Stool Management Systems for Preventing Environmental Spread of Clostridium difficile
Bibliographic record
Abstract
PURPOSE: The purpose of this study was to compare contamination of the immediate environment with Clostridium difficile spores and vegetative cells from 2 stool management systems over a period of 30 days in a controlled laboratory setting. DESIGN: In vitro, comparison trial. METHODS: Two stool management systems were compared over a 30-day period in a controlled laboratory setting. Sixteen systems were filled with sterile loose canine stool inoculated with 10 colony-forming units (CFUs) per milliliter of C difficile; specially prepared culture media were used to detect C difficile contamination on various surfaces of the device and in the immediate environment. Containment bags were changed daily and devices were refilled with inoculated stool to more closely imitate use in the clinical setting. A dichotomous outcome variable (growth vs no growth) was used to analyze contamination on a daily basis via the generalized estimating equation; devices were also compared on days 3, 10, 20, and 30 by measuring CFUs per device surface. Logistic regression analysis was used to analyze growth over time. When observations showed no growth, the Cochran-Mantel Haenszel test was used to compare study devices. RESULTS: Analysis revealed that 20.8% of anterior surfaces of the collection bags for device 1 were contaminated versus 83.9% of collection bags for device 2 (P < .001). Comparison of the tubing/hub interface resulted in similar findings; 20.8% of device 1 group were contaminated versus 86.3% of device 2 group (P < .001). Analysis of an absorbent pad placed under the device during daily changes found that 0.5% of device 1 were contaminated versus 38.1% of pads placed under device 2 (P < .001). CONCLUSIONS: Findings from this in vitro study show that stool management systems can limit or prevent environmental contamination of C difficile. Results also reveal significant differences in the 2 systems tested; we hypothesize that these differences are attributable to the interface between the tubing and collection bag, the point at which these systems are most often disconnected as collection bags become filled with fecal material. Further clinical studies are required to confirm the clinical relevance of the data presented in this in vitro study.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".