Purpose: To evaluate the compatibility and usability of test results obtained from the IDRA and Keratograph 5M in clinical settings by comparing their performance in patients with dry eye disease. Methods: From December 27 to 30, 2022, a study was conducted on 30 patients diagnosed with dry eye utilizing both the Keratograph 5M and IDRA devices. The parameters compared and analyzed included lipid layer thickness, tear meniscus height, tear film break-up time, and meibography. A paired t-test was used for statistical comparison. The lipid layer thickness in the Keratograph 5M was graded on a scale from 0 to 4 based on thickness. Results: No significant differences were found between the two devices in tear film break-up time, tear meniscus height, and meibography (p = 0.148, 0.072, 0.124, respectively). However, the tear lipid layer thickness measured by IDRA showed a proportional relationship with the grade assigned by the Keratograph 5M (Kendall R = 0.217, p = 0.037; Spearman R = 0.260, p = 0.045). Conclusions The IDRA device offers the advantage of performing multiple dry eye tests; simultaneously, thereby saving time compared to the Keratograph 5M. Both devices can be used compatibly with IDRA particularly advantageous for providing a numerical value for tear lipid layer thickness which enhances the convenience of dry eye diagnosis and treatment.

Objective: To test the performance of an artificial intelligence-based computer-aided diagnosis (AI-CAD) designed for fullfield digital mammography (FFDM) when applied to synthetic mammography (SM). Materials and Methods: We analyzed 501 women (mean age, 57 ± 11 years) who underwent preoperative mammography and breast cancer surgery. This cohort consisted of 1002 breasts, comprising 517 with cancer and 485 without. All patients underwent digital breast tomosynthesis (DBT) and FFDM during the preoperative workup. The SM is routinely reconstructed using DBT. Commercial AI-CAD (Lunit Insight MMG, version 1.1.7.2) was retrospectively applied to SM and FFDM to calculate the abnormality scores for each breast. The median abnormality scores were compared for the 517 breasts with cancer using the Wilcoxon signed-rank test. Calibration curves of abnormality scores were evaluated. The discrimination performance was analyzed using the area under the receiver operating characteristic curve (AUC), sensitivity, and specificity using a 10% preset threshold. Sensitivity and specificity were further analyzed according to the mammographic and pathological characteristics.The results of SM and FFDM were compared. Results: AI-CAD demonstrated a significantly lower median abnormality score (71% vs. 96%, P < 0.001) and poorer calibration performance for SM than for FFDM. SM exhibited lower sensitivity (76.2% vs. 82.8%, P < 0.001), higher specificity (95.5% vs.91.8%, P < 0.001), and comparable AUC (0.86 vs. 0.87, P = 0.127) than FFDM. SM showed lower sensitivity than FFDM in asymptomatic breasts, dense breasts, ductal carcinoma in situ, T1, N0, and hormone receptor-positive/human epidermal growth factor receptor 2-negative cancers but showed higher specificity in non-cancerous dense breasts. Conclusion AI-CAD showed lower abnormality scores and reduced calibration performance for SM than for FFDM.Furthermore, the 10% preset threshold resulted in different discrimination performances for the SM. Given these limitations, off-label application of the current AI-CAD to SM should be avoided.

Objective: In South Korea, there is a significant gap in systematic, evidence-based research on intensive case management (ICM) for individuals with severe mental illness (SMI). This study aims to evaluate the effectiveness of ICM through a randomized controlled trial (RCT) comparing ICM with standard case management (non-ICM). Methods: An RCT was conducted to assess the effectiveness of Seoul-intensive case management (S-ICM) vs. non-ICM in individuals with SMI in Seoul. A total of 78 participants were randomly assigned to either the S-ICM group (n=41) or the control group (n=37). Various clinical assessments, including the Brief Psychiatric Rating Scale (BPRS), Montgomery–Åsberg Depression Rating Scale, Health of the Nation Outcome Scale, and Clinical Global Impression-Improvement (CGI-I), along with quality-of-life measures such as the WHO Disability Assessment Schedule, WHO Quality of Life scale, and Multidimensional Scale of Perceived Social Support (MSPSS) were evaluated over a 3-month period. Statistical analyses, including analysis of covariance and logistic regression, were used to determine the effectiveness of S-ICM. Results: The S-ICM group had significantly lower odds of self-harm or suicidal attempts compared to the control group (adjusted odds ratio [aOR]=0.30, 95% confidence interval [CI]: 0.21–1.38). Psychiatric symptoms measured by the BPRS and perceived social support measured by the MSPSS significantly improved in the S-ICM group. The S-ICM group also had significantly higher odds of CGI-I compared to the control group (aOR=8.20, 95% CI: 2.66–25.32). Conclusion This study provides inaugural evidence on the effectiveness of S-ICM services, supporting their standardization and potential nationwide expansion.

Background: Lung ultrasound (LUS) has proven valuable in the initial assessment of coronavirus disease 2019 (COVID-19), but its role in detecting pulmonary fibrosis following intensive care remains unclear. This study aims to assess the presence of pulmonary sequelae and fibrosis-like changes using LUS in survivors of severe COVID-19 pneumonia one month after discharge. Methods: We prospectively enrolled patients with severe COVID-19 who required mechanical ventilation in the intensive care unit (ICU) and conducted LUS assessments from admission to the outpatient visit after discharge. We tracked changes in key LUS findings and applied our proprietary LUS scoring system. To evaluate LUS accuracy, we correlated measured LUS values with computed tomography scores. Results: We evaluated B-line presence, pleural thickness, and consolidation in 14 eligible patients. The LUS scores exhibited minimal changes, with values of 19.1, 19.2, and 17.5 at admission, discharge, and the outpatient visit, respectively. Notably, the number of B-lines decreased significantly, from 1.92 at admission to 0.56 at the outpatient visit (p<0.05), while pleural thickness increased significantly, from 2.05 at admission to 2.48 at the outpatient visit (p≤0.05). Conclusion This study demonstrates that LUS can track changes in lung abnormalities in severe COVID-19 patients from ICU admission through to outpatient follow-up. While pleural thickening and B-line patterns showed significant changes, no correlation was found between LUS and high-resolution computed tomography fibrosis scores. These findings suggest that LUS may serve as a supplementary tool for assessing pulmonary recovery in severe COVID-19 cases.

Objective: To test the performance of an artificial intelligence-based computer-aided diagnosis (AI-CAD) designed for fullfield digital mammography (FFDM) when applied to synthetic mammography (SM). Materials and Methods: We analyzed 501 women (mean age, 57 ± 11 years) who underwent preoperative mammography and breast cancer surgery. This cohort consisted of 1002 breasts, comprising 517 with cancer and 485 without. All patients underwent digital breast tomosynthesis (DBT) and FFDM during the preoperative workup. The SM is routinely reconstructed using DBT. Commercial AI-CAD (Lunit Insight MMG, version 1.1.7.2) was retrospectively applied to SM and FFDM to calculate the abnormality scores for each breast. The median abnormality scores were compared for the 517 breasts with cancer using the Wilcoxon signed-rank test. Calibration curves of abnormality scores were evaluated. The discrimination performance was analyzed using the area under the receiver operating characteristic curve (AUC), sensitivity, and specificity using a 10% preset threshold. Sensitivity and specificity were further analyzed according to the mammographic and pathological characteristics.The results of SM and FFDM were compared. Results: AI-CAD demonstrated a significantly lower median abnormality score (71% vs. 96%, P < 0.001) and poorer calibration performance for SM than for FFDM. SM exhibited lower sensitivity (76.2% vs. 82.8%, P < 0.001), higher specificity (95.5% vs.91.8%, P < 0.001), and comparable AUC (0.86 vs. 0.87, P = 0.127) than FFDM. SM showed lower sensitivity than FFDM in asymptomatic breasts, dense breasts, ductal carcinoma in situ, T1, N0, and hormone receptor-positive/human epidermal growth factor receptor 2-negative cancers but showed higher specificity in non-cancerous dense breasts. Conclusion AI-CAD showed lower abnormality scores and reduced calibration performance for SM than for FFDM.Furthermore, the 10% preset threshold resulted in different discrimination performances for the SM. Given these limitations, off-label application of the current AI-CAD to SM should be avoided.

Background: Lung ultrasound (LUS) has proven valuable in the initial assessment of coronavirus disease 2019 (COVID-19), but its role in detecting pulmonary fibrosis following intensive care remains unclear. This study aims to assess the presence of pulmonary sequelae and fibrosis-like changes using LUS in survivors of severe COVID-19 pneumonia one month after discharge. Methods: We prospectively enrolled patients with severe COVID-19 who required mechanical ventilation in the intensive care unit (ICU) and conducted LUS assessments from admission to the outpatient visit after discharge. We tracked changes in key LUS findings and applied our proprietary LUS scoring system. To evaluate LUS accuracy, we correlated measured LUS values with computed tomography scores. Results: We evaluated B-line presence, pleural thickness, and consolidation in 14 eligible patients. The LUS scores exhibited minimal changes, with values of 19.1, 19.2, and 17.5 at admission, discharge, and the outpatient visit, respectively. Notably, the number of B-lines decreased significantly, from 1.92 at admission to 0.56 at the outpatient visit (p<0.05), while pleural thickness increased significantly, from 2.05 at admission to 2.48 at the outpatient visit (p≤0.05). Conclusion This study demonstrates that LUS can track changes in lung abnormalities in severe COVID-19 patients from ICU admission through to outpatient follow-up. While pleural thickening and B-line patterns showed significant changes, no correlation was found between LUS and high-resolution computed tomography fibrosis scores. These findings suggest that LUS may serve as a supplementary tool for assessing pulmonary recovery in severe COVID-19 cases.

Background: Post-transplantation cyclophosphamide (PTCy) and anti-thymocyte globulin (ATG) are common pro‑ phylactic strategies for graft-versus-host disease (GVHD) after haploidentical hematopoietic stem cell transplantation (haplo-HSCT). Interleukin (IL)-6 is a surrogate marker for cytokine release syndrome (CRS) and acute GVHD.Method The clinical outcomes and complications of haplo-HSCT with PTCy plus ATG versus PTCy monotherapy were compared according to serum IL-6 levels at Chungnam National University Hospital (Daejeon, South Korea) from Jan‑ uary 2019 to February 2023. Results: Forty patients who underwent haplo-HSCT were analyzed. A significant difference in IL-6 levels was observed between the PTCy plus ATG and PTCy alone groups (7.47 ± 10.55 vs. 117.65 ± 127.67; p = 0.003). More patients in the PTCy plus ATG group had a CRS grade of 0 than in the PTCy alone group (p < 0.001). Serum IL-6 levels were associated with grades II–IV acute GVHD (r = 0.547, p < 0.001). The cumulative incidence (CI) of grades II–IV acute GVHD was significantly higher in the PTCy alone group (67.9% vs. 4.8%; p < 0.001). No significant difference in the CI for chronic GVHD was detected between the PTCy plus ATG and PTCy alone groups (72.1% vs. 82.0%; p = 0.730). The CI of 1-year non-relapse mortality was significantly higher in the PTCy alone group than in the PTCy plus ATG group (42.2% vs. 15.9%; p = 0.022). The 1-year overall survival (OS) was significantly better in the PTCy plus ATG group (75.9% vs. 35.3%; p = 0.011). The 1-year GVHD-free, relapse-free survival rate was 29.4% in the PTCy alone group and 54.0% in the PTCy plus ATG group (p = 0.038). Conclusion Serum IL-6 levels were higher in the PTCy alone group than in the PTCy plus ATG group. The addition of ATG before stem cell infusion affected IL-6 levels and reduced the incidences of CRS and grade II–IV acute GVHD in haplo-HSCT patients. This study suggests that PTCy plus ATG as GVHD prophylaxis in haplo-HSCT is beneficial in terms of clinical outcomes and complications of HSCT.