Results from the Canadian Nosocomial Infection Surveillance Program for detection of carbapenemase-producing<i>Acinetobacter</i>spp. in Canadian hospitals, 2010–16
Bibliographic record
Abstract
Objectives: Globally there is an increased prevalence of carbapenem-resistant Acinetobacter spp. (CRAs) and carbapenemase-producing Acinetobacter spp. (CPAs) in the hospital setting. This increase prompted the Canadian Nosocomial Infection Surveillance Program (CNISP) to conduct surveillance of CRA colonizations and infections identified from patients in CNISP-participating hospitals between 2010 and 2016. Methods: Participating acute care facilities across Canada submitted CRAs from 1 January 2010 to 31 December 2016. Patient data were collected from medical records using a standardized questionnaire. WGS was conducted on all CRAs and data underwent single nucleotide variant analysis, resistance gene detection and MLST. Results: The 7 year incidence rate of CRA was 0.02 per 10 000 patient days and 0.015 per 1000 admissions, with no significant increase observed over the surveillance period (P > 0.73). Ninety-four CRA isolates were collected from 58 hospitals, of which 93 (98.9%) were CPA. Carbapenemase OXA-235 group (48.4%) was the most common due to two separate clusters, followed by the OXA-23 group (41.9%). Patients with a travel history were associated with 38.8% of CRA cases. The all-cause 30 day mortality rate for infected cases was 24.4 per 100 CRA cases. Colistin was the most active antimicrobial agent (95.8% susceptibility). Conclusions: CRA remains uncommon in Canadian hospitals and the incidence did not increase from 2010 to 2016. Almost half of the cases were from two clusters harbouring OXA-235-group enzymes. Previous medical treatment during travel outside of Canada was common.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.002 | 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".