Attrition Rates in HIV Viral Load Monitoring and Factors Associated With Overdue Testing Among Children Within South Africa’s Antiretroviral Treatment Program: Retrospective Descriptive Analysis
Notice bibliographique
Résumé
BACKGROUND: Numerous studies in South Africa have reported low HIV viral load (VL) suppression and high attrition rates within the pediatric HIV treatment program. OBJECTIVE: Using routine laboratory data, we evaluated HIV VL monitoring, including mobility and overdue VL (OVL) testing, within 5 priority districts in South Africa. METHODS: We performed a retrospective descriptive analysis of National Health Laboratory Service (NHLS) data for children and adolescents aged 1-15 years having undergone HIV VL testing between May 1, 2019, and April 30, 2020, from 152 facilities within the City of Johannesburg, City of Tshwane, eThekwini, uMgungundlovu, and Zululand. HIV VL test-level data were deduplicated to patient-level data using the NHLS CDW (Corporate Data Warehouse) probabilistic record-linking algorithm and then further manually deduplicated. An OVL was defined as no subsequent VL determined within 18 months of the last test. Variables associated with the last VL test, including age, sex, VL findings, district type, and facility type, are described. A multivariate logistic regression analysis was performed to identify variables associated with an OVL test. RESULTS: Among 21,338 children and adolescents aged 1-15 years who had an HIV VL test, 72.70% (n=15,512) had a follow-up VL test within 18 months. Furthermore, 13.33% (n=2194) of them were followed up at a different facility, of whom 3.79% (n=624) were in a different district and 1.71% (n=281) were in a different province. Among patients with a VL of ≥1000 RNA copies/mL of plasma, the median time to subsequent testing was 6 (IQR 4-10) months. The younger the age of the patient, the greater the proportion with an OVL, ranging from a peak of 52% among 1-year-olds to a trough of 21% among 14-year-olds. On multivariate analysis, 2 consecutive HIV VL findings of ≥1000 RNA copies/mL of plasma were associated with an increased adjusted odds ratio (AOR) of having an OVL (AOR 2.07, 95% CI 1.71-2.51). Conversely, patients examined at a hospital (AOR 0.86, 95% CI 0.77-0.96), those with ≥2 previous tests (AOR 0.78, 95% CI 0.70-0.86), those examined in a rural district (AOR 0.63, 95% CI 0.54-0.73), and older age groups of 5-9 years (AOR 0.56, 95% CI 0.47-0.65) and 10-14 years (AOR 0.51, 95% CI 0.44-0.59) compared to 1-4 years were associated with a significantly decreased odds of having an OVL test. CONCLUSIONS: Considerable attrition occurs within South Africa's pediatric HIV treatment program, with over one-fourth of children having an OVL test 18 months subsequent to their previous test. In particular, younger children and those with virological failure were found to be at increased risk of having an OVL test. Improved HIV VL monitoring is essential for improving outcomes within South Africa's pediatric antiretroviral treatment program.
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 enseignantsNi 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.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,003 | 0,008 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,003 | 0,003 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 0,000 |
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.
score_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 découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».