Does Extending Clostridium Difficile Treatment In Patients Who Are Receiving Concomitant Antibiotics Reduce The Rate Of Relapse
Bibliographic record
Abstract
Purpose: Exposure to concomitant antibiotics during treatment for Clostridium difficile infection (CDI) is a major risk factor for relapse. This study compared the CDI relapse rates among patients who underwent CDI treatment while receiving concomitant antibiotics. Methods: This retrospective chart review evaluated consecutive adult patients with CDI who were receiving concomitant antibiotics at two acute care sites (Hamilton, Ontario) during 2011–2013. We compared the CDI relapse and mortality rates for regular CDI treatment (10–14 days) and extended CDI treatment (>14 days), and adjusted the analyses for several covariates. Results: We identified 457 patients with CDI, and 228 (50%) patients were considered eligible. A total of 101 (44.2%) patients were receiving regular CDI treatment and 127 (55.7%) patients were receiving extended CDI treatment. The relapse rates were similar for the regular and extended treatment groups in the univariate (17% and 23%, respectively; odds ratio [OR]: 1.4, 95% confidence interval [CI]: 0.7–2.7, p = 0.286) and multivariate analyses (OR: 0.7, 95% CI: 0.3–1.7, p = 0.425). A composite outcome (in-hospital mortality and/or CDI relapse) was higher for extended treatment (35% vs. 23%; OR: 1.9, 95% CI: 1.0–3.4, p = 0.039), although this difference was not significant in the multivariate analysis (OR: 1.2, 95% CI: 0.6–2.5, p = 0.648). Conclusions: We found no evidence to support extended CDI treatment among patients who are receiving concomitant antibiotics. However, further studies are needed to identify better methods for reducing the risk of relapse in this population.
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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 | 0.001 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".