosis of chronic obstructive pulmonary disease (OR, 4.04; 95% CI, 1.63-9.71), and lower serum albumin level (OR, 1.67; 95% CI, 1.06-2.72) were associated with unplanned discharge. Variables commonly associated with worse outcomes such as age, cognitive scores, delirium, and number of comorbidities were not barriers to returning home and should therefore not be used on their own to limit access to geriatric rehabilitation.
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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 | 0.000 | 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) | 0.002 | 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".