Background: The increasing incidence and mortality rates of tuberculosis among older individuals who suffer from multiple morbidities and are vulnerable to malnutrition are major obstacles to efforts to eradicate tuberculosis in the Republic of Korea. Herein, we identified the factors associated with mortality during anti-tuberculosis treatment in patients with pulmonary tuberculosis. Methods: We conducted a case-control study and extracted data from the database of a multi-center prospective observational cohort study in Korea. Among the participants with rifampicin-susceptible pulmonary tuberculosis, the survival group was defined as those who successfully completed treatment within one year, whereas the mortality group was defined as those who died during treatment. Univariable and multivariable logistic regression analyses were performed to identify factors associated with TB mortality. Results: Among 1,119 participants with pulmonary TB registered between 2019 and 2021, 799 and 59 were grouped in the survival and mortality groups, respectively. Age, positive smear results, alarming symptoms, nutrition risk score, Charlson comorbidity index score, and initial standard treatment regimen were significant based on univariable analysis and were selected for the multivariable logistic regression model. Nutrition risk score (adjusted odds ratio, 2.44; 95% confidence interval, 1.72–3.48) and Charlson comorbidity index score (adjusted odds ratio, 1.62; 95% confidence interval, 1.35–1.94) remained statistically significant in the multivariate analysis. Conclusion Nutritional status and comorbidities at baseline were identified as important factors associated with mortality in patients with pulmonary tuberculosis.

Background: The increasing incidence and mortality rates of tuberculosis among older individuals who suffer from multiple morbidities and are vulnerable to malnutrition are major obstacles to efforts to eradicate tuberculosis in the Republic of Korea. Herein, we identified the factors associated with mortality during anti-tuberculosis treatment in patients with pulmonary tuberculosis. Methods: We conducted a case-control study and extracted data from the database of a multi-center prospective observational cohort study in Korea. Among the participants with rifampicin-susceptible pulmonary tuberculosis, the survival group was defined as those who successfully completed treatment within one year, whereas the mortality group was defined as those who died during treatment. Univariable and multivariable logistic regression analyses were performed to identify factors associated with TB mortality. Results: Among 1,119 participants with pulmonary TB registered between 2019 and 2021, 799 and 59 were grouped in the survival and mortality groups, respectively. Age, positive smear results, alarming symptoms, nutrition risk score, Charlson comorbidity index score, and initial standard treatment regimen were significant based on univariable analysis and were selected for the multivariable logistic regression model. Nutrition risk score (adjusted odds ratio, 2.44; 95% confidence interval, 1.72–3.48) and Charlson comorbidity index score (adjusted odds ratio, 1.62; 95% confidence interval, 1.35–1.94) remained statistically significant in the multivariate analysis. Conclusion Nutritional status and comorbidities at baseline were identified as important factors associated with mortality in patients with pulmonary tuberculosis.

Background: The increasing incidence and mortality rates of tuberculosis among older individuals who suffer from multiple morbidities and are vulnerable to malnutrition are major obstacles to efforts to eradicate tuberculosis in the Republic of Korea. Herein, we identified the factors associated with mortality during anti-tuberculosis treatment in patients with pulmonary tuberculosis. Methods: We conducted a case-control study and extracted data from the database of a multi-center prospective observational cohort study in Korea. Among the participants with rifampicin-susceptible pulmonary tuberculosis, the survival group was defined as those who successfully completed treatment within one year, whereas the mortality group was defined as those who died during treatment. Univariable and multivariable logistic regression analyses were performed to identify factors associated with TB mortality. Results: Among 1,119 participants with pulmonary TB registered between 2019 and 2021, 799 and 59 were grouped in the survival and mortality groups, respectively. Age, positive smear results, alarming symptoms, nutrition risk score, Charlson comorbidity index score, and initial standard treatment regimen were significant based on univariable analysis and were selected for the multivariable logistic regression model. Nutrition risk score (adjusted odds ratio, 2.44; 95% confidence interval, 1.72–3.48) and Charlson comorbidity index score (adjusted odds ratio, 1.62; 95% confidence interval, 1.35–1.94) remained statistically significant in the multivariate analysis. Conclusion Nutritional status and comorbidities at baseline were identified as important factors associated with mortality in patients with pulmonary tuberculosis.

Background: The increasing incidence and mortality rates of tuberculosis among older individuals who suffer from multiple morbidities and are vulnerable to malnutrition are major obstacles to efforts to eradicate tuberculosis in the Republic of Korea. Herein, we identified the factors associated with mortality during anti-tuberculosis treatment in patients with pulmonary tuberculosis. Methods: We conducted a case-control study and extracted data from the database of a multi-center prospective observational cohort study in Korea. Among the participants with rifampicin-susceptible pulmonary tuberculosis, the survival group was defined as those who successfully completed treatment within one year, whereas the mortality group was defined as those who died during treatment. Univariable and multivariable logistic regression analyses were performed to identify factors associated with TB mortality. Results: Among 1,119 participants with pulmonary TB registered between 2019 and 2021, 799 and 59 were grouped in the survival and mortality groups, respectively. Age, positive smear results, alarming symptoms, nutrition risk score, Charlson comorbidity index score, and initial standard treatment regimen were significant based on univariable analysis and were selected for the multivariable logistic regression model. Nutrition risk score (adjusted odds ratio, 2.44; 95% confidence interval, 1.72–3.48) and Charlson comorbidity index score (adjusted odds ratio, 1.62; 95% confidence interval, 1.35–1.94) remained statistically significant in the multivariate analysis. Conclusion Nutritional status and comorbidities at baseline were identified as important factors associated with mortality in patients with pulmonary tuberculosis.

Objective: The performance of large language models (LLMs) and their potential utility in obstetric and gynecological education are topics of ongoing debate. This study aimed to contribute to this discussion by examining the recent advancements in LLM technology and their transformative potential in artificial intelligence. Methods: This study assessed the performance of generative pre-trained transformer (GPT)-3.5 and -4 in understanding clinical information, as well as its potential implications for obstetric and gynecological education. Obstetrics and gynecology residents at three hospitals underwent an annual promotional examination, from which 116 of the 170 questions over 4 years (2020-2023) were analyzed, excluding 54 questions with images. The scores achieved by GPT-3.5, -4, and the 100 residents were compared. Results: The average scores across all 4 years for GPT-3.5 and -4 were 38.79 (standard deviation [SD], 5.65) and 79.31 (SD, 3.67), respectively. For groups first-year resident, second-year resident, and third-year resident, the cumulative annual average scores were 79.12 (SD, 9.00), 80.95 (SD, 5.86), and 83.60 (SD, 6.82), respectively. No statistically significant differences were observed between the scores of GPT-4.0 and those of the residents. When analyzing questions specific to obstetrics, the average scores for GPT-3.5 and -4.0 were 33.44 (SD, 10.18) and 90.22 (SD, 7.68), respectively. Conclusion GPT-4 demonstrated exceptional performance in obstetrics, different types of data interpretation, and problem solving, showcasing the potential utility of LLMs in these areas. However, acknowledging the constraints of LLMs is crucial and their utilization should augment human expertise and discernment.