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Record W6991980307

Investigating hepatitis C and substance abuse risk factors for chronic kidney disease among HIV-infected individuals in the era of advanced antiretroviral therapy

2018· dissertation· en· W6991980307 on OpenAlexafffundabout

Bibliographic record

VenueeScholarship@McGill (McGill) · 2018
Typedissertation
Languageen
FieldMedicine
TopicHIV-related health complications and treatments
Canadian institutionsMcGill University Health Centre
FundersCanadian Institutes of Health ResearchMcGill University Health CentreMcGill UniversityStyrelsen för Internationellt Utvecklingssamarbete
KeywordsKidney diseaseCohortRenal functionHepatitis CCohort studyIncidence (geometry)Proportional hazards modelSubstance abuse
DOInot available

Abstract

fetched live from OpenAlex

Background: In the era of advanced antiretroviral therapy, comorbidities associated with aging have become a leading health concern among HIV-infected individuals.Several chronic kidney disease (CKD) risk factors are present among people living with HIV, including hepatitis C virus (HCV) co-infection and ongoing substance abuse, and unraveling the complex web of etiology is difficult.Given that CKD is often asymptomatic, it is important to identify those at highest risk to slow disease progression.Objectives: The overall objective of this thesis was to assess the risk of kidney function decline and CKD associated with hepatitis C co-infection in HIV and to test the hypothesis that substance abuse may explain part of the observed association.Specifically, my objectives were the following:1. Describe the incidence of CKD among HIV-infected Canadians initiating antiretroviral therapy and measure the association between HCV co-infection and CKD progression.2. Describe the prevalence of cocaine use among HCV-HIV co-infected Canadians and measure the association between cocaine abuse and prevalent and incident renal impairment. Describe annual rates of change in kidney function between co-infected Canadians whodeveloped a sustained virologic response (SVR) to HCV treatment and those who are chronically infected.Methods and Results: Data for Objective 1 were obtained from the Canadian Observational HIV Cohort (CANOC) and data for Objectives 2 and 3 were obtained from the Canadian Co-Infection Cohort (CCC) study.Chronic renal impairment (CRI) and CKD were defined by vii consecutive estimated glomerular filtration rate (eGFR) measurements, obtained at least three months apart, of values ≤ 70 and ≤ 60 mL/min/1.73m 2 , respectively.In objective 1, Cox proportional hazards models examined the association between HCV co-infection, defined by a combination of antibody status and clinical diagnoses, and CKD.In objective 2, discrete-time proportional hazards models examined the associations between chronic HCV viral replication and time-updated exposures of cocaine use with CRI.In objective 3, population-averaged linear regression models examined short-term eGFR trajectories associated with SVR.HCV co-infection and CKD (Objective 1): HCV co-infection was associated with a nearly twofold greater risk of incident CKD, after adjusting for traditional and HIV-related CKD risk factors.This association was not modified by past injection drug use history.Female sex, increasing age, larger HIV viral loads and cumulative exposures to tenofovir disoproxil fumarate (TDF) and lopinavir were also associated with CKD.Cocaine and renal impairment (Objective 2): Both prevalent and incident cohorts were developed to examine the association between self-reported cocaine use and CRI.In the prevalent cohort, past injection cocaine use was associated with a two-fold greater risk of CRI, after adjusting for important CKD risk factors.In the incident cohort, users who injected ≥ 3 days/week had the largest risk of CRI.Cumulative exposure to injection cocaine ≥ 75% of study follow-up time was also associated with CRI.Chronic HCV viral replication was not associated with CRI in all models.Non-injection cocaine use was similarly associated with CRI.viii SVR and kidney function decline (Objective 3): Risk-set sampling with propensity scores was used to match each study participant who achieved SVR with two chronically infected participants on the date of SVR.Matching with replacement using a caliper-free nearestneighbor approach was used.There was no appreciable difference in the annual rate of eGFR decline between both groups.Injection cocaine use remained the largest modifiable driver of eGFR decline among HIV-infected patients who achieved SVR.Conclusion: HCV co-infection was associated with CKD among HIV-infected Canadians initiating antiretroviral therapy.However, after accounting for injection and non-injection cocaine use, active HCV viral replication was not associated with early stages of eGFRmeasured kidney disease.Furthermore, eradication of chronic HCV infection through successful HCV treatment was found not to slow kidney function decline in the short-term.Overall, these finding suggest that substance abuse, specifically cocaine use, may explain some of the extrahepatic comorbidities associated with HCV among HIV-infected individuals.This body of work is informative for clinicians as it increases awareness of the impact of substance abuse when screening HCV-HIV co-infected patients for CKD and for researchers to account for cocaine use when studying questions of kidney dysfunction in co-infected populations.encouragement, patience, and guidance.I have been fortunate to have supervisors who cared so much about my work and have provided thoughtful responses to my questions.

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 score0.260
Threshold uncertainty score0.517

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0020.000
Scholarly communication0.0010.000
Open science0.0000.001
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 head0.016
GPT teacher head0.281
Teacher spread0.265 · 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 routes3
Has abstractyes

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