Prognostic Indicators of Carbapenem‐Resistant <i>Acinetobacter baumannii</i> Infection: A Meta‐Analysis and Systematic Review
Bibliographic record
Abstract
ABSTRACT Background Carbapenem‐resistant Acinetobacter baumannii (CRAB) infections are clinically difficult to treat owing to their lack of effective treatments and high mortality rates. This calls for the development of prognostic indicators to facilitate risk stratification and patient management. Aims To identify prognostic indicators of CRAB infections through a systematic review and meta‐analysis. Methods A systematic search was performed on PubMed, Embase, and Cochrane Library up to November 2024. Studies that reported the CRAB infections and their adverse outcomes (e.g., mortality, acute kidney injury, recurrent infections) were eligible for enrollment. Data were extracted from the studies by two reviewers, and the quality of the studies was determined using the Newcastle−Ottawa Scale (NOS). Meta‐analysis was performed using random‐effects or fixed‐effects models while considering the heterogeneity determined using the I ² statistics. Results Fourteen studies comprising 2250 patients were enrolled in the study. Notably, cardiovascular disease (OR: 1.59, 95% CI: 1.17–2.17), acute kidney injury (OR: 3.15, 95% CI: 1.69–5.88), shock (OR: 2.33, 95% CI: 1.50–3.63), pneumonia (OR: 1.28, 95% CI: 1.02–1.60), hematologic malignancy (OR: 2.23, 95% CI: 1.55–3.21), neutropenia (OR: 2.74, 95% CI: 1.48–5.06), and thrombocytopenia (OR: 1.49, 95% CI: 1.10–2.02) were found to be significant prognostic indicators predicting poor outcomes. The use of steroid therapy (OR: 1.29, 95% CI: 1.01–1.64) was linked to increased mortality risk. Conclusion In this meta‐analysis, we detected several prognostic indicators that correlated with poor adverse outcomes in patients with CRAB infections, which may help clinical decision‐making and risk‐stratification strategies. Trial Registration: PROSPERO 2024 CRD42024565429 Available from: https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42024565429 .
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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 | 0.014 | 0.034 |
| Meta-epidemiology (narrow) | 0.004 | 0.002 |
| Meta-epidemiology (broad) | 0.021 | 0.050 |
| Bibliometrics | 0.010 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".