Antibiotics and hospital-associated <i>Clostridioides difficile</i> infection: systematic review and meta-analysis 2020 update
Bibliographic record
Abstract
Abstract Background Clostridioides difficile infection (CDI) is the most common cause of healthcare facility-associated (HCFA) infectious diarrhoea in high-income countries. Antibiotic use is the most important modifiable risk factor for CDI. The most recent systematic review covered studies published until 31 st December 2012. Objectives To update the evidence for epidemiological associations between specific antibiotic classes and HCFA-CDI for the period 1 st January 2013 to 31 st December 2020. Data sources PubMed, Scopus, Web of Science Core Collection, WorldCat, and Proquest Dissertations and Theses. Study eligibility criteria, participants and exposures 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. Study appraisal and synthesis methods The Newcastle–Ottawa Scale for the Assessment of Quality was used to appraise study quality. To assess the association between each antibiotic class and HA-CDI, a pooled random effects meta-analysis was undertaken. Metaregression and sub-group analysis was used to investigate study characteristics identified a priori as potential sources of heterogeneity. Results Carbapenems, and 3 rd and 4 th generation cephalosporin antibiotics remain most strongly associated with HCFA-CDI, with cases more than twice as likely to have recent exposure to these antibiotics prior to developing CDI. Modest associations were observed for fluoroquinolones clindamycin, and beta-lactamase inhibitor combination penicillin antibiotics. Limitations Individual study effect sizes were variable and heterogeneity was observed for most antibiotic classes. Availability of a single reviewer to select, extract and critically appraise the studies. 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. Registration number Prospero CRD42020181817
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.013 | 0.033 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.016 | 0.028 |
| Bibliometrics | 0.009 | 0.009 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".