Utility of Gram stain in the clinical management of suspected ventilator-associated pneumonia. Secondary analysis of a multicenter randomized trial.
Bibliographic record
Abstract
PURPOSE: Gram stains of endotracheal aspirates (EA) and bronchoalveolar lavages (BAL) may guide empiric antibiotic therapy in critically ill patients with suspected ventilator-associated pneumonia (VAP). Previous studies differ regarding the ability of the Gram stain to predict final culture results. The aim of the present study was to evaluate the relationship between EA or BAL Gram stains and final culture results in intensive care unit patients with a suspected VAP. MATERIAL AND METHODS: We retrospectively analyzed data from the Canadian multicenter VAP study to correlate EA or BAL Gram stain and final culture results. We categorized Gram stains as Gram positive (GP) and Gram negative (GN) if any GP or GN organisms respectively were seen on staining. Cultures were considered "positive" if they yielded pathogenic organisms on final results. RESULTS: Seven hundred forty patients were enrolled in the study; 35 did not have a Gram stain done leaving 350 BALs and 355 EAs from 705 patients. Pooling BAL and EA results, we found the overall agreement between Gram stain class and pathogenic bacteria culture results to be poor (kappa = 0.36; 95% CI, 0.31-0.40). Among specimens with Gram stains showing no organisms, 99 (30%) of 331 grew pathogenic organisms. Among specimens with Gram stains showing no GN organisms, 113 (25%) of 452 grew pathogenic GN organisms. Among specimens with Gram stains showing no GP organisms, 45 (11%) of 428 grew pathogenic GP organisms. CONCLUSIONS: Gram stains performed for clinically suspected VAP poorly predict the final culture result and thus have a limited role in guiding initial empiric antibiotic therapy in such patients.
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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 | 0.009 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| 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".