Incidence and risk factors for recurrent <i>Clostridioides difficile</i> infection in pediatric at-risk groups in selected Pediatric Investigators Collaborative Network on Infections in Canada (PICNIC) hospitals
Bibliographic record
Abstract
Abstract Objectives: Incidence and risk factors for recurrent Clostridioides difficile infection (rCDI) are well established in adults, though data are lacking in pediatrics. We aimed to determine incidence of and risk factors for rCDI in pediatrics. Methods: This retrospective cohort study of pediatric patients was conducted at 3 tertiary-care hospitals in Canada with laboratory-confirmed CDI between April 1, 2012, and March 31, 2017. rCDI was defined as an episode of CDI occurring 8 weeks or less from diagnostic test date of the primary episode. We used logistic regression to determine and quantify risk factors significantly associated with rCDI. Results: In total, 286 patients were included in this study. The incidence proportion for rCDI was 12.9%. Among hospitalized patients, the incidence rate was estimated at 2.6 cases of rCDI per 1,000 hospital days at risk (95% confidence interval [CI], 1.7–3.9). Immunocompromised patients had higher incidence of rCDI (17.5%; P = .03) and higher odds of developing rCDI independently of antibiotic treatment given for the primary episode (odds ratio [OR], 2.31; 95% CI, 1.12–5.09). Treatment with vancomycin monotherapy did not show statistically significant protection from rCDI, independently of immunocompromised status (OR, 0.33; 95% CI, 0.05–1.15]). Conclusions: The identification of increased risk of rCDI in immunocompromised pediatric patients warrants further research into alternative therapies, prophylaxis, and prevention strategies to prevent recurrent disease burden within these groups. Treatment of the initial episode with vancomycin did not show statistically significant protection from rCDI.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 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".