Background/Aims: The coronavirus disease 2019 (COVID-19) pandemic has significantly impacted global health, exacerbated metabolic health issues, and altered lifestyle behaviors. This study examined the sex-specific impact of the COVID-19 outbreak on the incidence of metabolic syndrome using data from the Korea National Health and Nutrition Examination Survey (KNHANES). Methods: Data from the KNHANES VII (2018) and VIII (2019–2021), including 15,499 participants, were analyzed. The study population was stratified by sex, and further subdivisions were conducted based on the timeframe relative to the COVID-19 outbreak. Variables such as age, education level, household income, smoking status, and high-risk drinking were analyzed to assess their influence on the prevalence of metabolic syndrome. Results: The overall prevalence of metabolic syndrome significantly increased from 28.11% before the outbreak to 29.69% after the outbreak. Both males and females reported significant increases in waist circumference and fasting glucose levels. Age and education level differentially influenced the prevalence of metabolic syndrome between the sex. Smoking was significantly associated with increased prevalence in males, whereas high-risk drinking was associated with increased prevalence in males and decreased prevalence in females. Conclusions The COVID-19 pandemic has significantly increased the prevalence of metabolic syndrome with notable sex-specific differences. These findings highlight the need for sex-specific public health interventions to mitigate the impact of the pandemic on metabolic health.

Background/Aims: To analyze the characteristics of the sputum microbiota of patients with nontuberculous mycobacteria pulmonary disease (NTM-PD) based on treatment status. Methods: Twenty-eight sputum samples from 14 patients with NTM-PD, including 14 samples from the microbiologically cured group (7 at baseline and 7 during follow-up) and 14 from the treatment-refractory group (7 at baseline and 7 during follow-up) were included in this study. Bacterial microbiota was analyzed by sequencing the V3–V4 region of the 16S rRNA gene. Results: Among the 14 patients, most had infections with Mycobacterium avium complex (n = 6), followed by Mycobacterium abscessus (n = 5); three patients exhibited mixed infection with both organisms. Alpha-diversity was higher in the cured group than in the treatment refractory group in both the baseline sputum (ACE, p = 0.005; Chao1, p = 0.010; Jackknife, p = 0.022, 0.043; Shannon, p = 0.048) and follow-up sputum (ACE, p = 0.018). Linear discriminant analysis effect size revealed that several taxa showed differential distributions based on treatment status. At the species level, Streptococcus pneumoniae, Prevotella melaninogenica, Haemophilus parahaemolyticus, Haemophilus haemolyticus, Fusobacterium nucleatum, Neisseria elongata, and Prevotella denticola were more abundant in sputum from the microbiologically cured group than in that from the refractory group (all p < 0.05). Conclusions In contrast to patients with treatment-refractory NTM-PD, those with stable disease without recurrence had higher microbial diversity in their sputum, including several predominant taxa.

Purpose: Renal allograft rejection, either acute or chronic, is prevalent among many recipients. This study aimed to identify multiple Doppler ultrasound parameters for predicting renal allograft rejection. Materials and Methods: Between November 2021 and April 2022, 61 renal allograft recipients were studied prospectively after excluding two patients with dual transplants and seven with hydronephrosis. The analysis excluded 11 cases (10 due to missing Doppler data or pathology reports and one due to a high interquartile range/median dispersion value), resulting in a final analysis of 50 patients. Clinical characteristics, color Doppler imaging, superb microvascular imaging, and shear-wave imaging parameters were assessed by three experienced genitourinary radiologists. The Banff classification of the biopsy tissue served as the reference standard. Univariable and multivariable logistic regression, contingency matrices, and multiple machine-learning models were employed to estimate the associations. Results: Fifty kidney transplant recipients (mean age, 53.26±8.86 years; 29 men) were evaluated. Elasticity (≤14.8 kPa) demonstrated significant associations for predicting the combination of (borderline) T cell-mediated rejection (TCMR) categories (Banff categories 3 and 4) (p=0.006) and yielded equal or higher area under the receiver operating characteristics curve (AUC) values compared to various classifiers. Dispersion (>15.0 m/s/kHz) was the only significant factor for predicting the combination of nonTCMR categories (Banff categories 2, 5, and 6) (p=0.026) and showed equal or higher AUC values than multiple machine learning classifiers. Conclusion Elasticity (≤14.8 kPa) showed a significant association with the combination of (borderline) TCMR categories, whereas dispersion (>15.0 m/s/kHz) was significantly associated with the combination of non-TCMR categories in renal allografts.

Purpose: The Korean Cancer Study Group (KCSG) is a nationwide cancer clinical trial group dedicated to advancing investigator-initiated trials (IITs) by conducting and supporting clinical trials. This study aims to review IITs conducted by KCSG and quantitatively evaluate the survival and financial benefits of IITs for patients. Materials and Methods: We reviewed IITs conducted by KCSG from 1998 to 2023, analyzing progression-free survival (PFS) and overall survival (OS) gains for participants. PFS and OS benefits were calculated as the difference in median survival times between the intervention and control groups, multiplied by the number of patients in the intervention group. Financial benefits were assessed based on the cost of investigational products provided. Results: From 1998 to 2023, KCSG conducted 310 IITs, with 133 completed and published. Of these, 21 were included in the survival analysis. The analysis revealed that 1,951 patients in the intervention groups gained a total of 2,558.4 months (213.2 years) of PFS and 2,501.6 months (208.5 years) of OS, with median gains of 1.31 months in PFS and 1.58 months in OS per patient. When analyzing only statistically significant results, PFS and OS gain per patients was 1.69 months and 3.02 months, respectively. Investigational drug cost analysis from six available IITs indicated that investigational products provided to 252 patients were valued at 10,400,077,294 won (approximately 8,046,481 US dollars), averaging about 41,270,148 won (approximately 31,930 US dollars) per patient. Conclusion Our findings, based on analysis of published research, suggest that IITs conducted by KCSG led to survival benefits for participants and, in some studies, may have provided financial benefits by providing investment drugs.

Background/Aims: The coronavirus disease 2019 (COVID-19) pandemic has significantly impacted global health, exacerbated metabolic health issues, and altered lifestyle behaviors. This study examined the sex-specific impact of the COVID-19 outbreak on the incidence of metabolic syndrome using data from the Korea National Health and Nutrition Examination Survey (KNHANES). Methods: Data from the KNHANES VII (2018) and VIII (2019–2021), including 15,499 participants, were analyzed. The study population was stratified by sex, and further subdivisions were conducted based on the timeframe relative to the COVID-19 outbreak. Variables such as age, education level, household income, smoking status, and high-risk drinking were analyzed to assess their influence on the prevalence of metabolic syndrome. Results: The overall prevalence of metabolic syndrome significantly increased from 28.11% before the outbreak to 29.69% after the outbreak. Both males and females reported significant increases in waist circumference and fasting glucose levels. Age and education level differentially influenced the prevalence of metabolic syndrome between the sex. Smoking was significantly associated with increased prevalence in males, whereas high-risk drinking was associated with increased prevalence in males and decreased prevalence in females. Conclusions The COVID-19 pandemic has significantly increased the prevalence of metabolic syndrome with notable sex-specific differences. These findings highlight the need for sex-specific public health interventions to mitigate the impact of the pandemic on metabolic health.

Background/Aims: To analyze the characteristics of the sputum microbiota of patients with nontuberculous mycobacteria pulmonary disease (NTM-PD) based on treatment status. Methods: Twenty-eight sputum samples from 14 patients with NTM-PD, including 14 samples from the microbiologically cured group (7 at baseline and 7 during follow-up) and 14 from the treatment-refractory group (7 at baseline and 7 during follow-up) were included in this study. Bacterial microbiota was analyzed by sequencing the V3–V4 region of the 16S rRNA gene. Results: Among the 14 patients, most had infections with Mycobacterium avium complex (n = 6), followed by Mycobacterium abscessus (n = 5); three patients exhibited mixed infection with both organisms. Alpha-diversity was higher in the cured group than in the treatment refractory group in both the baseline sputum (ACE, p = 0.005; Chao1, p = 0.010; Jackknife, p = 0.022, 0.043; Shannon, p = 0.048) and follow-up sputum (ACE, p = 0.018). Linear discriminant analysis effect size revealed that several taxa showed differential distributions based on treatment status. At the species level, Streptococcus pneumoniae, Prevotella melaninogenica, Haemophilus parahaemolyticus, Haemophilus haemolyticus, Fusobacterium nucleatum, Neisseria elongata, and Prevotella denticola were more abundant in sputum from the microbiologically cured group than in that from the refractory group (all p < 0.05). Conclusions In contrast to patients with treatment-refractory NTM-PD, those with stable disease without recurrence had higher microbial diversity in their sputum, including several predominant taxa.

Purpose: Renal allograft rejection, either acute or chronic, is prevalent among many recipients. This study aimed to identify multiple Doppler ultrasound parameters for predicting renal allograft rejection. Materials and Methods: Between November 2021 and April 2022, 61 renal allograft recipients were studied prospectively after excluding two patients with dual transplants and seven with hydronephrosis. The analysis excluded 11 cases (10 due to missing Doppler data or pathology reports and one due to a high interquartile range/median dispersion value), resulting in a final analysis of 50 patients. Clinical characteristics, color Doppler imaging, superb microvascular imaging, and shear-wave imaging parameters were assessed by three experienced genitourinary radiologists. The Banff classification of the biopsy tissue served as the reference standard. Univariable and multivariable logistic regression, contingency matrices, and multiple machine-learning models were employed to estimate the associations. Results: Fifty kidney transplant recipients (mean age, 53.26±8.86 years; 29 men) were evaluated. Elasticity (≤14.8 kPa) demonstrated significant associations for predicting the combination of (borderline) T cell-mediated rejection (TCMR) categories (Banff categories 3 and 4) (p=0.006) and yielded equal or higher area under the receiver operating characteristics curve (AUC) values compared to various classifiers. Dispersion (>15.0 m/s/kHz) was the only significant factor for predicting the combination of nonTCMR categories (Banff categories 2, 5, and 6) (p=0.026) and showed equal or higher AUC values than multiple machine learning classifiers. Conclusion Elasticity (≤14.8 kPa) showed a significant association with the combination of (borderline) TCMR categories, whereas dispersion (>15.0 m/s/kHz) was significantly associated with the combination of non-TCMR categories in renal allografts.

Background/Aims: The coronavirus disease 2019 (COVID-19) pandemic has significantly impacted global health, exacerbated metabolic health issues, and altered lifestyle behaviors. This study examined the sex-specific impact of the COVID-19 outbreak on the incidence of metabolic syndrome using data from the Korea National Health and Nutrition Examination Survey (KNHANES). Methods: Data from the KNHANES VII (2018) and VIII (2019–2021), including 15,499 participants, were analyzed. The study population was stratified by sex, and further subdivisions were conducted based on the timeframe relative to the COVID-19 outbreak. Variables such as age, education level, household income, smoking status, and high-risk drinking were analyzed to assess their influence on the prevalence of metabolic syndrome. Results: The overall prevalence of metabolic syndrome significantly increased from 28.11% before the outbreak to 29.69% after the outbreak. Both males and females reported significant increases in waist circumference and fasting glucose levels. Age and education level differentially influenced the prevalence of metabolic syndrome between the sex. Smoking was significantly associated with increased prevalence in males, whereas high-risk drinking was associated with increased prevalence in males and decreased prevalence in females. Conclusions The COVID-19 pandemic has significantly increased the prevalence of metabolic syndrome with notable sex-specific differences. These findings highlight the need for sex-specific public health interventions to mitigate the impact of the pandemic on metabolic health.

Background/Aims: To analyze the characteristics of the sputum microbiota of patients with nontuberculous mycobacteria pulmonary disease (NTM-PD) based on treatment status. Methods: Twenty-eight sputum samples from 14 patients with NTM-PD, including 14 samples from the microbiologically cured group (7 at baseline and 7 during follow-up) and 14 from the treatment-refractory group (7 at baseline and 7 during follow-up) were included in this study. Bacterial microbiota was analyzed by sequencing the V3–V4 region of the 16S rRNA gene. Results: Among the 14 patients, most had infections with Mycobacterium avium complex (n = 6), followed by Mycobacterium abscessus (n = 5); three patients exhibited mixed infection with both organisms. Alpha-diversity was higher in the cured group than in the treatment refractory group in both the baseline sputum (ACE, p = 0.005; Chao1, p = 0.010; Jackknife, p = 0.022, 0.043; Shannon, p = 0.048) and follow-up sputum (ACE, p = 0.018). Linear discriminant analysis effect size revealed that several taxa showed differential distributions based on treatment status. At the species level, Streptococcus pneumoniae, Prevotella melaninogenica, Haemophilus parahaemolyticus, Haemophilus haemolyticus, Fusobacterium nucleatum, Neisseria elongata, and Prevotella denticola were more abundant in sputum from the microbiologically cured group than in that from the refractory group (all p < 0.05). Conclusions In contrast to patients with treatment-refractory NTM-PD, those with stable disease without recurrence had higher microbial diversity in their sputum, including several predominant taxa.

Purpose: Renal allograft rejection, either acute or chronic, is prevalent among many recipients. This study aimed to identify multiple Doppler ultrasound parameters for predicting renal allograft rejection. Materials and Methods: Between November 2021 and April 2022, 61 renal allograft recipients were studied prospectively after excluding two patients with dual transplants and seven with hydronephrosis. The analysis excluded 11 cases (10 due to missing Doppler data or pathology reports and one due to a high interquartile range/median dispersion value), resulting in a final analysis of 50 patients. Clinical characteristics, color Doppler imaging, superb microvascular imaging, and shear-wave imaging parameters were assessed by three experienced genitourinary radiologists. The Banff classification of the biopsy tissue served as the reference standard. Univariable and multivariable logistic regression, contingency matrices, and multiple machine-learning models were employed to estimate the associations. Results: Fifty kidney transplant recipients (mean age, 53.26±8.86 years; 29 men) were evaluated. Elasticity (≤14.8 kPa) demonstrated significant associations for predicting the combination of (borderline) T cell-mediated rejection (TCMR) categories (Banff categories 3 and 4) (p=0.006) and yielded equal or higher area under the receiver operating characteristics curve (AUC) values compared to various classifiers. Dispersion (>15.0 m/s/kHz) was the only significant factor for predicting the combination of nonTCMR categories (Banff categories 2, 5, and 6) (p=0.026) and showed equal or higher AUC values than multiple machine learning classifiers. Conclusion Elasticity (≤14.8 kPa) showed a significant association with the combination of (borderline) TCMR categories, whereas dispersion (>15.0 m/s/kHz) was significantly associated with the combination of non-TCMR categories in renal allografts.