Western blot score can estimate HIV-DNA size and timing of ART initiation in long-term virally suppressed children. This rapid, inexpensive, and easily reproducible tool can provide useful information to identify potential candidates for HIV remission studies.

funded by the PENTA-ID Foundation (http://penta-id.org/) through an independent grant by ViiV Healthcare U.K. The Laboratory Sciences Core of the Miami Center for AIDS Research (P30AI073961) provided technical support.The sequences presented in this article have been submitted to the Gene Expression Omnibus and Sequence Read Archive (https://www.ncbi.nlm.nih.gov/geo/) under accession number GSE138804.

Logistic regression (LR) is the most common prediction model in medicine. In recent years, supervised machine learning (ML) methods have gained popularity. However, there are many concerns about ML utility for small sample sizes. In this study, we aim to compare the performance of 7 algorithms in the prediction of 1-year mortality and clinical progression to AIDS in a small cohort of infants living with HIV from South Africa and Mozambique. The data set (n = 100) was randomly split into 70% training and 30% validation set. Seven algorithms (LR, Random Forest (RF), Support Vector Machine (SVM), K-Nearest Neighbor (KNN), Naïve Bayes (NB), Artificial Neural Network (ANN), and Elastic Net) were compared. The variables included as predictors were the same across the models including sociodemographic, virologic, immunologic, and maternal status features. For each of the models, a parameter tuning was performed to select the best-performing hyperparameters using 5 times repeated 10-fold cross-validation. A confusion-matrix was built to assess their accuracy, sensitivity, and specificity. RF ranked as the best algorithm in terms of accuracy (82,8%), sensitivity (78%), and AUC (0,73). Regarding specificity and sensitivity, RF showed better performance than the other algorithms in the external validation and the highest AUC. LR showed lower performance compared with RF, SVM, or KNN. The outcome of children living with perinatally acquired HIV can be predicted with considerable accuracy using ML algorithms. Better models would benefit less specialized staff in limited resources countries to improve prompt referral in case of high-risk clinical progression.

Introduction Complete follow-up of human immunodeficiency virus (HIV)-exposed infants (HEI) is crucial for a successful prevention of mother-to-child HIV transmission. This study analyzed the HEI follow-up and factors associated with loss to follow-up (LTFU) in southern Mozambique. Methods This retrospective cohort study used the data of HEI enrolled between June 2017 and June 2018, followed-up for 18 months. The outcomes were the proportion of infants with completed follow-up and a definitive diagnosis, and the presence of clinical events. Kaplan–Meier survival analysis was used to calculate the cumulative probability of LTFU and of clinical events. Factors associated with LTFU and clinical events were analyzed using Cox regression to calculate the hazard ratio (HR) and adjusted HR (AHR), with a 95% confidence interval (CI) and a significance cutoff of p <0.05. Results 1413 infants were enrolled (49% males) at a median age of 32 days (IQR 31–41); the median follow-up time was 12 months (IQR 8.2–14.2); 1129 (80%) completed follow-up and had a definitive diagnosis, 58 (4%) were HIV-positive, 225 (16%) were LTFU; 266 (19%) presented a clinical event. Factors associated with LTFU were: age >2 months at entry (AHR, 1.58; 95% CI, 1.12–2.23), non-exclusive breastfeeding (AHR, 1.44; 95% CI, 1.01–2.06), poor cotrimoxazole adherence (AHR, 3.42; 95% CI, 1.59–7.35), and clinical events (AHR, 0.51; 95% CI, 0.34–0.77). Factors associated with clinical events were: malnutrition (AHR, 10.06; 95% CI, 5.92–17.09), non-exclusive breastfeeding (AHR, 1.98; 95% CI, 1.34–2.93), no nevirapine prophylaxis (AHR, 1.67; 95% CI, 1.18–2.36), and poor cotrimoxazole adherence (AHR, 2.62; 95% CI, 1.10–6.22). Conclusion The high rate of HEI LTFU, associated with delayed linkage to postnatal care, poor prophylaxis adherence, non-exclusive breastfeeding, indicates the need to design a differentiated service delivery model that is tailored to the mothers’ and infants’ specific needs.

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