Prevention of <i>Clostridium difficile</i> Infection: A Systematic Survey of Clinical Practice Guidelines
Bibliographic record
Abstract
BACKGROUND Clostridium difficile infection (CDI) is the most common cause of hospital-acquired infectious diarrhea. OBJECTIVE To analyze the methodological quality, content, and supporting evidence among clinical practice guidelines (CPGs) on CDI prevention. DESIGN AND SETTING We searched medical databases and gray literature for CPGs on CDI prevention published January 2004-January 2015. Three reviewers independently screened articles and rated CPG quality using the Appraisal of Guidelines for Research and Evaluation II (AGREE II) instrument, composed of 23 items, rated 1-7, within 6 domains. We reported each domain score as a percentage of its maximum possible score and standardized range. We summarized recommendations, extracted their supporting articles, and rated individually the level of evidence using the Oxford Centre for Evidence-Based Medicine Levels of Evidence. RESULTS Of 2,578 articles screened, 5 guidelines met inclusion criteria. Median AGREE II scores and interquartile ranges were: clarity of presentation, 75.9% (75.9%-79.6%); scope and purpose, 74.1% (68.5%-85.2%); editorial independence, 63.9% (47.2%-66.7%); applicability, 43.1% (19.4%-55.6%); stakeholder involvement, 40.7% (38.9%-44.4%); and rigor of development, 18.1% (17.4%-35.4%). CPGs addressed several common strategies for CDI prevention, including antibiotic stewardship, hypochlorite solutions, probiotic prophylaxis, and bundle strategies. Recommendations were often not consistent with evidence, and most were based on low-level studies. CONCLUSION CPGs did not adhere well to AGREE II reporting standards. Furthermore, there was limited transparency in moving from evidence to recommendations. CDI prevention CPGs need to better adhere to AGREE-II and be transparent in moving from evidence to recommendations, and recommendations need to be consistent with available evidence. Infect Control Hosp Epidemiol 2016;37:901-908.
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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 | 0.062 | 0.291 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.018 | 0.025 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.001 |
| 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".