Effect of Smoking on Longitudinal Interferon-ϒ Release Assay Results among Close Contacts of People with Pulmonary Tuberculosis.

Diagnosis of M. tuberculosis (Mtb) infection in close contacts is critical for TB control. Smoking is a risk factor for Mtb infection and TB disease but its effect on longitudinal interferon-gamma release assay (IGRA) results remains unknown. We conducted a multi-site prospective study in Brazil between 2015-2019, among close contacts of adults with culture-confirmed pulmonary TB. IGRA was performed at baseline, month 6 if negative at baseline, and month 24-30 after enrollment. IGRA results were categorized as IGRA-positive (maintained from baseline to last visit), IGRA-conversion (from negative to positive at any time), IGRA-reversion (from positive to negative at any time), and IGRA-negative (maintained from baseline to last visit). Associations between IGRA results and smoking status at baseline (current/former vs never) in contacts were evaluated using propensity score-adjusted logistic regression models. Estimated propensity score was used as a covariate in models, which regressed the outcome (IGRA-positive, IGRA-conversion, IGRA-reversion) on smoking status. Of 430 close contacts, 89 (21%) were IGRA-positive, 30 (7%) were converters, 30 (7%) were reverters and 22 were indeterminate. Smoking frequency was 26 (29%) among IGRA-positive contacts, 7 (23%) in converters, and 3 (10%) in reverters. Smoking in contacts was associated with lower odds of IGRA-reversion (adjusted odds ratio = 0.16; 95% confidence interval = [0.03-0.70]). We did not detect associations between smoking and IGRA-positive or IGRA-conversion. Our findings highlight the importance of smoking on longitudinal IGRA results. This has implications for clinical care and clinical trials in which IGRA status is monitored or used as an outcome.

Prediction Models for Adverse Drug Reactions During Tuberculosis Treatment in Brazil.

BACKGROUND: Tuberculosis (TB) treatment-related adverse drug reactions (TB-ADRs) can negatively affect adherence and treatment success rates. METHODS: We developed prediction models for TB-ADRs, considering participants with drug-susceptible pulmonary TB who initiated standard TB therapy. TB-ADRs were determined by the physician attending the participant, assessing causality to TB drugs, the affected organ system, and grade. Potential baseline predictors of TB-ADR included concomitant medication (CM) use, human immunodeficiency virus (HIV) status, glycated hemoglobin (HbA1c), age, body mass index (BMI), sex, substance use, and TB drug metabolism variables (NAT2 acetylator profiles). The models were developed through bootstrapped backward selection. Cox regression was used to evaluate TB-ADR risk. RESULTS: There were 156 TB-ADRs among 102 of the 945 (11%) participants included. Most TB-ADRs were hepatic (n = 82 [53%]), of moderate severity (grade 2; n = 121 [78%]), and occurred in NAT2 slow acetylators (n = 62 [61%]). The main prediction model included CM use, HbA1c, alcohol use, HIV seropositivity, BMI, and age, with robust performance (c-statistic = 0.79 [95% confidence interval {CI}, .74-.83) and fit (optimism-corrected slope and intercept of -0.09 and 0.94, respectively). An alternative model replacing BMI with NAT2 had similar performance. HIV seropositivity (hazard ratio [HR], 2.68 [95% CI, 1.75-4.09]) and CM use (HR, 5.26 [95% CI, 2.63-10.52]) increased TB-ADR risk. CONCLUSIONS: The models, with clinical variables and with NAT2, were highly predictive of TB-ADRs.

Three-phase generalized raking and multiple imputation estimators to address error-prone data.

Validation studies are often used to obtain more reliable information in settings with error-prone data. Validated data on a subsample of subjects can be used together with error-prone data on all subjects to improve estimation. In practice, more than one round of data validation may be required, and direct application of standard approaches for combining validation data into analyses may lead to inefficient estimators since the information available from intermediate validation steps is only partially considered or even completely ignored. In this paper, we present two novel extensions of multiple imputation and generalized raking estimators that make full use of all available data. We show through simulations that incorporating information from intermediate steps can lead to substantial gains in efficiency. This work is motivated by and illustrated in a study of contraceptive effectiveness among 83 671 women living with HIV, whose data were originally extracted from electronic medical records, of whom 4732 had their charts reviewed, and a subsequent 1210 also had a telephone interview to validate key study variables.

Tuberculosis Treatment Outcomes in Brazil: Different Predictors for Each Type of Unsuccessful Outcome.

BACKGROUND: Successful tuberculosis (TB) treatment is necessary for disease control. The World Health Organization (WHO) has a target TB treatment success rate of ≥90%. We assessed whether the different types of unfavorable TB treatment outcome had different predictors. METHODS: Using data from Regional Prospective Observational Research for Tuberculosis-Brazil, we evaluated biological and behavioral factors associated with each component of unsuccessful TB outcomes, recently updated by WHO (death, loss to follow-up [LTFU], and treatment failure). We included culture-confirmed, drug-susceptible, pulmonary TB participants receiving standard treatment in 2015-2019. Multinomial logistic regression models with inverse probability weighting were used to evaluate the distinct determinants of each unsuccessful outcome. RESULTS: Of 915 participants included, 727 (79%) were successfully treated, 118 (13%) were LTFU, 44 (5%) had treatment failure, and 26 (3%) died. LTFU was associated with current drug-use (adjusted odds ratio [aOR] = 5.3; 95% confidence interval [CI], 3.0-9.4), current tobacco use (aOR = 2.9; 95% CI, 1.7-4.9), and being a person with HIV (PWH) (aOR = 2.0; 95% CI, 1.1-3.5). Treatment failure was associated with PWH (aOR = 2.7; 95% CI, 1.2-6.2) and having diabetes (aOR = 2.2; 95% CI, 1.1-4.4). Death was associated with anemia (aOR = 5.3; 95% CI, 1.4-19.7), diabetes (aOR = 3.1; 95% CI, 1.4-6.7), and PWH (aOR = 3.9; 95% CI, 1.3-11.4). Direct observed therapy was protective for treatment failure (aOR = 0.5; 95% CI, .3-.9) and death (aOR = 0.5; 95% CI, .2-1.0). CONCLUSIONS: The treatment success rate was below the WHO target. Behavioral factors were most associated with LTFU, whereas clinical comorbidities were correlated with treatment failure and death. Because determinants of unsuccessful outcomes are distinct, different intervention strategies may be needed to improve TB outcomes.

Antibiotic prescribing practices for acute respiratory illness in children less than 24 months of age in Kenema, Sierra Leone: is it time to move beyond algorithm driven decision making?

BACKGROUND: Lower respiratory tract infections are the leading cause of mortality in young children globally. In many resource-limited settings clinicians rely on guidelines such as IMCI or ETAT + that promote empiric antibiotic utilization for management of acute respiratory illness (ARI). Numerous evaluations of both guidelines have shown an overall positive response however, several challenges have also been reported, including the potential for over-prescribing of unnecessary antibiotics. The aims of this study were to describe the antibiotic prescribing practices for children less than 24 months of age with symptoms of ARI, that were admitted to Kenema Government Hospital (KGH) in the Eastern Province of Sierra Leone, and to identify the number of children empirically prescribed antibiotics who were admitted to hospital with ARI, as well as their clinical signs, symptoms, and outcomes. METHODS: We conducted a prospective study of children < 24 months of age admitted to the KGH pediatric ward with respiratory symptoms between October 1, 2020 and May 31, 2022. Study nurses collected data on demographic information, medical and medication history, and information on clinical course while hospitalized. RESULTS: A total of 777 children were enrolled. Prior to arrival at the hospital, 224 children (28.8%) reported taking an antibiotic for this illness without improvement. Only 15 (1.9%) children received a chest radiograph to aid in diagnosis and 100% of patients were placed on antibiotics during their hospital stay. CONCLUSIONS: Despite the lives saved, reliance on clinical decision-support tools such as IMCI and ETAT + for pediatric ARI, is resulting in the likely over-prescribing of antibiotics. Greater uptake of implementation research is needed to develop strategies and tools designed to optimize antibiotic use for ARI in LMIC settings. Additionally, much greater priority needs to be given to ensuring clinicians have the basic tools for clinical diagnosis, as well as greater investments in essential laboratory and radiographic diagnostics that help LMIC clinicians move beyond the sole reliance on algorithm based clinical decision making.

Efficient odds ratio estimation under two-phase sampling using error-prone data from a multi-national HIV research cohort.

Persons living with HIV engage in routine clinical care, generating large amounts of data in observational HIV cohorts. These data are often error-prone, and directly using them in biomedical research could bias estimation and give misleading results. A cost-effective solution is the two-phase design, under which the error-prone variables are observed for all patients during Phase I, and that information is used to select patients for data auditing during Phase II. For example, the Caribbean, Central, and South America network for HIV epidemiology (CCASAnet) selected a random sample from each site for data auditing. Herein, we consider efficient odds ratio estimation with partially audited, error-prone data. We propose a semiparametric approach that uses all information from both phases and accommodates a number of error mechanisms. We allow both the outcome and covariates to be error-prone and these errors to be correlated, and selection of the Phase II sample can depend on Phase I data in an arbitrary manner. We devise a computationally efficient, numerically stable EM algorithm to obtain estimators that are consistent, asymptotically normal, and asymptotically efficient. We demonstrate the advantages of the proposed methods over existing ones through extensive simulations. Finally, we provide applications to the CCASAnet cohort.

Testing, Inequities and Vulnerability of Adolescents to Sexually Transmitted Infections.

Sexually transmitted infections (STIs) should form part of the comprehensive healthcare agenda for adolescents and young people (A&Y) and testing plays a strategic role in STI prevention. However, little attention has been paid to the social and programmatic obstacles to this practice among A&Y. The aim of this study is to describe the prevalence of testing for syphilis and HIV reported by a group of A&Y, analyzing its relationship with variables potentially indicative of inequities related to vulnerability to STIs. This was a cross-sectional survey applied to students at public high schools in three cities in the state of São Paulo, Brazil. The responses of 369 young people who reported having started sexual life were analyzed. The analysis included description of the frequencies of demographic and socioeconomic variables and their associations with testing for syphilis and HIV through the chi-square test. The concentration index (CI) was also calculated, with construction of the respective concentration curve for the associated variables. Positive associations were found between occurrence of testing and living in homes with up to three inhabitants, living in a marital situation with a regular or committed partnership, previous use of primary care services and previous use of hospitals or emergency services. The concentration curve for testing STIs showed significant contributions from the associated variables. The findings indicated that situations of inequity need to be addressed in order to reduce A&Y's vulnerability to STIs.

Pregnancies among women living with HIV using contraceptives and antiretroviral therapy in western Kenya: a retrospective, cohort study.

BACKGROUND: Preventing unintended pregnancies is paramount for women living with HIV (WLHIV). Previous studies have suggested that efavirenz-containing antiretroviral therapy (ART) reduces contraceptive effectiveness of implants, but there are uncertainties regarding the quality of the electronic medical record (EMR) data used in these prior studies. METHODS: We conducted a retrospective, cohort study of EMR data from 2011 to 2015 among WLHIV of reproductive age accessing HIV care in public facilities in western Kenya. We validated a large subsample of records with manual chart review and telephone interviews. We estimated adjusted incidence rate ratios (aIRRs) with Poisson regression accounting for the validation sampling using inverse probability weighting and generalized raking. RESULTS: A total of 85,324 women contributed a total of 170,845 women-years (w-y) of observation time; a subset of 5080 women had their charts reviewed, and 1285 underwent interviews. Among implant users, the aIRR of pregnancy for efavirenz- vs. nevirapine-containing ART was 1.9 (95% CI 1.6, 2.4) using EMR data only and 3.2 (95% CI 1.8, 5.7) when additionally using both chart review and interview validated data. Among efavirenz users, the aIRR of pregnancy for depomedroxyprogesterone acetate (DMPA) vs. implant use was 1.8 (95% CI 1.5, 2.1) in EMR only and 2.4 (95% CI 1.0, 6.1) using validated data. CONCLUSION: Pregnancy rates are higher when contraceptive implants are concomitantly used with efavirenz-containing ART, though rates were similar to leading alternative contraceptive methods such as DMPA. Our data provides policymakers, program staff, and WLHIV greater confidence in guiding their decision-making around contraceptive and ART options. Our novel, 3-phase validation sampling provides an innovative tool for using routine EMR data to improve the robustness of data quality.

Efficient semiparametric inference for two-phase studies with outcome and covariate measurement errors.

In modern observational studies using electronic health records or other routinely collected data, both the outcome and covariates of interest can be error-prone and their errors often correlated. A cost-effective solution is the two-phase design, under which the error-prone outcome and covariates are observed for all subjects during the first phase and that information is used to select a validation subsample for accurate measurements of these variables in the second phase. Previous research on two-phase measurement error problems largely focused on scenarios where there are errors in covariates only or the validation sample is a simple random sample of study subjects. Herein, we propose a semiparametric approach to general two-phase measurement error problems with a quantitative outcome, allowing for correlated errors in the outcome and covariates and arbitrary second-phase selection. We devise a computationally efficient and numerically stable expectation-maximization algorithm to maximize the nonparametric likelihood function. The resulting estimators possess desired statistical properties. We demonstrate the superiority of the proposed methods over existing approaches through extensive simulation studies, and we illustrate their use in an observational HIV study.

Neotectonics as a structural control of the boundaries of the Pantanal Matogrossense Sub-Regions.

Characterized by fluvio-alluvial sedimentation processes, the heterogeneity in the Pantanal Basin allows its division in several sub-regions, which present natural characteristics of their own. It is possible to find in the literature different proposals to subdivide the Pantanal plain, which vary in total area and number of sub-regions. Each author uses specific criteria - mainly vegetation, soil and humidity - in his delimitation, but does not consider the tectonic aspects of the basin. In this sense, we intend to analyze three Pantanal delimitations from the literature and to relate them to the neotectonic context of the Pantanal plain by comparing the boundaries proposed in the delimitations to structural lineaments present in the basin. As a result, we observe that the comparison of the Pantanal boundaries with the lineaments shows a high compatibility between them, suggesting the influence of these structures in the development of the sub-regions.

A new approach for modeling patient overall radiosensitivity and predicting multiple toxicity endpoints for breast cancer patients.

INTRODUCTION: Evaluation of patient characteristics inducing toxicity in breast radiotherapy, using simultaneous modeling of multiple endpoints. METHODS AND MATERIALS: In 269 early-stage breast cancer patients treated with whole-breast irradiation (WBI) after breast-conserving surgery, toxicity was scored, based on five dichotomized endpoints. Five logistic regression models were fitted, one for each endpoint and the effect sizes of all variables were estimated using maximum likelihood (MLE). The MLEs are improved with James-Stein estimates (JSEs). The method combines all the MLEs, obtained for the same variable but from different endpoints. Misclassification errors were computed using MLE- and JSE-based prediction models. For associations, p-values from the sum of squares of MLEs were compared with p-values from the Standardized Total Average Toxicity (STAT) Score. RESULTS: With JSEs, 19 highest ranked variables were predictive of the five different endpoints. Important variables increasing radiation-induced toxicity were chemotherapy, age, SATB2 rs2881208 SNP and nodal irradiation. Treatment position (prone position) was most protective and ranked eighth. Overall, the misclassification errors were 45% and 34% for the MLE- and JSE-based models, respectively. p-Values from the sum of squares of MLEs and p-values from STAT score led to very similar conclusions, except for the variables nodal irradiation and treatment position, for which STAT p-values suggested an association with radiosensitivity, whereas p-values from the sum of squares indicated no association. Breast volume was ranked as the most significant variable in both strategies. DISCUSSION: The James-Stein estimator was used for selecting variables that are predictive for multiple toxicity endpoints. With this estimator, 19 variables were predictive for all toxicities of which four were significantly associated with overall radiosensitivity. JSEs led to almost 25% reduction in the misclassification error rate compared to conventional MLEs. Finally, patient characteristics that are associated with radiosensitivity were identified without explicitly quantifying radiosensitivity.

Primary isolated osteoma cutis of the face.

We report a healthy, 44-year-old woman presenting with an at least a 20-year history of hardened papules in the forehead region, extending to the scalp. The biopsy and histopathologic exam confirmed a diagnosis of osteoma cutis. We review the literature review and discuss the classification of the cutaneous ossification process presented, along with the results of the surgical treatment.

Evaluating empiric antibiotic prescribing for hospitalized children in Mozambique through the introduction of a quarterly syndromic antibiogram: An implementation science protocol.

Antimicrobials are the most frequently prescribed drug in pediatrics, with an estimated 37% of infants and 61% of hospitalized children having received them. Approximately 20-50% of prescriptions have been shown to be potentially unnecessary or inappropriate. The World Health Organization (WHO) estimates that the continued increase in antimicrobial resistance by the year 2050 will lead to the death of 10 million people per year. This paper describes a protocol to be used in a future study to evaluate the implementation of a quarterly syndromic antibiogram, aimed to improve the use of antibiotics for the treatment of pediatric bacterial infections at the Maputo Central Hospital, Mozambique. This study uses implementation science methods framed by the Dynamic Adaption Process (DAP) and RE-AIM conceptual frameworks to develop a multi-phase, mixed-methods evaluation utilizing qualitative and quantitative approaches. The pediatric inpatient services at HCM consist of approximately 18 physicians and 60 nurses. Additionally, the microbiology laboratory consists of eight laboratory technicians. We anticipate analyzing approximately 9,000 medical records. Qualitative methods include in-depth interviews with clinicians, laboratory technicians, and administrators to explore current knowledge and practices around antibiotic decision making, facilitators and barriers to intervention implementation, as well as acceptability and satisfaction with the intervention roll-out. Qualitative analysis will be performed with NVivo 12 software. Quantitative methods include extracting data from existing records from the pediatric ward of Hospital Central de Maputo (HCM) guided by the RE-AIM framework to explore intervention utilization and other factors influencing its implementation. Quantitative descriptive and inferential statistical analysis will be performed using R Studio statistical software. The findings from this evaluation will be shared with hospital administrators and relevant national policymakers and may be used by the Ministry of Health in deciding to expand this approach to other hospitals. The expected results of this research include the development of standard operating guidelines for the creation, distribution, and use of a quarterly syndromic antibiogram for antibiotic decision making that is informed by local epidemiology. Findings from this study will be used to develop a larger multi-site trial in Mozambique.

Estimating optimal therapeutic drug levels of anti-tuberculosis medications based on treatment safety and effectiveness.

Background: Therapeutic drug ranges (TDR) for standard anti-tuberculosis (TB) treatment have been determined based on expected drug levels at least 2 hours after taking the dose. In this study we constructed TDR for TB drug levels based on minimizing drug toxicity and maximizing treatment effectiveness. Methods: Participants were followed prospectively in the Regional Prospective Observational Research in Tuberculosis (RePORT)-Brazil observational cohort study. We focused on participants with culture-confirmed drug-susceptible pulmonary TB who underwent standard TB therapy. TDR were estimated for each TB drug separately: isoniazid (INH), rifampin (RIF), ethambutol (EMB), and pyrazinamide (PZA). TDR were defined as drug concentrations that were both safe and effective: safety was defined as the probability of having an ADR of at most 5%, while effectiveness was defined as a probability of at least 95% of not having either TB treatment failure or recurrence. Results: There were 765 plasma samples from 448 patients; 110 (24.6%) were people with HIV, 9 (2.0%) had a grade 3 or higher ADR, and 15 (3.3%) had treatment failure/recurrence. Higher drug concentrations of INH, RIF and EMB were associated with increased odds of having ADR. High concentrations of INH suggested protection against treatment failure/recurrence. Estimated therapeutic drug range for INH (2.3-8.2 µg/ml) and for RIF (0.5-7.5 µg/ml) differed from the currently recommended drug ranges (3-5 µg/ml and 8-24 µg/ml, respectively). Estimates for PZA and EMB were similar to the currently recommended values. Conclusions: Our estimated upper end TDR were higher for INH and lower for RIF compared to currently recommended ranges.

Genetic ancestry proportion influences risk of adverse events from tuberculosis treatment in Brazil.

Tuberculosis (TB) treatment is highly effective, but response to therapy can vary by geography, race, and ethnicity. We assessed for differences in TB treatment response in a representative and heterogeneous Brazilian population. We estimated genetic ancestry proportion according to major ancestry groups (African, European, and Amerindian ancestry) in the Regional Prospective Observational Research in Tuberculosis (RePORT)-Brazil cohort. RePORT-Brazil is an observational prospective cohort study of individuals with newly-diagnosed, culture-confirmed, pulmonary TB. TB treatment outcomes that were attributed to TB treatment included Grade 2 or higher adverse drug reaction (ADR), Grade 3 or higher ADR, hepatic ADR, and failure/recurrence. Ancestry proportion was the main predictor in logistic regression for each outcome, with adjustments for candidate confounders. There were 941 pulmonary TB patients included in this study. We observed a decreased risk of Grade 2+ ADR when African ancestry proportion increased by 10% (Odds Ratio [OR] 0.41, 95% Confidence Interval [CI] 0.20 -0.85) and an increased risk for Grade 2+ ADR with increasing European ancestry (OR 2.84, 95% CI 1.47 - 5.48). We then performed the same analysis adding HIV status as an interaction term. The decreased risk for Grade 2+ ADR seen for African ancestry proportion did not hold for persons living with HIV; we observed increased risk for Grade 2+ ADR with increasing African ancestry proportion. There were no associations with Amerindian ancestry or for other treatment outcomes. In this Brazilian TB cohort, toxicity risk was associated with African and European ancestry, divergent, and affected by HIV. #RePORT-Brazil Consortium members include: Aline Benjamin and Flavia M. Sant'Anna Instituto Nacional de Infectologia Evandro Chagas, Fiocruz, Rio de Janeiro, Brazil Jamile Garcia de Oliveira and João Marine Clínica de Saúde Rinaldo Delmare, Rio de Janeiro, Brazil Adriana Rezende and Anna Cristina Carvalho Secretaria de Saúde de Duque de Caxias, Rio de Janeiro, Brazil Michael Rocha and Betânia Nogueira Instituto Brasileiro para Investigação da Tuberculose, Fundação José Silveira, Salvador, Brazil Alexandra Brito and Renata Spener Fundação Medicina Tropical Dr. Heitor Vieira Dourado, Manaus, Brazil Megan Turner Vanderbilt University Medical Center, Nashville, USA.

Time spent at health facility is a key driver of patient satisfaction, but did not influence retention to HIV care: A serial cross-sectional study in Mozambique.

INTRODUCTION: Patient satisfaction with clinical services can have an effect on retention in HIV care and adherence to antiretroviral therapy. This study assessed patient satisfaction and its association with retention and viral suppression in Zambézia Province, Mozambique. METHODS: Monthly exit interviews with persons living with HIV were completed from August 2017-January 2019 in 20 health facilities; clinical data were extracted from medical records. Regression analyses assessed the effect of satisfaction scores on retention and viral suppression, adjusting for age, sex, education, civil status, time on treatment, and site. Satisfaction scores were correlated with time spent at health facilities using generalized linear regression models. RESULTS: Data from 4388 patients were analyzed. Overall median satisfaction score was 75% (IQR 53%-84%); median time spent at facilities (from arrival until completion of clinical services) was 2h54min (IQR 1h48min-4h). Overall satisfaction score was not associated with higher odds of retention or viral suppression, but association was seen between satisfaction regarding attention given to patient and respect and higher odds of viral suppression. Patient satisfaction was negatively associated with time spent in facility (Spearman's correlation -0.63). Increased time spent at facility (from 1 to 3 hours) was not associated with lower retention in care (OR 0.72 [95%CI:0.52-1.01] and 0.83 [95%CI: 0.63-1.09] at 6- and 12-months, respectively), nor with a lower odds of viral suppression (OR 0.96 [95%CI: 0.71-1.32]). CONCLUSIONS: Strategies to reduce patient wait times at the health facility warrant continued prioritization. Differentiated models of care have helped considerably, but novel approaches are still needed to further decongest crowded health facilities. In addition, a good client-provider communication and positive attitude can improve patient satisfaction with health services, with an overall improved retention.

Impact of Xpert MTB/RIF implementation in tuberculosis case detection and control in Brazil: a nationwide intervention time-series analysis (2011-2022).

Background: Since 2014, Brazil has gradually implemented the Xpert MTB/RIF (Xpert) test to enhance early tuberculosis (TB) and drug-resistant (DR-TB) detection and control, yet its nationwide impact remains underexplored. Our study conducts an intervention time-series analysis (ITSA) to evaluate how the Xpert's implementation has improved TB and DR-TB detection nationwide. Methods: 1,061,776 cases from Brazil's National TB Registry (2011-2022) were reviewed and ITSA (2011-2019) was used to gauge the impact of the Xpert's adoption on TB and DR-TB notification. Granger Causality and dynamic regression modelling determined if incorporating Xpert testing as an external regressor enhanced forecasting accuracy for Brazil's future TB trends. Findings: Xpert implementation resulted in a 9.7% increase in TB notification and substantial improvements in DR-TB (63.6%) and drug-susceptible TB (92.1%) detection compared to expected notifications if it had not been implemented. Xpert testing counts also presented a time-dependent relationship with DR-TB detection post-implementation, and improved predictions in forecasting models, which depicted a potential increase in TB and DR-TB detection in the next six years. Interpretation: This study underscores the critical role of Xpert's adoption in boosting TB and DR-TB detection in Brazil, reinforcing the case for its widespread use in disease control. Improvements in prediction accuracy resulting from integrating Xpert data are crucial for allocating resources and reducing the incidence of TB. By acknowledging Xpert's role in both disease control and improving predictions, we advocate for its expanded use and further research into advanced molecular diagnostics for effective TB and DR-TB control. Funding: FIOCRUZ.

Assessment of an in-house IgG ELISA targeting SARS-CoV-2 RBD: Applications in infected and vaccinated individuals.

The study evoluated an in-house Spike Receptor Binding Domain Enzyme-Linked Immunosorbent Assay (RBD-IgG-ELISA) for detecting SARS-CoV-2 IgG antibodies in infected and vaccinated individuals. The assay demonstrated a sensitivity of 91%, specificity of 99.25%, and accuracy of 95.13%. Precision and reproducibility were highly consistent. The RBD-IgG-ELISA was able to detect 96.25% of Polymerase chain reaction (PCR) confirmed cases for SARS-CoV-2 infection, demonstrating positive and negative predictive values of 99,18% and 91,69%, respectively. In an epidemiological survey, ELISA, lateral flow immunochromatographic assay (LFIA), and electrochemiluminescence immunoassay (ECLIA) exhibited diagnostic sensitivities of 68.29%, 63.41%, and 70.73%, respectively, along with specificities of 82.93%, 80.49%, and 80.49%, respectively. Agreement between RBD-IgG-ELISA/PCR was moderate (k index 0.512). However, good agreement between different assays (RBD-IgG-ELISA/LFIA k index 0.875, RBD-IgG-ELISA/ECLIA k index 0.901). Test performance on individuals' samples were inferior due to seroconversion time and chronicity. The IgG-RBD-ELISA assay demonstrated its effectiveness in monitoring antibody levels among healthcare professionals, revealing significant differences both before and after the administration of the third vaccine dose, with heightened protection levels observed following the third dose in five Coronavirus disease (COVID-19) vaccine regimens. In conclusion, the RBD-IgG-ELISA exhibits high reproducibility, specificity, and sensitivity, making it a suitable assay validated for serosurveillance and for obtaining information about COVID-19 infections or vaccinations.

Multidrug-Resistant Bacterial Infections Among Very Low Birthweight Infants With Late-Onset Sepsis in Johannesburg, South Africa.

Background: An estimated 2.4 million babies died within the first 28 days of life in 2020. The third leading cause of neonatal death continues to be neonatal sepsis. Sepsis-causing bacterial pathogens vary temporally and geographically and, with a rise in multidrug-resistant organisms (MDROs), pose a threat to the neonatal population. Methods: This was a single-center, retrospective study of very low birth weight (VLBW) infants with late-onset sepsis (LOS) admitted to a neonatal unit in South Africa. We aimed to calculate the prevalence of multidrug-resistant (MDR) infections in this population. The data collected included demographic and clinical characteristics, length of hospital stay, risk factors for MDRO and mortality, and microbiology results. Logistic regression was used to assess the association between prespecified risk factors with MDR infections and mortality. Results: Of 2570 VLBW infants admitted, 34% had LOS, of which 33% was caused by MDROs. Infection with Acinetobacter spp., Pseudomonas spp., extended-spectrum beta-lactamase Klebsiella spp., or Escherichia coli was associated with the highest mortality in the LOS cohort. Infants with congenital infections (adjusted odds ratio [aOR], 5.13; 95% CI, 1.19-22.02; P = .028) or a history of necrotizing enterocolitis (aOR, 2.17; 95% CI, 1.05-4.49; P = .037) were at significantly higher risk for MDR infections. Conclusions: More than one-third of LOS cases in VLBW infants were caused by MDROs in this study. MDR infections cause substantial neonatal mortality. Antimicrobial stewardship programs, infection control protocols, and ongoing surveillance are needed to prevent further emergence and spread of MDR infections worldwide.

Favorable Impact of Community Adherence Support Groups on Retention in Care and Viral Suppression Rates Among Persons with HIV Receiving Antiretroviral Therapy in Mozambique.

The community adherence support group (CASG) was one of the first differentiated service delivery (DSD) models introduced in Mozambique. This study assessed the impact of this model on retention in care, loss to follow-up (LTFU), and viral suppression among antiretroviral therapy (ART)-treated adults in Mozambique. A retrospective cohort study included CASG-eligible adults enrolled between April 2012 and October 2017 at 123 health facilities in Zambézia Province. Propensity score matching (1:1 ratio) was used to allocate CASG members and those who never enrolled in a CASG. Logistic regressions were performed to estimate the impact of CASG membership on 6- and 12-month retention and viral load (VL) suppression. Cox proportional regression was used to model differences in LTFU. Data from 26,858 patients were included. The median age at CASG eligibility was 32 years and 75% were female, with 84% residing in rural areas. A total of 93% and 90% of CASG members were retained in care at 6 and 12 months, respectively, while 77% and 66% non-CASG members were retained during the same periods. The odds of being retained in care at 6 and 12 months were significantly higher among patients receiving ART through CASG support (adjusted odds ratio [aOR] = 4.19 [95% confidence interval; CI: 3.79-4.63], p < .001, and aOR = 4.43 [95% CI: 4.01-4.90], p < .001, respectively). Among 7,674 patients with available VL measurements, the odds of being virally suppressed were higher among CASG members (aOR = 1.14 [95% CI: 1.02-1.28], p < .001). Non-CASG members had a significantly higher likelihood of being LTFU (adjusted hazard ratio = 3.45 [95% CI: 3.20-3.73], p < .001). While Mozambique rapidly scales up multi-month drug dispensation as the preferred DSD model, this study emphasizes the continued importance of CASG as an efficacious DSD alternative, especially among patients residing in rural areas, where CASG acceptability is higher.