The Emerging Epidemiology of VRE in Canada: Results of the CNISP Passive Reporting Network, 1994 to 1998
Bibliographic record
Abstract
OBJECTIVE: To provide a rapid and efficient means of collecting descriptive epidemiological data on occurrences of vancomycin-resistant enterococcus (VRE) in Canada. DESIGN AND METHODS: Passive reporting of data on individual or cluster occurrences of VRE using a one-page surveillance form. SETTING: The surveillance form was periodically distributed to all Canadian Hospital Epidemiology Committee members, Community and Hospital Infection Control Association members, L'Association des professionnels pour la prevention des infections members and provincial laboratories, representing 650 health care facilities across Canada. PATIENTS: Patients colonized or infected with VRE within Canadian health care facilities. RESULTS: Until the end of 1998, 263 reports of VRE were received from 113 health care facilities in 10 provinces, comprising a total of 1315 cases of VRE, with 1246 cases colonized (94.7%), 61 infected (4.6%)and eight of unknown status. (0.6%). VRE occurrences were reported in 56% of acute care teaching facilities and 38% of acute care community facilities. All facilities of more than 800 beds reported VRE occurences compared with only 10% of facilities with less than 200 beds (r2=0.86). Medical and surgical wards accounted for 51.4% of the reported VRE occurences. Sixty-five (24.7%) reports indicated an index case was from a foreign country, with 85.2% from the United States and 14.8% from other countries. Some type of screening was conducted in 50% of the sites. CONCLUSIONS: A VRE passive reporting network provided a rapid and efficient means of providing data on the evolving epidemiology of VRE 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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".