Ertapenem for the treatment of bloodstream infections due to ESBL-producing Enterobacteriaceae: a multinational pre-registered cohort study
Bibliographic record
Abstract
OBJECTIVES: Data about the efficacy of ertapenem for the treatment of bloodstream infections (BSI) due to ESBL-producing Enterobacteriaceae (ESBL-E) are limited. We compared the clinical efficacy of ertapenem and other carbapenems in monomicrobial BSI due to ESBL-E. METHODS: A multinational retrospective cohort study (INCREMENT project) was performed (ClinicalTrials.gov identifier: NCT01764490). Patients given monotherapy with ertapenem or other carbapenems were compared. Empirical and targeted therapies were analysed. Propensity scores were used to control for confounding; sensitivity analyses were performed in subgroups. The outcome variables were cure/improvement rate at day 14 and all-cause 30 day mortality. RESULTS: The empirical therapy cohort (ETC) and the targeted therapy cohort (TTC) included 195 and 509 patients, respectively. Cure/improvement rates were 90.6% with ertapenem and 75.5% with other carbapenems (P = 0.06) in the ETC and 89.8% and 82.6% (P = 0.02) in the TTC, respectively; 30 day mortality rates were 3.1% and 23.3% (P = 0.01) in the ETC and 9.3% and 17.1% (P = 0.01) in the TTC, respectively. Adjusted ORs (95% CI) for cure/improvement with empirical and targeted ertapenem were 1.87 (0.24-20.08; P = 0.58) and 1.04 (0.44-2.50; P = 0.92), respectively. For the propensity-matched cohorts it was 1.18 (0.43-3.29; P = 0.74). Regarding 30 day mortality, the adjusted HR (95% CI) for targeted ertapenem was 0.93 (0.43-2.03; P = 0.86) and for the propensity-matched cohorts it was 1.05 (0.46-2.44; P = 0.90). Sensitivity analyses were consistent except for patients with severe sepsis/septic shock, which showed a non-significant trend favouring other carbapenems. CONCLUSIONS: Ertapenem appears as effective as other carbapenems for empirical and targeted therapy of BSI due to ESBL-E, but further studies are needed for patients with severe sepsis/septic shock.
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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 | 0.006 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".