Discharge Delay in Patients with Community‐Acquired Pneumonia Managed on a Critical Pathway
Bibliographic record
Abstract
INTRODUCTION: It has previously been reported that a critical pathway for community-acquired pneumonia (CAP) significantly reduces bed days per patient managed but results in no difference in average length of stay, suggesting that discharge criteria were not successfully implemented. The present study sought to identify factors in the timing of discharge not taken into account by discharge criteria. METHODS: Patients admitted with CAP and placed on a pneumonia critical pathway were studied. Patients' functional and cognitive status were evaluated using the Barthel Index, Hierarchical Assessment of Balance and Mobility (HABAM) and the Mini-Mental Status Examination. Once discharge criteria were met, the patient, a family member and the treating physician were interviewed to identify other factors contributing to length of stay. RESULTS: Thirty-one patients were enrolled in the study; 12 were discharged when they met discharge criteria and 19 stayed in hospital longer. There were no differences between patients discharged at stability versus those with an increased length of stay in terms of demographics, pneumonia severity score, functional or cognitive status at discharge using the Barthel Index (87.3+/-11.1 versus 83.8+/-8.6, respectively; P=0.46) and MMSE (27.1+/-1.1 versus 27.3+/-1.1, respectively; P=0.64); however, there was a significant difference in HABAM score at the time clinical stability was reached (22.6+/-1.3 versus 17.4+/-3.5, respectively; P=0.03), which correlated with physician and family assessments of patients' readiness for discharge. CONCLUSIONS: HABAM may be a useful tool to identify patients at risk of remaining in hospital after objective discharge criteria are met. Additional resources may be targeted at these patients to reduce length of stay in CAP.
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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 | 0.000 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".