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Record W3041023931 · doi:10.1186/s13756-020-00758-x

The 2017 global point prevalence survey of antimicrobial consumption and resistance in Canadian hospitals

2020· article· en· W3041023931 on OpenAlexaffabout
Charles Frenette, David Sperlea, Greg J. German, Kevin Afra, Jennifer Boswell, Sandra Chang, Herman Goossens, Jennifer Grant, Marie-Astrid Lefebvre, Allison McGeer, Dominic Mertz, Michelle Science, Ann Versporten, Daniel J. G. Thirion

Bibliographic record

VenueAntimicrobial Resistance and Infection Control · 2020
Typearticle
Languageen
FieldImmunology and Microbiology
TopicAntibiotic Use and Resistance
Canadian institutionsMcGill UniversityHospital for Sick ChildrenHamilton Health SciencesMontreal Children's HospitalUniversité de MontréalFraser HealthMount Sinai HospitalVancouver General HospitalHealth PEIRichmond HospitalMcGill University Health Centre
Fundersnot available
KeywordsMedicineAntibiotic resistanceAntimicrobial stewardshipAntimicrobialMedical microbiologyPharmacistDrug resistanceEmergency medicineIntensive care medicineInternal medicineFamily medicineAntibioticsPharmacy

Abstract

fetched live from OpenAlex

BACKGROUND: Patient-level surveillance (indication, appropriate choice, dosing, route, duration) of antimicrobial use in Canadian hospitals is needed to reduce antimicrobial overuse and misuse. Patient-level surveillance has not been performed on a national level in Canada. The Global Point Prevalence Survey of Antimicrobial Consumption and Resistance (Global-PPS) is an international collaborative to monitor antimicrobial use and resistance in hospitals worldwide. Global-PPS locally documents on a single day patient-level antimicrobial prescribing practices. This article presents the results of the 2017 Global-PPS in Canadian hospitals with established antimicrobial stewardship programs. METHODS: Hospitals part of the Canadian Nosocomial Infection Surveillance Program were invited to participate. Surveys could be performed any time in the 2017 calendar year. All in-patient wards in each hospital were surveyed by a physician, pharmacist or nurse with infectious disease training. RESULTS: Fourteen Canadian hospitals participated in the survey. Of 4118 patients, 1400 patients (34.0%) received a total of 2041 antimicrobials. Overall, 73.1% (n = 1493) of antimicrobials were for therapeutic use, 14.2% (n = 288) were for medical prophylaxis, 8.3% (n = 170) were for surgical prophylaxis, 1.8% (n = 37) were for other reasons, and 0.2% (n = 3) were used as prokinetic agents. Only 2.5% (n = 50) were for unknown reasons. For antimicrobials for therapeutic use, 29.9% of patients were treated for lower respiratory tract (343/1147), 10.5% for intra-abdominal (120/1147), 9.3% for skin and soft tissue (107/1147) and 7.5% for gastro-intestinal (86/1147) infections. CONCLUSIONS: Standardized methodology amongst Global-PPSs allows the comparison of our results to the 2015 Global-PPS. The prevalence of antimicrobial use on medical, surgical, and intensive care wards are similar to those previously observed in North America. Indication of antimicrobials has not been previously reported on such a large scale in Canadian hospitals. This report serves as a comparison for further point prevalence surveys that are currently underway. It will be used for identifying opportunities and benchmarking in antibiotic stewardship.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.028
Threshold uncertainty score0.201

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0040.008
Science and technology studies0.0020.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.010
GPT teacher head0.237
Teacher spread0.227 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations32
Published2020
Admission routes2
Has abstractyes

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