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Record W4319927283 · doi:10.1155/2023/9465158

Retrospective Cohort Analysis of Outpatient Antibiotic Use for <i>Clostridioides difficile</i>‐Indicated Agents in British Columbia, from 2000 to 2018

2023· article· en· W4319927283 on OpenAlexafffundabout
Ariana Saatchi, Sungeun Kim, Fawziah Marra

Bibliographic record

VenueCanadian Journal of Infectious Diseases and Medical Microbiology · 2023
Typearticle
Languageen
FieldMedicine
TopicClostridium difficile and Clostridium perfringens research
Canadian institutionsUniversity of British Columbia
FundersCanadian Institutes of Health Research
KeywordsClostridioidesRetrospective cohort studyMedicineCohortAntibioticsEmergency medicineInternal medicineMicrobiologyBiology

Abstract

fetched live from OpenAlex

Background: (CDI) is the most common cause of nosocomial diarrheal infections. Historically, metronidazole was the first-line treatment, but guidelines now indicate oral vancomycin and fidaxomicin as primary antibiotics for initial episodes. A provincial stewardship program has operated in British Columbia (BC), since 2005. Since the program's inception, surveillance of antibiotic use has been ongoing. However, this is the first study to review community-acquired CDI-indicated antibiotic use. Moreover, this study offers the first interpretation of fidaxomicin use in BC since its addition to the provincial formulary. Methods: A retrospective cohort analysis included all outpatient dispensations for CDI-related antibiotics from January 1, 2000, to December 31, 2018. Antibiotic dispensations were extracted for metronidazole, vancomycin, and fidaxomicin. Consumption rates were calculated as prescriptions per 1000 population. Rates were examined overall and then stratified by medication, age, and sex. Secondary outcomes of interest included an examination of adherence to provincial special authority criteria; and proportions of outpatient antibiotic use attributable to administrative health records for CDI. Results: The average annual rate of prescribing was 18.5 per 1000 population for all CDI-indicated antibiotics. The rate of prescribing increased (15%) over the 19-year study period, from 17.2 to 19.8 dispensations per 1000 population. Metronidazole accounted for the most antibiotics dispensed in every study year; however, by 2018 it demonstrated the most modest increase in use (15%). In comparison, fidaxomicin increased by 226% by 2018. Vancomycin had the highest percentage increase (621%), with the greatest change occurring from 2014 to 2015, correlating to the dissemination of new clinical practice guidelines. Conclusion: This is the first study to evaluate outpatient prescribing for CDI-indicated antibiotics, and one of the few studies to examine fidaxomicin since its introduction to Canadian formularies. Although causation cannot be inferred from study results, oral vancomycin, and fidaxomicin use has increased in line with, or in advance-of guidelines.

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

Direct model labels (unvalidated)

Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.

Model armCategoriesStudy designConfidence
gemmano category
Domain: not available · Genre: Empirical
About the Canadian research system: no · About a Canadian topic: no
Observationallow
gptno category
Domain: not available · Genre: Empirical
About the Canadian research system: yes · About a Canadian topic: yes
Observationalhigh
models agreeAgreement compares identical category sets and study designs across arms.

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)0.002
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 score0.125
Threshold uncertainty score0.251

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.006
Science and technology studies0.0020.000
Scholarly communication0.0020.000
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.015
GPT teacher head0.266
Teacher spread0.252 · 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

Labeled directly by 2 models reading the full record.

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

Citations1
Published2023
Admission routes3
Has abstractyes

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