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Record W4364381304 · doi:10.1503/cmaj.220717

Characterizing the cascade of care for hepatitis C virus infection among Status First Nations peoples in Ontario: a retrospective cohort study

2023· article· en· W4364381304 on OpenAlexaffvenueabout
Andrew Mendlowitz, Karen E. Bremner, Murray Krahn, Jennifer Walker, William Wong, Beate Sander, Lyndia Jones, Wanrudee Isaranuwatchai, Jordan J. Feld

Bibliographic record

VenueCanadian Medical Association Journal · 2023
Typearticle
Languageen
FieldMedicine
TopicHepatitis C virus research
Canadian institutionsMcMaster UniversityPublic Health OntarioHamilton Health SciencesUniversity Health NetworkAssembly of First NationsSinai Health SystemUniversity of WaterlooToronto Public HealthSt. Michael's Hospital
Fundersnot available
KeywordsMedicineCohortRetrospective cohort studyHepatitis C virusHepatitis CInternal medicineImmunologyFamily medicineVirus

Abstract

fetched live from OpenAlex

BACKGROUND: As First Nations Peoples are a priority focus of Canada's commitment to eliminating hepatitis C virus (HCV) as a public health threat, understanding individuals' progression from diagnosis to cure can guide prioritization of elimination efforts. We sought to characterize and identify gaps in the HCV care cascade for Status First Nations peoples in Ontario. METHODS: In this retrospective cohort study, a partnership between the Ontario First Nations HIV/AIDS Education Circle and academic researchers, HCV testing records (1999-2018) for Status First Nations peoples in Ontario were linked to health administrative data. We defined the cascade of care as 6 stages, as follows: tested positive for HCV antibody, tested for HCV RNA, tested positive for HCV RNA, HCV genotyped, initiated treatment and achieved sustained viral response (SVR). We mapped the care cascade from 1999 to 2018, and estimated the number and proportion of people at each stage. We stratified analyses by sex, diagnosis date and location of residence. We used Cox regression to analyze the secondary outcomes, namely the associations between undergoing HCV RNA testing and initiating treatment, and demographic and clinical predictors. RESULTS: = 801, 79.9%) of treated people achieved SVR, with 34 (4.2%) experiencing reinfection or relapse. Undergoing testing for HCV RNA was more likely among people in older age categories (within 1 yr of antibody test; adjusted hazard ratio [HR] 1.30, 95% confidence interval [CI] 1.19-1.41, among people aged 41-60 yr; adjusted HR 1.47, 95% CI 1.18-1.81, among people aged > 60 yr), those living in rural areas (adjusted HR 1.20, 95% CI 1.10-1.30), those with an index date after Dec. 31, 2013 (era of treatment with direct-acting antiviral regimens) (adjusted HR 1.99, 95% CI 1.85-2.15) and those with a record of substance use or addictive disorders (> 1 yr after antibody test; adjusted HR 1.38, 95% CI 1.18-1.60). Treatment initiation was more likely among people in older age categories at index date (adjusted HR 1.32, 95% CI 1.15-1.50, among people aged 41-60 yr; adjusted HR 2.62, 95% CI 1.80-3.82, among people aged > 60 yr) and those with a later diagnosis year (adjusted HR 2.71, 95% CI 2.29-3.22). INTERPRETATION: In comparison with HCV testing and diagnosis, a substantial gap in treatment initiation remains among Status First Nations populations in Ontario. Elimination efforts that prioritize linkage to care and integration with harm reduction and substance use services are needed to close gaps in HCV care among First Nations populations in Ontario.

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)0.003
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 score0.054
Threshold uncertainty score0.109

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.003
Science and technology studies0.0020.001
Scholarly communication0.0010.001
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 head0.013
GPT teacher head0.287
Teacher spread0.274 · 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

Citations13
Published2023
Admission routes3
Has abstractyes

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