Healthcare-associated bloodstream infections (HABSI) in Quebec after the establishment of BACTOT, a hospital-wide provincial HABSI surveillance program
Bibliographic record
Abstract
Background. We described the secular trends of HABSI incidence rates (IRs) in Quebec between April 1st, 2007 and March 31st, 2017 in eligible hospitals that have participated in BACTOT since its inception. We then evaluated the HABSI trend over surveillance year in eligible hospitals that have participated in BACTOT for at least 3 years without interruption, regardless of their date of entry. Methods. HABSI IRs over calendar time were analysed by fitting Poisson regression models using Generalized Estimating Equations and were stratified by infection source. For analysis over surveillance time, we used a Bayesian framework to fit multilevel Poisson regression to HABSI and its most common subtypes to decompose their mean rates into a surveillance year effect, periodic effect, and hospital effect. Cohort-level risk of surveillance years 2 to 10 relative to year 1 were calculated. A subgroup analysis was performed by fitting the same Bayesian models to hospitals that participated for less than 10 years to exclude hospitals that may have been conducting surveillance prior to participation. Results. In calendar years, HABSI rates did not exhibit statistically significant changes from year to year. Non-catheter-associated-primary BSIs were the only HABSI type that exhibited a sustained change across the 10 years, increasing from 0.69/10,000 patient-days (95% CI: 0.59-0.80) in 2007-08 to 1.42/10,000 patient-days (95% CI: 1.27-1.58) in 2016-17. For HABSI, CA-BSI, and BSI-UTI, there was no difference between the estimated risks of surveillance years 2 to 10 compared to surveillance year 1. As for NCA-BSI, the risk of the 10th year of surveillance was 29% (95% CI: 1-89%) higher than the risk in the first year. In the subgroup analysis, no differences in risks were detected between the years for HABSI and all analysed subtypes. Conclusion. Despite ongoing surveillance, HABSI rates have not decreased over either calendar time or over surveillance time. While surveillance may continue for data collection and documentation purposes, for improvements in rates, targeted interventions must be employed and evaluated.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| 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".