An evaluation of toxigenic <i>Clostridioides difficile</i> positivity as a patient outcome metric of antimicrobial stewardship in Saudi Arabia
Bibliographic record
Abstract
Background: Antimicrobial stewardship has been associated with a reduction in the incidence of healthcare-associated Clostridium difficile infection (HA-CDI). However, CDI remains under-recognised in many low and middle-income countries where clinical and surveillance resources required to identify HA-CDI are often lacking. The rate of toxigenic C. difficile stool positivity in the stool of hospitalised patients may offer an alternative metric for these settings, but its utility remains largely untested. Aim/objective: To examine the impact of antimicrobial stewardship on the rate of toxigenic C. difficile positivity among hospitalised patients presenting with diarrhea Methods: A 12-year retrospective review of laboratory data was conducted to compare the rates of toxigenic C. difficile in diarrhoea stool of patients in a hospital in Saudi Arabia, before and after implementation of an antimicrobial stewardship programme. Result: There was a significant decline in the rate of toxigenic C. difficile positivity from 9.8 to 7.4% following the implementation of the antimicrobial stewardship programme, and a reversal of a rising trend. Discussion: The rate of toxigenic C. difficile positivity may be a useful patient outcome metric for evaluating the long-term impact of antimicrobial stewardship on CDI, especially in settings with limited surveillance resources. The accuracy of this metric is, however, dependent on the avoidance of arbitrary repeated testing of a patient for cure, and testing only unformed or diarrhoea stool specimens. Further studies are required within and beyond Saudi Arabia to examine the utility of this metric.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".