Characteristics of Patients Described as Sub-acute in an Acute Care Hospital
Bibliographic record
Abstract
Frail older patients suffer from multiple, complex needs that often go unmet in an acute care setting. Failure to recognize the geriatric giants in frail older adults is resulting in the misclassification of this population. This study investigated "sub-acute" frail, older-adult in-patients in a tertiary care teaching hospital. Although identified as being no longer acutely ill, all participants (n = 62) required active medical and/or nursing care. Frail older patients, often acutely ill, were being misclassified as sub-acute when the acuity of their illness went unrecognized which resulted in equally unrecognized disease presentations. The majority of participants wished to be cared for at or closer to home. The lack of post-acute-care service within our health care system and risk aversion on the part of hospital staff resulted in lengthy hospital stays and/or in patients being funneled into existing services (nursing homes) against their desire to go home.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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".