AMMI Canada ‐ CACMID Annual Conference
Bibliographic record
Abstract
Background: Surveillance of healthcare-associated infections (HAI) is an important component of an infection prevention and control program and is a primary step toward the prevention of HAI.The only data available on the overall burden of illness in Canada related to HAI are that from the previous point prevalence survey that was conducted by CNISP in 2002.oBjective: To estimate the prevalence of HAI in Canadian acute care hospitals participating in the CNISP. Study deSign:A point-prevalence study for HAI conducted in February 2009 in 49 hospitals across Canada.reSultS: 9953 patients were surveyed; 8599 (86.4%) were adults (>18 years of age), 622 (6.4%) were 1 to 17 years of age , and 732 (7.4%) were infants under the age of 1 year.1231 HAI were detected in 1173 patients, for a prevalence of 124 per 1000 patients surveyed, compared with 111 per 1000 in surveyed in 2002.The most common HAI was urinary tract infection (4.3%,) followed by pneumonia, (2.7%), surgical site infections (2.3%), bloodstream infections (1.7%), and Clostridium difficile disease (1.2%).3998 (40.2%) patients were on antimicrobial agents compared to 36.6% in 2002 (p<0.0001) and 1470 (14.8%) were on isolation precautions in 2009 compared to 7.6% in 2002 (p<0.0001).concluSion: In this follow-up national point prevalence study in Canada, the prevalence of HAI increased slightly, largely attributed to an increased prevalence of UTI and CDI with a decrease in pneumonia and BSI.There was also a significant increase in antimicrobial use and a doubling of prevalence of patients on isolation, the latter related to CDI and antimicrobial resistant organisms.These data will also be useful to provide an estimate of the health burden of HAI in Canada.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.005 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.303 | 0.091 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".