Pediatric oncology and stem cell transplant patients with healthcare‐associated <i>Clostridium difficile</i> infection were already colonized on admission
Bibliographic record
Abstract
Clostridium difficile is the leading cause of healthcare-associated infections worldwide. The diagnosis of C. difficile infection (CDI) in pediatric oncology patients is complex as diarrhea is common, and there is a high rate of colonization in infants and young children. This study was conducted to assess the accuracy of the surveillance definitions of healthcare-associated CDI (HA-CDI) and to determine the prevalence of toxigenic C. difficile colonization among pediatric oncology and stem cell transplant patients. METHODS: A prospective cohort study was conducted over a three-year period in an inpatient pediatric oncology and stem cell transplant setting. Baseline stool samples were collected within three days of admission and were genotypically compared with clinically indicated samples submitted after three days of admission. RESULTS: A total of 175 patients were recruited with a total of 536 admissions. The adjusted prevalence of baseline toxigenic C. difficile colonization among admissions was 32.8%. Seventy-eight percent of positive admissions did not have history of CDI. Colonization with a toxigenic strain on admission was predictive of CDI (OR = 28.6; 95% CI, 6.58-124.39; P < 0.001). Nearly all clinical isolates (8/9) shared identical pulsed-field gel electrophoresis patterns with baseline isolates or were closely related (1/9). Only one of the 11 cases that were considered HA-CDI was potentially nosocomially acquired. CONCLUSION: The prevalence of colonization with toxigenic C. difficile in our cohort is high. Unfortunately, the current CDI surveillance definitions overestimate the incidence of HA-CDI in pediatric oncology and stem cell transplantation settings.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".