Validation of a Rapid Diagnostic Strategy for Determination of Significant Bacterial Counts in Bronchoalveolar Lavage Samples
Bibliographic record
Abstract
CONTEXT: Bacterial cultures of bronchoscopic samples require 1 to 2 days for results to be available for use in clinical decisions. We developed a rapid diagnostic testing strategy that is highly sensitive for screening bacteria in bronchoalveolar lavage (BAL) samples, with results available within hours of collection. OBJECTIVE: To validate the ability of a bacterial adenosine triphosphate (ATP) assay and routine Gram stain microscopy to detect significant bacterial counts in BAL samples. DESIGN: Four hundred seventy-seven BAL samples from 319 patients suspected of having pneumonia were tested using a rapid diagnostic strategy, consisting of Gram stain and a bacterial ATP assay. Rapid results were compared with quantitative cultures with a positive cutoff of 10(4) CFU/mL or higher. RESULTS: Significant bacterial counts were identified in 107 samples (22%). The most common etiologic agents were Staphylococcus aureus (25%), Haemophilus influenzae (17%), and Streptococcus pneumoniae (12%). The rapid test results were false negative in 5 cases (S aureus in 2, both Klebsiella pneumoniae and S aureus in 1, and Stenotrophomonas maltophilia and S pneumoniae in 1 case each). The sensitivity, specificity, positive predictive value, negative predictive value, and accuracy of the rapid diagnostic strategy were 95.3%, 54.9%, 37.9%, 97.6%, and 63.9%, respectively. CONCLUSION: A negative result with this rapid diagnostic testing strategy rules out significant bacterial counts in BAL samples with a high degree of certainty and may allow use of narrow-spectrum antimicrobial agents or withholding of empiric antimicrobial therapy in patients suspected of having ventilator-associated pneumonia.
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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 | 0.019 | 0.039 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".