As the pandemic of coronavirus disease 2019 (COVID-19) spreads, new data emerge and understanding of the disease improves. Reports associated with children are growing but still scarce.^1-3 The epicenter of the epidemic has displaced to Europe. The first case in Spain was declared on January 31, 2020, and the first case in the Madrid region was declared on February 27, 2020.

Some clusters of children with a multisystem inflammatory syndrome (MIS-C) associated with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection have been reported. We describe the epidemiological and clinical features of children with MIS-C in Spain. MIS-C is a potentially severe condition that presents in children with recent SARS-CoV-2 infection.

Background: Future strategies aiming to achieve HIV-1 remission are likely to target individuals with small reservoir size. Setting: We retrospectively investigated factors associated with HIV-1 DNA levels in European, perinatally HIV-infected children starting antiretroviral therapy (ART) <6 months of age. Methods: Total HIV-1 DNA was measured from 51 long-term suppressed children aged 6.3 years (median) after initial viral suppression. Factors associated with log₁₀ total HIV-1 DNA were analyzed using linear regression. Results: At ART initiation, children were aged median [IQR] 2.3 [1.2–4.1] months, CD4% 37 [24–45] %, CD8% 28 [18–36] %, log₁₀ plasma viral load (VL) 5.4 [4.4–5.9] copies per milliliter. Time to viral suppression was 7.98 [4.6–19.3] months. After suppression, 13 (25%) children had suboptimal response [≥2 consecutive VL 50–400 followed by VL <50] and/or experienced periods of virological failure [≥2 consecutive VL ≥400 followed by VL <50]. Median total HIV-1 DNA was 43 [6195] copies/10⁶ PBMC. Younger age at therapy initiation was associated with lower total HIV-1 DNA (adjusted coefficient [AC] 0.12 per month older, P = 0.0091), with a month increase in age at ART start being associated with a 13% increase in HIV DNA. Similarly, a higher proportion of time spent virally suppressed (AC 0.10 per 10% higher, P = 0.0022) and the absence of viral failure/suboptimal response (AC 0.34 for those with fail/suboptimal response, P = 0.0483) were associated with lower total HIV-1 DNA. Conclusions: Early ART initiation and a higher proportion of time suppressed are linked with lower total HIV-1 DNA. Early ART start and improving adherence in perinatally HIV-1–infected children minimize the size of viral reservoir.

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.