Guideline adherence for empirical treatment of pneumonia and patient outcome. Treating pneumonia in the Netherlands.
Bibliographic record
Abstract
INTRODUCTION: According to the Dutch guidelines, severity of community acquired pneumonia (CAP) (mild, moderate-severe, severe) should be based on either PSI, CURB65 or a 'pragmatic' classification. In the last mentioned, the type of ward of admission, as decided by the treating physician, is used as classifier: no hospital admission is mild, admission to a general ward is moderate-severe and admission to an intensive care unit (ICU) is severe CAP. Empiric antibiotic recommendations for each severity class are uniform. We investigated, in 23 hospitals, which of the three classification systems empirical treatment of CAP best adhered to, and whether a too narrow spectrum coverage (according to each of the systems) was associated with a poor patient outcome (in-hospital mortality or need for ICU admission). PATIENTS AND METHODS: Prospective observational study in 23 hospitals. RESULTS: 271 (26%) of 1047 patients with CAP confirmed by X-ray were categorised in the same severity class with all three classification methods. Proportions of patients receiving guideline-adherent antibiotics were 62.9% (95% CI 60.0-65.8%) for the pragmatic, 43.1% (95% CI 40.1-46.1%) for PSI and 30.5% (95% CI 27.8-33.3%) for CURB65 classification. 'Under-treatment' based on the pragmatic classification was associated with a trend towards poor clinical outcome, but no such trend was apparent for the other two scoring systems. CONCLUSIONS: Concordance between three CAP severity classification systems was low, implying large heterogeneity in antibiotic treatment for CAP patients. Empirical treatment appeared most adherent to the pragmatic classification. Non-adherence to treatment recommendations based on the PSI and CURB65 was not associated with a poor clinical outcome.
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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 | 0.004 | 0.026 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".