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Enregistrement W4211009657 · doi:10.1016/j.eclinm.2022.101298

Mortality in HIV and tuberculosis patients following implementation of integrated HIV-TB treatment: Results from an open-label cluster-randomized trial

2022· article· en· W4211009657 sur OpenAlexfundno aff
Kogieleum Naidoo, Santhanalakshmi Gengiah, Nonhlanhla Yende‐Zuma, Regina Mlobeli, Jacqueline Ngozo, Nhlakanipho Memela, Nesri Padayatchi, Pierre Barker, Andrew Nunn, Salim S. Abdool Karim

Notice bibliographique

RevueEClinicalMedicine · 2022
Typearticle
Langueen
DomaineMedicine
ThématiqueHIV/AIDS Research and Interventions
Établissements canadiensnon disponible
Organismes subventionnairesMedical Research CouncilSouth African Medical Research CouncilProvidence Health CareEuropean CommissionNewton FundNational Department of HealthUnited States Agency for International Development
Mots-clésMedicineTuberculosisRandomized controlled trialFamily medicinePopulationCluster randomised controlled trialHealth careHuman immunodeficiency virus (HIV)Emergency medicineNursingInternal medicineEnvironmental health

Résumé

récupéré en direct d'OpenAlex

Background HIV-TB treatment integration reduces mortality. Operational implementation of integrated services is challenging. This study assessed the impact of quality improvement (QI) for HIV-TB integration on mortality within primary healthcare (PHC) clinics in South Africa. Methods An open-label cluster randomized controlled study was conducted between 2016 and 2018 in 40 rural clinics in South Africa. The study statistician randomized PHC nurse-supervisors 1:1 into 16 clusters (eight nurse-supervisors supporting 20 clinics per arm) to receive QI, supported HIV-TB integration intervention or standard of care (control). Nurse supervisors and clinics under their supervision, based in the study health districts were eligible for inclusion in this study. Nurse supervisors were excluded if their clinics were managed by municipal health (different resource allocation), did not offer co-located antiretroviral therapy (ART) and TB services, services were performed by a single nurse, did not receive non-governmental organisation (NGO) support, patient data was not available for > 50% of attendees. The analysis population consists of all patients newly diagnosed with (i) both TB and HIV (ii) HIV only (among patients previously treated for TB or those who never had TB before) and (iii) TB only (among patients already diagnosed with HIV or those who were never diagnosed with HIV) after QI implementation in the intervention arm, or enrolment in the control arm. Mortality rates was assessed 12 months post enrolment, using unpaired t -tests and cox-proportional hazards model. (Clinicaltrials.gov, NCT02654613, registered 01 June 2015, trial closed). Findings Overall, 21 379 participants were enrolled between December 2016 and December 2018 in intervention and control arm clinics: 1329 and 841 HIV-TB co-infected (10·2%); 10 799 and 6 611 people living with Human Immunodeficiency Virus (HIV)/ acquired immunodeficiency syndrome (AIDS) (PLWHA) only (81·4%); 1 131 and 668 patients with TB only (8·4%), respectively. Average cluster sizes were 1657 (range 170–5782) and 1015 (range 33–2027) in intervention and control arms. By 12 months, 6529 (68·7%) and 4074 (70·4%) were alive and in care, 568 (6·0%) and 321 (5·6%) had completed TB treatment, 1078 (11·3%) and 694 (12·0%) were lost to follow-up, with 245 and 156 deaths occurring in intervention and control arms, respectively. Mortality rates overall [95% confidence interval (CI)] was 4·5 (3·4–5·9) in intervention arm, and 3·8 (2·6–5·4) per 100 person-years in control arm clusters [mortality rate ratio (MRR): 1·19 (95% CI 0·79–1·80)]. Mortality rates among HIV-TB co-infected patients was 10·1 (6·7–15·3) and 9·8 (5·0–18·9) per 100 person-years, [MRR: 1·04 (95% CI 0·51–2·10)], in intervention and control arm clusters, respectively. Interpretation HIV-TB integration supported by a QI intervention did not reduce mortality in HIV-TB co-infected patients. Demonstrating mortality benefit from health systems process improvements in real-world operational settings remains challenging. Despite the study being potentially underpowered to demonstrate the effect size, integration interventions were implemented using existing facility staff and infrastructure reflecting the real-world context where most patients in similar settings access care, thereby improving generalizability and scalability of study findings. Funding Research reported in this publication was supported by South African Medical Research Council (SAMRC), and UK Government's Newton Fund through United Kingdom Medical Research Council (UKMRC).

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)0,003
score de la tête « metaresearch » (Gemma)0,003
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesCharge utile insuffisante (le modèle a refusé de juger)
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Essai randomisé · Signal consensuel: Essai randomisé
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,135
Score d'incertitude au seuil1,000

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0030,003
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0010,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0010,000

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 Opus0,086
Tête enseignante GPT0,464
Écart entre enseignants0,378 · 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'étudeEssai randomisé
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

Citations20
Publié2022
Routes d'admission1
Résumé présentoui

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