Type 2 Diabetes Mellitus (T2DM) is a chronic disease closely related to personal life style. Therefore, achieving effective self-management is one of the most important ways to control it. There is evidence that social support can help to improve the self-management ability of patients with T2DM, but which social support is more effective has been rarely explored. The purpose of this study is to construct an integrated model to analyze which social support has more significant impact on self-management of T2DM, and provide reasonable suggestions to health care providers on how to effectively play the role of social support. We established a social support indicator evaluation system and proposed an integrated model that combines ANP (Analytical Network Process) and CRITIC (CRiteria Importance through Intercriteria Correlation) methods to evaluate the impact of social support on T2DM self-management from both subjective and objective perspectives. The weights calculated by the model will serve as the basis for us to judge the importance of different social support indicators. Informational support (weighting 49.26%) is the most important criteria, followed by tangible support (weighting 39.24%) and emotional support (weighting 11.51%). Among 11 sub-criteria, guidance (weighting 23.05%) and feedback (weighting 14.68%) are two most relevant with T2DM self-management. This result provides ideas and evidence for health care providers on how to offer more effective social support. To our knowledge, this is the first study in which Multi-Criteria Decision Making (MCDM) tools, specifically ANP and CRITIC, are used to evaluate the impact of social support on improving self-management of type 2 diabetes. The study suggests that incorporating two sub-indicators of guidance and feedback into the diabetes care programs may have great potential to improve T2DM self-management and further control patient blood glucose and reduce complications.

This study aimed to estimate the adverse events (AE) rate during anti-tuberculosis treatment and to explore AE-related risk factors. New and previously treated smear-positive tuberculosis (TB) cases were enrolled from eight regions in China between April 2009 and October 2010. The AE rate was estimated, and AE risk factors during anti-TB treatment were assessed using Cox proportional models. Among 2091 Chinese subjects with anti-TB treatment, 462 (22.1%, 95% confidence interval (CI), 20.3–23.9) patients developed AE, with liver injury and gastrointestinal reactions constituting the most common AE. Specifically, 9.8% (95% CI, 8.5–11.1) and 6.3% (95% CI, 5.3–7.4) developed liver injuries and gastrointestinal reactions, respectively. We found that AE rate differed by regions, TB knowledge score, symptoms score and smoking status. Liver injuries were associated with age, sex and smoking status; gastrointestinal reactions were associated with education level and symptom score. Improving patients’ knowledge on TB could reduce AE rate.

Tuberculosis (TB) remains a formidable global public health challenge. The rising prevalence of drug-resistant TB and increased human immunodeficiency virus(HIV) co-infection further exacerbate TB control efforts. Mycobacterium tuberculosis (Mtb) achieves highly heterogeneous infection outcomes (active disease, latency, or clearance) through immune evasion and host metabolic reprogramming. While conventional diagnostic techniques offer cost-effectiveness and accessibility without complex infrastructure, they are constrained by low sensitivity, prolonged turnaround times, and an inability to distinguish latent TB infection (LTBI) from active TB disease (ATB). Recent research into host-derived biomarkers provides a promising strategy to overcome diagnostic bottlenecks by deciphering characteristic molecular changes in host–pathogen interactions. This review systematically reviews advances in host-derived biomarkers for TB diagnosis, critically discussing the clinical potential, translational challenges, and future research directions of integrated multi-omics biomarker panels to enhance diagnostic sensitivity and specificity, differentiate ATB from LTBI, and guide precision therapy.

This study aims to explore the interaction of glycemic control and statin use on the treatment outcomes of pulmonary tuberculosis‐diabetes comorbidity (PTB‐DM) patients. A nested case‐control study was conducted in a tuberculosis patients’ cohort. We defined cases as patients who experienced unfavorable outcomes. Glycemic control was estimated at the baseline. Statin use was obtained from medical records. The multivariate logistic regression models were developed, and the interaction table invented by Andersson was adopted to analyze the interaction of glycemic control and statin use on treatment outcomes. A total of 2,047 patients were included in this study. There was a significant interaction between glycemic control and statin use on the treatment outcomes. Patients with good glycemic control and no statin use (OR = 0.464, 95% CI: 0.360–0.623) had a lower risk of unfavorable outcomes than those with poor glycemic control and statin use (OR = 0.604, 95% CI: 0.401–0.734). Patients with good glycemic control and statin use had the lowest risk of unfavorable outcomes (OR = 0.394, 95% CI: 0.264–0.521). Glycemic control in diabetes‐tuberculosis treatment should be paid considerable attention. Patients can benefit from statin use even if they have poor glycemic control. Patients with good glycemic control and statin use can have the best outcomes.

Background: Tuberculosis remains a major global public health challenge, particularly among children. This study aims to provide a comprehensive assessment of the global, regional, and national burden of tuberculosis among children (0–14 years) using data from the Global Burden of Disease (GBD) 2021 study. Methods: Data on the incidence of tuberculosis (drug-susceptible, MDR-TB, and XDR-TB), as well as disability-adjusted life years (DALYs), among children aged 0–14 years in 204 countries and territories from 1990 to 2021 were obtained from the GBD 2021 study. Estimated annual percentage changes (EAPCs) in age-standardised incidence rates (ASIRs) and DALY rate were calculated overall and stratified by age, sex, and sociodemographic index (SDI) to quantify temporal trends. Spearman correlation analyses were performed to assess associations between tuberculosis burden and SDI. Results: In 2021, there were an estimated 759,300 new tuberculosis cases (ASIR: 37.7 per 100,000 population) among children globally, including 32,515 cases of MDR-TB (ASIR: 1.6) and 1193 cases of XDR-TB (ASIR: 0.1). Both global ASIR and DALY rate exhibited a declining trend from 1990 to 2021, with EAPC of −2.61% (95%CI: −2.74 to −2.47) and −4.38% (−4.61 to −4.14), respectively. From 1990 to 2021, High-income North America was the only GBD region with an increasing ASIR for tuberculosis (EAPC = 1.12, 95% CI: 0.61 to 1.64). From 1990 to 2021, there was no significant change in ASIR of MDR-TB (EAPC = 1.18, 95% CI: −0.16 to 2.54). However, eight of the 21 GBD regions exhibited increasing trends in the ASIR of MDR-TB, with the largest increase observed in Oceania (11.99, 10.49 to 13.52), followed by Central Asia (9.76, 6.48 to 13.13) and South Asia (5.71, 3.10 to 8.38). A strong negative correlation was observed between tuberculosis burden and SDI, with the highest disease burden concentrated in low-SDI regions. Conclusions: Achieving elimination targets will require stronger diagnostics and treatment for childhood tuberculosis, alongside reduced transmission, improved infection detection, and preventive therapy for exposed children, especially those under 5 years.