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Record W2789276597 · doi:10.1093/jcag/gwy008.031

A30 FIRST YEAR OUTCOMES FROM A PROVINCIALLY FUNDED NON-FIBROSIS RESTRICTED HEPATITIS C TREATMENT PROGRAM IN PRINCE EDWARD ISLAND

2018· article· en· W2789276597 on OpenAlexaffabout
Jordan Francheville, Robin Rankin, Jeremy Beck, Connie Hoare, Ruben Khan, Stefanie Materniak, Greg J. German, Lisa Barrett, Najme Wall, Daniel Smyth

Bibliographic record

VenueJournal of the Canadian Association of Gastroenterology · 2018
Typearticle
Languageen
FieldMedicine
TopicHepatitis C virus research
Canadian institutionsHorizon Health NetworkHealth PEIDalhousie University
Fundersnot available
KeywordsMedicineReferralTriageObservational studyFamily medicinePublic healthEmergency medicineInternal medicineNursing

Abstract

fetched live from OpenAlex

The availability of novel curative therapies for hepatitis C virus (HCV) infection has created a unique opportunity to mitigate complications of untreated disease, and improve both clinical programming and treatment access. Between September 2014 and October 2015 local care providers, government, industry, and HCV community groups in Prince Edward Island (PEI) created a province-wide model of care. Core components of the program include: centralized referral, triage, and intake by HCV nurse specialist; HCV treatment specialists; non-fibrosis restricted public access to direct-acting antiviral (DAA) therapy; patient education, follow-up with public and industry-affiliated nursing support; and voluntary patient enrollment into a treatment registry. We evaluated performance of this care model, and both demographic, outcome, and treatment-effectiveness measures for treated patients. Using a prospective observational study design, all chronic HCV referrals received from April 2015 to April 2016 were recorded in the program database. Primary analysis examined program parameters including the time from referral to assessment/treatment, as well as the number of referrals, assessments and treatment initiations. A secondary analysis involved evaluation of treatment effectiveness among all treated patients using intent-to-treat analysis. In the first year of the program, 242 patient referrals were received, 123 patients were seen for intake assessments and 93 initiated on DAAs with prioritization to patients with advanced fibrosis. This is compared to only 4 treatment initiations in the province in the 2 years prior to program implementation. The median time from assessment to treatment initiation was 3 weeks. Overall, 82 of the 84 (97.6%) patients for whom outcome data was available achieved sustained virologic response (SVR) at post-treatment week 12; 1 was lost to follow-up and 1 died following therapy completion from an unrelated event. Detailed demographics and on-treatment data was obtained from 70 patients enrolled in the voluntary treatment registry of whom 27.1% were cirrhotic, 24.3% treatment-experienced, and 82.4% reported on-treatment adverse events. No adverse events were deemed serious or resulted in treatment discontinuation. Initial data from the PEI program demonstrates how comprehensive care programs can be used to facilitate timely access to assessment and initiation of HCV therapy. High SVR rates seen in our real-world cohort were reflective of that seen in registration trials including in difficult to treat patient populations. It is hoped that similar models of care throughout Canada will facilitate broader access to curative HCV therapies, especially in under resourced settings. Health Research Foundation of Innovative Medicines Canada, Dalhousie Medical Research Foundation

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 score0.630
Threshold uncertainty score0.735

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0010.000
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 head0.014
GPT teacher head0.277
Teacher spread0.263 · 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

Citations0
Published2018
Admission routes2
Has abstractyes

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