MétaCan
Menu
Back to cohort
Record W2982130754 · doi:10.1093/ofid/ofz360.999

1135. The 2018 Global Point Prevalence Survey of Antimicrobial Consumption and Resistance: Pediatric Results from 26 Canadian Hospitals

2019· article· en· W2982130754 on OpenAlexaffabout
Marie-Astrid Lefebvre, Ann Versporten, Marie Carrier, Sandra Chang, Jeannette Comeau, Yannick Émond, Charles Frenette, Sarah Khan, Daniel L. Landry, Timothy MacLaggan, Trong Tien Nguyen, Tuyen Nguyen, Louis Valiquette, Dominik Mertz, Ines Pauwels, Herman Goossens

Bibliographic record

VenueOpen Forum Infectious Diseases · 2019
Typearticle
Languageen
FieldMedicine
TopicNeonatal and Maternal Infections
Canadian institutionsCentre intégré de santé et de services sociaux de Chaudière-AppalachesCentre Intégré de Santé et de Services Sociaux des LaurentidesHorizon Health NetworkVitalité Health NetworkMcMaster UniversityUniversité de MontréalUniversité de SherbrookeMontreal Children's HospitalDr. Georges-L.-Dumont University Hospital CentreIzaak Walton Killam Health CentreHôpital Maisonneuve-RosemontRichmond HospitalMcGill UniversityMcGill University Health CentreCentre intégré universitaire de santé et de services sociaux de la Mauricie-et-du-Centre-du-Québec
Fundersnot available
KeywordsMedicineAntimicrobialTazobactamAntibiotic resistancePiperacillinAntimicrobial stewardshipTrimethoprimMedical prescriptionInternal medicinePediatricsAntibioticsEmergency medicineEmpiric therapyIntensive care medicineImipenem

Abstract

fetched live from OpenAlex

Abstract Background Inappropriate antimicrobial use (AMU) is strongly associated with antimicrobial resistance. The Global Point Prevalence Survey (Global-PPS) is a standardized tool that is used worldwide to characterize inpatient AMU. We report pediatric results from 26 Canadian hospitals that participated in the Global-PPS in 2018. Methods The survey was completed by each site on the Global-PPS website for all patients aged 0–17 years hospitalized in a neonatal or pediatric ward on a chosen day between January and December 2018. Data collected included ward type, demographics, antimicrobials prescribed, diagnosis, type of indication (community-acquired [CA] vs. healthcare-associated [HA]) and type of therapy (empiric vs. targeted). Quality indicators included guideline compliance, medical record documentation of diagnosis, antimicrobial stop/review date, and surgical prophylaxis (SP) duration. Results Of the 26 sites, 23 were mixed and 3 were pediatric hospitals, with data on 767 inpatients. Overall, 25.8% (n = 198) of patients received at least one antimicrobial, and 21.9% (n = 168) were on at least one antibiotic. The highest AMU was found in Hematology-Oncology (84%), Pediatric Intensive Care (55.3%) and surgical (42.1%) units. Of the 330 antimicrobial prescriptions, 40.9% were for CA infections, 23% for medical prophylaxis, 20% for HA infections and 2.7% for SP. The most commonly treated infections were sepsis (16%) and lower respiratory tract infection (12.1%). The top five prescribed antibiotics were aminopenicillins (20.4%), aminoglycosides (16.1%), third-generation cephalosporins (15.4%), piperacillin–tazobactam (7.5%) and trimethoprim-sulfamethoxazole (7.5%). Diagnosis and stop/review date were documented for 88.1% and 65.1% of prescriptions, respectively. Compliance to local guidelines was found in 91.5% of therapies. SP exceeded 24 hours in 88.9% of courses. Conclusion The Global-PPS generated Canada-wide data on inpatient pediatric AMU, which will allow hospitals to benchmark and develop local quality improvement interventions to enhance appropriate AMU. Targets for improvement include suboptimal antimicrobial stop/review date documentation and prolonged SP. Disclosures All authors: No reported disclosures.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.126
Threshold uncertainty score0.768

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.012
GPT teacher head0.265
Teacher spread0.254 · 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 teacher head, 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

Citations3
Published2019
Admission routes2
Has abstractyes

Explore more

Same venueOpen Forum Infectious DiseasesSame topicNeonatal and Maternal InfectionsFrench-language works237,207