Background: and Purpose Parkinson’s disease (PD) is characterized by various prodromal symptoms, and these symptoms are mostly investigated retrospectively. While some symptoms such as rapid eye movement sleep behavior disorder are highly specific, others are common. This makes it challenging to predict those at risk of PD based solely on less-specific prodromal symptoms. The prediction accuracy when using only less-specific symptoms can be improved by analyzing the vast amount of information available using sophisticated deep-learning techniques. This study aimed to improve the performance of deep-learning-based screening in detecting prodromal PD using medical-claims data, including prescription information. Methods: We sampled 820 PD patients and 8,200 age- and sex-matched non-PD controls from Korean National Health Insurance cohort data. A deep-learning algorithm was developed using various combinations of diagnostic codes, medication codes, and prodromal periods. Results: During the prodromal period from year -3 to year 0, predicting PD using only diagnostic codes yielded a high accuracy of 0.937. Adding medication codes for the same period did not increase the accuracy (0.931–0.935). For the earlier prodromal period (year -6 to year -3), the accuracy of PD prediction decreased to 0.890 when using only diagnostic codes. The inclusion of all medication-codes data increased that accuracy markedly to 0.922. Conclusions A deep-learning algorithm using both prodromal diagnostic and medication codes was effective in screening PD. Developing a surveillance system with automatically collected medical-claims data for those at risk of developing PD could be cost-effective. This approach could streamline the process of developing disease-modifying drugs by focusing on the most-appropriate candidates for inclusion in accurate diagnostic tests.

Background: and Purpose Parkinson’s disease (PD) is characterized by various prodromal symptoms, and these symptoms are mostly investigated retrospectively. While some symptoms such as rapid eye movement sleep behavior disorder are highly specific, others are common. This makes it challenging to predict those at risk of PD based solely on less-specific prodromal symptoms. The prediction accuracy when using only less-specific symptoms can be improved by analyzing the vast amount of information available using sophisticated deep-learning techniques. This study aimed to improve the performance of deep-learning-based screening in detecting prodromal PD using medical-claims data, including prescription information. Methods: We sampled 820 PD patients and 8,200 age- and sex-matched non-PD controls from Korean National Health Insurance cohort data. A deep-learning algorithm was developed using various combinations of diagnostic codes, medication codes, and prodromal periods. Results: During the prodromal period from year -3 to year 0, predicting PD using only diagnostic codes yielded a high accuracy of 0.937. Adding medication codes for the same period did not increase the accuracy (0.931–0.935). For the earlier prodromal period (year -6 to year -3), the accuracy of PD prediction decreased to 0.890 when using only diagnostic codes. The inclusion of all medication-codes data increased that accuracy markedly to 0.922. Conclusions A deep-learning algorithm using both prodromal diagnostic and medication codes was effective in screening PD. Developing a surveillance system with automatically collected medical-claims data for those at risk of developing PD could be cost-effective. This approach could streamline the process of developing disease-modifying drugs by focusing on the most-appropriate candidates for inclusion in accurate diagnostic tests.

Background: and Purpose Parkinson’s disease (PD) is characterized by various prodromal symptoms, and these symptoms are mostly investigated retrospectively. While some symptoms such as rapid eye movement sleep behavior disorder are highly specific, others are common. This makes it challenging to predict those at risk of PD based solely on less-specific prodromal symptoms. The prediction accuracy when using only less-specific symptoms can be improved by analyzing the vast amount of information available using sophisticated deep-learning techniques. This study aimed to improve the performance of deep-learning-based screening in detecting prodromal PD using medical-claims data, including prescription information. Methods: We sampled 820 PD patients and 8,200 age- and sex-matched non-PD controls from Korean National Health Insurance cohort data. A deep-learning algorithm was developed using various combinations of diagnostic codes, medication codes, and prodromal periods. Results: During the prodromal period from year -3 to year 0, predicting PD using only diagnostic codes yielded a high accuracy of 0.937. Adding medication codes for the same period did not increase the accuracy (0.931–0.935). For the earlier prodromal period (year -6 to year -3), the accuracy of PD prediction decreased to 0.890 when using only diagnostic codes. The inclusion of all medication-codes data increased that accuracy markedly to 0.922. Conclusions A deep-learning algorithm using both prodromal diagnostic and medication codes was effective in screening PD. Developing a surveillance system with automatically collected medical-claims data for those at risk of developing PD could be cost-effective. This approach could streamline the process of developing disease-modifying drugs by focusing on the most-appropriate candidates for inclusion in accurate diagnostic tests.

A 40-year-old female visited our clinic for visual disturbance of the right eye, in which a few creamy-yellow retinal lesions and visual field constrictions were noted. She had been treated for primary CNS lymphoma and was in complete remission. After failure to follow-up for three months, she lost vision in the right eye, at which time active panuveitis was seen. Decreased vision and field constriction was observed in the left eye. Her left eye showed a granular pattern and dye leakage from the vessels and disc on fluorescein angiography and small RPE humps were seen in optical coherence tomography (OCT). Diffuse large malignant B-cells with strong immunoreactivities with CD20 immunostaining were seen in the epiretinal membrane biopsy specimen. Intravitreal injections of methotrexate (MTX) (800 microgram/0.1 ml in the right eye, 400 microgram/0.05 ml in the left eye) were performed twice weekly for one month, once weekly for the following month, once every two weeks for the next month, followed by nine monthly injections. Both eyes were free from malignant cells on vitreous biopsy six months later. There was no leakage seen by angiography, but the granular pattern persisted. Visual field constriction was slightly improved, and the small RPE humpsdetachments seen in OCT disappeared. EOG Arden ratio was decreased in both eyes, and b wave amplitude of scotopic ERG was decreased in the left eye. She was free from recurrence until six months later. No ocular complications except minimal opacity of the crystalline lenses were noted in both eyes.
Adult ; Antimetabolites, Antineoplastic/*administration & dosage ; Drug Administration Schedule ; Eye Neoplasms/*drug therapy ; Female ; Humans ; Injections ; Lymphoma/*drug therapy ; Methotrexate/*administration & dosage ; Treatment Outcome ; Vitreous Body

No abstract available.
Diffusion Magnetic Resonance Imaging ; Diffusion ; Optic Nerve Diseases ; Optic Nerve ; Optic Neuritis

No abstract available.
Blepharoptosis ; Headache ; Sinusitis

Traffic-related pollutants have been reported to increase the morbidity of respiratory diseases. In order to apply management policies related to motor vehicles, studies of the floating population living in cities are important. The rate of metro rail transit system use by passengers residing in Seoul is about 54% of total public transportation use. Through the rate of metro use, the people-flow ratios in each administrative area were calculated. By applying a people-flow ratio based on the official census count, the floating population in 25 regions was calculated. The reduced level of deaths among the floating population in 14 regions having the roadside monitoring station was calculated as assuming a 20% reduction of mobile emission based on the policy. The hourly floating population size was calculated by applying the hourly population ratio to the regional population size as specified in the official census count. The number of people moving from 5 a.m. to next day 1 a.m. could not be precisely calculated when the population size was applied, but no issue was observed that would trigger a sizable shift in the rate of population change. The three patterns of increase, decrease, and no change of population in work hours were analyzed. When the concentration of particulate matter less than 10 μm in aerodynamic diameter was reduced by 20%, the number of excess deaths varied according to the difference of the floating population. The effective establishment of directions to manage the pollutants in cities should be carried out by considering the floating population. Although the number of people using the metro system is only an estimate, this disadvantage was supplemented by calculating inflow and outflow ratio of metro users per time in the total floating population in each region. Especially, 54% of metro usage in public transport causes high reliability in application.
Censuses ; Korea ; Motor Vehicles ; Particulate Matter ; Population Density ; Seoul ; Transportation

Salivary function in mammals may be defective for various reasons, such as aging, Sjogren's syndrome or radiation therapy in head and neck cancer patients. Recently, tissue-specific stem cell therapy has attracted public attention as a next-generation therapeutic reagent. In the present study, we isolated tissue-specific stem cells from the human submandibular salivary gland (hSGSCs). To efficiently isolate and amplify hSGSCs in large amounts, we developed a culture system (lasting 4-5 weeks) without any selection. After five passages, we obtained adherent cells that expressed mesenchymal stem cell surface antigen markers, such as CD44, CD49f, CD90 and CD105, but not the hematopoietic stem cell markers, CD34 and CD45, and that were able to undergo adipogenic, osteogenic and chondrogenic differentiation. In addition, hSGSCs were differentiated into amylase-expressing cells by using a two-step differentiation method. Transplantation of hSGSCs to radiation-damaged rat salivary glands rescued hyposalivation and body weight loss, restored acinar and duct cell structure, and decreased the amount of apoptotic cells. These data suggest that the isolated hSGSCs, which may have characteristics of mesenchymal-like stem cells, could be used as a cell therapy agent for the damaged salivary gland.
Amylases/genetics/metabolism ; Animals ; Antigens, CD/genetics/metabolism ; Apoptosis ; Cell Differentiation ; Humans ; Male ; Mesenchymal Stromal Cells/*cytology/metabolism ; Radiation Injuries, Experimental ; Rats ; Rats, Wistar ; *Regeneration ; Salivary Glands/cytology/injuries/physiology/*surgery ; *Salivation ; *Stem Cell Transplantation

Sarcoidosis is an idiopathic multisystemic granulomatous disorder that most commonly affects young adults. It most frequently presents with bilateral hilar lesions, lymphadenopathy, pulmonary infiltration and cutaneous or ocular lesions. Cutaneous sarcoidosis occurs in 20% to 35% of the case of systemic sarcoidosis, but it can occur without systemic disease, as in the patient whose case is described herein. We present a patient with cutaneous sarcoidosis and who developed specific sarcoidosis lesions in the mucous membrane of the lower lip. To the best of our knowledge, the lip is the rare site for the occurance of sarcoidosis, as reported in the Korean literature. Herein, we report on a 53-year-old woman who had an asymptomatic mass on the lip and this was diagnosed as sarcoidosis.
Female ; Humans ; Lip ; Lymphatic Diseases ; Membranes ; Middle Aged ; Mucous Membrane ; Sarcoidosis ; Young Adult

Background: This study was performed to evaluate the effect of a wagon as a transport vehicle instead of the standard stretcher car to reduce children’s anxiety of separation from parents. The secondary goal was to evaluate whether this anxiolytic effect was related to age. Methods: We divided 80 children (age 2–7 years) into two groups. The stretcher group was transferred to the operating room on a conventional stretcher car, whereas the wagon group was transferred using a wagon. The level of anxiety was evaluated three times using the Modified Yale Preoperative Anxiety Scale (mYPAS): in the waiting area (T0), in the hallway to the operating room (T1), and before induction of anesthesia (T2). Results: The mYPAS score was significantly lower in the wagon group (36.7 [31.7, 51.7]) than in the stretcher group (51.7 [36.7, 83.3]) at T1 (P = 0.007). However, there was no difference in the mYPAS score between the two groups at T2 (46.7 [32.5, 54.2] vs. 51.7 [36.7, 75.0], respectively, P = 0.057). The baseline anxiety tended to be lower with increasing age (r = −0.248, P = 0.031). During transportation to the operating room, the increase in the mYPAS score (T1-T0) was greater as the age of children decreased in the stretcher group (r = −0.340, P = 0.034). However, no correlation was observed in the wagon group (r = −0.053, P = 0.756). Conclusion The wagon method decreased preoperative anxiety, suggesting that it may be a good alternative for reducing preoperative anxiety in children.