Background/Aims: The kidneys and retina are highly vascularized organs that frequently exhibit shared pathologies, with nephropathy often associated with retinopathy. Previous studies have successfully predicted estimated glomerular filtration rates (eGFRs) using fundus photographs. We evaluated the performance of the Modification of Diet in Renal Disease (MDRD) and Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) formulas in eGFR prediction. Methods: We enrolled patients with fundus photographs and corresponding creatinine measurements taken on the same date. One photograph per eye was randomly selected, resulting in a final dataset of 45,108 patients (88,260 photographs). Data including sex, age, and blood creatinine levels were collected for eGFR calculation using the MDRD and CKD-EPI formulas. EfficientNet B3 models were used to predict each parameter. Results: Deep neural network models accurately predicted age and sex using fundus photographs. Sex was identified as a confounding variable in creatinine prediction. The MDRD formula was more susceptible to this confounding effect than the CKD-EPI formula. Notably, the CKD-EPI formula demonstrated superior performance compared to the MDRD formula (area under the curve 0.864 vs. 0.802). Conclusions Fundus photographs are a valuable tool for screening renal function using deep neural network models, demonstrating the role of noninvasive imaging in medical diagnostics. However, these models are susceptible to the influence of sex, a potential confounding factor. The CKD-EPI formula, less susceptible to sex bias, is recommended to obtain more reliable results.

Background/Aims: The kidneys and retina are highly vascularized organs that frequently exhibit shared pathologies, with nephropathy often associated with retinopathy. Previous studies have successfully predicted estimated glomerular filtration rates (eGFRs) using fundus photographs. We evaluated the performance of the Modification of Diet in Renal Disease (MDRD) and Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) formulas in eGFR prediction. Methods: We enrolled patients with fundus photographs and corresponding creatinine measurements taken on the same date. One photograph per eye was randomly selected, resulting in a final dataset of 45,108 patients (88,260 photographs). Data including sex, age, and blood creatinine levels were collected for eGFR calculation using the MDRD and CKD-EPI formulas. EfficientNet B3 models were used to predict each parameter. Results: Deep neural network models accurately predicted age and sex using fundus photographs. Sex was identified as a confounding variable in creatinine prediction. The MDRD formula was more susceptible to this confounding effect than the CKD-EPI formula. Notably, the CKD-EPI formula demonstrated superior performance compared to the MDRD formula (area under the curve 0.864 vs. 0.802). Conclusions Fundus photographs are a valuable tool for screening renal function using deep neural network models, demonstrating the role of noninvasive imaging in medical diagnostics. However, these models are susceptible to the influence of sex, a potential confounding factor. The CKD-EPI formula, less susceptible to sex bias, is recommended to obtain more reliable results.

Background/Aims: The kidneys and retina are highly vascularized organs that frequently exhibit shared pathologies, with nephropathy often associated with retinopathy. Previous studies have successfully predicted estimated glomerular filtration rates (eGFRs) using fundus photographs. We evaluated the performance of the Modification of Diet in Renal Disease (MDRD) and Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) formulas in eGFR prediction. Methods: We enrolled patients with fundus photographs and corresponding creatinine measurements taken on the same date. One photograph per eye was randomly selected, resulting in a final dataset of 45,108 patients (88,260 photographs). Data including sex, age, and blood creatinine levels were collected for eGFR calculation using the MDRD and CKD-EPI formulas. EfficientNet B3 models were used to predict each parameter. Results: Deep neural network models accurately predicted age and sex using fundus photographs. Sex was identified as a confounding variable in creatinine prediction. The MDRD formula was more susceptible to this confounding effect than the CKD-EPI formula. Notably, the CKD-EPI formula demonstrated superior performance compared to the MDRD formula (area under the curve 0.864 vs. 0.802). Conclusions Fundus photographs are a valuable tool for screening renal function using deep neural network models, demonstrating the role of noninvasive imaging in medical diagnostics. However, these models are susceptible to the influence of sex, a potential confounding factor. The CKD-EPI formula, less susceptible to sex bias, is recommended to obtain more reliable results.

Background/Aims: The kidneys and retina are highly vascularized organs that frequently exhibit shared pathologies, with nephropathy often associated with retinopathy. Previous studies have successfully predicted estimated glomerular filtration rates (eGFRs) using fundus photographs. We evaluated the performance of the Modification of Diet in Renal Disease (MDRD) and Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) formulas in eGFR prediction. Methods: We enrolled patients with fundus photographs and corresponding creatinine measurements taken on the same date. One photograph per eye was randomly selected, resulting in a final dataset of 45,108 patients (88,260 photographs). Data including sex, age, and blood creatinine levels were collected for eGFR calculation using the MDRD and CKD-EPI formulas. EfficientNet B3 models were used to predict each parameter. Results: Deep neural network models accurately predicted age and sex using fundus photographs. Sex was identified as a confounding variable in creatinine prediction. The MDRD formula was more susceptible to this confounding effect than the CKD-EPI formula. Notably, the CKD-EPI formula demonstrated superior performance compared to the MDRD formula (area under the curve 0.864 vs. 0.802). Conclusions Fundus photographs are a valuable tool for screening renal function using deep neural network models, demonstrating the role of noninvasive imaging in medical diagnostics. However, these models are susceptible to the influence of sex, a potential confounding factor. The CKD-EPI formula, less susceptible to sex bias, is recommended to obtain more reliable results.

Background/Aims: The kidneys and retina are highly vascularized organs that frequently exhibit shared pathologies, with nephropathy often associated with retinopathy. Previous studies have successfully predicted estimated glomerular filtration rates (eGFRs) using fundus photographs. We evaluated the performance of the Modification of Diet in Renal Disease (MDRD) and Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) formulas in eGFR prediction. Methods: We enrolled patients with fundus photographs and corresponding creatinine measurements taken on the same date. One photograph per eye was randomly selected, resulting in a final dataset of 45,108 patients (88,260 photographs). Data including sex, age, and blood creatinine levels were collected for eGFR calculation using the MDRD and CKD-EPI formulas. EfficientNet B3 models were used to predict each parameter. Results: Deep neural network models accurately predicted age and sex using fundus photographs. Sex was identified as a confounding variable in creatinine prediction. The MDRD formula was more susceptible to this confounding effect than the CKD-EPI formula. Notably, the CKD-EPI formula demonstrated superior performance compared to the MDRD formula (area under the curve 0.864 vs. 0.802). Conclusions Fundus photographs are a valuable tool for screening renal function using deep neural network models, demonstrating the role of noninvasive imaging in medical diagnostics. However, these models are susceptible to the influence of sex, a potential confounding factor. The CKD-EPI formula, less susceptible to sex bias, is recommended to obtain more reliable results.

Background: A healthcare system’s collapse due to a pandemic, such as the coronavirus disease 2019 (COVID-19), can expose healthcare workers (HCWs) to various mental health problems. This study aimed to investigate the impact of the COVID-19 pandemic on the depression and anxiety of HCWs. Methods: A nationwide questionnaire-based survey was conducted on HCWs who worked in healthcare facilities and public health centers in Korea in December 2020. Patient Health Questionnaire-9 (PHQ-9) and Generalized Anxiety Disorder-7 (GAD-7) were used to measure depression and anxiety. To investigate factors associated with depression and anxiety, stepwise multiple logistic regression analysis was performed. Results: A total of 1,425 participating HCWs were included. The mean depression score (PHQ-9) of HCWs before and after COVID-19 increased from 2.37 to 5.39, and the mean anxiety score (GAD-7) increased from 1.41 to 3.41. The proportion of HCWs with moderate to severe depression (PHQ-9 ≥ 10) increased from 3.8% before COVID-19 to 19.5% after COVID-19, whereas that of HCWs with moderate to severe anxiety (GAD-7 ≥ 10) increased from 2.0% to 10.1%. In our study, insomnia, chronic fatigue symptoms and physical symptoms after COVID-19, anxiety score (GAD-7) after COVID-19, living alone, and exhaustion were positively correlated with depression. Furthermore, post-traumatic stress symptoms, stress score (Global Assessment of Recent Stress), depression score (PHQ-9) after COVID-19, and exhaustion were positively correlated with anxiety. Conclusion In Korea, during the COVID-19 pandemic, HCWs commonly suffered from mental health problems, including depression and anxiety. Regularly checking the physical and mental health problems of HCWs during the COVID-19 pandemic is crucial, and social support and strategy are needed to reduce the heavy workload and psychological distress of HCWs.

Objective: Recently, evidence has suggested that the pathophysiology and risk factors of intracranial atherosclerosis (ICAS) differs from those of extracranial atherosclerosis (ECAS). In addition, novel parameters reflecting metabolic conditions, such as insulin resistance or atherogenic dyslipidemia, based on triglycerides (TG) and other biomarkers, have emerged. In this study, we evaluated the association between TG-related parameters and symptomatic cerebral atherosclerosis in patients with acute ischemic stroke resulting from large artery atherosclerosis (LAA). Methods: We assessed consecutive acute LAA-stroke patients between January 2010 and December 2020. Based on the radiological findings, we classified the relevant symptomatic arteries that caused the index stroke into LAA-ICAS and LAA-ECAS. As TGrelated parameters, the atherogenic index of plasma (AIP) and TG-glucose (TyG) index were calculated according to the following formulas: AIP = log10 (TG Level/High-density Lipoprotein Cholesterol Level), TyG Index = Ln (TG Level × Glucose Level/2). Results: A total of 519 patients with LAA-stroke were evaluated. In multivariable logistic regression analysis to identify predictors of LAA-ICAS, AIP was significantly associated with LAA-ICAS (adjusted odds ratio [aOR], 3.60; 95% confidence interval [CI], 1.60–8.06). TyG index also showed a statistically significant relationship with LAA-ICAS (aOR, 1.60; 95% CI, 1.11–2.32). However, TG per se did not show a statistical association with LAA-ECAS. Conclusion TG-related parameters were more closely associated with stroke by ICAS than by ECAS. The metabolic conditions reflected by the AIP or TyG index, rather than hypertriglyceridemia itself, may play a greater role in determining the relevant vessel causally involved in a stroke.

Objectives: The aim of this study was to determine the most effective treatment approach by comparing the impacts of various otolith reduction techniques in patients with apogeotropic lateral semicircular canal benign paroxysmal positional vertigo (LC-BPPV). Methods: We performed a multicenter randomized prospective study from January to December 2015, involving 72 consecutive patients with apogeotropic LC-BPPV. The patients were divided into three treatment groups: therapeutic head-shaking (group A), the Gufoni-Appiani maneuver (group B), and the cupulolith repositioning maneuver (CuRM; group C). Each group underwent evaluation and treatment up to the fourth week. Treatment success was defined as the disappearance of positional vertigo and nystagmus. Results: This study included 72 patients (49 male and 23 female), with a mean (±standard deviation) age of 55.4±13.5 years. The mean duration of vertigo experienced prior to treatment was 3.9±4.4 days. The mean latency and duration of nystagmus were 2.7±3.0 seconds and 47.9±15.8 seconds, respectively. The overall treatment frequency was 2.0±0.9. The number of treatments differed significantly among the three groups (P<0.05). After 4 weeks, the success rates for groups A, B, and C were 90.5%, 92.3%, and 100%, respectively. No significant difference was observed in the success rate across treatment methods and periods (P>0.05). However, CuRM was the only method with a 100% treatment success rate. Conclusion While no clear difference was observed among the three treatments for LC-BPPV, CuRM was found to be superior to the other approaches in the long term.

Background: Traumatic spinal injuries in children are uncommon and result in different patterns of injuries due to the anatomical characteristics of children’s spines. However, there are only a few epidemiological studies of traumatic spinal injury in children. The purpose of this study was to investigate the characteristics of traumatic spinal injury in children. Methods: We retrospectively reviewed the cases of pediatric patients (age < 18 years) with traumatic spinal injury who were treated at a level 1 trauma center between January 2017 and December 2021. We divided them into three groups according to age and analyzed demographics, injury mechanism, level of injury, and injury pattern. Results: A total of 62 patients (255 fractures) were included, and the mean age was 13.8 ± 3.2 years. There were 5 patients (22 fractures) in group I (0–9 years), 24 patients (82 fractures) in group II (10–14 years), and 33 patients (151 fractures) in group III (15–17 years). Both the Injury Severity Score and the Revised Trauma Score were highest in group I, but there was no statistical difference between the age groups. Fall from height was the most common injury mechanism, of which 63% were suicide attempts. The level of spinal injury was different in each age group, T10–L2 injury being the most common. In all age groups, the number of multilevel continuous injury was larger than that of single-level injury or multilevel noncontinuous injury. Surgical intervention was required in 33.9%, and mortality was 3.2%. Conclusions In our study, fall from height was the most common mechanism of injury, and there were many suicide attempts associated with mental health issues. Thoracolumbar junction injuries were predominant, and the rate of multilevel contiguous injuries was high. The support and interest of the society and families for adolescent children seem crucial in preventing spinal trauma, and image testing of the entire spine is essential when evaluating pediatric spinal injuries.