Impact of Isolating Clostridium difficile Carriers on the Burden of Isolation Precautions: A Time Series Analysis
Bibliographic record
Abstract
Background: The isolation of asymptomatic Clostridium difficile (CD) carriers may decrease the incidence of hospital-associated C. difficile infections (CDI), but its impact on isolation precaution needs is unknown. Methods: A time series analysis was conducted to investigate the impact of isolating CD carriers on the burden of isolation precautions from 2008 to 2016 in a Canadian hospital. To account for the changes in C. difficile infection control policies, the series was divided into 3 intervention periods: period 1 (2008-2011), isolation of patients with CDI until symptom resolution; period 2 (2011-2013), isolation of patients with CDI until discharge; and period 3 (2013-2016), isolation of patients with CDI and CD carriers until discharge. We compared the prevalence of isolation-days for C. difficile (ie, for either CDI or carriage) per 1000 patient-days between study periods. Changes in trend were analyzed by segmented regression analysis. Results: A total of 806357 patient-days and 20455 isolation-days were included. Isolation-day prevalence during periods 1, 2, and 3 were 12.9, 26.2, and 37.8 isolation-days per 1000 patient-days, respectively (P < .001 between periods). Isolating CD carriers was associated with an increase in isolation-days' prevalence compared with period 2 (rate ratio [RR], 1.66; P < .001) followed by a significant decrease in trend (RR per 4-week period, 0.97; P < .001). The downward trend was mainly due to decreasing isolation needs for patients with CDI (RR per 4-week period, 0.94; P < .001) rather than for carriage (RR per 4-week period, 0.996; P = .21). Conclusions: Isolating CD carriers led to an initial increase in isolation needs that was partially compensated by a decrease in isolation needs for 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 | 0.004 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".