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Record W7162087562 · doi:10.82308/44450

Visits to primary care physicians and the impact on Hepatitis C Virus (HCV) transmission among HCV- seronegative persons who inject drugs

2014· dissertation· en· W7162087562 on OpenAlexaboutno aff
Adelina Artenie

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldMedicine
TopicHIV, Drug Use, Sexual Risk
Canadian institutionsnot available
Fundersnot available
KeywordsTransmission (telecommunications)AttendanceHepatitis C virusLogistic regressionHepatitis CPrimary careCohortCohort study

Abstract

fetched live from OpenAlex

Introduction: Persons who inject drugs (PWID) are confronted with a considerably high risk of infection with the Hepatitis C Virus (HCV). To effectively avert HCV transmission rates in this population, international guidelines recommend combining multiple prevention strategies. While the role of primary care physicians (PCP) in HCV prevention is increasingly emphasized, PWID have generally suboptimal contacts with primary healthcare services, and little is known about the factors that may enhance or deter contacts. Further, no study has yet examined the effect of visiting a PCP on HCV transmission among PWID. Aims: This investigation had three specific objectives: (I) to examine the prevalence of visiting a PCP, (II) to explore the associated factors, and (III) to assess the effect of visiting a PCP as part of a comprehensive prevention approach, on HCV transmission, among PWID at risk of HCV infection. Methods: A prospective cohort study, HEPCO, was carried out among HCV-seronegative PWID in Montréal, Canada (2004 – 2011). At each semi-annual visit, an interviewer-administered questionnaire elicited information on socio-demographic factors, drug use patterns and related behaviors, as well as healthcare and community-based services use. Blood samples were drawn and tested for HCV antibodies. Using the Gelberg-Andersen Health Model, logistic regression analyses were carried out on baseline data to examine predisposing, need and enabling factors associated with PCP visits. To investigate the association between visiting a PCP and HCV incidence, a Cox-regression model was conducted among participants reporting needle exchange program (NEP) attendance at baseline. Results: Of 349 participants having completed the baseline questionnaire (80.8% male, mean age: 34), 32.1% reported having visited a PCP in the previous six months. In logistic regression analyses, among predisposing factors, male gender (Adjusted Odds Ratio (AOR)= 0.45, [0.25 - 0.82]), chronic homelessness (AOR= 0.09, [0.01 – 0.69]) and cocaine injection (AOR= 0.46, [0.28-0.75]) were negatively associated with PCP visits. Need factors did not correlate significantly with the outcome. Among enabling factors, reporting a greater proportion of the income through stable sources (AOR= 2.07, [1.18 – 3.62]), contact with food banks (AOR= 2.02, [1.20 – 3.38]) and contact with street nurses (AOR= 3.85 [1.49 – 9.96]) were positively associated with PCP visits. Among 160 HCV-seronegative PWID having attended NEP at baseline and followed-up at least once, HCV incidence was 23.1 per 100 person-years [18.0 – 29.3]. In a multivariate Cox regression model adjusting for age, gender and HCV-risk factors, visiting a PCP was found to significantly reduce the risk of HCV-seroconversion (Adjusted Hazard Ratio= 0.52, [0.27 – 0.98]). Interpretation: Only a minority of PWID reported having visited a PCP. While specific predisposing factors seem to render PWID less likely to visit PCP, contacts with community-based outreach services may play an important role in engaging these individuals into primary care. Further, findings suggest that visiting a PCP, as part of a comprehensive HCV prevention approach, has a protective effect on HCV transmission.

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)0.000
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 score0.289
Threshold uncertainty score0.575

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.010
GPT teacher head0.311
Teacher spread0.301 · 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
Published2014
Admission routes1
Has abstractyes

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