Outcomes and complications of hospitalised patients with HIV-TB co-infection

A comparative study on TB incidence and HIVTB coinfection using machine learning models on WHO global TB dataset

Tuberculosis, a deadly and contagious disease caused by Mycobacterium tuberculosis, remains a significant global public health threat. HIV co-infection significantly increases the risk of active TB recurrence and prolongs medical treatment for tuberculosis (TB). The study focuses on using advanced machine learning (ML) techniques to predict TB incidence and HIV-TB co-infection using data from the 2023 World Health Organization (WHO) Global TB burden database. The estimated rate for all types of tuberculosis per 100,000 people (E_inc_100k) and the estimated rate of HIV-positive tuberculosis incidence per 100,000 people (e_inc_tbhiv_100k) are the two main goal factors in the dataset. F1 score, accuracy, precision, recall, and the Receiver Operating Characteristic-Area Under the Curve (ROC-AUC) were among the important metrics used to evaluate the model's performance. With 99.7% accuracy, 99.80% precision, 99.6% recall, a 99.7% F1 score, and a 99.7% ROC-AUC score, the Extreme Gradient Boosting (XGB) model outperformed other models for e_inc_100k. The e_inc_tbhiv_100k records outstanding performance from the Gradient Boosting (GB) model, with 98.58% accuracy, 98.32% precision, 98.73% recall, a 98.53% F1 score, and a 98.58% ROC-AUC score. Finally, the study aligns with the UNAIDS and WHO End TB Strategy, indicating a progression in combating TB and TB-HIV co-infection in public health workflow.

Prevalence, treatment outcomes and determinants of TB/HIV coinfection: A 4-year retrospective review of national tuberculosis registry in a country in a MENA region

Background

The co-occurrence of tuberculosis (TB) and AIDS (HIV) has emerged as a significant public health challenge. This study investigated the epidemiological factors and treatment outcomes of TB in individuals based on their HIV status in Iran.

Methods

The current study was a descriptive-analytical cross-sectional study that focused on new patients diagnosed with TB in Iran between 2018 and 2021. Patients' data were sourced from the National Tuberculosis Registry database of Iran. A multiple logistic regression model was used to investigate the relationship between the most important influencing factors and TB/HIV coinfection.

Results

Over a 4-year period, a study was conducted on 25,011 new TB patients out of 30,762 registered in the national database. TB and HIV were coinfected in 672 cases (2.68%). The highest number of coinfection cases were found in patients with smear-negative pulmonary tuberculosis (249 patients, 37.05%) and extrapulmonary tuberculosis (123 patients, 18.19%). TB patients with coinfection had a median TB treatment duration of three months longer than others. The success rate of TB treatment was lower in patients with coinfection (437 patients, 65.02%) than in non-coinfection patients (20,302 patients, 83.41%). Treatment success probability in smear-positive pulmonary tuberculosis patients with and without coinfection was lower than other types of TB. Logistic regression analysis showed that having a TB risk factor was the strongest predictor of coinfection, with an odds ratio of 29.73 (95% CI: 22.05-40.07), followed by having an HIV risk factor with an odds ratio of 17.52 (95% CI: 13.68-22.45).

Conclusions

The findings of this research offer significant insights into the potential causes of HIV coinfection in individuals with TB, which could be used to inform the development of policies and strategies aimed at enhancing the identification and treatment of TB patients who are at risk of TB/HIV coinfection and to promote optimal health status for patients with TB.

Osteoarticular tuberculosis cases in the southwest of China: A 9-year retrospective study

Background

Osteoarticular tuberculosis (TB) is an uncommon form of extrapulmonary TB. In this study, we analyzed the epidemiological characteristics, common sites, and drug resistance profiles of osteoarticular TB infections occurring in southwest China.

Methods

A total of 3,254 cases of patients clinically diagnosed with osteoarticular TB infections between 2013 and 2021 were retrospectively analyzed. Patients' demographic and clinical characteristics were collected. Drug sensitivity testing was performed using the microporous plate ratio method. Chi-squared analysis was used to analyze the rates of and trends in mycobacterial isolates.

Results

Of the 3,254 patients, 1,968 (60.5%) were men and boys, and 1,286 (39.5%) were women and girls; patients' ages ranged from 1 to 91 years, with an average of 42 ± 19.3 years. In terms of disease, 2,261 (69.5%) had spinal TB, mainly thoracic (815, 36%) or lumbar (1,080, 48%); joint TB was found in 874 cases (26.9%), mainly occurring in the knee (263, 30%) or hip (227, 26%); and both spinal and joint TB were observed in 119 cases (3.7%). Drug susceptibility tests were performed on 241 isolated strains of MTB; 70 strains (29.0%) were resistant to at least one drug, and MDR-TB and XDR-TB were observed in 7.1 and 1.2% of strains, respectively.

Conclusions

In southwest China over this period, osteoarticular TB mainly affected middle-aged and young men with poor nutritional status. Patients from ethnic minority areas also accounted for a large proportion of cases. Spinal TB is prone to occur in the lumbar and thoracic vertebrae, and joint TB is prone to occur in the lower limb joints. Additionally, there has been an increasing trend in the number of TB cases over the past 9 years, and drug resistance has also increased.

Genetic and hormonal mechanisms underlying sex-specific immune responses in tuberculosis

Tuberculosis (TB), the world's deadliest bacterial infection, afflicts more human males than females, with a male/female (M/F) ratio of 1.7. Sex disparities in TB prevalence, pathophysiology, and clinical manifestations are widely reported, but the underlying biological mechanisms remain largely undefined. This review assesses epidemiological data on sex disparity in TB, as well as possible underlying hormonal and genetic mechanisms that might differentially modulate innate and adaptive immune responses in males and females, leading to sex differences in disease susceptibility. We consider whether this sex disparity can be extended to the efficacy of vaccines and discuss novel animal models which may offer mechanistic insights. A better understanding of the biological factors underpinning sex-related immune responses in TB may enable sex-specific personalized therapies for TB.