Background: Posttransplant diabetes mellitus (PTDM) complicates kidney transplant recipients (KTRs) in morbidity and mortality. This study aimed to predict PTDM risk in KTRs using machine learning and deep learning models. Methods: Data were obtained from the Korea Organ Transplantation Registry, a nationwide cohort study of KTRs. Four machine learning algorithms, including eXtreme Gradient Boosting (XGBoost), CatBoost, light gradient boosting machine and logistic regression, and deep learning were implemented on 41 pretransplant and 31 posttransplant variables to predict PTDM. Model performance was assessed using the area under the curve (AUC) of the receiver operating characteristic curve, accuracy, precision, recall, and F1 score. Results: Among 3,213 KTRs, 497 patients (15.5%) developed PTDM within 1 year. The PTDM group had higher age, body mass index (BMI), triglyceride level, and prevalence of hypertension and cardiovascular disease, and lower total cholesterol level at baseline than the No-PTDM group. The XGBoost model showed the highest AUC (0.738) and F1 score (0.42), and modest accuracy (0.86), while the CatBoost model exhibited the highest accuracy (0.87) and precision (0.79). Feature importance in XGBoost was highest for recipient age, followed by baseline BMI, triglyceride level at posttransplant 6 months, baseline glycated hemoglobin and high-density lipoprotein cholesterol level, white blood cell (WBC) count and serum uric acid level at 6 months, baseline WBC count, and tacrolimus trough level at discharge. Conclusion The XGBoost model demonstrated the best performance for predicting PTDM within 1 year, offering an accurate tool for early identification and personalized care of high-risk KTRs for PTDM.

Background/Aims: The programmed death 1 (PD-1)/programmed death-ligand 1 (PD-L1) pathway has not been fully evaluated in inflammatory bowel disease. We evaluated PD-1/PD-L1 levels in patients with ulcerative colitis (UC) and their significance in tonsil-derived mesenchymal stem cells (TMSCs) treatment. Methods: Using acute and chronic murine colitis model, we measured the PD-1 and PD-L1 levels in inflamed colonic tissues pre- and post-treatment with TMSCs. We also measured PD-1 and PD-L1 levels in colonic tissues from UC patients, compared to normal controls. Results: In the analysis using human colonic tissues, a significant increase in the levels of PD-1 and PD-L1 was observed in the colonic mucosa of patients with UC compared with normal controls (p < 0.001 and p = 0.005, respectively). When comparing the maximal disease extent, PD-L1 levels were highest in patients with proctitis (38.5 ± 46.7), followed by left-side colitis (17.5 ± 23.1) and extensive colitis (5.2 ± 8.2) (p < 0.001). In the chronic colitis model, the level of PD-L1 was decreased (p = 0.040) and the level of PD-1 increased more than in normal controls (p = 0.047). After treatment with TMSC, significant improvements were observed in body weight, disease activity index, and colon length recovery. Additionally, the levels of PD-1 and PD-L1 were recovered; PD-L1 significantly increased (p = 0.031), while the level of PD-1 decreased (p = 0.310). Conclusions The altered expression of PD-1 and PD-L1 in colonic mucosa may be a possible mechanism of UC, and T-MSC-derived PD-L1 could help suppress colitis.

Purpose: The increase in thyroid cancer incidence has inevitably led to an increase in thyroid cancer surgeries. This meta-regression analysis aimed to determine if the rate of post-thyroidectomy complications changes by year. Materials and Methods: PubMed and Embase databases were used to perform a systematic literature search of studies published from January 1, 2005, using the keywords “thyroidectomy” and “complication.” A meta-regression was performed for post-thyroidectomy hypocalcemia and bleeding. Results: This meta-analysis included 25 studies involving 927751 individuals. Through the years of publications in this study, there was no significant difference in the proportion of post-thyroidectomy hypocalcemia and bleeding (p=0.9978, 0.6393). Conclusion Although the number of thyroid surgeries has recently increased, the incidence of post-thyroidectomy hypocalcemia and bleeding did not significantly increase.

Objective: This study aimed to develop a Korean version of the Nonsuicidal Self-injury Inventory (K-NSSI) through the Deliberate Self-harm Inventory (DSHI) developed by Gratz for the Korean context and confirm its reliability and validity for clinical application. Methods: A total of 188 participants were analyzed utilizing the DSHI, the Korean version of the Self-harm Inventory, the Personality Assessment Inventory-Borderline Features (PAI-BOR), and the DSM-5 Level-2-Depression scale (Level-2-Dep). Cronbach’s α assessed their reliability, while frequency analysis examined the items of the K-NSSI scales.Validity of the K-NSSI was confirmed through correlation analyses between K-NSSI (tendency for and frequency of nonsuicidal self-injury [NSSI] behavior) and SHI, PAI-BOR total scale, four subscales of PAI-BOR, and Level-2-Dep scale. Polyserial correlations analyzed the correlation between the presence of NSSI behavior and other scales.Confirmatory factor analysis and structural equation modeling explored the relationship between borderline personality features and self-harm. Results: Cronbach’s α was 0.71, indicating an “acceptable” level of reliability. Statistically significant correlations were observed between the presence of NSSI behavior and the total scores of SHI and PAI-BOR, and the four subscales of PAI-BOR. The frequency of NSSI showed statistically significant correlations with the total score of SHI and PAI-BOR, and its four subscales. Notably, 13.8% of participants reported engaging in self-harm behaviors, 26.9% reported a single occurrence, and 73.1% reported two or more instances. Structural equation modeling demonstrated that self-harm adequately predicted borderline personality traits. Conclusion This study successfully validated the adaptation of DSHI into K-NSSI. The K-NSSI can facilitate interventions for self-harm incidents.

Objective: This study aimed to develop a Korean version of the Nonsuicidal Self-injury Inventory (K-NSSI) through the Deliberate Self-harm Inventory (DSHI) developed by Gratz for the Korean context and confirm its reliability and validity for clinical application. Methods: A total of 188 participants were analyzed utilizing the DSHI, the Korean version of the Self-harm Inventory, the Personality Assessment Inventory-Borderline Features (PAI-BOR), and the DSM-5 Level-2-Depression scale (Level-2-Dep). Cronbach’s α assessed their reliability, while frequency analysis examined the items of the K-NSSI scales.Validity of the K-NSSI was confirmed through correlation analyses between K-NSSI (tendency for and frequency of nonsuicidal self-injury [NSSI] behavior) and SHI, PAI-BOR total scale, four subscales of PAI-BOR, and Level-2-Dep scale. Polyserial correlations analyzed the correlation between the presence of NSSI behavior and other scales.Confirmatory factor analysis and structural equation modeling explored the relationship between borderline personality features and self-harm. Results: Cronbach’s α was 0.71, indicating an “acceptable” level of reliability. Statistically significant correlations were observed between the presence of NSSI behavior and the total scores of SHI and PAI-BOR, and the four subscales of PAI-BOR. The frequency of NSSI showed statistically significant correlations with the total score of SHI and PAI-BOR, and its four subscales. Notably, 13.8% of participants reported engaging in self-harm behaviors, 26.9% reported a single occurrence, and 73.1% reported two or more instances. Structural equation modeling demonstrated that self-harm adequately predicted borderline personality traits. Conclusion This study successfully validated the adaptation of DSHI into K-NSSI. The K-NSSI can facilitate interventions for self-harm incidents.

Objective: This study aimed to develop a Korean version of the Nonsuicidal Self-injury Inventory (K-NSSI) through the Deliberate Self-harm Inventory (DSHI) developed by Gratz for the Korean context and confirm its reliability and validity for clinical application. Methods: A total of 188 participants were analyzed utilizing the DSHI, the Korean version of the Self-harm Inventory, the Personality Assessment Inventory-Borderline Features (PAI-BOR), and the DSM-5 Level-2-Depression scale (Level-2-Dep). Cronbach’s α assessed their reliability, while frequency analysis examined the items of the K-NSSI scales.Validity of the K-NSSI was confirmed through correlation analyses between K-NSSI (tendency for and frequency of nonsuicidal self-injury [NSSI] behavior) and SHI, PAI-BOR total scale, four subscales of PAI-BOR, and Level-2-Dep scale. Polyserial correlations analyzed the correlation between the presence of NSSI behavior and other scales.Confirmatory factor analysis and structural equation modeling explored the relationship between borderline personality features and self-harm. Results: Cronbach’s α was 0.71, indicating an “acceptable” level of reliability. Statistically significant correlations were observed between the presence of NSSI behavior and the total scores of SHI and PAI-BOR, and the four subscales of PAI-BOR. The frequency of NSSI showed statistically significant correlations with the total score of SHI and PAI-BOR, and its four subscales. Notably, 13.8% of participants reported engaging in self-harm behaviors, 26.9% reported a single occurrence, and 73.1% reported two or more instances. Structural equation modeling demonstrated that self-harm adequately predicted borderline personality traits. Conclusion This study successfully validated the adaptation of DSHI into K-NSSI. The K-NSSI can facilitate interventions for self-harm incidents.

Objective: This study aimed to develop a Korean version of the Nonsuicidal Self-injury Inventory (K-NSSI) through the Deliberate Self-harm Inventory (DSHI) developed by Gratz for the Korean context and confirm its reliability and validity for clinical application. Methods: A total of 188 participants were analyzed utilizing the DSHI, the Korean version of the Self-harm Inventory, the Personality Assessment Inventory-Borderline Features (PAI-BOR), and the DSM-5 Level-2-Depression scale (Level-2-Dep). Cronbach’s α assessed their reliability, while frequency analysis examined the items of the K-NSSI scales.Validity of the K-NSSI was confirmed through correlation analyses between K-NSSI (tendency for and frequency of nonsuicidal self-injury [NSSI] behavior) and SHI, PAI-BOR total scale, four subscales of PAI-BOR, and Level-2-Dep scale. Polyserial correlations analyzed the correlation between the presence of NSSI behavior and other scales.Confirmatory factor analysis and structural equation modeling explored the relationship between borderline personality features and self-harm. Results: Cronbach’s α was 0.71, indicating an “acceptable” level of reliability. Statistically significant correlations were observed between the presence of NSSI behavior and the total scores of SHI and PAI-BOR, and the four subscales of PAI-BOR. The frequency of NSSI showed statistically significant correlations with the total score of SHI and PAI-BOR, and its four subscales. Notably, 13.8% of participants reported engaging in self-harm behaviors, 26.9% reported a single occurrence, and 73.1% reported two or more instances. Structural equation modeling demonstrated that self-harm adequately predicted borderline personality traits. Conclusion This study successfully validated the adaptation of DSHI into K-NSSI. The K-NSSI can facilitate interventions for self-harm incidents.

Objective: This study involved a meta-analysis of South Korean studies regarding psychosocial interventions for patients with breast cancer to provide basic data to support the development of an integrated healthcare service model. Methods: Randomized controlled studies with a pretest-posttest design were selected, and those presenting means, standard deviations, and standardized mean differences were included. For quality evaluation and heterogeneity testing, the Jadad scale and the Q-value and I 2 were used. To estimate the effect size of each study, Hedge’s g was used. Publication bias was analyzed with the Funnel plot and Egger’s regression test. Results: Of the 28 studies selected for the, meta-analysis was performed on eight. The total number of datasets included in the meta-analysis was 33. The evaluation based on the Jadad scale revealed no significant inter-rater variation (p = 0.35). The mean number of sessions was 7.93 and the mean intervention time was 13.2 hours. The interventions were mostly administered in a group structure (94%) and, regarding the type, they were categorized as integrated (36.4%), cognitive (30.3%), and meditation (24.2%). The mean effect size was 1.21 against no treatment group. Conclusion The analyzed studies showed heterogeneity, with a corresponding asymmetry found on the Funnel plot. Despite the heterogeneity and publication bias, the mean effect size was significantly large. Cognitive interventions, meditation, and psychological education programs are expected to assist in reducing negative emotions and enhancing quality of life in patients with breast cancer.

OBJECTIVES: Proteinuria is widely used to predict cardiovascular risk. However, there is insufficient evidence to predict how changes in proteinuria may affect the incidence of cardiovascular disease. METHODS: The study included 265,236 Korean adults who underwent health checkups in 2003-2004 and 2007-2008. They were categorized into 4 groups based on changes in proteinuria (negative: negative → negative; resolved: proteinuria ≥1+ → negative; incident: negative → proteinuria ≥1+; persistent: proteinuria ≥1+ → proteinuria ≥1+). We conducted 6 years of follow-up to identify the risks of developing ischemic heart disease (IHD), acute myocardial infarction (AMI), and angina pectoris according to changes in proteinuria. A multivariate Cox proportional-hazards model was used to calculate adjusted hazard ratios (HRs) and 95% confidence intervals (CIs) for incident IHD, AMI, and angina pectoris. RESULTS: The IHD risk (expressed as HR [95% CI]) was the highest for persistent proteinuria, followed in descending order by incident and resolved proteinuria, compared with negative proteinuria (negative: reference, resolved: 1.211 [95% CI, 1.104 to 1.329], incident: 1.288 [95% CI, 1.184 to 1.400], and persistent: 1.578 [95% CI, 1.324 to 1.881]). The same pattern was associated with AMI (negative: reference, resolved: 1.401 [95% CI, 1.048 to 1.872], incident: 1.606 [95% CI, 1.268 to 2.035], and persistent: 2.069 [95% CI, 1.281 to 3.342]) and angina pectoris (negative: reference, resolved: 1.184 [95% CI, 1.065 to 1.316], incident: 1.275 [95% CI, 1.160 to 1.401], and persistent: 1.554 [95% CI, 1.272 to 1.899]). CONCLUSIONS Experiencing proteinuria increased the risks of IHD, AMI, and angina pectoris even after proteinuria resolved.