2399. β-Lactam Therapy for Potential AmpC-Producing Organisms: A Cohort Study and an Updated Systematic Review and Meta-Analysis
Bibliographic record
Abstract
Certain organisms, including Serratia, Providentia, Acinetobacter, Citrobacter, Enterobacter, and Morganella species (SPACE-M) may possess an inducible broad-spectrum β-lactamase, AmpC, which is not inhibited by most β-lactamase inhibitors. Our objective was to determine whether treating SPACE-M bloodstream infections (BSI) with potentially hydrolyzable β-lactams was associated with increased risk of 30-day mortality. A retrospective cohort study was performed including all adult cases of bacteremia attributed to SPACE-M species between April 2010 and June 2015 at the McGill University Health Centre (Montreal, Canada). We used multivariable logistic regression to estimate the odds ratio (OR) of death or recurrence within 30 days for potentially hydrolyzable β-lactams vs. other therapies. We then updated a systematic review and meta-analysis comparing carbapenems to β-lactam/β-lactamase inhibitors (BL/BLIs). We included studies published up to December 31, 2017 and calculated the unadjusted OR for mortality within 30 days comparing BL/BLI vs. carbapenems as definitive therapy. Over the 5-year period, there were 173 BSI involving SPACE-M organisms at our center. After adjusting for patient comorbidities and severity of the initial illness, the use of hydrolyzable β-lactams as definitive therapy was not associated with an increased risk of death or recurrence when compared with other antimicrobial agents (OR 1.20, 95% CI 0.40–3.62). The meta-analysis further suggested that patients treated with BL/BLI therapy have similar outcomes to those treated with carbapenems (30-day mortality OR 1.13, 95% CI 0.58–2.20). The use of β-lactam/β-lactamase inhibitors may remain a viable carbapenem-sparing option for patients with potential AmpC-producing organisms. All authors: No reported disclosures.
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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 | 0.008 | 0.019 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.011 | 0.030 |
| Bibliometrics | 0.008 | 0.010 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".