Multidrug-resistant organism bloodstream infections in solid organ transplant recipients and impact on mortality: a systematic review
Bibliographic record
Abstract
Abstract Background Bloodstream infections (BSIs) cause significant morbidity and mortality in solid organ transplant (SOT) recipients. There are few data regarding the contribution of MDR organisms (MDROs) to these infections. We evaluated the resistance percentage of MDRO BSIs in SOT recipients and the associated mortality. Methods A systematic review of MEDLINE and Embase databases up to January 2024, for studies of adult SOT recipients that quantified MDRO BSI resistance percentage and/or associated crude mortality. MDROs studied were carbapenem-resistant Enterobacterales (CRE), Acinetobacter baumannii (CRAB) and Pseudomonas aeruginosa (CRPA), third-generation cephalosporin-resistant Enterobacterales (3GCR-E), MRSA and VRE. Resistance percentage and mortality outcomes were reported as median (IQR) and crude mortality (%), respectively. Results Of 945 studies identified, 52 were included. Most were retrospective (41/52) and/or single centre (37/52), and liver transplantation was the most frequently studied SOT type (22/52). High resistance percentages of BSIs were noted, ranging from 13.6% CRE for Enterobacterales to 59.2% CRAB for A. baumannii. Resistance percentage trends decreased over time, but these changes were not statistically significant. Asia had the highest resistance percentages for MRSA [86.2% (IQR 77.3%–94.6%)], 3GCR-E [59.5% (IQR 40.5%–66.7%)] and CRE [35.7% (IQR 8.3%–63.1%)]. North America had the highest VRE resistance percentages [77.7% (IQR 54.6%–94.7%)]. Crude mortality was 15.4%–82.4% and was consistently higher than for non-MDRO BSIs. Conclusions MDRO BSI resistance percentages were high for all pathogens studied (IQR 24.6%–69.4%) but there was geographical and temporal heterogeneity. MDRO BSIs were associated with high mortality in SOT recipients. Microbiological and clinical data in this vulnerable population were incomplete, highlighting the need for robust international multicentre studies.
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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 | 0.003 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.006 |
| Bibliometrics | 0.010 | 0.012 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".