The Performance of Direct Disk Diffusion for Community Acquired Bacteremia due to Gram-Negative Bacilli and Its Impact on Physician Treatment Decisions
Bibliographic record
Abstract
Background. Direct disk diffusion susceptibility testing provides faster results than standard microtitre susceptibility. The direct result may impact patient outcome in sepsis if it is accurate and if physicians use the information to promptly and appropriately change antibiotic treatment. Objective. To compare the performance of direct disk diffusion with standard susceptibility and to consider physician decisions in response to these early results, for community acquired bacteremia with Gram-negative Bacilli. Methods. Retrospective observational study of all positive blood cultures with Gram-negative Bacilli, collected over one year. Physician antibiotic treatment decisions were assessed by an infectious diseases physician based on information available to the physician at the time of the decision. Results. 89 bottles growing Gram-negative Bacilli were included in the analysis. Direct disk diffusion agreement with standard susceptibility varied widely. In 47 cases (52.8%), the physician should have changed to a narrower spectrum but did not, in 18 cases (20.2%), the physician correctly narrowed from appropriate broad coverage, and in 8 cases (9.0%), the empiric therapy was correct. Discussion. Because inoculum is not standardized, direct susceptibility results do not agree with standard susceptibility results for all drugs. Physicians do not act on direct susceptibility results. Conclusion. Direct susceptibility should be discontinued in clinical microbiology laboratories.
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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 | 0.013 | 0.113 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".