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Record W2794398035 · doi:10.1093/jcag/gwy008.188

A187 OBSERVATIONAL RETROSPECTIVE ANALYSIS OF PATIENTS IN THE CANADIAN ABBVIECARE (AC) HCV PATIENT SUPPORT PROGRAM

2018· article· en· W2794398035 on OpenAlexaffabout
N Ackad, Patricia Landry, R El Marazi

Bibliographic record

VenueJournal of the Canadian Association of Gastroenterology · 2018
Typearticle
Languageen
FieldHealth Professions
TopicArtificial Intelligence in Healthcare
Canadian institutionsABB (Canada)
Fundersnot available
KeywordsMedicineDiscontinuationInternal medicineMedical prescriptionLogistic regressionObservational studyRetrospective cohort studyEpidemiologyRibavirinHepatitis CHepatitis C virusPediatricsVirusImmunology

Abstract

fetched live from OpenAlex

Recently developed hepatitis C virus (HCV) medications are much better tolerated and require much shorter treatment courses than those previously available. Furthermore, they are more effective at controlling and eradicating HCV. HCV epidemiology in Canada is well documented but not for patients being treated with the newly available medications. Analysis of the Canadian AC HCV database was undertaken to characterize enrolled patients, to tabulate reported treatment outcomes and to identify variables that may be associated with those outcomes, including patient-reported cure rates, treatment completion and treatment initiation. An observational retrospective study design was used to query the data in the AC HCV database. Data was anonymized, screened and validated. Descriptive analyses were performed and logistic regression employed to identify determinants of treatment initiation. Of 1,919 patients enrolled, 1,332 reported initiating treatment, 1,073 completing treatment and 519 reported viral response. Patients averaged 56 years old and 2/3 were male. Most were covered under Provincial drug plans. Only 2% of patients initiating treatment reported discontinuation. Not quite half of patients completing treatment reported virological response, but with only 9 treatment failures, a 98.3% cure rate among patients with complete data was computed (G1a:97.9%, 287/293, G1b: 98.9%, 183/185, G4: 100%, 21/21). Regression analysis performed to explore associations with treatment initiation showed that province of residence (BC, QC & SK vs. ON), fibrosis score >1 and ribavirin co-prescription were significantly associated with greater likelihood to initiate treatment. Patients covered by public insurance were 37% less likely to initiate treatment than those covered by private insurance (p=.007). Regression analysis to explore associations between patient characteristics and either failure to complete treatment or treatment success could not be reliably performed because patients reporting discontinuation or treatment failure were too few. The AC population reflected the Canadian population in its distribution except that PEI was overrepresented in the database, likely reflecting the success of that province’s unique HCV management strategy. Patient reported treatment result (cure/failure), recorded by 48.4% of those who completed treatment, was 98.3% positive, to be treated with caution because of incomplete reporting but consistent with clinical trial results (≥90% cured at 12 weeks). The present study successfully described many attributes of the patient population participating in the AC HCV program. Based on patient initiation, completion and patient activation model scores, the program may promote patients’ engagement in their treatment. Abbvie Corporation, Canada

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 score0.246
Threshold uncertainty score0.495

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.005
Science and technology studies0.0030.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.065
GPT teacher head0.390
Teacher spread0.325 · 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".

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Citations0
Published2018
Admission routes2
Has abstractyes

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