Background: The etiology of adolescent idiopathic scoliosis is multifactorial, and the influence of lifestyle factors such as sleep is not clearly understood. Differences in scoliosis incidence between urban and rural areas have been reported, but the contributing factors remain unclear. Therefore, this study investigated the association between sleep patterns and the incidence of idiopathic scoliosis and explored whether these patterns contribute to the observed urban-rural disparity. Methods: This retrospective study utilized data from the Korea Children and Youth Panel Survey (2010–2016) and the Health Insurance Review and Assessment Service for 4,693 students (age, 7–18 years). Various lifestyle factors including sleep patterns, learning time, and activity times, were compared between urban and rural areas, and a correlation analysis was performed between these factors and the age-specific incidence of idiopathic scoliosis. Results: Urban students, who exhibited higher idiopathic scoliosis incidence rates, tended to have later bedtimes and shorter total sleep durations than rural students. Longer learning hours were also observed in urban areas. Significant correlations were found between idiopathic scoliosis incidence and bedtime (p = 0.031), total sleep time (p = 0.026), and changes in total sleep time (p = 0.011). Conclusions Our findings indicate that later bedtimes and shorter sleep durations may contribute to idiopathic scoliosis development in children and adolescents. The higher idiopathic scoliosis incidence in urban students than in rural students could be partially explained by these sleep pattern differences, highlighting the need for further research into the role of sleep in scoliosis onset and prevention.

Purpose: To investigate the association between metabolic syndrome (MetS) and nocturia in a nationally representative U.S. adult population, focusing on individual metabolic components and subgroup differences by age and sex. Materials and Methods: We analyzed data from 8,518 adults aged ≥20 years who participated in the National Health and Nutrition Examination Survey from 2005 to 2014. Nocturia was defined as ≥2 nighttime voids. MetS was defined by the presence of ≥3 National Cholesterol Education Program Adult Treatment Panel III criteria. Multivariate logistic regression and restricted cubic spline (RCS) analyses were used to assess associations, adjusting for demographic and behavioral covariates. Results: Overall, 23.3% of participants had MetS and 29.6% reported nocturia. MetS was independently associated with nocturia (adjusted odds ratio [OR] 1.387, 95% confidence interval 1.236–1.557). A dose–response relationship was observed, with nocturia risk increasing. Central obesity (OR 1.564), elevated fasting glucose (OR 1.397), and elevated blood pressure (OR 1.311) showed the strongest associations. RCS analyses revealed linear associations for waist circumference and systolic blood pressure, and nonlinear associations for diastolic blood pressure and glucose. Sex-specific analyses revealed distinct nonlinear patterns, particularly for waist circumference among male participants and triglyceride levels among female participants. The association remained consistent across most age and sex groups, except in males aged 20–40 years. Conclusions MetS and its components are independently associated with nocturia. The observed sex-specific differences suggest that metabolic contributors to nocturia may differ by sex supporting nocturia as a potential clinical marker of underlying cardiometabolic dysfunction.

Purpose: The purpose of this study was to explore the association between benign prostatic hyperplasia (BPH) and the incidence of falls from the perspective of geriatric morbid conditions. Methods: Data were sourced from the triennial National Survey of Older Koreans conducted by the Ministry of Health and Welfare (2017–2020). In total, 8,135 male participants aged 65 and older were included, and information was gathered through questionnaires and physical measurements. Logistic regression analysis was utilized to determine the impact of BPH on the risk of falls, and subgroup analyses were conducted to examine the influence of BPH on specific types of falls. Results: Of the participants, 15.2% (1,238 of 8,135) reported that their BPH treatment exceeded 3 months, and 8.0% (648 of 8,135) reported experiencing falls, with 61.4% (398/648) of these falls resulting in injuries. A significant association was identified between BPH and both falls (odds ratio [OR], 1.798; 95% confidence interval [CI], 1.479–2.185) and falls with injuries (OR, 2.133; 95% CI, 1.689–2.694). A subgroup analysis indicated a correlation between BPH and falls in groups having one (OR, 1.912; 95% CI, 1.356–2.694) and 2 or more conditions (OR, 1.856; 95% CI, 1.455–2.367) involving visual and auditory impairments, cognitive decline, depression, lower motor weakness, and limitations in daily activities. Conclusions The findings indicate that BPH contributes to the incidence of falls among older men, particularly those with comorbid conditions. Considering the heightened fall risk among elderly individuals suffering from multiple morbidities, particularly those with BPH, targeted interventions are essential for mitigating the risk of falls in this vulnerable group.

Purpose: Semantic segmentation is a fundamental part of the surgical application of deep learning. Traditionally, segmentation in vision tasks has been performed using convolutional neural networks (CNNs), but the transformer architecture has recently been introduced and widely investigated. We aimed to investigate the performance of deep learning models in segmentation in robot-assisted radical prostatectomy (RARP) and identify which of the architectures is superior for segmentation in robotic surgery. Materials and Methods: Intraoperative images during RARP were obtained. The dataset was randomly split into training and validation data. Segmentation of the surgical instruments, bladder, prostate, vas and seminal vesicle was performed using three CNN models (DeepLabv3, MANet, and U-Net++) and three transformers (SegFormer, BEiT, and DPT), and their performances were analyzed. Results: The overall segmentation performance during RARP varied across different model architectures. For the CNN models, DeepLabV3 achieved a mean Dice score of 0.938, MANet scored 0.944, and U-Net++ reached 0.930. For the transformer architectures, SegFormer attained a mean Dice score of 0.919, BEiT scored 0.916, and DPT achieved 0.940. The performance of CNN models was superior to that of transformer models in segmenting the prostate, vas, and seminal vesicle. Conclusions Deep learning models provided accurate segmentation of the surgical instruments and anatomical structures observed during RARP. Both CNN and transformer models showed reliable predictions in the segmentation task; however, CNN models may be more suitable than transformer models for organ segmentation and may be more applicable in unusual cases. Further research with large datasets is needed.

Purpose: With the recent rising interest in artificial intelligence (AI) in medicine, many studies have explored the potential and usefulness of AI in urological diseases. This study aimed to comprehensively review recent applications of AI in urologic oncology. Materials and Methods: We searched the PubMed-MEDLINE databases for articles in English on machine learning (ML) and deep learning (DL) models related to general surgery and prostate, bladder, and kidney cancer. The search terms were a combination of keywords, including both “urology” and “artificial intelligence” with one of the following: “machine learning,” “deep learning,” “neural network,” “renal cell carcinoma,” “kidney cancer,” “urothelial carcinoma,” “bladder cancer,” “prostate cancer,” and “robotic surgery.” Results: A total of 58 articles were included. The studies on prostate cancer were related to grade prediction, improved diagnosis, and predicting outcomes and recurrence. The studies on bladder cancer mainly used radiomics to identify aggressive tumors and predict treatment outcomes, recurrence, and survival rates. Most studies on the application of ML and DL in kidney cancer were focused on the differentiation of benign and malignant tumors as well as prediction of their grade and subtype. Most studies suggested that methods using AI may be better than or similar to existing traditional methods. Conclusions AI technology is actively being investigated in the field of urological cancers as a tool for diagnosis, prediction of prognosis, and decision-making and is expected to be applied in additional clinical areas soon. Despite technological, legal, and ethical concerns, AI will change the landscape of urological cancer management.

Purpose: We investigated the relationship between nocturia and mortality risk in the United States. Methods: Data were obtained from the National Health and Nutrition Examination Survey 2005–2010. Mortality data were obtained by linking the primary database to death certificate data found in the National Death Index with mortality follow-up up to December 31, 2015. Nocturia was defined based on symptoms reported in the symptom questionnaire. We categorized patients into 2 groups: mild nocturia (2–3 voidsight) and moderate-to severe nocturia (≥4 voidsight). Multiple Cox regression analyses were performed with adjustment for confounding variables at the baseline survey. Results: This study included 9,892 adults (4,758 men, 5,134 women). Nocturia occurred in 3,314 individuals (33.5%). Nocturia was significantly associated with all-cause mortality (hazard ratio [HR], 1.23; 95% confidence interval [CI], 1.10–1.39) and cardiovascular disease (CVD) mortality (HR, 1.55; 95% CI, 1.19–2.01). Moreover, the mortality risk increased with increasing nocturia severity. Further analysis with propensity score matching showed that nocturia was still significantly associated with all-cause mortality and CVD mortality. In subgroup analysis according to sex, nocturia was significantly associated with allcause mortality and CVD mortality in men. In women, moderate-to-severe nocturia was significantly associated with allcause mortality and CVD mortality. In subgroup analysis according to cardio-metabolic diseases, nocturia was associated with CVD mortality in patients with diabetes mellitus, hypertension, dyslipidemia, or CVD at baseline. In subgroup analysis of patients without diabetes mellitus, hypertension or CVD, nocturia was significantly associated with all-cause mortality. Conclusions Nocturia was significantly associated with mortality in men and women after adjusting for major confounding factors.

Purpose: This study aimed to examine the causes of death in Korean patients who underwent radical prostatectomy for prostate cancer and investigate the relationship between comorbidity and mortality. Materials and Methods: We conducted a retrospective multicenter cohort study including 4,064 consecutive patients who had prostate cancer and underwent radical prostatectomy between January 1998 and June 2013. The primary endpoint of this study was all-cause mortality, and the secondary endpoints were cancer-specific mortality (CSM) and other-cause mortality (OCM). Charlson comorbidity index (CCI) was calculated to assess the comorbidities of each patient. Results: Of 4,064 patients, 446 (11.0%) died during follow-up. The cause of death was prostate cancer in 132 patients (29.6%), other cancers in 121 patients (27.1%), and vascular disease in 57 patients (12.8%) in our cohort. The overall 10-year CSM rate was lower than the OCM rate (4.6% vs. 10.5%). The 10-year CSM rate was lower than the OCM rate in low- to intermediate-risk group patients (1.2% vs. 10.6%), whereas they were similar in high-risk group patients (11.8% vs. 10.1%). In the multivariable analysis, CCI was independently associated with all-cause mortality after radical prostatectomy, regardless of age and pathologic features. Conclusion Death from prostate cancer was rare in Korean men who underwent radical prostatectomy. Clinicians should be aware of the possibility of overtreatment of low-risk prostate cancer in men with significant comorbidity. Our findings may help to facilitate counseling and plan management in this patient group.