Objectives: In South Korea, there has been a continuous decrease in the incidence of tuberculosis (TB) attributable to a national TB elimination program; however, TB still poses a significant socioeconomic burden. This study aimed to analyze factors associated with successful TB treatment and to identify refractory patient groups with unfavorable outcomes. Methods: We analyzed anonymized data on 89,150 patients with TB provided by the Korea Disease Control and Prevention Agency. Specifically, we collected independent variables, which were categorized as individual, regional, and medical facility factors. Individual factors included age, sex, nationality, TB type, drug-resistant status, category of TB, housing type, underlying disease status, number of referrals, and smoking status. Regional factors referred to the region where the TB case was reported. Medical facility factors included the first visit to a medical facility, categorized by hospital type and the distinction between private–public mix (PPM) and non-PPM depending on the presence or absence of dedicated TB nurses. These factors were analyzed in relation to treatment success to identify refractory patient groups with unfavorable outcomes. Results: Multivariable logistic regression analysis revealed the following significant factors associated with successful TB treatment: sex, nationality, status of drug-resistant TB, category of TB, number of referrals, region of TB registry, underlying diseases, and smoking status. Specifically, compared with their relevant counterparts, male patients had a lower rate of successful treatment (adjusted odds ratio [aOR]: 0.66, reference [Ref.]: women); Korean nationals had a higher rate of treatment success (aOR: 7.20, Ref. foreign residents in Korea); resistant TB was associated with a lower rate of treatment success (aOR: 0.35, Ref.: non-resistant TB status); newly treated patients had a higher rate of treatment success (aOR: 1.75, Ref.: retreatment patient); switching hospitals once (aOR: 1.78), never (aOR: 1.41), or twice (aOR: 1.37) was associated with increased treatment success (Ref.: three or more times); having zero (aOR: 1.45), one (aOR: 1.31), or two (aOR: 1.24) underlying diseases was associated with a higher rate of treatment success (Ref. three or more underlying diseases); and past smokers (aOR: 1.40) and non-smokers (aOR: 1.35) had a higher rate of treatment success (Ref.: current smokers). Conclusions: Our study identified several factors contributing to unfavorable treatment outcomes in tuberculosis patients, including male patients, foreign residents in Korea, drug-resistant TB, retreatment patients, frequent hospital switching, multiple underlying diseases, and current smoking status. These research findings could inform the development of efficient management strategies and policies for improving the treatment success rate among patients with TB.

Delayed isolation of tuberculosis (TB) can cause unexpected exposure of healthcare workers (HCWs). This study identified the predictive factors and clinical impact of delayed isolation. We retrospectively reviewed the electronic medical records of index patients and HCWs who underwent contact investigation after TB exposure during hospitalization at the National Medical Center, between January 2018 and July 2021. Among the 25 index patients, 23 (92.0%) were diagnosed with TB based on the molecular assay, and 18 (72.0%) had a negative acid-fast bacilli smear. Sixteen (64.0%) patients were hospitalized via the emergency room, and 18 (72.0%) were admitted to a non-pulmonology/infectious disease department. According to the patterns of delayed isolation, patients were classified into five categories. Among 157 close-contact events in 125 HCWs, 75 (47.8%) occurred in Category A. Twenty-five (20%) HCWs had multiple TB exposures (n = 57 events), of whom 37 (64.9%) belonged to Category A (missed during emergency situations). After contact tracing, latent TB infection was diagnosed in one (1.2%) HCW in Category A, who was exposed during intubation. Delayed isolation and TB exposure mostly occurred during pre-admission in emergency situations. Effective TB screening and infection control are necessary to protect HCWs, especially those who routinely contact new patients in high-risk departments.

Serological tests offer the potential in order to improve the diagnosis of tuberculosis (TB). Macrophage migration inhibitory factor (MIF) plays a protective role in infection control in TB; however, to date, no studies on antibody responses to MIF have been reported. We measured immunoglobulin (Ig)A and IgG responses to MIF in individuals with either active tuberculosis (ATB; n = 65), latent tuberculosis (LTBI; n = 53), or in non-infected individuals (NI; n = 62). The QuantiFERON-TB Gold In-Tube (QFT-GIT) assay was used in order to screen for LTBI. The level of IgA against MIF was significantly lower in LTBI and ATB patients than in NI individuals, was significantly related to LTBI and ATB diagnosis, and it could discriminate between LTBI and ATB. In contrast, the level of IgG against MIF was significantly lower in LTBI patients than in NI individuals and was significantly related to LTBI diagnosis. Anti-MIF IgG levels were significantly lower in AFB-negative TB, minimal TB, and new ATB patients, than in the NI group. IgA and IgG levels against MIF both showed significant negative correlations with IFN-γ levels, as assessed using the QFT-GIT test. Although none of the antibodies could achieve high diagnostic predictive power individually, our results suggest the possibility of using IgA antibody responses to MIF in the diagnosis of LTBI and ATB.