Global Practice Variation in the Management of <i>Clostridioides difficile</i> Infections: An International Cross-Sectional Survey of Clinicians
Bibliographic record
Abstract
Abstract Background Clostridioides difficile infections (CDIs) are associated with significant morbidity, mortality, and economic burden globally. International guidelines conflict on various aspects of management, so we conducted a clinician survey to evaluate global practice variability on CDI diagnosis, treatment, and prophylaxis to inform future clinical trials. Methods An anonymous online survey through REDCap was distributed through multiple channels. Attending physicians, infectious disease pharmacists, and fellows in infectious diseases or medical microbiology who had managed ≥3 cases of CDI in the preceding year were eligible. Responses were compared across continents by chi-square test. Results Three hundred fifty-nine survey responses were collected from 31 countries and 6 continents (North America 80.5%, Europe 11.7%, other continents 7.8%). A 2-step CDI diagnostic algorithm was used by 75.8% of respondents with heterogeneity in assay type. Similarly, there was significant variability in first-line agents for the treatment of first episodes and first recurrences of uncomplicated CDI and a lack of consensus on treatments for fulminant CDI. Secondary CDI prophylaxis during antibiotic re-exposure was most commonly used in North America (84.1%), followed by other continents (50.0%) and Europe (31.0%; P < .001). Oral vancomycin was the most frequently used agent (96.3%), with significant variability in the dose (125–500 mg daily) and duration (1–28 days; P < .01). Conclusions Substantial global variability exists with respect to CDI diagnosis, treatment, and secondary prophylaxis, likely due to divergent guidelines and a paucity of robust evidence. These findings highlight critical knowledge gaps and areas of clinical equipoise and underscore the need for further randomized controlled trials to establish harmonized international best practices for CDI.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".