Evaluation of early antimicrobial therapy adaptation guided by the BetaLACTA® test: a case-control study
Bibliographic record
Abstract
BACKGROUND: Rapid diagnostic tests detecting microbial resistance are needed for limiting the duration of inappropriateness of empirical antimicrobial therapy (EAT) in intensive care unit patients, besides reducing the use of broad-spectrum antibiotics. We hypothesized that the betaLACTA® test (BLT) could lead to early increase in the adequacy of antimicrobial therapy. METHODS: This was a case-control study. Sixty-one patients with BLT-guided adaptation of EAT were prospectively included, and then matched with 61 "controls" having similar infection characteristics (community or hospital-acquired, and source of infection), in whom EAT was conventionally adapted to antibiogram results. Endpoints were to compare the proportion of appropriate (primary endpoint) and optimal (secondary endpoint) antimicrobial therapies with each of the two strategies, once microbiological sample culture results were available. RESULTS: Characteristics of patients, infections and EAT at inclusion were similar between groups. Nine early escalations of EAT occurred in the BLT-guided adaptation group, reaching 98% appropriateness vs. 77% in the conventional adaptation group (p < 0.01). The BLT reduced the time until escalation of an inappropriate EAT from 50.5 (48-73) to 27 (24-28) hours (p < 0.01). Seventeen early de-escalations occurred in the BLT-guided adaptation group, compared to one in the conventional adaptation group, reducing patients' exposure to broad-spectrum beta-lactam such as carbapenems. In multivariate analysis, use of the BLT was strongly associated with early appropriate (OR = 18 (3.4-333.8), p = 0.006) and optimal (OR = 35.5 (9.6-231.9), p < 0.001) antimicrobial therapies. Safety parameters were similar between groups. CONCLUSIONS: Our study suggests that a BLT-guided adaptation strategy may allow early beta-lactam adaptation from the first 24 hours following the beginning of sepsis management.
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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 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| 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 | 0.000 |
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".