Ceftazidime-avibactam and aztreonam combination for Carbapenem-resistant Enterobacterales bloodstream infections with presumed <i>Metallo-β-lactamase</i> production: a systematic review and meta-analysis
Bibliographic record
Abstract
Introduction Carbapenem-resistant Enterobacterales (CRE) due to Metallo-β-lactamase (MBL) production are treated with either polymyxins or the novel combination of ceftazidime-avibactam and aztreonam (AA). This study aims to evaluate the 30-day mortality of AA in patients with BSI caused by MBL-CRE infections.Methodology In this systematic review and meta-analysis, all articles up to June 2023 were screened using search terms like ‘CRE’, ‘MBL’, ‘AA’ and ‘polymyxins’. The risk ratio for AA vs polymyxins was pooled using a random-effect model, and the results were represented by a point estimate with a 95% confidence interval.Results After removing the duplicates, the titles and abstracts of 455 articles were screened, followed by a full-text screening of 50 articles. A total of 24 articles were included for systematic review, and four comparative studies were included in the meta-analysis. All four studies had a moderate or serious risk of bias. The pooled risk ratio for 30-day mortality for AA vs. polymyxins was 0.51 (95%CI: 0.34–0.76), p < 0.001. There was no significant heterogeneity.Conclusion The meta-analysis from studies with a high risk of bias shows that AA is associated with lesser 30-day mortality when compared to polymyxins in patients with MBL-producing CRE BSI. Registration with PROSPERO- CRD42023433608.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.010 | 0.019 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.020 | 0.044 |
| Bibliometrics | 0.008 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".