Empiric Therapy With Carbapenem-Sparing Regimens for Bloodstream Infections due to Extended-Spectrum β-Lactamase–Producing Enterobacteriaceae: Results From the INCREMENT Cohort
Bibliographic record
Abstract
BACKGROUND: There is little information about the efficacy of active alternative drugs to carbapenems except β-lactam/β-lactamase inhibitors for the treatment of bloodstream infections (BSIs) due to extended-spectrum β-lactamase-producing Enterobacteriaceae (ESBL-E). The objective of this study was to assess the outcomes of patients with BSI due to ESBL-E who received empiric therapy with such drugs (other active drugs [OADs]) or carbapenems. METHODS: A multinational retrospective cohort study of patients with BSI due to ESBL-E who received empiric treatment with OADs or carbapenems was performed. Cox regression including a propensity score for receiving OADs was performed to analyze 30-day all-cause mortality as main outcome. Clinical failure and length of stay were also analyzed. RESULTS: Overall, 335 patients were included; 249 received empiric carbapenems and 86 OADs. The most frequent OADs were aminoglycosides (43 patients) and fluoroquinolones (20 patients). Empiric therapy with OADs was not associated with mortality (hazard ratio [HR], 0.75; 95% confidence interval [CI], .38-1.48) in the Cox regression analysis. Propensity score-matched pairs, subgroups, and sensitivity analyses did not show different trends; specifically, the adjusted HR for aminoglycosides was 1.05 (95% CI, .51-2.16). OADs were neither associated with 14-day clinical failure (adjusted odds ratio, 0.62; 95% CI, .29-1.36) nor length of hospital stay. CONCLUSIONS: We were unable to show that empiric treatment with OAD was associated with a worse outcome compared with carbapenems. This information allows more options to be considered for empiric therapy, at least for some patients, depending on local susceptibility patterns of ESBL-E.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".