Weighted-incidence syndromic combination antibiograms to guide empiric treatment of critical care infections: a retrospective cohort study
Bibliographic record
Abstract
INTRODUCTION: Empiric antimicrobial selection for critical care infections must balance the need for timely adequate coverage with the resistance pressure exerted by broadspectrum agents. We estimated the potential of weighted incidence syndromic combination antibiograms (WISCAs) to improve time to adequate coverage for critical care infections. In contrast to traditional antibiograms, WISCAs display the likelihood of coverage for a specific infectious syndrome (rather than individual pathogens), and also take into account the potential for poly-microbial infections and the use of multi-drug regimens. METHODS: Cases of ventilator-associated pneumonia (VAP) and catheter-related bloodstream infection (CRBSI) were identified over three years using stringent surveillance criteria. Based on the susceptibility profile of the culprit pathogens, we calculated the WISCA percentages of infections that would have been adequately covered by common antimicrobial(s). We then computed the excess percentage coverage offered by WISCA regimens compared to the actual antimicrobials administered to patients by 12 h, 24 h, and 48 h from culture collection. RESULTS: Among 163 patients with critical care infection, standard practice only resulted in adequate coverage of 35% of patients by 12 h, 52% by 24 h, and 75% by 48 h. No WISCA mono-therapy regimen offered greater than 85% adequate overall coverage for VAP and CRBSI. A wide range of dual therapy regimens would have conferred greater than 90% adequate coverage, with excess coverage estimated to be as high as +56%, +42% and +18% at 12 h, 24 h and 48 h, respectively. We did not detect a decrease in mortality associated with early adequate treatment, and so could not estimate potential downstream benefits. CONCLUSIONS: WISCA-derived empiric antimicrobial regimens can be calculated for patients with intensive care unit (ICU)-acquired infections, and have the potential to reduce time to adequate treatment. Prospective research must confirm whether implementation of WISCA prescribing aids facilitate timely adequate treatment and improved ICU outcomes.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".