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Record 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 on 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

Bibliographic record

VenueEClinicalMedicine · 2022
Typearticle
Languageen
FieldMedicine
TopicHIV/AIDS Research and Interventions
Canadian institutionsnot available
FundersMedical Research CouncilSouth African Medical Research CouncilProvidence Health CareEuropean CommissionNewton FundNational Department of HealthUnited States Agency for International Development
KeywordsMedicineTuberculosisRandomized controlled trialFamily medicinePopulationCluster randomised controlled trialHealth careHuman immunodeficiency virus (HIV)Emergency medicineNursingInternal medicineEnvironmental health

Abstract

fetched live from 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).

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.135
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.086
GPT teacher head0.464
Teacher spread0.378 · 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 teacher head, not a consensus.

Study designRandomized trial
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

Citations20
Published2022
Admission routes1
Has abstractyes

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