Risk factors associated with bloodstream infections caused by Acinetobacter baumannii in hospital settings: A systematic review and meta-analysis
Bibliographic record
Abstract
<h2>Abstract</h2><h3>Background</h3> <i>Acinetobacter baumannii</i> represents a significant public health issue in hospital settings because of its high-level resistance to various antimicrobials. Early detection of patients at risk of <i>A. baumannii</i> bloodstream infection (BSI) is crucial. <h3>Objectives</h3> To investigate risk factors for <i>A. baumannii</i> BSI by means of a systematic review and meta-analysis. <h3>Methods</h3> MEDLINE, Embase, Web of Science and Scopus libraries were used to systematically search available evidence. Two authors independently performed screening, full-text review, data extraction and quality assessments. A third author resolved any conflicts. A meta-analysis was conducted with common and random effects models for risk factors investigated in at least four studies. <h3>Results</h3> Overall, 25 studies (13 cohort and 12 case-control studies) were included. All studies were classified as good quality studies using the Newcastle-Ottawa scale (≥ 6/9 stars). Most studies were performed in intensive care units on critically ill patients. Only one study used simple logistic regression, while the majority performed multivariate regression. The meta-analysis revealed that previous antimicrobial therapy (OR 2.30, 95 % CI 1.89 - 2.81), central-line catheter use (OR 3.51, 95 % CI 2.45 – 5.01) and mechanical ventilation (OR 3.29, 95 % CI 2.13 - 5.09) were associated with an increased risk of developing <i>A. baumannii</i> BSI. <h3>Conclusion</h3> Previous antimicrobial therapy, central-line catheter use, and mechanical ventilation were associated with <i>A. baumannii</i> bloodstream infections. Infection prevention and control programmes should address these risk factors to reduce such infections.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".