The impact of colonization by multidrug resistant bacteria on graft survival, risk of infection, and mortality in recipients of solid organ transplant: systematic review and meta-analysis
Bibliographic record
Abstract
BACKGROUND: The Global increase in colonization by multidrug-resistant (MDR) bacteria poses a significant concern. The precise impact of MDR colonization in solid organ transplant recipients (SOTR) remains not well established. OBJECTIVES: To assess the impact of MDR colonization on SOTR's mortality, infection, or graft loss. METHODS AND DATA SOURCES: Data from PROSPERO, OVID Medline, OVID EMBASE, Wiley Cochrane Library, ProQuest Dissertations, Theses Global, and SCOPUS were systematically reviewed, spanning from inception until 20 March 2023. The study protocol was registered with PROSPERO (CRD42022290011) and followed the PRISMA guidelines. STUDY ELIGIBILITY CRITERIA, PARTICIPANTS, INTERVENTIONS, AND ASSESSMENT OF RISK OF BIAS: Cohorts and case-control studies that reported on adult SOTR colonized by Methicillin-resistant Staphylococcus aureus (MRSA), vancomycin-resistant enterococci (VRE), extended-spectrum β-lactamase (ESBL) or carbapenem-resistant Enterobacteriaceae. (CRE), or MDR-pseudomonas, and compared to noncolonized, were included. Two reviewers assessed eligibility, conducted a risk of bias evaluation using the Newcastle-Ottawa Scale, and rated certainty of evidence using the GRADE approach. METHODS OF DATA SYNTHESIS: statistic. RESULTS: = 0). Subgroup analysis indicated a higher association between CRE or ESBL colonization with outcomes (CRE: death OR, 3.94; mixed infections OR, 24.8; ESBL: mixed infections OR, 10.3; no mortality data) compared to MRSA (Death: OR, 2.25; mixed infection: OR, 7.75) or VRE colonization (Death: p 0.20, mixed infections: OR, 5.71). CONCLUSIONS: MDR colonization in SOTR, particularly CRE, is associated with increased mortality. Despite the low certainty of the evidence, actions to prevent MDR colonization in transplant candidates are warranted.
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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 | 0.021 | 0.054 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.024 | 0.043 |
| Bibliometrics | 0.009 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.003 | 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".