Incidence of and risk factors for active tuberculosis in human immunodeficiency virus-infected patients in South Korea

History of Acquired Immune Deficiency Syndrome in Korea

The first human immunodeficiency virus (HIV) infection was reported in Korea in 1985. The number of HIV-infected persons domestically increased in the 1990s showing epidemic indigenousization. Since then, the number of new infections gradually increased every year, and recently more than 1,000 newly infected cases were reported per year. A total of 12,522 infected individuals have been reported up to 2015, of which 2,020 died. The male to female ratio was 15.4:1, and 34.2% of them were under 30 years old. The infection route was homosexual and bisexual contact in 60.1% of cases and heterosexual contact in 34.6% of cases. Candidiasis, Pneumocystis pneumonia, tuberculosis were common as a AIDS (acquired immune deficiency syndrome)-defining illness. But with the introduction of antiretroviral therapy in the late 1990s, non-AIDS defining illnesses such as metabolic complications, cardiovascular diseases, bone diseases, and neuropsychiatric disorders such as neurocognitive dysfunction, depression, and anxiety are emerging as new health problems. The management policy switched its focus from regulating and monitoring of HIV-infected persons to ensuring access to treatment and promotion of voluntary HIV testing in high-risk groups. Also as the age of the infected persons increases, a need for various supports such as social rehabilitation, life counseling, and welfare has emerged.

Association between diabetes mellitus and active tuberculosis: A systematic review and meta-analysis

The burgeoning epidemic of diabetes mellitus (DM) is one of the major global health challenges. We systematically reviewed the published literature to provide a summary estimate of the association between DM and active tuberculosis (TB). We searched Medline and EMBASE databases for studies reporting adjusted estimates on the TB–DM association published before December 22, 2015, with no restrictions on region and language. In the meta-analysis, adjusted estimates were pooled using a DerSimonian-Laird random-effects model, according to study design. Risk of bias assessment and sensitivity analyses were conducted. 44 eligible studies were included, which consisted of 58,468,404 subjects from 16 countries. Compared with non-DM patients, DM patients had 3.59–fold (95% confidence interval (CI) 2.25–5.73), 1.55–fold (95% CI 1.39–1.72), and 2.09–fold (95% CI 1.71–2.55) increased risk of active TB in four prospective, 16 retrospective, and 17 case-control studies, respectively. Country income level (3.16–fold in low/middle–vs. 1.73–fold in high–income countries), background TB incidence (2.05–fold in countries with >50 vs. 1.89–fold in countries with ≤50 TB cases per 100,000 person-year), and geographical region (2.44–fold in Asia vs. 1.71–fold in Europe and 1.73–fold in USA/Canada) affected appreciably the estimated association, but potential risk of bias, type of population (general versus clinical), and potential for duplicate data, did not. Microbiological ascertainment for TB (3.03–fold) and/or blood testing for DM (3.10–fold), as well as uncontrolled DM (3.30–fold), resulted in stronger estimated association. DM is associated with a two- to four-fold increased risk of active TB. The association was stronger when ascertainment was based on biological testing rather than medical records or self-report. The burgeoning DM epidemic could impact upon the achievements of the WHO “End TB Strategy” for reducing TB incidence.

A clinical scoring system to prioritise investigation for tuberculosis among adults attending HIV clinics in South Africa

Background

The World Health Organization (WHO) recommendation for regular tuberculosis (TB) screening of HIV-positive individuals with Xpert MTB/RIF as the first diagnostic test has major resource implications.

Objective

To develop a diagnostic prediction model for TB, for symptomatic adults attending for routine HIV care, to prioritise TB investigation.

Design

Cohort study exploring a TB testing algorithm.

Setting

HIV clinics, South Africa.

Participants

Representative sample of adult HIV clinic attendees; data from participants reporting ≥1 symptom on the WHO screening tool were split 50:50 to derive, then internally validate, a prediction model.

Outcome

TB, defined as “confirmed” if Xpert MTB/RIF, line probe assay or M. tuberculosis culture were positive; and “clinical” if TB treatment started without microbiological confirmation, within six months of enrolment.

Results

Overall, 79/2602 (3.0%) participants on ART fulfilled TB case definitions, compared to 65/906 (7.2%) pre-ART. Among 1133/3508 (32.3%) participants screening positive on the WHO tool, 1048 met inclusion criteria for this analysis: 52/515 (10.1%) in the derivation and 58/533 (10.9%) in the validation dataset had TB. Our final model comprised ART status (on ART > 3 months vs. pre-ART or ART < 3 months); body mass index (continuous); CD4 (continuous); number of WHO symptoms (1 vs. >1 symptom). We converted this to a clinical score, using clinically-relevant CD4 and BMI categories. A cut-off score of ≥3 identified those with TB with sensitivity and specificity of 91.8% and 34.3% respectively. If investigation was prioritised for individuals with score of ≥3, 68% (717/1048) symptomatic individuals would be tested, among whom the prevalence of TB would be 14.1% (101/717); 32% (331/1048) of tests would be avoided, but 3% (9/331) with TB would be missed amongst those not tested.

Conclusion

Our clinical score may help prioritise TB investigation among symptomatic individuals.

Epidemiologic link between tuberculosis and cigarette/biomass smoke exposure: Limitations despite the vast literature

The geographic overlap between the prevalence of cigarette smoke (CS) exposure and tuberculosis (TB) in the world is striking. In recent years, relatively large number of studies has linked cigarette or biomass fuel smoke exposure and various aspects of TB. Our goals are to summarize the significance of the known published studies, graphically represent reports that quantified the association and discuss their potential limitations. PubMed searches were performed using the key words 'tuberculosis' with 'cigarette', 'tobacco', 'smoke' or 'biomass fuel smoke.' The references of relevant articles were examined for additional pertinent papers. A large number of mostly case-control and cross-sectional studies significantly associate both direct and second-hand smoke exposure with tuberculous infection, active TB, and/or more severe and lethal TB. Fewer link biomass fuel smoke exposure and TB. While a number of studies interpreted the association with multivariate analysis, other confounders are often not accounted for in these analyses. It is also important to emphasize that these retrospective studies can only show an association and not any causal link. We further explored the possibility that even if CS exposure is a risk factor for TB, several mechanisms may be responsible. Numerous studies associate cigarette and biomass smoke exposure with TB but the mechanism(s) remains largely unknown. While the associative link of these two health maladies is well established, more definitive, mechanistic studies are needed to cement the effect of smoke exposure on TB pathogenesis and to utilize this knowledge in empowering public health policies.