Empirical treatment against cytomegalovirus and tuberculosis in HIV-infected infants with severe pneumonia: study protocol for a multicenter, open-label randomized controlled clinical trial.

BACKGROUND: Pneumonia is the primary cause of death among HIV-infected children in Africa, with mortality rates as high as 35-40% in infants hospitalized with severe pneumonia. Bacterial pathogens and Pneumocystis jirovecii are well known causes of pneumonia-related death, but other important causes such as cytomegalovirus (CMV) and tuberculosis (TB) remain under-recognized and undertreated. The immune response elicited by CMV may be associated with the risk of developing TB and TB disease progression, and CMV may accelerate disease caused both by HIV and TB. Minimally invasive autopsies confirm that CMV and TB are unrecognized causes of death in children with HIV. CMV and TB may also co-infect the same child. The aim of this study is to compare the impact on 15-day and 1-year mortality of empirical treatment against TB and CMV plus standard of care (SoC) versus SoC in HIV-infected infants with severe pneumonia. METHODS: This is a Phase II-III, open-label randomized factorial (2 × 2) clinical trial, conducted in six African countries. The trial has four arms. Infants from 28 to 365 days of age HIV-infected and hospitalized with severe pneumonia will be randomized (1:1:1:1) to (i) SoC, (ii) valganciclovir, (iii) TB-T, and (iv) TB-T plus valganciclovir. The primary endpoint of the study is all-cause mortality, focusing on the short-term (up to 15 days) and long-term (up to 1 year) mortality. Secondary endpoints include repeat hospitalization, duration of oxygen therapy during initial admission, severe and notable adverse events, adverse reactions, CMV and TB prevalence at enrolment, TB incidence, CMV viral load reduction, and evaluation of diagnostic tests such as GeneXpert Ultra on fecal and nasopharyngeal aspirate samples and urine TB-LAM. DISCUSSION: Given the challenges in diagnosing CMV and TB in children and results from previous autopsy studies that show high rates of poly-infection in HIV-infected infants with respiratory disease, this study aims to evaluate a new approach including empirical treatment of CMV and TB for this patient population. The potential downsides of empirical treatment of these conditions include toxicity and medication interactions, which will be evaluated with pharmacokinetics sub-studies. TRIAL REGISTRATION: ClinicalTrials.gov , NCT03915366, Universal Trial Number U111-1231-4736, Pan African Clinical Trial Registry PACTR201994797961340.

Seroprevalence of anti-SARS-CoV-2 antibodies in women attending antenatal care in eastern Ethiopia

Information on the cumulative incidence of SARS-CoV-2 in East Africa is scarce. We conducted serosurveillance of anti-SARS-CoV-2 antibodies among pregnant women attending their first antenatal care visit in three health facilities in eastern Ethiopia. We collected data using questionnaire and a blood sample from 3,312 pregnant women between April 1, 2020 and March 31, 2021 at health facilities in Haramaya, Aweday and Harar. We selected 1,447 blood samples at random and assayed these for anti-SARS-CoV-2 antibodies at Hararghe Health Research laboratory using WANTAI(R) SARS-CoV-2 Rapid Test for total immunoglobulin. Temporal trends in seroprevalence were analysed with a {chi}2 test for trend and multivariable binomial regression. Among 1,447 sera tested, 83 were positive for anti-SARS-CoV-2 antibodies giving a crude seroprevalence of 5.7% (95% CI 4.6%, 7.0%). Of 160 samples tested in April-May, 2020, none was seropositive; the first seropositive sample was identified in June and seroprevalence rose steadily thereafter ({chi}2 test for trend, p=0.003) reaching a peak of 11.8% in February, 2021. In the multivariable model, seroprevalence was approximately 3% higher in first-trimester mothers compared to later presentations, and rose by 0.75% (95% CI 0.31%, 1.20%) per month of calendar time. This clinical convenience sample illustrates the dynamic of the SARS-CoV-2 epidemic in young adults in eastern Ethiopia; infection was rare before June 2020 but it spread in a linear fashion thereafter, rather than following intermittent waves, and reached 10% by the beginning of 2021. After one year of surveillance, most pregnant mothers remained susceptible.

Postdischarge Mortality Prediction in Sub-Saharan Africa

Background: Although the burden of postdischarge mortality (PDM) in low-income settings appears to be significant, no clear recommendations have been proposed in relation to follow-up care after hospitalization. We aimed to determine the burden of pediatric PDM and develop predictive models to identify children who are at risk for dying after discharge. Methods: Deaths after hospital discharge among children aged <15 years in the last 17 years were reviewed in an area under demographic and morbidity surveillance in Southern Mozambique. We determined PDM over time (up to 90 days) and derived predictive models of PDM using easily collected variables on admission. Results: Overall PDM was high (3.6%), with half of the deaths occurring in the first 30 days. One primary predictive model for all ages included young age, moderate or severe malnutrition, a history of diarrhea, clinical pneumonia symptoms, prostration, bacteremia, having a positive HIV status, the rainy season, and transfer or absconding, with an area under the curve of 0.79 (0.75-0.82) at day 90 after discharge. Alternative models for all ages including simplified clinical predictors had a similar performance. A model specific to infants <3 months old was used to identify as predictors being a neonate, having a low weight-for-age z score, having breathing difficulties, having hypothermia or fever, having oral candidiasis, and having a history of absconding or transfer to another hospital, with an area under the curve of 0.76 (0.72-0.91) at day 90 of follow-up. Conclusions: Death after discharge is an important although poorly recognized contributor to child mortality. A simple predictive algorithm based on easily recognizable variables could readily be used to identify most infants and children who are at a high risk of dying after discharge.