Background: This study aimed to determine whether a shorter high-dose rifampicin regimen is non-inferior to the standard 6-month tuberculosis regimen. Methods: This multicenter, randomized, open-label, non-inferiority trial enrolled participants with respiratory specimen positivity by Xpert MTB/RIF assay or Mycobacterium tuberculosis culture without rifampicin-resistance. Participants were randomized at 1:1 to the investigational or control group. The investigational group received high-dose rifampicin (30 mg/kg/day), isoniazid, and pyrazinamide until culture conversion, followed by high-dose rifampicin and isoniazid for 12 weeks. The control group received the standard 6-month regimen. The primary outcome was the rate of unfavorable outcomes at 18 months post-randomization. The non-inferiority margin was set at <6% difference in unfavorable outcomes rates. The study is registered with ClinicalTrials.gov (NCT04485156) Results: Between 4 November 2020 and 3 January 2022, 76 participants were enrolled. Of these, 58 were included in the modified intention-to-treat analysis. Unfavorable outcomes occurred in 10 (31.3%) of 32 in the control group and 10 (38.5%) of 26 in the investigational group. The difference was 7.2% (95% confidence interval, ∞ to 31.9%), failing to prove non-inferiority. Serious adverse events and grade 3 or higher adverse events did not differ between the groups. Conclusion The shorter high-dose rifampicin regimen failed to demonstrate non-inferiority but had an acceptable safety profile.

Purpose: This study aimed to explore the effects of both the presence and size of posterior subependymal germinal matrix hemorrhage (PS-GMH), considered a mild form of hemorrhage, on the neurodevelopmental outcomes of extremely preterm infants. Methods: A retrospective analysis was conducted on 221 extremely preterm infants, assessing their initial and term-equivalent age (TEA) cranial ultrasound (cUS) examinations from 2016 to 2021. Infants were classified based on the presence and size (small/large) of PS-GMH. Neurodevelopmental outcomes at corrected ages of 18-24 months were analyzed in 135 infants. Results: PS-GMH was identified in 86.9% (192/221) of the infants, with 13.5% (26/192) exhibiting large PS-GMH. Among the 135 infants who were followed up, those with PS-GMH were found to have younger gestational ages (P<0.001) and a higher incidence of maternal chorioamnionitis (P=0.016) than those without PS-GMH. Significant differences were observed in the incidence of grade II intraventricular hemorrhage (IVH) on initial cUS (P=0.003) and ventriculomegaly at TEA cUS (P=0.026) across the groups with no PS-GMH, small PS-GMH, and large PS-GMH. The large PS-GMH group exhibited a higher occurrence of grade II IVH than the small PS-GMH group (P=0.006). However, ventriculomegaly incidence did not significantly vary with PS-GMH status. Neurodevelopmental outcomes were also not significantly different across PS-GMH statuses. The adjusted odds ratios for any neurodevelopmental impairment, compared to the no PS-GMH group, were 1.70 (95% confidence interval [CI], 0.40 to 7.26; P=0.471) for all PS-GMH, 1.61 (95% CI, 0.37 to 6.93; P=0.526) for small PS-GMH, and 3.84 (95% CI, 0.62 to 24.00; P=0.150) for large PS-GMH. Conclusion PS-GMH was frequently observed in extremely preterm infants; however, it did not independently predict adverse neurodevelopmental outcomes.

Objective: To prospectively evaluate the effect of accelerated deep learning-based reconstruction (Accel-DL) on improving brain magnetic resonance imaging (MRI) quality and reducing scan time compared to that in conventional MRI. Materials and Methods: This study included 150 participants (51 male; mean age 57.3 ± 16.2 years). Each group of 50 participants was scanned using one of three 3T scanners from three different vendors. Conventional and Accel-DL MRI images were obtained from each participant and compared using 2D T1- and T2-weighted and 3D gradient-echo sequences. Accel-DL acquisition was achieved using optimized scan parameters to reduce the scan time, with the acquired images reconstructed using U-Net-based software to transform low-quality, undersampled k-space data into high-quality images. The scan times of Accel-DL and conventional MRI methods were compared. Four neuroradiologists assessed the overall image quality, structural delineation, and artifacts using Likert scale (5- and 3-point scales). Inter-reader agreement was assessed using Fleiss’ kappa coefficient. Signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) were calculated, and volumetric quantification of regional structures and white matter hyperintensities (WMHs) was performed. Results: Accel-DL showed a mean scan time reduction of 39.4% (range, 24.2%–51.3%). Accel-DL improved overall image quality (3.78 ± 0.71 vs. 3.36 ± 0.61, P < 0.001), structure delineation (2.47 ± 0.61 vs. 2.35 ± 0.62, P < 0.001), and artifacts (3.73 ± 0.72 vs. 3.71 ± 0.69, P = 0.016). Inter-reader agreement was fair to substantial (κ = 0.34–0.50). SNR and CNR increased in Accel-DL (82.0 ± 23.1 vs. 31.4 ± 10.8, P = 0.02; 12.4 ± 4.1 vs. 4.4 ± 11.2, P = 0.02). Bland-Altman plots revealed no significant differences in the volumetric measurements of 98.2% of the relevant regions, except in the deep gray matter, including the thalamus. Five of the six lesion categories showed no significant differences in WMH segmentation, except for leukocortical lesions (r = 0.64 ± 0.29). Conclusion Accel-DL substantially reduced the scan time and improved the quality of brain MRI in both spin-echo and gradientecho sequences without compromising volumetry, including lesion quantification.

Objective: To prospectively evaluate the effect of accelerated deep learning-based reconstruction (Accel-DL) on improving brain magnetic resonance imaging (MRI) quality and reducing scan time compared to that in conventional MRI. Materials and Methods: This study included 150 participants (51 male; mean age 57.3 ± 16.2 years). Each group of 50 participants was scanned using one of three 3T scanners from three different vendors. Conventional and Accel-DL MRI images were obtained from each participant and compared using 2D T1- and T2-weighted and 3D gradient-echo sequences. Accel-DL acquisition was achieved using optimized scan parameters to reduce the scan time, with the acquired images reconstructed using U-Net-based software to transform low-quality, undersampled k-space data into high-quality images. The scan times of Accel-DL and conventional MRI methods were compared. Four neuroradiologists assessed the overall image quality, structural delineation, and artifacts using Likert scale (5- and 3-point scales). Inter-reader agreement was assessed using Fleiss’ kappa coefficient. Signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) were calculated, and volumetric quantification of regional structures and white matter hyperintensities (WMHs) was performed. Results: Accel-DL showed a mean scan time reduction of 39.4% (range, 24.2%–51.3%). Accel-DL improved overall image quality (3.78 ± 0.71 vs. 3.36 ± 0.61, P < 0.001), structure delineation (2.47 ± 0.61 vs. 2.35 ± 0.62, P < 0.001), and artifacts (3.73 ± 0.72 vs. 3.71 ± 0.69, P = 0.016). Inter-reader agreement was fair to substantial (κ = 0.34–0.50). SNR and CNR increased in Accel-DL (82.0 ± 23.1 vs. 31.4 ± 10.8, P = 0.02; 12.4 ± 4.1 vs. 4.4 ± 11.2, P = 0.02). Bland-Altman plots revealed no significant differences in the volumetric measurements of 98.2% of the relevant regions, except in the deep gray matter, including the thalamus. Five of the six lesion categories showed no significant differences in WMH segmentation, except for leukocortical lesions (r = 0.64 ± 0.29). Conclusion Accel-DL substantially reduced the scan time and improved the quality of brain MRI in both spin-echo and gradientecho sequences without compromising volumetry, including lesion quantification.

Background: This study aimed to determine whether a shorter high-dose rifampicin regimen is non-inferior to the standard 6-month tuberculosis regimen. Methods: This multicenter, randomized, open-label, non-inferiority trial enrolled participants with respiratory specimen positivity by Xpert MTB/RIF assay or Mycobacterium tuberculosis culture without rifampicin-resistance. Participants were randomized at 1:1 to the investigational or control group. The investigational group received high-dose rifampicin (30 mg/kg/day), isoniazid, and pyrazinamide until culture conversion, followed by high-dose rifampicin and isoniazid for 12 weeks. The control group received the standard 6-month regimen. The primary outcome was the rate of unfavorable outcomes at 18 months post-randomization. The non-inferiority margin was set at <6% difference in unfavorable outcomes rates. The study is registered with ClinicalTrials.gov (NCT04485156) Results: Between 4 November 2020 and 3 January 2022, 76 participants were enrolled. Of these, 58 were included in the modified intention-to-treat analysis. Unfavorable outcomes occurred in 10 (31.3%) of 32 in the control group and 10 (38.5%) of 26 in the investigational group. The difference was 7.2% (95% confidence interval, ∞ to 31.9%), failing to prove non-inferiority. Serious adverse events and grade 3 or higher adverse events did not differ between the groups. Conclusion The shorter high-dose rifampicin regimen failed to demonstrate non-inferiority but had an acceptable safety profile.

Purpose: This study aimed to explore the effects of both the presence and size of posterior subependymal germinal matrix hemorrhage (PS-GMH), considered a mild form of hemorrhage, on the neurodevelopmental outcomes of extremely preterm infants. Methods: A retrospective analysis was conducted on 221 extremely preterm infants, assessing their initial and term-equivalent age (TEA) cranial ultrasound (cUS) examinations from 2016 to 2021. Infants were classified based on the presence and size (small/large) of PS-GMH. Neurodevelopmental outcomes at corrected ages of 18-24 months were analyzed in 135 infants. Results: PS-GMH was identified in 86.9% (192/221) of the infants, with 13.5% (26/192) exhibiting large PS-GMH. Among the 135 infants who were followed up, those with PS-GMH were found to have younger gestational ages (P<0.001) and a higher incidence of maternal chorioamnionitis (P=0.016) than those without PS-GMH. Significant differences were observed in the incidence of grade II intraventricular hemorrhage (IVH) on initial cUS (P=0.003) and ventriculomegaly at TEA cUS (P=0.026) across the groups with no PS-GMH, small PS-GMH, and large PS-GMH. The large PS-GMH group exhibited a higher occurrence of grade II IVH than the small PS-GMH group (P=0.006). However, ventriculomegaly incidence did not significantly vary with PS-GMH status. Neurodevelopmental outcomes were also not significantly different across PS-GMH statuses. The adjusted odds ratios for any neurodevelopmental impairment, compared to the no PS-GMH group, were 1.70 (95% confidence interval [CI], 0.40 to 7.26; P=0.471) for all PS-GMH, 1.61 (95% CI, 0.37 to 6.93; P=0.526) for small PS-GMH, and 3.84 (95% CI, 0.62 to 24.00; P=0.150) for large PS-GMH. Conclusion PS-GMH was frequently observed in extremely preterm infants; however, it did not independently predict adverse neurodevelopmental outcomes.

Background: The World Health Organization has declared the end of the coronavirus disease 2019 (COVID-19) public health emergency. However, this did not indicate the end of COVID-19. Several months after the infection, numerous patients complain of respiratory or nonspecific symptoms; this condition is called long COVID. Even patients with mild COVID-19 can experience long COVID, thus the burden of long COVID remains considerable. Therefore, we conducted this study to comprehensively analyze the effects of long COVID using multi-faceted assessments. Materials and Methods: We conducted a prospective cohort study involving patients diagnosed with COVID-19 between February 2020 and September 2021 in six tertiary hospitals in Korea. Patients were followed up at 1, 3, 6, 12, 18, and 24 months after discharge. Long COVID was defined as the persistence of three or more COVID-19-related symptoms. The primary outcome of this study was the prevalence of long COVID after the period of COVID-19. Results: During the study period, 290 patients were enrolled. Among them, 54.5 and 34.6% experienced long COVID within 6 months and after more than 18 months, respectively. Several patients showed abnormal results when tested for post-traumatic stress disorder (17.4%) and anxiety (31.9%) after 18 months. In patients who underwent follow-up chest computed tomography 18 months after COVID-19, abnormal findings remained at 51.9%. Males (odds ratio [OR], 0.17; 95% confidence interval [CI], 0.05–0.53; P=0.004) and elderly (OR, 1.04; 95% CI, 1.00–1.09; P=0.04) showed a significant association with long COVID after 12–18 months in a multivariable logistic regression analysis. Conclusion Many patients still showed long COVID after 18 months post SARS-CoV-2 infection. When managing these patients, the assessment of multiple aspects is necessary.

Background/Aims: The Korean guidelines for Helicobacter pylori treatment were revised in 2020, however, the extent of adherence to these guidelines in clinical practice remains unclear. Herein, we initiated a prospective, nationwide, multicenter registry study in 2021 to evaluate the current management of H.pylori infection in Korea. Methods: This interim report describes the adherence to the revised guidelines and their impact on firstline eradication rates. Data on patient demographics, diagnoses, treatments, and eradication outcomes were collected using a web-based electronic case report form. Results: A total of 7,261 patients from 66 hospitals who received first-line treatment were analyzed.The modified intention-to-treat eradication rate for first-line treatment was 81.0%, with 80.4% of the prescriptions adhering to the revised guidelines. The most commonly prescribed regimen was the 14-day clarithromycin-based triple therapy (CTT; 42.0%), followed by tailored therapy (TT; 21.2%), 7-day CTT (14.1%), and 10-day concomitant therapy (CT; 10.1%). Time-trend analysis demonstrated significant increases in guideline adherence and the use of 10-day CT and TT, along with a decrease in the use of 7-day CTT (all p<0.001). Multivariate logistic regression analysis revealed that guideline adherence was significantly associated with first-line eradication success (odds ratio, 2.03; 95% confidence interval, 1.61 to 2.56; p<0.001). Conclusions The revised guidelines for the treatment of H. pylori infection have been increasingly adopted in routine clinical practice in Korea, which may have contributed to improved first-line eradication rates. Notably, the 14-day CTT, 10-day CT, and TT regimens are emerging as the preferred first-line treatment options among Korean physicians.

The common data model (CDM) has found widespread application in healthcare studies, but its utilization in cancer research has been limited. This article describes the development and implementation strategy for Cancer Clinical Library Databases (CCLDs), which are standardized cancer-specific databases established under the Korea-Clinical Data Utilization Network for Research Excellence (K-CURE) project by the Korean Ministry of Health and Welfare. Fifteen leading hospitals and fourteen academic associations in Korea are engaged in constructing CCLDs for 10 primary cancer types. For each cancer type-specific CCLD, cancer data experts determine key clinical data items essential for cancer research, standardize these items across cancer types, and create a standardized schema. Comprehensive clinical records covering diagnosis, treatment, and outcomes, with annual updates, are collected for each cancer patient in the target population, and quality control is based on six-sigma standards. To protect patient privacy, CCLDs follow stringent data security guidelines by pseudonymizing personal identification information and operating within a closed analysis environment. Researchers can apply for access to CCLD data through the K-CURE portal, which is subject to Institutional Review Board and Data Review Board approval. The CCLD is considered a pioneering standardized cancer-specific database, significantly representing Korea’s cancer data. It is expected to overcome limitations of previous CDMs and provide a valuable resource for multicenter cancer research in Korea.

Objective: To prospectively evaluate the effect of accelerated deep learning-based reconstruction (Accel-DL) on improving brain magnetic resonance imaging (MRI) quality and reducing scan time compared to that in conventional MRI. Materials and Methods: This study included 150 participants (51 male; mean age 57.3 ± 16.2 years). Each group of 50 participants was scanned using one of three 3T scanners from three different vendors. Conventional and Accel-DL MRI images were obtained from each participant and compared using 2D T1- and T2-weighted and 3D gradient-echo sequences. Accel-DL acquisition was achieved using optimized scan parameters to reduce the scan time, with the acquired images reconstructed using U-Net-based software to transform low-quality, undersampled k-space data into high-quality images. The scan times of Accel-DL and conventional MRI methods were compared. Four neuroradiologists assessed the overall image quality, structural delineation, and artifacts using Likert scale (5- and 3-point scales). Inter-reader agreement was assessed using Fleiss’ kappa coefficient. Signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) were calculated, and volumetric quantification of regional structures and white matter hyperintensities (WMHs) was performed. Results: Accel-DL showed a mean scan time reduction of 39.4% (range, 24.2%–51.3%). Accel-DL improved overall image quality (3.78 ± 0.71 vs. 3.36 ± 0.61, P < 0.001), structure delineation (2.47 ± 0.61 vs. 2.35 ± 0.62, P < 0.001), and artifacts (3.73 ± 0.72 vs. 3.71 ± 0.69, P = 0.016). Inter-reader agreement was fair to substantial (κ = 0.34–0.50). SNR and CNR increased in Accel-DL (82.0 ± 23.1 vs. 31.4 ± 10.8, P = 0.02; 12.4 ± 4.1 vs. 4.4 ± 11.2, P = 0.02). Bland-Altman plots revealed no significant differences in the volumetric measurements of 98.2% of the relevant regions, except in the deep gray matter, including the thalamus. Five of the six lesion categories showed no significant differences in WMH segmentation, except for leukocortical lesions (r = 0.64 ± 0.29). Conclusion Accel-DL substantially reduced the scan time and improved the quality of brain MRI in both spin-echo and gradientecho sequences without compromising volumetry, including lesion quantification.