The incidence rate of tuberculosis and its associated factors among HIV-positive persons in Sub-Saharan Africa: a systematic review and meta-analysis

Progress in Pharmacometrics Implementation and Regulatory Integration in Africa: A Systematic Review

The availability of clinical trial data, advocacy, and increased funding has facilitated the implementation of pharmacometrics in Africa, resulting in the establishment of additional training programs for pharmacometricians. This study conducted a systematic review to evaluate the progress made from the implementation of pharmacometrics in clinical drug development and its adoption into drug approval by regulatory authorities in Africa. We performed a comprehensive literature search using major databases such as PubMed and Google Scholar. The study included articles published until 2024, with no lower cutoff. Articles were excluded if not addressing the research question or of pharmacometrics studies done outside Africa with no collaboration with African researchers (study setting). For the review, a total of 121 articles were included for analysis. Among the reported pharmacometrics approaches, Population pharmacokinetics modeling approaches are the most used (95 (78.5%)). South Africa and Uganda researchers have the most research output in pharmacometrics in Africa (82 (89.1%) and 7 (7.61%), respectively), with the University of Cape Town (South Africa) producing the highest (71 (78.8%)) of all article in Africa. The most studied conditions are TB (43 (35.5%)), HIV (33 (27.3%), TB and HIV (22 (18.2%)), and malaria (12 (9.92%). Pharmacometrics is gaining momentum in Africa, and the progress made since inception will significantly improve the safety and efficacy of therapeutic agents used to treat HIV, TB, and other emerging conditions.

Proportion of active tuberculosis among HIV-infected children after antiretroviral therapy in Ethiopia: A systematic review and meta-analysis

Despite effectiveness of antiretroviral therapy in reducing mortality of opportunistic infections among HIV infected children, however tuberculosis (TB) remains a significant cause for morbidity and attributed for one in every three deaths. HIV-infected children face disproportionate death risk during co-infection of TB due to their young age and miniatures immunity makes them more vulnerable. In Ethiopia, there is lack of aggregated data TB and HIV mortality in HIV infected children. We conducted an extensive systematic review of literature using Preferred Reporting of Systematic Review and Meta-Analysis (PRISMA) guideline. Five electronic databases were used mainly Scopus, PubMed, Medline, Web of Science, and Google scholar for articles searching. The pooled proportion of TB was estimated using a weighted inverse variance random-effects meta-regression using STATA version-17. Heterogeneity of the articles was evaluated using Cochran's Q test and I2 statistic. Subgroup analysis, sensitivity test, and Egger's regression were conducted for publication bias. This met-analysis is registered in Prospero-CRD42024502038. In the final met-analysis report, 13 out of 1221 articles were included and presented. During screening of 6668 HIV-infected children for active TB occurrence, 834 cases were reported after ART was initiated. The pooled proportion of active TB among HIV infected children was found 12.07% (95% CI: 10.71-13.41). In subgroup analysis, the Oromia region had 15.6% (95%CI: 10.2-20.6) TB burden, followed by southern Ethiopia 12.8% (95%CI: 10.03-15.67). During meta-regression, missed isoniazid Preventive therapy (IPT) (OR: 2.28), missed contrimoxazole preventive therapy (OR: 4.26), WHO stage III&IV (OR: 2.27), and level of Hgb ≤ 10gm/dl (OR = 3.11.7) were predictors for active TB. The systematic review found a higher proportion of active TB in HIV-infected children in Ethiopia compared to estimated rates in end TB strategy. To prevent premature death during co-infection, implement effective TB screening and cases tracing strategies in each follow up is needed.

LSTM-Based Prediction Model for Tuberculosis Among HIV-Infected Patients Using Structured Electronic Medical Records: A Retrospective Machine Learning Study

Background

Both HIV and TB are chronic infectious diseases requiring long-term treatment and follow-up, resulting in extensive electronic medical records. With the exponential growth of health and medical big data, effectively extracting and analyzing these data has become the research hotspot. As a fundamental aspect of artificial intelligence, machine learning has been extensively applied in medical research, encompassing diagnosis, treatment, patient monitoring, drug development, and epidemiological investigations. This significantly enhances medical information systems and facilitates the interoperability of medical data.

Methods

In our study, we analyzed longitudinal data from the electronic health records of 4540 patients, gathered from the National Clinical Research Center for Infectious Diseases in Shenzhen, China, spanning from 2017 to 2021. Initially, we employed the fine-tuned ChatGLM to structure the electronic medical records. Subsequently, we utilized a multi-layer perceptron to classify each patient and determined the presence of tuberculosis in HIV patients. Using machine learning-based natural language processing, we structured these records to build a specialized database for HIV and TB co-infection. We studied the epidemiological characteristics, focusing on incidence patterns, patient characteristics, and influencing factors, to uncover the transmission characteristics of these diseases in Shenzhen. Additionally, we used Long Short-Term Memory to create a predictive model for TB co-infection among HIV patients, based on their medical records. This model predicted the risk of TB co-infection, providing scientific evidence for clinical decision-making and enabling early detection and precise intervention.

Results

Based on the refined ChatGLM model tailored for structured electronic health records, the accuracy of symptom extraction consistently surpassed 0.95 precision. Key symptoms such as diarrhea and normal showed precision rates exceeding 0.90. High scores were also achieved in recall and F1 scores. Among 4540 HIV patients, 758 were diagnosed with concurrent tuberculosis, indicating a 16.7% co-infection rate, while syphilis co-infection affected 25.1%, underscoring the prevalence of concurrent infections among HIV patients. Utilizing electronic health records, a Multilayer Perceptron classifier was developed as a benchmark against Long Short-Term Memory to predict high-risk groups for HIV and tuberculosis co-infections. The Multilayer Perceptron classifier demonstrated predictive ability with AUROC values ranging from 0.616 to 0.682 on the test set, suggesting opportunities for further optimization and generalization despite its accuracy in identifying HIV-TB co-infections. In tuberculosis intelligent diagnosis based on laboratory results, the Long Short-Term Memory showed consistent performance across 5-fold cross-validation, with AUROC values ranging from 0.827 to 0.850, indicating reliability and consistency in tuberculosis prediction. Furthermore, by optimizing classification thresholds, the model achieved an overall accuracy of 81.18% in distinguishing HIV co-infected tuberculosis from simple HIV infection.

Conclusion

Combining the Multilayer Perceptron classifier with Long Short-Term Memory represented an advanced approach for effectively extracting electronic health records and utilizing it for disease prediction. This underscored the superior performance of deep learning techniques in managing both structured and unstructured medical data. Models leveraging laboratory time-series data demonstrated notably better performance compared to those relying solely on electronic health records for predicting tuberculosis incidence. This emphasized the benefits of deep learning in handling intricate medical data and provided valuable insights for healthcare providers exploring the use of deep learning in disease prediction and management.

Tuberculosis-associated mortality and risk factors for HIV-infected population in Ethiopia: a systematic review and meta-analysis

Background

Despite the effectiveness of antiretroviral therapy in reducing mortality from opportunistic infections among people living with HIV (PLHIV), tuberculosis (TB) continues to be a significant cause of death, accounting for over one-third of all deaths in this population. In Ethiopia, there is a lack of comprehensive and aggregated data on the national level for TB-associated mortality during co-infection with HIV. Therefore, this systematic review and meta-analysis aimed to estimate TB-associated mortality and identify risk factors for PLHIV in Ethiopia.

Methods

We conducted an extensive systematic review of the literature using the Preferred Reporting of Systematic Review and Meta-Analysis (PRISMA) guidelines. More than seven international electronic databases were used to extract 1,196 published articles from Scopus, PubMed, MEDLINE, Web of Science, HINARY, Google Scholar, African Journal Online, and manual searching. The pooled mortality proportion of active TB was estimated using a weighted inverse variance random-effects meta-regression using STATA version-17. The heterogeneity of the articles was evaluated using Cochran's Q test and I 2 statistic test. Subgroup analysis, sensitivity analysis, and Egger's regression were conducted to investigate publication bias. This systematic review is registered in Prospero with specific No. CRD42024509131.

Results

Overall, 22 individual studies were included in the final meta-analysis reports. During the review, a total of 9,856 cases of TB and HIV co-infection were screened and 1,296 deaths were reported. In the final meta-analysis, the pooled TB-associated mortality for PLHIV in Ethiopia was found to be 16.2% (95% CI: 13.0-19.2, I 2 = 92.9%, p = 0.001). The subgroup analysis revealed that the Amhara region had a higher proportion of TB-associated mortality, which was reported to be 21.1% (95% CI: 18.1-28.0, I 2 = 84.4%, p = 0.001), compared to studies conducted in Harari and Addis Ababa regions, which had the proportions of 10% (95% CI: 6-13.1%, I 2 = 83.38%, p = 0.001) and 8% (95% CI: 1.1-15, I 2 = 87.6%, p = 0.001), respectively. During the random-effects meta-regression, factors associated with co-infection of mortality in TB and HIV were identified, including WHO clinical stages III & IV (OR = 3.01, 95% CI: 1.9-4.7), missed co-trimoxazole preventive therapy (CPT) (OR = 1.89, 95% CI: 1.05-3.4), and missed isoniazid preventive therapy (IPT) (OR = 1.8, 95% CI: 1.46-2.3).

Conclusion

In Ethiopia, the mortality rate among individuals co-infected with TB/HIV is notably high, with nearly one-fifth (16%) of individuals succumbing during co-infection; this rate is considered to be higher compared to other African countries. Risk factors for death during co-infection were identified; the included studies examined advanced WHO clinical stages IV and III, hemoglobin levels (≤10 mg/dL), missed isoniazid preventive therapy (IPT), and missed cotrimoxazole preventive therapy (CPT) as predictors. To reduce premature deaths, healthcare providers must prioritize active TB screening, ensure timely diagnosis, and provide nutritional counseling in each consecutive visit.

Systematic review registration

Trial registration number in Prospero =CRD42024509131 https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=509131.

Risk score prediction for bacteriologically confirmed tuberculosis among adults with HIV on antiretroviral therapy in northwest Ethiopia: prognostic model development

OBJECTIVE

This study was aimed at developing a risk score prediction model for bacteriologically confirmed tuberculosis (TB) among adults with HIV receiving antiretroviral therapy in Ethiopia.

METHODS

An institutional-based retrospective follow-up study was conducted among 569 adults with HIV on ART. We used demographic and clinical prognostic factors to develop a risk prediction model. Model performance was evaluated by discrimination and calibration using the area under the receiver operating characteristic (AUROC) curve and calibration plot. Bootstrapping was used for internal validation. A decision curve analysis was used to evaluate the clinical utility.

RESULTS

Opportunistic infection, functional status, anemia, isoniazid preventive therapy, and WHO clinical stages were used to develop risk prediction. The AUROC curve of the original model was 87.53% [95% confidence interval (CI): 83.88-91.25] and the calibration plot ( P -value = 0.51). After internal validation, the AUROC curve of 86.61% (95% CI: 82.92-90.29%) was comparable with the original model, with an optimism coefficient of 0.0096 and good calibration ( P -value = 0.10). Our model revealed excellent sensitivity (92.65%) and negative predictive value (NPV) (98.60%) with very good specificity (70.06%) and accuracy (72.76%). After validation, accuracy (74.85%) and specificity (76.27%) were improved, but sensitivity (86.76%) and NPV (97.66%) were relatively reduced. The risk prediction model had a net benefit up to 7.5 threshold probabilities.

CONCLUSION

This prognostic model had very good performance. Moreover, it had very good sensitivity and excellent NPV. The model could help clinicians use risk estimation and stratification for early diagnosis and treatment to improve patient outcomes and quality of life.

Incidence and predictors of tuberculosis among HIV-infected children after initiation of antiretroviral therapy in Ethiopia: A systematic review and meta-analysis

BACKGROUND

Globally, Tuberculosis (TB) is the main cause of morbidity and mortality among infectious disease. TB and Human Immune Virus (HIV) are the two deadly pandemics which interconnected each other tragically, and jeopardize the lives of children; particularly in Sub-Saharan Africa. Therefore, this review was aimed to determine the aggregated national pooled incidence of tuberculosis among HIV- infected children and its predictors in Ethiopia.

METHODS

An electronic search engine (HINARI, PubMed, Scopus, web of science), Google scholar and free Google databases were searched to find eligible studies. Quality of the studies was checked using the Joanna Briggs Institute (JBI) quality assessment checklists for cohort studies. Heterogeneity between studies was evaluated using Cochrane Q-test and the I2 statistics.

RESULT

This review revealed that the pooled national incidence of tuberculosis among children with HIV after initiation of ART was 3.63% (95% CI: 2.726-4.532) per 100-person-years observations. Being Anemic, poor and fair ART adherence, advanced WHO clinical staging, missing of cotrimoxazole and isoniazid preventing therapy, low CD4 cell count, and undernutrition were significant predictors of tuberculosis incidence.

CONCLUSION

The study result indicated that the incidence of TB among HIV- infected children is still high. Therefore, parents/guardians should strictly follow and adjust nutritional status of their children to boost immunity, prevent undernutrition and opportunistic infections. Cotrimoxazole and isoniazid preventive therapy need to continually provide for HIV- infected children for the sake of enhancing CD4/immune cells, reduce viral load, and prevent from advanced disease stages. Furthermore, clinicians and parents strictly follow ART adherence.

Incidence rate of tuberculosis among HIV infected children in Ethiopia: systematic review and meta-analysis

BACKGROUND

Tuberculosis is one the leading causes of death from a single infectious disease, caused by the bacillus mycobacterium tuberculosis. In Ethiopia, even though several primary studies have been conducted on the incidence of tuberculosis among HIV-infected children, the pooled incidence rate of tuberculosis among HIV-infected children (aged 0-14 years) is unknown. Therefore, the main objectives of this systematic review and meta-analysis are to estimate the pooled incidence rate of tuberculosis among HIV-infected children and its predictors in Ethiopia.

METHOD

International electronic databases such as PubMed, HINARI, Science Direct, Google Scholar, and African Journals Online were searched using different search engines.  Quality of primary studies was checked using the Joanna Briggs Institute checklist. The heterogeneity of studies was tested using I-square statistics. Publication bias was tested using a funnel plot and Egger's test. Forest plots and tables were used to present the results. The random effect model was used to estimate the pooled incidence of tuberculosis among children living with HIV.

RESULT

A total of 13 studies were included in this systematic review and meta-analysis. The pooled incidence of tuberculosis among HIV-infected children was 3.77 (95% CI: 2.83, 5.02) per 100-person-year observations. Advanced HIV disease (HR: 2.72, 95% CI: 1.9; 3.88), didn't receive complete vaccination (HR: 4.40, 95% CI: 2.16; 8.82), stunting (HR: 2.34, 95% CI: 1.64, 3.33), underweight (HR: 2.30, 95% CI: 1.61; 3.22), didn't receive Isoniazid preventive therapy (HR: 3.64, 95% CI: 2.22, 5.96), anemia (HR: 3.04, 95% CI: 2.34; 3.98), fair or poor antiretroviral therapy adherence (HR: 2.50, 95% CI: 1.84; 3.40) and didn't receive cotrimoxazole preventive therapy (HR: 3.20, 95% CI: 2.26; 4.40) were predictors of tuberculosis coinfection among HIV infected children.

CONCLUSION

This systematic review and meta-analysis concluded that the overall pooled incidence rate of tuberculosis among HIV-infected children was high in Ethiopia as compared to the END TB strategy targets. Therefore, emphasis has to be given to drug adherence (ART and Isoniazid) and nutritional counseling. Moreover, early diagnosis and treatment of malnutrition and anemia are critical to reduce the risk of TB coinfection.

REGISTRATION

Registered in PROSPERO with ID: CRD42023474956.

HIV co-infection is associated with reduced Mycobacterium tuberculosis transmissibility in sub-Saharan Africa

Persons living with HIV are known to be at increased risk of developing tuberculosis (TB) disease upon infection with Mycobacterium tuberculosis (Mtb). However, it has remained unclear how HIV co-infection affects subsequent Mtb transmission from these patients. Here, we customized a Bayesian phylodynamic framework to estimate the effects of HIV co-infection on the Mtb transmission dynamics from sequence data. We applied our model to four Mtb genomic datasets collected in sub-Saharan African countries with a generalized HIV epidemic. Our results confirm that HIV co-infection is a strong risk factor for developing active TB. Additionally, we demonstrate that HIV co-infection is associated with a reduced effective reproductive number for TB. Stratifying the population by CD4+ T-cell count yielded similar results, suggesting that, in this context, CD4+ T-cell count is not a better predictor of Mtb transmissibility than HIV infection status alone. Together, our genome-based analyses complement observational household contact studies, and more firmly establish the negative association between HIV co-infection and Mtb transmissibility.

Active tuberculosis incidence among treatment failure experienced patients in North Wollow Zone: A multicenter historical cohort

Background

In Ethiopia, tuberculosis (TB) is a significant cause of death among individuals living with HIV, especially in resource-limited areas and those who have experienced treatment failure. However, there is the paucity of data regarding TB among treatment failures experienced people living with HIV. This study aimed to estimate the rate and identify predictors of tuberculosis among patients who received second-line treatment in North Wollo, Northeast Ethiopia.

Methods

A retrospective follow-up study was conducted on 474 HIV-infected patients who experienced treatment failure. The study period ranged from January 2015 to September 30, 2021. The incidence of TB was assessed using a Cox proportional hazard regression model, after ensuring that all assumptions were met. Factors associated with active TB were determined by analyzing adjusted hazard ratios and 95% confidence intervals.

Results

In a study of 474 HIV-positive patients on second-line antiretroviral treatment, we found an incidence rate of 3.6% with 17 new cases of TB observed over 4412.4 persons per year (PPY). The overall incidence density rate was estimated to be 0.39 cases per 100 PPY (95% CI: 0.239-0.618). Regarding the occurrence of active TB in second-line patients, WHO clinical treatment stage (T3 and T4), missed isoniazid preventive therapy had a significantly higher risk (AHR: 13.225, 95% CI: 2.894-60.434, p = 0.001), while being married was associated with a lower risk (AHR: 0.203, 95% CI: 0.045-0.907, p = 0.001).

Conclusion

A high incidence of active TB was observed shortly after initiating second-line antiretroviral treatment. Factors such as being in the WHO clinical treatment stage (T3 and T4) and marital status were determinants for active TB. To improve overall survival rates, it is vital to enhance early TB screening and implement effective isoniazid preventive therapy.

Advances in Antiretroviral Therapy for Patients with Human Immunodeficiency Virus-Associated Tuberculosis

Tuberculosis is one of the most common opportunistic infections and a prominent cause of death in patients with human immunodeficiency virus (HIV) infection, in spite of near-universal access to antiretroviral therapy (ART) and tuberculosis preventive therapy. For patients with active tuberculosis but not yet receiving ART, starting ART after anti-tuberculosis treatment can complicate clinical management due to drug toxicities, drug-drug interactions and immune reconstitution inflammatory syndrome (IRIS) events. The timing of ART initiation has a crucial impact on treatment outcomes, especially for patients with tuberculous meningitis. The principles of ART in patients with HIV-associated tuberculosis are specific and relatively complex in comparison to patients with other opportunistic infections or cancers. In this review, we summarize the current progress in the timing of ART initiation, ART regimens, drug-drug interactions between anti-tuberculosis and antiretroviral agents, and IRIS.

Phenotypic and Genotypic Drug Resistance of Mycobacterium tuberculosis Strains Isolated from HIV-Infected Patients from a Third-Level Public Hospital in Mexico

BACKGROUND

Drug-resistant tuberculosis (TB) is associated with higher mortality rates in patients with human immunodeficiency virus (HIV). In Mexico, the number of deaths due to TB among the HIV-positive population has tripled in recent years.

METHODS

Ninety-three Mycobacterium tuberculosis strains isolated from the same number of HIV-infected patients treated in a public hospital in Mexico City were studied to determine the drug resistance to first- and second-line anti-TB drugs and to identify the mutations associated with the resistance.

RESULTS

Of the 93 patients, 82.7% were new TB cases, 86% were male, and 73% had extrapulmonary TB. Most patients (94%) with a CD4 T-lymphocyte count <350 cells/mm3 were associated with extrapulmonary TB (p <0.0001), whilst most patients (78%) with a CD4 T-lymphocyte count >350 cells/mm3 were associated with pulmonary TB (p = 0.0011). Eighty-two strains were pan-susceptible, four mono-resistant, four poly-resistant, two multidrug-resistant, and one was extensively drug-resistant. In the rifampicin-resistant strains, rpoB S531L was the mutation most frequently identified, whereas the inhA C15T and katG S315T1 mutations were present in isoniazid-resistant strains. The extensively drug-resistant strain also contained the mutation gyrA D94A.

CONCLUSIONS

These data highlight the need to promptly diagnose the drug resistance of M. tuberculosis among all HIV-infected patients by systematically offering access to first- and second-line drug susceptibility testing and to tailor the treatment regimen based on the resistance patterns to reduce the number of deaths in HIV-infected patients.