Renal Impairment and Clinical Outcomes of <i>Clostridium difficile</i> Infection in Two Randomized Trials
Bibliographic record
Abstract
BACKGROUND/AIMS: Patients with chronic kidney disease (CKD) have increased risk for Clostridium difficile infection (CDI) and for subsequent mortality. We determined the effect of CKD on response to treatment for CDI. METHODS: This is a post hoc analysis of two randomized controlled phase 3 trials that enrolled patients with CDI. Patients received either fidaxomicin 200 mg b.i.d. or vancomycin 125 mg q.i.d. for 10 days. Univariate and multivariate analyses compared end points by treatment received and CKD stage. RESULTS: At baseline, 27, 21, and 9% of the patients had stage 2 (60-89 ml/min/1.73 m(2)), stage 3 (30-59), and stage 4 or higher (<30) CKD. Cure rates were similar for normal (91%) and stage 2 CKD (92%), but declined to 80% for stage 3 and to 75% for stage 4 CKD (p < 0.001 for trend). Time to resolution of diarrhea (TTROD) increased with stage 3 and stage 4 CKD. CDI recurrence rates 4 weeks after treatment were 16, 20, 27, and 24% for normal, stage 2, stage 3, and stage 4 or higher CKD, respectively. Mortality increased with CKD stage. In multivariate analyses, stage 3 or higher CKD correlated with lower odds of cure, greater chance of recurrence, and lower odds of sustained response 28 days after treatment. Initial cure rates were similar in the vancomycin or fidaxomicin groups; however, the rate of recurrence was higher following vancomycin treatment independent of renal function. The presence of immunosuppression did not alter this effect. CONCLUSION: Progressive CKD is associated with increased TTROD, lower cure rates, and higher recurrence rates with treatment of 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 | 0.011 | 0.017 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.009 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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".