Antibiotics and healthcare facility-associated <i>Clostridioides difficile</i> infection: systematic review and meta-analysis 2020 update
Bibliographic record
Abstract
BACKGROUND: Antibiotic use is the most important modifiable risk factor for healthcare facility-associated Clostridioides difficile infection (HCFA-CDI). Previous systematic reviews cover studies published until 31 December 2012. OBJECTIVES: To update the evidence for associations between antibiotic classes and HCFA-CDI to 31 December 2020. METHODS: PubMed, Scopus, Web of Science Core Collection, WorldCat and Proquest Dissertations & Theses were searched for studies published since 1 January 2013. Eligible studies were those conducted among adult hospital inpatients, measured exposure to individual antibiotics or antibiotic classes, included a comparison group and measured the occurrence of HCFA-CDI as an outcome. The Newcastle-Ottawa Scale was used to appraise study quality. To assess the association between each antibiotic class and HCFA-CDI, a pooled random-effects meta-analysis was undertaken. Meta-regression and subgroup analysis was used to investigate study characteristics identified a priori as potential sources of heterogeneity. RESULTS: Carbapenems and third- and fourth-generation cephalosporin antibiotics remain the most strongly associated with HCFA-CDI, with cases more than twice as likely to have recent exposure to these antibiotics prior to developing HCFA-CDI. Modest associations were observed for fluoroquinolones, clindamycin and β-lactamase inhibitor combination penicillin antibiotics. Individual study effect sizes were variable and heterogeneity was observed for most antibiotic classes. CONCLUSIONS: This review provides the most up-to-date synthesis of evidence in relation to the risk of HCFA-CDI associated with exposure to specific antibiotic classes. Studies were predominantly conducted in North America or Europe and more studies outside of these settings are needed.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.016 | 0.005 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| 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".