Reevaluating Cumulative HIV-1 Viral Load as a Prognostic Predictor: Predicting Opportunistic Infection Incidence and Mortality in a Ugandan Cohort.

Recent studies have evaluated cumulative human immunodeficiency virus type 1 (HIV-1) viral load (cVL) for predicting disease outcomes, with discrepant results. We reviewed the disparate methodological approaches taken and evaluated the prognostic utility of cVL in a resource-limited setting. Using data on the Infectious Diseases Institute (Makerere University, Kampala, Uganda) cohort, who initiated antiretroviral therapy in 2004-2005 and were followed up for 9 years, we calculated patients' time-updated cVL by summing the area under their viral load curves on either a linear scale (cVL1) or a logarithmic scale (cVL2). Using Cox proportional hazards models, we evaluated both metrics as predictors of incident opportunistic infections and mortality. Among 489 patients analyzed, neither cVL measure was a statistically significant predictor of opportunistic infection risk. In contrast, cVL2 (but not cVL1) was a statistically significant predictor of mortality, with each log10 increase corresponding to a 1.63-fold (95% confidence interval: 1.02, 2.60) elevation in mortality risk when cVL2 was accumulated from baseline. However, whether cVL is predictive or not hinges on difficult choices surrounding the cVL metric and statistical model employed. Previous studies may have suffered from confounding bias due to their focus on cVL1, which strongly correlates with other variables. Further methodological development is needed to illuminate whether the inconsistent predictive utility of cVL arises from causal relationships or from statistical artifacts.

Steady-state pharmacokinetics of rilpivirine under different meal conditions in HIV-1-infected Ugandan adults.

OBJECTIVES: To investigate the effect of food on the steady-state pharmacokinetics of rilpivirine when administered as a fixed-dose combination tablet containing tenofovir disoproxil fumarate, emtricitabine plus rilpivirine (TDF/FTC/RPV) in HIV-1-infected Ugandan patients. METHODS: This was an open-label, three-period, longitudinal pharmacokinetic study with patients serving as their own controls. Fifteen consenting and virologically suppressed HIV-1-infected adults were switched from an efavirenz-based regimen to TDF/FTC/RPV for 56 days. Enrolled patients underwent 24 h blood sampling with TDF/FTC/RPV dosing in the fasted state (day 42), with a low-fat meal (11 g of fat/353 kcal, day 49) and with a moderate-fat meal (19 g of fat/589 kcal, day 56; reference). A viral load assessment was performed on day 56. RESULTS: Rilpivirine AUC0-24 was significantly decreased by 16% (geometric mean ratio, 90% CI: 0.84, 0.73-0.96) during administration in the fasted state when compared with AUC0-24 during administration with a moderate-fat meal. Similarly, rilpivirine C24 was significantly decreased by 21% (0.79, 0.65-0.97) in the fasted state compared with a moderate-fat meal. Pharmacokinetic parameters were unchanged during administration with a low-fat meal, except for C24, which was significantly increased by 15% (1.15, 1.01-1.31) when compared with the moderate-fat meal. Rilpivirine Cmax was similar under the three meal conditions. Virological suppression was unchanged at the end of the study. CONCLUSIONS: A food effect was observed for steady-state pharmacokinetic parameters of rilpivirine (AUC0-24 and C24) when TDF/FTC/RPV was administered in the fasted state compared with the moderate-fat meal. The TDF/FTC/RPV formulation can be administered with either a low-fat or moderate-fat meal.

Potential for high dynamic range Sedia Limiting Antigen antibody assay to support viral load monitoring during antiretroviral therapy.

INTRODUCTION: Viral Load (VL) monitoring is a crucial component of patient care during antiretroviral therapy (ART) but is not routinely available in many resource-constrained settings, where millions of patients will require care for decades to come. We hypothesise a serologic 'recent infection' test (Sedia LAg assay) which has a high dynamic range for detecting antigen-driven antibody response can provide informative proxies for VL trajectories. METHODS: A retrospective study where we analysed data linked via specimens in a well-described repository for recent infection test benchmarking (CEPHIA collaboration). Patient panels were comprised of 1) observations straddling ART start; 2) observations from a period of stable viral suppression; 3) observations straddling rebound after a period of viral suppression. We analysed an individual's Sedia LAg ELISA normalised optical density (ODn) trends within these categories. Using groups 2) and 3) we evaluated the specificity and sensitivity of a proposed proxy for "the latest observation is at a time of VL rebound"; proxy was defined as follows: we estimated patient-specific mean-previous-ODn for all observations with at least two preceding virally suppressed observations. We considered various thresholds to define both "VL suppression" and "ODn uptick". RESULTS: In regression analysis by category: 1) ODn gradients are statistically significantly negative just after ART-start (p = 0.010); 2) During periods of stable viral suppression, ODn tended to decline, but not statistically significantly, for a range of clinically meaningful "VL suppression" thresholds; 3) comparing ODn values just before, versus at, "VL rebound", ODn changes were statistically significantly increasing at rebound (p = 0.001). In the analysis comparing groups 2) and 3), at a Z score threshold of 0.8, the proposed proxy for a first viral rebound had an observed specificity and sensitivity both close to 90%. CONCLUSION: The high dynamic range of serological tests previously investigated for defining 'recent infection' has potential, as demonstrated using the Sedia LAg ELISA, to provide meaningful information about the success of ART, during treatment initiation, at times of stable suppression, and to flag possible viral rebound. It should be investigated how this can be combined with patient management workflows and (clinical and) other data, to provide efficiencies in long-term monitoring viral control in resource-limited settings.

Elicitation of domain knowledge for a machine learning model for paediatric critical illness in South Africa.

Objectives: Delays in identification, resuscitation and referral have been identified as a preventable cause of avoidable severity of illness and mortality in South African children. To address this problem, a machine learning model to predict a compound outcome of death prior to discharge from hospital and/or admission to the PICU was developed. A key aspect of developing machine learning models is the integration of human knowledge in their development. The objective of this study is to describe how this domain knowledge was elicited, including the use of a documented literature search and Delphi procedure. Design: A prospective mixed methodology development study was conducted that included qualitative aspects in the elicitation of domain knowledge, together with descriptive and analytical quantitative and machine learning methodologies. Setting: A single centre tertiary hospital providing acute paediatric services. Participants: Three paediatric intensivists, six specialist paediatricians and three specialist anaesthesiologists. Interventions: None. Measurements and main results: The literature search identified 154 full-text articles reporting risk factors for mortality in hospitalised children. These factors were most commonly features of specific organ dysfunction. 89 of these publications studied children in lower- and middle-income countries. The Delphi procedure included 12 expert participants and was conducted over 3 rounds. Respondents identified a need to achieve a compromise between model performance, comprehensiveness and veracity and practicality of use. Participants achieved consensus on a range of clinical features associated with severe illness in children. No special investigations were considered for inclusion in the model except point-of-care capillary blood glucose testing. The results were integrated by the researcher and a final list of features was compiled. Conclusion: The elicitation of domain knowledge is important in effective machine learning applications. The documentation of this process enhances rigour in such models and should be reported in publications. A documented literature search, Delphi procedure and the integration of the domain knowledge of the researchers contributed to problem specification and selection of features prior to feature engineering, pre-processing and model development.

Quantitative interpretation of Sedia LAg Assay test results after HIV diagnosis.

BACKGROUND: Testing for 'recent HIV infection' is common in surveillance, where only population-level estimates (of incidence) are reported. Typically, 'recent infection' is a category, obtained by applying a threshold on an underlying continuous biomarker from some laboratory assay(s). Interpreting the biomarker values obtained for individual subjects, as estimates of the date of infection, has obvious potential applications in the context of studies of early infection, and has also for some years attracted significant interest as an extra component of post-test counselling and treatment initiation. The applicable analyses have typically run aground on the complexity of the full biomarker growth model, which is in principle a non-linear mixed-effects model of unknown structure, the fitting of which seems infeasible from realistically obtainable data. METHODS: It is known that to estimate Mean Duration of Recent Infection (MDRI) at a given value of the recent/non-recent -infection discrimination threshold, one may compress the full biomarker growth model into a relation capturing the probability of a recent test result as a function of time t since infection, given a value of assay threshold h which defines the recent/non-recent discrimination. We demonstrate that the derivative (gradient), with respect to h. of the probability of recent infection, seen as a function of both t and h, is identical to the formal likelihood relevant to Bayesian inference of the time since seroconversion, for a subject yielding an assay result h, at or close to the date of their first positive HIV test. This observation bypasses the need for fitting a complex detailed biomarker growth model. Using publicly available data from the CEPHIA collaboration, we calibrated this likelihood function for the Sedia Lag assay, and performed Bayesian inference on hypothetical infection data. RESULTS: We demonstrate the generation of posteriors for infection date, for patients with various delays between their last negative and first positive HIV test, and a range of LAg assay results (ODn) hypothetically obtained on the date of the first positive result. CONCLUSION: Depending on the last-negative / first-positive interval, there is a range of ODn values that yields posteriors significantly different from the uniform prior one would be left with based merely on interval censoring. Hence, a LAg ODn obtained on the date of, or soon after, diagnosis contains potentially significant information about infection dating. It seems worth analysing other assays with meaningful dynamic range, especially tests already routinely used in primary HIV diagnosis (for example chemiluminescent assays and reader/cartridge lateral flow tests which admit objective variable line intensity readings) which have a sufficient dynamic range that corresponds to a clinically meaningful range of times-since-infection that are worth distinguishing from each other.

An Artificial Neural Network Model for Pediatric Mortality Prediction in Two Tertiary Pediatric Intensive Care Units in South Africa. A Development Study.

Objectives: The performance of mortality prediction models remain a challenge in lower- and middle-income countries. We developed an artificial neural network (ANN) model for the prediction of mortality in two tertiary pediatric intensive care units (PICUs) in South Africa using free to download and use software and commercially available computers. These models were compared to a logistic regression model and a recalibrated version of the Pediatric Index of Mortality 3. Design: This study used data from a retrospective cohort study to develop an artificial neural model and logistic regression model for mortality prediction. The outcome evaluated was death in PICU. Setting: Two tertiary PICUs in South Africa. Patients: 2,089 patients up to the age of 13 completed years were included in the study. Interventions: None. Measurements and Main Results: The AUROC was higher for the ANN (0.89) than for the logistic regression model (LR) (0.87) and the recalibrated PIM3 model (0.86). The precision recall curve however favors the ANN over logistic regression and recalibrated PIM3 (AUPRC = 0.6 vs. 0.53 and 0.58, respectively. The slope of the calibration curve was 1.12 for the ANN model (intercept 0.01), 1.09 for the logistic regression model (intercept 0.05) and 1.02 (intercept 0.01) for the recalibrated version of PIM3. The calibration curve was however closer to the diagonal for the ANN model. Conclusions: Artificial neural network models are a feasible method for mortality prediction in lower- and middle-income countries but significant challenges exist. There is a need to conduct research directed toward the acquisition of large, complex data sets, the integration of documented clinical care into clinical research and the promotion of the development of electronic health record systems in lower and middle income settings.

Development of artificial neural network models for paediatric critical illness in South Africa.

Objectives: Failures in identification, resuscitation and appropriate referral have been identified as significant contributors to avoidable severity of illness and mortality in South African children. In this study, artificial neural network models were developed to predict a composite outcome of death before discharge from hospital or admission to the PICU. These models were compared to logistic regression and XGBoost models developed on the same data in cross-validation. Design: Prospective, analytical cohort study. Setting: A single centre tertiary hospital in South Africa providing acute paediatric services. Patients: Children, under the age of 13 years presenting to the Paediatric Referral Area for acute consultations. Outcomes: Predictive models for a composite outcome of death before discharge from hospital or admission to the PICU. Interventions: None. Measurements and main results: 765 patients were included in the data set with 116 instances (15.2%) of the study outcome. Models were developed on three sets of features. Two derived from sequential floating feature selection (one inclusive, one parsimonious) and one from the Akaike information criterion to yield 9 models. All developed models demonstrated good discrimination on cross-validation with mean ROC AUCs greater than 0.8 and mean PRC AUCs greater than 0.53. ANN1, developed on the inclusive feature-et demonstrated the best discrimination with a ROC AUC of 0.84 and a PRC AUC of 0.64 Model calibration was variable, with most models demonstrating weak calibration. Decision curve analysis demonstrated that all models were superior to baseline strategies, with ANN1 demonstrating the highest net benefit. Conclusions: All models demonstrated satisfactory performance, with the best performing model in cross-validation being an ANN model. Given the good performance of less complex models, however, these models should also be considered, given their advantage in ease of implementation in practice. An internal validation study is now being conducted to further assess performance with a view to external validation.

A systematic review and meta-analysis of the sensitivity of antibody tests for the laboratory confirmation of COVID-19.

Aim: The aim of this study was to investigate the utility of serological tests for the diagnosis of COVID-19 during the first week of symptom onset in patients confirmed with the real-time RT-PCR. Materials & methods: A systematic review and meta-analysis of 58 publications were performed using data obtained from Academic Search Ultimate, Africa-wide, Scopus, Web of Science and MEDLINE. Results: We found that the highest pooled sensitivities were obtained with ELISA IgM-IgG and chemiluminescence immunoassay IgM tests. Conclusion: Serological tests have low sensitivity within the first week of symptom onset and cannot replace nucleic acid amplification tests. However, serological assays can be used to support nucleic acid amplification tests.

Comorbidities in SARS-CoV-2 Patients: a Systematic Review and Meta-Analysis.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has rapidly spread across the globe at unprecedented speed and is showing no signs of slowing down. The outbreak of coronavirus disease 2019 (COVID-19) has led to significant health burden in infected patients especially in those with underlying comorbidities. The aim of this study was to evaluate the correlation between comorbidities and their role in the exacerbation of disease in COVID-19 patients leading to fatal outcomes. A systematic review was conducted using data from MEDLINE, Scopus, Web of Science, and EMBASE databases published from 1 December 2019 to 15 September 2020. Fifty-three articles were included in the systematic review. Of those 53 articles, 8 articles were eligible for meta-analysis. Hypertension, obesity, and diabetes mellitus were identified to be the most prevalent comorbidities in COVID-19 patients. Our meta-analysis showed that cancer, chronic kidney diseases, diabetes mellitus, and hypertension were independently associated with mortality in COVID-19 patients. Chronic kidney disease was statistically the most prominent comorbidity leading to death. However, despite having high prevalence, obesity was not associated with mortality in COVID-19 patients.IMPORTANCE COVID-19 has plagued the world since it was first identified in December 2019. Previous systematic reviews and meta-analysis were limited by various factors such as the usage of non-peer reviewed data and were also limited by the lack of clinical data on a global scale. Comorbidities are frequently cited as risk factors for severe COVID-19 outcomes. However, the degree to which specific comorbidities impact the disease is debatable. Our study selection involves a global reach and covers all comorbidities that were reported to be involved in the exacerbation of COVID-19 leading to fatal outcomes, which allows us to identify the specific comorbidities that have higher risk in patients. The study highlights COVID-19 high-risk groups. However, further research should focus on the status of comorbidities and prognosis in COVID-19 patients.

Correction: Cumulative viral load as a predictor of CD4+ T-cell response to antiretroviral therapy using Bayesian statistical models.

[This corrects the article DOI: 10.1371/journal.pone.0224723.].

Cumulative viral load as a predictor of CD4+ T-cell response to antiretroviral therapy using Bayesian statistical models.

INTRODUCTION: There are Challenges in statistically modelling immune responses to longitudinal HIV viral load exposure as a function of covariates. We define Bayesian Markov Chain Monte Carlo mixed effects models to incorporate priors and examine the effect of different distributional assumptions. We prospectively fit these models to an as-yet-unpublished data from the Tshwane District Hospital HIV treatment clinic in South Africa, to determine if cumulative log viral load, an indicator of long-term viral exposure, is a valid predictor of immune response. METHODS: Models are defined, to express 'slope', i.e. mean annual increase in CD4 counts, and 'asymptote', i.e. the odds of having a CD4 count ≥500 cells/µL during antiretroviral treatment, as a function of covariates and random-effects. We compare the effect of using informative versus non-informative prior distributions on model parameters. Models with cubic splines or Skew-normal distributions are also compared using the conditional Deviance Information Criterion. RESULTS: The data of 750 patients are analyzed. Overall, models adjusting for cumulative log viral load provide a significantly better fit than those that do not. An increase in cumulative log viral load is associated with a decrease in CD4 count slope (19.6 cells/µL (95% credible interval: 28.26, 10.93)) and a reduction in the odds of achieving a CD4 counts ≥500 cells/µL (0.42 (95% CI: 0.236, 0.730)) during 5 years of therapy. Using informative priors improves the cumulative log viral load estimate, and a skew-normal distribution for the random-intercept and measurement error results is a better fit compared to using classical Gaussian distributions. DISCUSSION: We demonstrate in an unpublished South African cohort that cumulative log viral load is a strong and significant predictor of both CD4 count slope and asymptote. We argue that Bayesian methods should be used more frequently for such data, given their flexibility to incorporate prior information and non-Gaussian distributions.

Performance comparison of the Maxim and Sedia Limiting Antigen Avidity assays for HIV incidence surveillance.

BACKGROUND: Two manufacturers, Maxim Biomedical and Sedia Biosciences Corporation, supply CDC-approved versions of the HIV-1 Limiting Antigen Avidity EIA (LAg) for detecting 'recent' HIV infection in cross-sectional incidence estimation. This study assesses and compares the performance of the two assays for incidence surveillance. METHODS: We ran both assays on a panel of 2,500 well-characterized HIV-1-infected specimens. We analysed concordance of assay results, assessed reproducibility using repeat testing and estimated mean durations of recent infection (MDRIs) and false-recent rates (FRRs) for a range of normalized optical density (ODn) thresholds, alone and in combination with viral load thresholds. We defined three hypothetical surveillance scenarios, similar to the Kenyan and South African epidemics, and a concentrated epidemic. These scenarios allowed us to evaluate the precision of incidence estimates obtained by means of various recent infection testing algorithms (RITAs) based on each of the two assays. RESULTS: The Maxim assay produced lower ODn values than the Sedia assay on average, largely as a result of higher calibrator readings (mean OD of 0.749 vs. 0.643), with correlation of normalized readings lower (R2 = 0.908 vs. R2 = 0.938). Reproducibility on blinded control specimens was slightly better for Maxim. The MDRI of a Maxim-based algorithm at the 'standard' threshold (ODn ≤1.5 & VL >1,000) was 201 days (95% CI: 180,223) and for Sedia 171 (152,191). The difference Differences in MDRI were estimated at 32.7 (22.9,42.8) and 30.9 days (21.7,40.7) for the two algorithms, respectively. Commensurately, the Maxim algorithm had a higher FRR in treatment-naive subjects (1.7% vs. 1.1%). The two assays produced similar precision of incidence estimates in the three surveillance scenarios. CONCLUSIONS: Differences between the assays can be primarily attributed to the calibrators supplied by the manufacturers. Performance for surveillance was extremely similar, although different thresholds were optimal (i.e. produced the lowest variance of incidence estimates) and at any given ODn threshold, different estimates of MDRI and FRR were obtained. The two assays cannot be treated as interchangeable: assay and algorithm-specific performance characteristic estimates must be used for survey planning and incidence estimation.

Systematic review of statistically-derived models of immunological response in HIV-infected adults on antiretroviral therapy in Sub-Saharan Africa.

INTRODUCTION: In Sub-Saharan African (SSA) resource limited settings, Cluster of Differentiation 4 (CD4) counts continue to be used for clinical decision making in antiretroviral therapy (ART). Here, HIV-infected people often remain with CD4 counts <350 cells/µL even after 5 years of viral load suppression. Ongoing immunological monitoring is necessary. Due to varying statistical modeling methods comparing immune response to ART across different cohorts is difficult. We systematically review such models and detail the similarities, differences and problems. METHODS: 'Preferred Reporting Items for Systematic Review and Meta-Analyses' guidelines were used. Only studies of immune-response after ART initiation from SSA in adults were included. Data was extracted from each study and tabulated. Outcomes were categorized into 3 groups: 'slope', 'survival', and 'asymptote' models. Wordclouds were drawn wherein the frequency of variables occurring in the reviewed models is indicated by their size and color. RESULTS: 69 covariates were identified in the final models of 35 studies. Effect sizes of covariates were not directly quantitatively comparable in view of the combination of differing variables and scale transformation methods across models. Wordclouds enabled the identification of qualitative and semi-quantitative covariate sets for each outcome category. Comparison across categories identified sex, baseline age, baseline log viral load, baseline CD4, ART initiation regimen and ART duration as a minimal consensus set. CONCLUSION: Most models were different with respect to covariates included, variable transformations and scales, model assumptions, modelling strategies and reporting methods, even for the same outcomes. To enable comparison across cohorts, statistical models would benefit from the application of more uniform modelling techniques. Historic efforts have produced results that are anecdotal to individual cohorts only. This study was able to define 'prior' knowledge in the Bayesian sense. Such information has value for prospective modelling efforts.

Is CD4 monitoring needed among ugandan clients achieving a virologic and immunologic response to treatment?

It is unclear whether ongoing CD4 monitoring is needed following immunologic and virologic response to antiretroviral therapy (ART). We investigated the proportion of clients who achieved a virologic and immunologic response and then had a subsequent CD4 count <200 cells/µL despite continued virologic suppression. Included in this analysis were clients receiving ART through the Rakai Health Sciences Program between June 2004-May 2013 who achieved a CD4 ≥200 cells/µL and VL ≤400 copies/mL and who had three sets of CD4 and VL measurements (defined as a sequence) within a 390 day period. A CD4 decline was defined as any drop in CD4 count to <200 cells/µL during a period of viral suppression. A total of 1553 clients were included, 68% females, mean age of 35.5 years (SD 8.3), median baseline CD4 count 183 cells/µL (IQR 106-224). 43 (2.8%) clients developed CD4 declines, the majority, 32/43 (74%), among individuals whose initial CD4 was <300 cells/µL. Of the 43 clients with CD4 declines, 24 had an additional CD4 measurement and 20/24 (83%) achieved a CD4 ≥200 cell/µL on their next measurement (median 285 cells/µL; IQR 220-365). CD4 declines were significantly greater among those with lower CD4 at sequence initiation [adjusted hazard ratio (AHR) 4.3 (95% CI 2.1, 9.0) CD4 200-249 versus ≥350 cells/µL]. Clients who achieved an immunologic and virologic response to ART were unlikely to experience a subsequent CD4 count decline to <200 cells/µL, and among those experiencing a decline, the majority were transient in nature. Thus, ongoing CD4 monitoring could be omitted.

Among patients with sustained viral suppression in a resource-limited setting, CD4 gains are continuous although gender-based differences occur.

INTRODUCTION: There is conflicting data on long-term CD4 immune recovery after combination antiretroviral therapy (ART) in resource-limited settings. Virologic suppression is rarely documented in cohorts from sub-Saharan Africa so objective evidence of adherence is biologically unsubstantiated. We sought to investigate long-term patterns of immune recovery in Ugandan patients on ART with sustained viral suppression. METHODS: A prospective cohort of patients starting ART between April, 2004 and April, 2005 at the Infectious Diseases Institute with sustained viral suppression (viral load ≤ 400 copies/ml at month 6 and 12) while on first-line ART. Propensity scores were used to adjust for treatment allocation (nevirapine or efavirenz) at ART initiation. Data were analyzed using Kaplan Meier methods and cross-sectional time series regression. RESULTS: Three hundred and fifty-six patients were included in the analysis.71.6% were female, 87% in WHO stage 3 or 4, median age was 37 years, (IQR:32-43), and median CD4 count was 108 cells/µL, (IQR:35-174) at ART start. At multivariable analysis, lower immune recovery (measured by change in CD4 from ART start at each time interval) was associated with male-gender (-59, 95% CI: 90, -28, P<0.001), baseline CD4 count of 101-200 cells/µL (-35, 95% CI: 62, -9, P=0.009) and >200 (-64, 95% CI: 101, -26, P=0.001), and use of AZT at baseline (-47, 95% CI: -74, -20, P=0.001). Median time to reach >400 cells/µL was longer in males (197.4 weeks, IQR:119.9-312.0), compared to females (144.7 weeks, IQR:96.6-219.7, P<0.001). The cumulative probability of attaining CD4 >400 cells/µL over 7 years was higher in females compared to males (P<0.001). CONCLUSIONS: There was long-term, continuous, immunologic recovery up to 7 years after ART initiation in an urban Ugandan cohort. Virologically suppressed women had better sustained immune recovery than men. Men take longer to immune reconstitute and have a lower probability of reaching a CD4 cell count >400 cells/µL. The biologic mechanisms of these gender differences need further exploration.

A randomized controlled trial to evaluate the effectiveness of a board game on patients' knowledge uptake of HIV and sexually transmitted diseases at the Infectious Diseases Institute, Kampala, Uganda.

BACKGROUND: As the number of HIV infections continues to rise, the search for effective health education strategies must intensify. A new educational board game was developed to increase HIV peoples' attention and knowledge to HIV and sexually transmitted infections (STIs) information. The object of this study was to assess the effect of this educational board game on the uptake of knowledge. METHODS: A randomized controlled trial where patients attending the Infectious Diseases Clinic, Kampala, Uganda were randomized to either play the board game (intervention arm) or to attend a health talk (standard of care arm). Participants' knowledge was assessed before and after the education sessions through a questionnaire. RESULTS: One hundred eighty HIV-positive participants were enrolled, 90 for each study arm. The pretest scores were similar for each arm. There was a statistically significant increase in uptake of knowledge of HIV and STIs in both study arms. Compared with patients in the standard of care arm, participants randomized to the intervention arm had higher uptake of knowledge (4.7 points, 95% confidence interval: 3.9 to 5.4) than the controls (1.5 points, 95% confidence interval: 0.9 to 2.1) with a difference in knowledge uptake between arms of 3.2 points (P < 0.001). Additionally, both participants and facilitators preferred the board game to the health talk as education method. CONCLUSIONS: The educational game significantly resulted in higher uptake of knowledge of HIV and STIs. Further evaluation of the impact of this educational game on behavioral change in the short and long term is warranted.

Evaluation of in-house PCR for diagnosis of smear-negative pulmonary tuberculosis in Kampala, Uganda.

BACKGROUND: Nucleic acid amplification tests (NAATs) have offered hope for rapid diagnosis of tuberculosis (TB). However, their efficiency with smear-negative samples has not been widely studied in low income settings. Here, we evaluated in-house PCR assay for diagnosis of smear-negative TB using Lowenstein-Jensen (LJ) culture as the baseline test. Two hundred and five pulmonary TB (PTB) suspects with smear-negative sputum samples, admitted on a short stay emergency ward at Mulago Hospital in Kampala, Uganda, were enrolled. Two smear-negative sputum samples were obtained from each PTB suspect and processed simultaneously for identification of MTBC using in-house PCR and LJ culture. RESULTS: Seventy two PTB suspects (35%, 72/205) were LJ culture positive while 128 (62.4%, 128/205) were PCR-positive. The sensitivity and specificity of in-house PCR for diagnosis of smear-negative PTB were 75% (95% CI 62.6-85.0) and 35.9% (95% CI 27.2-45.3), respectively. The positive and negative predictive values were 39% (95% CI 30.4-48.2) and 72.4% (95% CI 59.1-83.3), respectively, while the positive and negative likelihood ratios were 1.17 (95% CI 0.96-1.42) and 0.70 (95% CI 0.43-1.14), respectively. One hundred and seventeen LJ culture-negative suspects (75 PCR-positive and 42 PCR-negative) were enrolled for follow-up at 2 months. Of the PCR-positive suspects, 45 (60%, 45/75) were still alive, of whom 29 (64.4%, 29/45) returned for the follow-up visit; 15 (20%, 15/75) suspects died while another 15 (20%, 15/75) were lost to follow-up. Of the 42 PCR-negative suspects, 22 (52.4%, 22/42) were still alive, of whom 16 (72.7%, 16/22) returned for follow-up; 11 (26.2%, 11/42) died while nine (21.4%, 9/42) were lost to follow-up. Overall, more PCR-positive suspects were diagnosed with PTB during follow-up visits but the difference was not statistically significant (27.6%, 8/29 vs. 25%, 4/16, p = 0.9239). Furthermore, mortality was higher for the PCR-negative suspects but the difference was also not statistically significant (26.2% vs. 20% p = 0.7094). CONCLUSION: In-house PCR correlates poorly with LJ culture for diagnosis of smear-negative PTB. Therefore, in-house PCR may not be adopted as an alternative to LJ culture.