Characterizing and Developing Strategies for the Treatment of Community‐Acquired Pneumonia at a Community Hospital
Bibliographic record
Abstract
BACKGROUND: Patients admitted to Lions Gate Hospital, North Vancouver, British Columbia, with a primary diagnosis of community-acquired pneumonia (CAP) have a mean length of stay (LOS) of 9.1 days compared with 7.9 days for peer group hospitals. This difference of 1.2 days results in an annual potential savings of 406 bed days and warranted an investigation into the management of CAP. OBJECTIVE: To characterize and provide recommendations for the management of CAP. METHODS: A retrospective chart review of patients admitted with a primary diagnosis of CAP between May 1, 2000 and August 31, 2000. RESULTS: Fifty-one patients were included in the study, with a mean LOS of 9.9 days and a median LOS of five days. Based on pneumonia severity index scores calculated for each patient, eight patients (16%) were admitted inappropriately. Initial empirical antibiotic choices were consistent with the Canadian CAP guidelines in 27 patients (53%), with inconsistencies arising mainly because cephalosporin or azithromycin monotherapy regimens were prescribed. Step-down from intravenous to oral antibiotics occurred in approximately 20 patients (39%). An additional 12 patients (24%) could have undergone step-down, and step-down was not applicable in 19 patients (37%). The potential annual cost avoidance from implementing admission criteria based on a pneumonia severity index score, applying step-down criteria and promoting early discharge criteria was estimated to be $220,000. CONCLUSIONS: Considerable variability exists in the treatment of CAP. A CAP preprinted order sheet was developed to address the issues identified in the present study and provide consistency in the management of CAP at Lions Gate Hospital.
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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 | 0.007 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 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".