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Enregistrement W2027074474 · doi:10.1111/j.1360-0443.2011.03708.x

Commentary on Thorne <i>et al</i>. (2012): HIV prevention and treatment in female injection drug users – a work in progress

2011· letter· en· W2027074474 sur OpenAlexaboutno aff
Ronald C. Hershow

Notice bibliographique

RevueAddiction · 2011
Typeletter
Langueen
DomaineMedicine
ThématiqueHIV, Drug Use, Sexual Risk
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésMedicinePopulationTransmission (telecommunications)PregnancyHuman immunodeficiency virus (HIV)Environmental healthFamily medicineDemographySociology

Résumé

récupéré en direct d'OpenAlex

In this issue of Addiction, Thorne et al. [1], demonstrate convincingly that pregnant HIV-infected injection drug users (IDUs) who underwent childbirth in Ukraine from 2000–2010 had more advanced HIV clinical status, less access to mother-to-child prevention (PMTCT) services, more adverse pregnancy outcomes, and a higher HIV vertical transmission rate than HIV-infected non-IDU women. More than three decades since the first description of an HIV outbreak among IDUs in New York City [2], these data reinforce the higher burden of HIV in this marginalized, impoverished and stigmatized population. This study's findings also offer an opportunity to reflect on the particular vulnerabilities and barriers to proven HIV prevention and treatment services confronting female IDUs. A previous study showed that the slow uptake of highly active antiretroviral therapy (HAART) in Ukraine's PMTCT programs contrasted with Western Europe where MTCT had nearly been eliminated [3]. Women in the Ukraine were also 83% less likely to receive an HIV diagnosis before pregnancy than Western European women [3]. As such, the data presented by Thorne et al. are particularly pertinent to resource-limited areas where IDU is the main epidemic driver: eastern, central and Southeast Asia and Eastern Europe. Their data show that PMTCT programs must be added to a list of HIV services with unequal access for IDUs—a list that includes general antiretroviral (ARVs) access. Indeed, in the five countries (including Ukraine) identified by Wolfe et al. [4] as IDU-driven mega-epidemics, IDUs represent 67% of HIV/AIDS cases, but only 25% of persons receiving ARVs [5]. Poor access to ARVs also occurs in resource-rich countries like the United States, partly attributable to health insurance disparities [6]. However, even in Canada, where all persons who clinically qualify have free access to ARVs, ARV utilization by female IDUs is suboptimal [7, 8]. As Thorne et al. indicate, one of the best ways to stop HIV vertical transmission is to prevent HIV infection in the mother. They and others [5, 9] have pointed to the current deficient availability of proven IDU HIV prevention strategies in the Ukraine and other areas of the world. Beyrer et al. [5] estimate that a 60% reduction in the unmet need for opioid substitution therapy, syringe exchange programs, and ARV therapy could reduce HIV transmission in Odessa by 41% between 2010–2015. These programs are urgently needed, but as this study demonstrates, the availability of free, state-run prevention programs does not always ensure equal access to IDUs. Women, in particular, may encounter individual, structural, and environmental level barriers that remain largely undefined. In fact, gender-specific research in IDU populations is sparse. A few studies have demonstrated that female IDUs are at elevated risk for HIV infection compared to men [10–12]. Several explanations have been proposed for these gender disparities, but further study is urgently needed to identify issues of particular importance in different cultural contexts. Studies in Canada suggest that women, compared to men, may be more engaged in street-survival activities that interfere with their access to HIV services [7]. It has also been suggested that women are more likely to experience serious depression [13], a potential mediator of risky behaviors and poor adherence to prevention and treatment programs. Several studies show that women's drug using networks are more frequently composed of friends and sex partners [14]. This places a woman at dual risk of HIV infection through risky injection and sexual practices. Furthermore, men frequently control access to drugs [15, 16] and as a result, transactional sex may become an important means of obtaining them. Unstable housing, economic insecurity, and fear of drug withdrawal symptoms may also increase dependence on men and compromise a woman's ability to negotiate safer sex and injection practices. This dependence may expose women to intimate partner violence, a key factor that further undermines a woman's ability to control injection and sexual risk [17]. Lastly, both IDU and female sex work increase a woman's risk of incarceration. Studies from Thailand and Iran reveal that IDUs who use drugs while incarcerated are at greatly elevated risk of HIV acquisition [18, 19]. Thorne et al. report some heartening secular trends in the Ukraine, including a significant increase in the proportion of IDUs aware of their HIV status at conception and the decline in MTCT rates among pregnant IDUs (17.6% in 2000–2001 to 3.8% in 2008–2009). However, for too many, PMTCT remains what the poet Langston Hughes called a ‘dream deferred’. Further study is imperative to identify the factors and issues that prevent female IDUs from utilizing prenatal care, PMTCT, and other HIV preventive and treatment services. Political will and financial commitment is needed to initiate proven harm reduction and HAART-driven PMTCT programs informed and customized by careful study of the particular challenges that affect female IDUs globally. None.

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 distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,000
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesMéta-épidémiologie (sens strict)
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: Sans objet
GenreSignal candidat: Commentaire · Signal consensuel: Commentaire
Score de désaccord entre enseignants0,238
Score d'incertitude au seuil1,000

Scores Codex et Gemma par catégorie

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

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 Opus0,034
Tête enseignante GPT0,314
Écart entre enseignants0,281 · 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 tête enseignante, pas un consensus.

Devis d'étudeSans objet
Domainenon disponible
GenreCommentaire

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
Publié2011
Routes d'admission1
Résumé présentoui

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