A population-based matched cohort study examining the mortality and costs of patients with community-onset Clostridium difficile infection identified using emergency department visits and hospital admissions
Bibliographic record
Abstract
Few studies have evaluated the mortality or quantified the economic burden of community-onset Clostridium difficile infection (CDI). We estimated the attributable mortality and costs of community-onset CDI. We conducted a population-based matched cohort study. We identified incident subjects with community-onset CDI using health administrative data (emergency department visits and hospital admissions) in Ontario, Canada between January 1, 2003 and December 31, 2010. We propensity-score matched each infected subject to one uninfected subject and followed subjects in the cohort until December 31, 2011. We evaluated all-cause mortality and costs (unadjusted and adjusted for survival) from the healthcare payer perspective (2014 Canadian dollars). During our study period, we identified 7,950 infected subjects. The mean age was 63.5 years (standard deviation = 22.0), 62.7% were female, and 45.0% were very high users of the healthcare system. The relative risk for 30-day, 180-day, and 1-year mortality were 7.32 (95% confidence interval [CI], 5.94-9.02), 3.55 (95%CI, 3.17-3.97), and 2.59 (95%CI, 2.37-2.83), respectively. Mean attributable cumulative 30-day, 180-day, and 1-year costs (unadjusted for survival) were $7,434 (95%CI, $7,122-$7,762), $12,517 (95%CI, $11,687-$13,366), and $13,217 (95%CI, $12,062-$14,388). Mean attributable cumulative 1-, 2-, and 3-year costs (adjusted for survival) were $10,700 (95%CI, $9,811-$11,645), $13,312 (95%CI, $12,024-$14,682), and $15,812 (95%CI, $14,159-$17,571). Infected subjects had considerably higher risk of all-cause mortality and costs compared with uninfected subjects. This study provides insight on an understudied patient group. Our study findings will facilitate assessment of interventions to prevent community-onset 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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".