Objective: To evaluate the prognostic impact of radiologic and pathologic features in patients with interstitial lung disease (ILD) other than idiopathic pulmonary fibrosis (IPF), and to identify the factors associated with the development of progressive pulmonary fibrosis (PPF) and survival. Materials and Methods: This study retrospectively enrolled 75 patients diagnosed with ILD other than IPF who underwent surgical lung biopsy between January 2004 and December 2020. Three chest radiologists independently reviewed the CT features and extent of fibrosis on preoperative and follow-up CT scans. Two pathologists reviewed the histopathological features, including the presence of interstitial pneumonia. The time to PPF and overall survival were estimated using the Kaplan-Meier method. The associations of CT and pathological features with PPF and all-cause mortality were examined using standard Cox regression and time-dependent Cox models, respectively. Results: A total of 75 non-IPF ILD patients (mean age ± standard deviations 56.4 ± 13.2 years; range, 40–88 years) were enrolled. The median follow-up duration was 75.3 months (range, 7.8–189.8 months). Traction bronchiectasis on CT (adjusted hazard ratio [HR], 6.40; P = 0.003) and body mass index (adjusted HR per 1-kg/m2 increase, 0.82; P = 0.002) were found to be significantly associated with PPF in multivariable analysis. Radiological progression (adjusted HR, 18.44;P < 0.001), symptomatic progression (adjusted HR, 4.19; P = 0.011), and age (adjusted HR for 1-year increase, 1.12; P < 0.001) were significantly associated with death. Conclusion Traction bronchiectasis on CT was a significant predictor of PPF, while radiologic and symptomatic progression and older age were associated with poorer survival in patients with ILD other than IPF. These findings indicate that careful radiological evaluation and symptom monitoring may help to predict disease progression and outcomes in patients with nonIPF ILD.

Purpose: To develop and validate an artificial intelligence (AI)-based personalized outcome prediction model for upper-urinary tract urothelial carcinoma patients undergoing radical nephroureterectomy. Materials and Methods: Data from patients who underwent radical nephroureterectomy between 2010 and 2020 across three hospitals were retrospectively analyzed. A model was developed using one tertiary center’s data and externally validated with data from two other hospitals. An AI model using XGBoost as risk estimator and bootstrapped Weibull Accelerated Failure Time model for 10-year survival probability was employed. Hyperparameter tuning used Optuna method. Model efficacy was assessed using concordance index, average Brier score, D-calibration, and six-month interval time-dependent area under the curve (AUC). Results: Of 1,039 patients, 627 qualified after excluding 50 with neoadjuvant chemotherapy. Model development used 564 patients (507 training, 57 test) with 9:1 stratified random split, plus 63 for internal validation and 362 for external validation. Significant parameters included preoperative glomerular filtration rate (p<0.001), hydroureteronephrosis (p=0.013), pathological N stage (p<0.001), concurrent carcinoma in situ (p<0.001), disease progression (p<0.001), and survival rate (p<0.001). Disease-free survival (DFS) model’s concordance index: internal validation 0.789, external validations 0.734 and 0.771. Overall survival (OS) model’s concordance index: internal validation 0.819, external validations 0.780 and 0.771. Mean time-dependent AUC was 0.66–0.77 for DFS and 0.67–0.80 for OS during 10-year periods. Conclusions AI-based model effectively predicts disease-free and OS outcomes for upper-urinary tract urothelial carcinoma patients with post-radical nephroureterectomy, showcasing robust performance across multicenter settings.

Background and Objectives: This study aimed to analyze the outcomes of Fontan surgery in the Republic of Korea, as there were only a few studies from Asian countries. Methods: The medical records of 1,732 patients who underwent Fontan surgery in 10 cardiac centers were reviewed. Results: Among them, 1,040 (58.8%) were men. The mean age at Fontan surgery was 4.3±4.2 years, and 395 (22.8%) patients presented with heterotaxy syndrome. According to the types of Fontan surgery, 157 patients underwent atriopulmonary (AP) type; 303, lateral tunnel (LT) type; and 1,266, extracardiac conduit (ECC) type. The overall survival rates were 91.7%, 87.1%, and 74.4% at 10, 20, and 30 years, respectively. The risk factors of early mortality were male, heterotaxy syndrome, AP-type Fontan surgery, high mean pulmonary artery pressure (mPAP) in pre-Fontan cardiac catheterization, and early Fontan surgery year. The risk factors of late mortality were heterotaxy syndrome, genetic disorder, significant atrioventricular valve regurgitation (AVVR) before Fontan surgery, high mPAP in pre-Fontan cardiac catheterization, and no fenestration. Conclusions In Asian population with a high incidence of heterotaxy syndrome, the heterotaxy syndrome was identified as the poor prognostic factors for Fontan surgery. The preoperative low mPAP and less AVVR are associated with better early and long-term outcomes of Fontan surgery.

Purpose: This study aimed to develop standardized guidelines for telephone consultations and assess the impact of computerization on clinical utility. Methods: Guidelines for patient classification were developed for 14 symptoms, validated by experts, and integrated into a real-time computer program. Patient classification involved categorizations of ‘observation,’ ‘outpatient,’ and ‘emergency’.Subsequent to computerization, a survey was conducted to evaluate its usefulness. Results: Items with an Item-Content Validity Index (I-CVI) score of 0.75 or lower were removed or adjusted within the guidelines. Analysis of 200 consultation records indicated that lung cancer (87 cases) was the most common disease and the most prevalent symptom was pain (57 cases). Among 93 cases classified as ‘observation’, 6 patients visited the emergency room. Among 30 cases categorized as ‘outpatient’, 24 patients visited a clinic, and 6 patients visited the emergency room. Of the 19 cases classified as ‘emergency’, 18 patients actually visited the emergency room. User satisfaction from 12 nurses was very high, with an average score of 3.7/4. Conclusion Due to the standardized telephone triage and the concurrent implementation of a computerized program, healthcare professionals can conveniently and comprehensively analyze big data pertaining to patients’ symptoms. Ultimately, nurses were able to receive help with more specialized telenursing.

Background: Achieving a definitive genetic diagnosis of unexplained multiple congenital anomalies (MCAs) in neonatal intensive care units (NICUs) infants is challenging because of the limited diagnostic capabilities of conventional genetic tests. Although the implementation of whole genome sequencing (WGS) has commenced for diagnosing MCAs, due to constraints in resources and faculty, many NICUs continue to utilize chromosomal microarray (CMA) and/or karyotyping as the initial diagnostic approach. We aimed to evaluate the diagnostic efficacy of WGS in infants with MCAs who have received negative results from karyotyping and/or CMA. Methods: In this prospective study, we enrolled 80 infants with MCAs who were admitted to a NICU at a single center and had received negative results from CMA and/or karyotyping.The phenotypic characteristics were classified according to the International Classification of Diseases and the Human Phenotype Ontology. We assessed the diagnostic yield of trioWGS in infants with normal chromosomal result and explored the process of diagnosing by analyzing both phenotype and genotype. Also, we compared the phenotype and clinical outcomes between the groups diagnosed with WGS and the undiagnosed group. Results: The diagnostic yield of WGS was 26% (21/80), of which 76% were novel variants.There was a higher diagnostic yield in cases of craniofacial abnormalities, including those of the eye and ear, and a lower diagnostic yield in cases of gastrointestinal and genitourinary abnormalities. In addition, higher rates of rehabilitation therapy and gastrostomy were observed in WGS-diagnosed infants than in undiagnosed infants. Conclusion This prospective cohort study assessed the usefulness of trio-WGS following chromosomal analysis for diagnosing MCAs in the NICU and revealed improvements in the diagnostic yield and clinical utility of WGS.

Background: Bladder cancer is characterized by frequent mutations, which provide potential therapeutic targets for most patients. The effectiveness of emerging personalized therapies depends on an accurate molecular diagnosis, for which the accurate estimation of the neoplastic cell percentage (NCP) is a crucial initial step. However, the established method for determining the NCP, manual counting by a pathologist, is time-consuming and not easily executable. Methods: To address this, artificial intelligence (AI) models were developed to estimate the NCP using nine convolutional neural networks and the scanned images of 39 cases of urinary tract cancer. The performance of the AI models was compared to that of six pathologists for 119 cases in the validation cohort. The ground truth value was obtained through multiplexed immunofluorescence. The AI model was then applied to 41 cases in the application cohort that underwent next-generation sequencing testing, and its impact on the copy number variation (CNV) was analyzed. Results: Each AI model demonstrated high reliability, with intraclass correlation coefficients (ICCs) ranging from 0.82 to 0.88. These values were comparable or better to those of pathologists, whose ICCs ranged from 0.78 to 0.91 in urothelial carcinoma cases, both with and without divergent differentiation/ subtypes. After applying AI-driven NCP, 190 CNV (24.2%) were reclassified with 66 (8.4%) and 78 (9.9%) moved to amplification and loss, respectively, from neutral/minor CNV. The neutral/minor CNV proportion decreased by 6%. Conclusions These results suggest that AI models could assist human pathologists in repetitive and cumbersome NCP calculations.