ObjectiveThis study aimed to evaluate the relationship between insulin resistance and the bone mineral density (BMD) of femur and lumbar spine in Korean adults who are expected to exhibit near peak bone mass.MethodsData from the Korean National Health and Nutrition Examination Survey 2008–2010 were analyzed. A total of 2,750 participants aged 25−35 years were included. Insulin resistance was assessed using a homeostatic model assessment of insulin resistance (HOMA-IR) and serum fasting insulin.ResultsIn a multivariate linear regression analysis, the HOMA-IR was significantly inversely associated with the BMD of the total hip (TH, β = −0.052, P = 0.002), femoral neck (FN, β = −0.072, P<0.001), femoral trochanter (FTr, β = −0.055, P = 0.003), femoral intertrochanter (FITr, β = −0.041, P = 0.015), and lumbar spine (LS, β = −0.063, P = 0.001) among all study subjects after adjustment for gender, age, height, weight, whole body fat mass percentage, systolic blood pressure, diastolic blood pressure, total cholesterol, triglyceride, high-density lipoprotein cholesterol, low-density lipoprotein cholesterol, vitamin D, smoking, alcohol intake, physical activity, education level, and household income in both genders as well as labor, the use of oral contraceptives, and age at menarche in females. The serum fasting insulin was significantly inversely associated with the BMD of the TH (β = −0.055, P = 0.001), FN (β = −0.072, P<0.001), FTr (β = −0.055, P = 0.003), FITr (β = −0.045, P = 0.009), and LS (β = −0.064, P = 0.001) among all subjects in a multivariate linear regression analysis.ConclusionOur results suggest that insulin resistance may be independently and inversely associated with the near peak bone mass of the femur and lumbar spine.

Purpose This study aimed to predict the composition of urolithiasis using deep learning from urinary stone images. Materials and Methods We classified 1,332 stones into 31 classes according to the stone composition. The top 4 classes with a frequency of 110 or more (class 1: calcium oxalate monohydrate [COM] 100%, class 2: COM 80%+struvite 20%, class 3: COM 60%+calcium oxalate dihydrate [COD] 40%, class 4: uric acid 100%) were selected. With the 965 stone images of the top 4 classes, we used the seven convolutional neural networks (CNN) to classify urinary stones and compared their classification performances. Results Among the seven models, Xception_Ir0.001 showed the highest accuracy, precision, and recall and was selected as the CNN model to predict the stone composition. The sensitivity and specificity for the 4 classes by Xception_Ir0.001 were as follows: class 1 (94.24%, 91.73%), class 2 (85.42%, 96.14%), class 3 (86.86%, 99.59%), and class 4 (94.96%, 98.82%). The sensitivity and specificity of the individual components of the stones were as follows. COM (98.82%, 94.96%), COD (86.86%, 99.64%), struvite (85.42%, 95.59%), and uric acid (94.96%, 98.82%). The area under the curves for class 1, 2, 3, and 4 were 0.98, 0.97, 1.00, and 1.00, respectively. Conclusions This study showed the feasibility of deep learning for the diagnostic ability to assess urinary stone composition from images. It can be an alternative tool for conventional stone analysis and provide decision support to urologists, improving the effectiveness of diagnosis and treatment.

Background Demographic change and advances in technology affect transurethral surgery and outpatient procedures in the urologic field. There are few population-based studies that accurately assess the trend of transurethral surgery and outpatient procedures including diagnostic tests. We investigated the recent epidemiologic trends in transurethral surgeries and urological outpatient procedures from 2009 to 2016 in Korea using the entire population-based cohort. Methods We analyzed medical service claim data of transurethral surgery, urological outpatient procedures submitted by medical service providers from the Health Insurance Review and Assessment Service from 2009 to 2016. Results Transurethral ureter surgery increased by 134.9% from 14,635 in 2009 to 34,382 in 2016 (B = 2,698; R 2 = 0.98; P < 0.001). The transurethral bladder surgery increased by 65.5% from 12,482 in 2009 to 20,658 in 2016 (B = 1,149; R 2 = 0.97; P < 0.001). Over the 8-years period, there were not significant changes in transurethral prostate (B = 43; R 2 = 0.04; P = 0.617) and urethral surgery (B = −12; R 2 = 0.18; P = 0.289). The significantly increasing trends in cystoscopy (B = 5,260; R 2 = 0.95; P < 0.001) and uroflowmetry (B = 53,942; R 2 = 0.99; P < 0.001) were observed during the 8-year period. There was no difference in bladder catheterization during the 8-year period. Urodynamic study (UDS: B = −2,156; R 2 = 0.77; P = 0.003) and electrical stimulation treatment (EST: B = −1,034; R 2 = 0.87; P < 0.001) significantly decreased. Conclusion In Korea, transurethral ureter surgery and transurethral bladder surgery have been continuously increasing. Transurethral prostate surgery and transurethral urethral surgery remained constant with no increase or decrease. Cystoscopy and uroflowmetry continue to increase, while UDS and EST continue to decrease.

Purpose: The Korean Renal Cancer Study Group (KRoCS) provides consensus recommendations on the role of cytoreductive nephrectomy (CRN) in patients with metastatic renal cell carcinoma (mRCC).Materials and Methods: A group of mRCC experts from the Korean Urological Oncology Society convened at the 2021 KRoCS meeting on CRN for mRCC.Results: The consensus document was developed to address 4 questions related that were judged to be the most relevant to patient care: (1) Is there a role for CRN in patients planning targeted therapy? (2) Is there a role for CRN in patients planning immuno-oncology agents? (3) When is the optimal time of CRN in patients planning systemic treatment? (4) What is the ideal patient selection for CRN? The panelists have come up with following consensus. For mRCC patients, CRN should be considered only in those with IMDC (International Metastatic Renal Cell Carcinoma Database Consortium) favorable and intermediate risk disease, regardless of the systemic treatment plans. Timing of CRN should consider the risk group as well as the number of risk factors, but is generally recommended for after assessing the degree of response to initial systemic treatment. Patients with good performance status, limited metastatic burden on top of resectable primary tumor are candidates recommended for CRN with or without metastasectomy with priority.Conclusions: In conclusion, there is still a role for CRN in the multimodality treatment of mRCC. Careful patient selection is of paramount importance. As the treatment landscape of mRCC continues to change, the role of CRN in the current immuno-oncology era will require more exploration.