Purpose: This study aimed to validate pivotal pre-test probability (PTP)-coronary artery disease (CAD) models (CAD consortium model and IJC-CAD model). Materials and Methods: Traditional PTP models-CAD consortium models: two traditional PTP models were used under the CAD consortium framework, namely CAD1 and CAD2. Machine learning (ML)-based PTP models: two ML-based PTP models were derived from CAD1 and CAD2, and used to enhance predictive capabilities [ML-CAD2 and ML-IJC (IJC-CAD)]. The primary endpoint was obstructive CAD. The performance evaluation of these PTP models was conducted using receiver-operating characteristic analysis. Results: The study included 238 participants, among whom 157 individuals (65.9% of the total sample) had CAD. The IJC-CAD model demonstrated the highest performance with an area under the curve (AUC) of 0.860 [95% confidence interval (CI): 0.812– 0.909]. Following this, the ML-CAD2 model exhibited an AUC of 0.814 (95% CI: 0.758–0.870), CAD1 showed an AUC of 0.767 (95% CI: 0.705–0.830), and CAD2 had an AUC of 0.785 (95% CI: 0.726–0.845). Each of the PTP models was adjusted to have a CAD score cutoff that classified cases with a sensitivity of over 95%. The respective cutoff values were as follows: CAD1 and CAD2 >12, MLCAD2 >0.380, and IJC-CAD >0.367. All PTP models achieved a CAD sensitivity of over 95%. Similar to the AUC performance, the accuracy of the PTP models was highest for IJC-CAD, reaching 80.3%. The accuracy of ML-CAD2 was 77.7%, while that for CAD1 and CAD2 was 74.8% and 75.2%, respectively. Conclusion ML-CAD2 and IJC-CAD showed superior performance compared to traditional existing models (CAD1 and CAD2)

Purpose: This study aimed to validate pivotal pre-test probability (PTP)-coronary artery disease (CAD) models (CAD consortium model and IJC-CAD model). Materials and Methods: Traditional PTP models-CAD consortium models: two traditional PTP models were used under the CAD consortium framework, namely CAD1 and CAD2. Machine learning (ML)-based PTP models: two ML-based PTP models were derived from CAD1 and CAD2, and used to enhance predictive capabilities [ML-CAD2 and ML-IJC (IJC-CAD)]. The primary endpoint was obstructive CAD. The performance evaluation of these PTP models was conducted using receiver-operating characteristic analysis. Results: The study included 238 participants, among whom 157 individuals (65.9% of the total sample) had CAD. The IJC-CAD model demonstrated the highest performance with an area under the curve (AUC) of 0.860 [95% confidence interval (CI): 0.812– 0.909]. Following this, the ML-CAD2 model exhibited an AUC of 0.814 (95% CI: 0.758–0.870), CAD1 showed an AUC of 0.767 (95% CI: 0.705–0.830), and CAD2 had an AUC of 0.785 (95% CI: 0.726–0.845). Each of the PTP models was adjusted to have a CAD score cutoff that classified cases with a sensitivity of over 95%. The respective cutoff values were as follows: CAD1 and CAD2 >12, MLCAD2 >0.380, and IJC-CAD >0.367. All PTP models achieved a CAD sensitivity of over 95%. Similar to the AUC performance, the accuracy of the PTP models was highest for IJC-CAD, reaching 80.3%. The accuracy of ML-CAD2 was 77.7%, while that for CAD1 and CAD2 was 74.8% and 75.2%, respectively. Conclusion ML-CAD2 and IJC-CAD showed superior performance compared to traditional existing models (CAD1 and CAD2)

Purpose: This study aimed to validate pivotal pre-test probability (PTP)-coronary artery disease (CAD) models (CAD consortium model and IJC-CAD model). Materials and Methods: Traditional PTP models-CAD consortium models: two traditional PTP models were used under the CAD consortium framework, namely CAD1 and CAD2. Machine learning (ML)-based PTP models: two ML-based PTP models were derived from CAD1 and CAD2, and used to enhance predictive capabilities [ML-CAD2 and ML-IJC (IJC-CAD)]. The primary endpoint was obstructive CAD. The performance evaluation of these PTP models was conducted using receiver-operating characteristic analysis. Results: The study included 238 participants, among whom 157 individuals (65.9% of the total sample) had CAD. The IJC-CAD model demonstrated the highest performance with an area under the curve (AUC) of 0.860 [95% confidence interval (CI): 0.812– 0.909]. Following this, the ML-CAD2 model exhibited an AUC of 0.814 (95% CI: 0.758–0.870), CAD1 showed an AUC of 0.767 (95% CI: 0.705–0.830), and CAD2 had an AUC of 0.785 (95% CI: 0.726–0.845). Each of the PTP models was adjusted to have a CAD score cutoff that classified cases with a sensitivity of over 95%. The respective cutoff values were as follows: CAD1 and CAD2 >12, MLCAD2 >0.380, and IJC-CAD >0.367. All PTP models achieved a CAD sensitivity of over 95%. Similar to the AUC performance, the accuracy of the PTP models was highest for IJC-CAD, reaching 80.3%. The accuracy of ML-CAD2 was 77.7%, while that for CAD1 and CAD2 was 74.8% and 75.2%, respectively. Conclusion ML-CAD2 and IJC-CAD showed superior performance compared to traditional existing models (CAD1 and CAD2)

Purpose: This study aimed to validate pivotal pre-test probability (PTP)-coronary artery disease (CAD) models (CAD consortium model and IJC-CAD model). Materials and Methods: Traditional PTP models-CAD consortium models: two traditional PTP models were used under the CAD consortium framework, namely CAD1 and CAD2. Machine learning (ML)-based PTP models: two ML-based PTP models were derived from CAD1 and CAD2, and used to enhance predictive capabilities [ML-CAD2 and ML-IJC (IJC-CAD)]. The primary endpoint was obstructive CAD. The performance evaluation of these PTP models was conducted using receiver-operating characteristic analysis. Results: The study included 238 participants, among whom 157 individuals (65.9% of the total sample) had CAD. The IJC-CAD model demonstrated the highest performance with an area under the curve (AUC) of 0.860 [95% confidence interval (CI): 0.812– 0.909]. Following this, the ML-CAD2 model exhibited an AUC of 0.814 (95% CI: 0.758–0.870), CAD1 showed an AUC of 0.767 (95% CI: 0.705–0.830), and CAD2 had an AUC of 0.785 (95% CI: 0.726–0.845). Each of the PTP models was adjusted to have a CAD score cutoff that classified cases with a sensitivity of over 95%. The respective cutoff values were as follows: CAD1 and CAD2 >12, MLCAD2 >0.380, and IJC-CAD >0.367. All PTP models achieved a CAD sensitivity of over 95%. Similar to the AUC performance, the accuracy of the PTP models was highest for IJC-CAD, reaching 80.3%. The accuracy of ML-CAD2 was 77.7%, while that for CAD1 and CAD2 was 74.8% and 75.2%, respectively. Conclusion ML-CAD2 and IJC-CAD showed superior performance compared to traditional existing models (CAD1 and CAD2)

Purpose: This study aimed to validate pivotal pre-test probability (PTP)-coronary artery disease (CAD) models (CAD consortium model and IJC-CAD model). Materials and Methods: Traditional PTP models-CAD consortium models: two traditional PTP models were used under the CAD consortium framework, namely CAD1 and CAD2. Machine learning (ML)-based PTP models: two ML-based PTP models were derived from CAD1 and CAD2, and used to enhance predictive capabilities [ML-CAD2 and ML-IJC (IJC-CAD)]. The primary endpoint was obstructive CAD. The performance evaluation of these PTP models was conducted using receiver-operating characteristic analysis. Results: The study included 238 participants, among whom 157 individuals (65.9% of the total sample) had CAD. The IJC-CAD model demonstrated the highest performance with an area under the curve (AUC) of 0.860 [95% confidence interval (CI): 0.812– 0.909]. Following this, the ML-CAD2 model exhibited an AUC of 0.814 (95% CI: 0.758–0.870), CAD1 showed an AUC of 0.767 (95% CI: 0.705–0.830), and CAD2 had an AUC of 0.785 (95% CI: 0.726–0.845). Each of the PTP models was adjusted to have a CAD score cutoff that classified cases with a sensitivity of over 95%. The respective cutoff values were as follows: CAD1 and CAD2 >12, MLCAD2 >0.380, and IJC-CAD >0.367. All PTP models achieved a CAD sensitivity of over 95%. Similar to the AUC performance, the accuracy of the PTP models was highest for IJC-CAD, reaching 80.3%. The accuracy of ML-CAD2 was 77.7%, while that for CAD1 and CAD2 was 74.8% and 75.2%, respectively. Conclusion ML-CAD2 and IJC-CAD showed superior performance compared to traditional existing models (CAD1 and CAD2)

Purpose: BRAF mutations are detected in 30%-80% of papillary thyroid cancer (PTC) cases. DaBRAFenib and trametinib showed promising antitumor activity in patients with BRAFV600E-mutated metastatic melanoma and non–small cell lung cancer. This study aimed to evaluate the efficacy and safety of daBRAFenib and trametinib in patients with metastatic BRAFV600E-mutated thyroid cancer. Materials and Methods: This was a retrospective study to evaluate the efficacy of daBRAFenib and trametinib in patients with metastatic BRAFV600E-mutated PTC. The patients received daBRAFenib 150 mg twice daily and trametinib 2 mg once daily at the Samsung Medical Center. This study evaluated the progression-free survival (PFS), objective response rate (ORR), disease control rate (DCR) overall survival (OS), and safety of daBRAFenib and trametinib. Results: Between December 2019 and January 2022, 27 PTC patients including eight patients with poorly differentiated or anaplastic transformation, received daBRAFenib and trametinib. The median age was 73.0 years, and the median follow-up period was 19.8 months. The majority (81.5%) had undergone thyroidectomy, while 8 patients had received prior systemic treatments. ORR was 73.1%, with 19 partial responses, and DCR was 92.3%. Median PFS was 21.7 months, and median OS was 21.7 months. Treatment-related adverse events included generalized weakness (29.6%), fever (25.9%), and gastrointestinal problems (22.2%). Dose reduction due to adverse events was required in 81.5% of the patients. Conclusion DaBRAFenib and trametinib demonstrated a high ORR with promising PFS; however, most patients with BRAFV600E-mutated metastatic PTC required a dose reduction.

BACKGROUND AND OBJECTIVES: The correlations between plaque characteristics and plaque rupture location according to segmental lesion analysis have not been well defined. The aim of this study was to assess those characteristics of ST-segment elevation myocardial infarction (STEMI) culprit lesions according to segmental lesion geometry using virtual histology intravascular ultrasound (VH-IVUS). METHODS: Sixty single discrete lesions found in the left anterior descending (LAD) coronary arteries of 60 patients with STEMI were included. Each lesion was divided into 3 segments based on lumen area (LA) index, calculated by dividing the lesion LA by the reference LA. RESULTS: Among the 3 segments, the mid-segment showed the highest proportion of necrotic core (NC; proximal, mid-, and distal segments: 20.9±11.8%, 22.7±11.3%, and 17.5±11.2%, respectively, p=0.044). VH-IVUS-derived thin-cap fibroatheroma (VH-TCFA) was also more frequently found in the mid-segment than in proximal and distal segments (36.7%, 58.3%, and 16.7%, p < 0.001). The mid-segment also showed the highest prevalence of plaque rupture (45.0%, 78.3% and 11.7%, p < 0.001) and thrombus (61.7%, 95.0%, and 41.7%, p < 0.001) compared to proximal or distal segments. When the lesions were divided into 2 groups according to the median value (4.0 mm2) of minimum lumen area (MLA), plaque rupture at the distal segment was observed only in high MLA lesions (23.3% vs. 0.0%, p=0.011). CONCLUSION: Analysis of longitudinal lesion geometry using the LA index can be useful in evaluating plaque vulnerability and the incidence of plaque rupture and thrombus in STEMI patients.
Coronary Artery Disease ; Coronary Vessels ; Diagnostic Imaging ; Humans ; Incidence ; Myocardial Infarction* ; Plaque, Atherosclerotic ; Prevalence ; Rupture ; Thrombosis ; Ultrasonography

PURPOSE: The purpose of this study was to investigate the reality, status of clinical nurses' emotional labor and the relationship with physical discomfort, burnout, depression and social support. METHODS: A thousand three hundred sixteen clinical nurses from 42 hospitals nationwide participated in this study. Questionnaires were developed for evaluating the reality and status of emotional labor of clinical nurses after interviewing focus groups and reviewing literatures. Data were analyzed using descriptive statistics, t-test, ANOVA, Pearson correlation coefficient. RESULTS: Ninety eight percent of nurses had answered having emotional labor and they experienced 82 times per year, 9.6 times during last a month which means they experience it every other day. The one who provoke emotional labor were patients, guardians, physicians, supervisor, and colleagues in sequence. Eighty percent of nurses had intention to leave their jobs after experiencing emotional labor. They were doing more surface acting than deep acting of emotional labor. CONCLUSION: Clinical nurses in Korea experienced excessively high level of emotional labor and delayed responding to clients' requests due to lack of time for caring each patient was revealed as one of the main causes of emotional labor.
Depression ; Focus Groups ; Humans ; Intention ; Korea

PURPOSE: Infliximab is currently used for the treatment of active Crohn's disease (CD). We aimed to assess the efficacy and safety of infliximab therapy and to determine the predictors of response in Korean patients with CD. MATERIALS AND METHODS: A total of 317 patients who received at least one infliximab infusion for active luminal CD (n=198) and fistulizing CD (n=86) or both (n=33) were reviewed retrospectively in 29 Korean referral centers. Clinical outcomes of induction and maintenance therapy with infliximab, predictors of response, and adverse events were evaluated. RESULTS: In patients with luminal CD, the rates of clinical response and remission at week 14 were 89.2% and 60.0%, respectively. Male gender and isolated colonic disease were associated with higher remission rates at week 14. In week-14 responders, the probabilities of sustained response and remission were 96.2% and 93.3% at week 30 and 88.0% and 77.0% at week 54, respectively. In patients with fistulizing CD, clinical response and remission were observed in 85.0% and 56.2% of patients, respectively, at week 14. In week-14 responders, the probabilities of sustained response and remission were 94.0% and 97.1%, respectively, at both week 30 and week 54. Thirty-nine patients (12.3%) experienced adverse events related to infliximab. Serious adverse events developed in 19 (6.0%) patients including seven cases of active pulmonary tuberculosis. CONCLUSION: Infliximab induction and maintenance therapy are effective and well tolerable in Korean patients with luminal and fistulizing CD. However, clinicians must be aware of the risk of rare yet critical adverse events.
Colonic Diseases ; Crohn Disease* ; Humans ; Infliximab* ; Male ; Phenobarbital ; Referral and Consultation ; Retrospective Studies ; Tuberculosis ; Tuberculosis, Pulmonary

BACKGROUND/AIMS: It is well known that the menopause is related to interference in lipid metabolism, obesity, and a hypercoagulable state. The aim of the present study was to examine the impact of the menopause in middle-aged Korean females with acute myocardial infarction (AMI). METHODS: A total of 1,781 middle-aged females (aged < 65 years) in the Korean Acute Myocardial Infarction registry were enrolled into this study between November 2005 and December 2013. The patients were divided into two groups; the pre-menopause group (≤ 55 years old) and the menopause group (56-64 years old). Major adverse cardiac events (MACE) were analyzed over a one-year follow-up period. RESULTS: The pre-menopause and menopause groups comprised 669 patients (mean age, 49.1 ± 5.6 years) and 1,112 patients (mean age, 60.6 ± 2.6 years), respectively. The incidence of hypertension (42.2% vs. 59.4%, p < 0.001), diabetes mellitus (DM) (27.4% vs. 35.7%, p < 0.001), and dyslipidemia (12.9% vs. 17.7%, p = 0.008) were more frequent in menopausal patients. Additionally, the rates of smoking (20% vs. 12.7%, p < 0.001) and familial history (12% vs. 6.8%, p < 0.001) were higher in the pre-menopause group. The cumulative rates of MACE did not show any differences between the two groups. A history of atrial fibrillation, previous AMI and DM, higher Killip class, and multi-vessel disease were independent risk factors for predicting one-year MACE. CONCLUSIONS: The survival analysis demonstrated that there was no significant difference in MACE rates between the pre-menopause and menopause groups during the one-year follow-up. Therefore, middle-aged pre-menopausal women should be treated more intensively, regardless of whether they are menopausal.
Atrial Fibrillation ; Diabetes Mellitus ; Dyslipidemias ; Female* ; Follow-Up Studies ; Humans ; Hypertension ; Incidence ; Lipid Metabolism ; Menopause ; Myocardial Infarction* ; Obesity ; Premenopause ; Prognosis ; Risk Factors ; Smoke ; Smoking