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Enregistrement 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 sur OpenAlexafffundabout

Notice bibliographique

RevueeScholarship@McGill (McGill) · 2018
Typedissertation
Langueen
DomaineMedicine
ThématiqueHIV-related health complications and treatments
Établissements canadiensMcGill University Health Centre
Organismes subventionnairesCanadian Institutes of Health ResearchMcGill University Health CentreMcGill UniversityStyrelsen för Internationellt Utvecklingssamarbete
Mots-clésKidney diseaseCohortRenal functionHepatitis CCohort studyIncidence (geometry)Proportional hazards modelSubstance abuse
DOInon disponible

Résumé

récupéré en direct d'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.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction machine sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.

score de la tête « metaresearch » (Codex)0,001
score de la tête « metaresearch » (Gemma)0,003
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: Observationnel
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,260
Score d'incertitude au seuil0,517

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0010,003
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0010,002
Études des sciences et des technologies0,0020,000
Communication savante0,0010,000
Science ouverte0,0000,001
Intégrité de la recherche0,0000,001
Charge utile insuffisante (le modèle a refusé de juger)0,0020,000

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,016
Tête enseignante GPT0,281
Écart entre enseignants0,265 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeObservationnel
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2018
Routes d'admission3
Résumé présentoui

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