OBJECTIVE: Many people dealing with Parkinson’s disease (PD) turn to complementary and alternative medicine when searching for a cure or relief from symptoms. Acupuncture is widely used in the Korean PD population to alleviate symptoms and in hopes of curing the illness. However, acupuncture use for PD patients has only recently begun to be studied scientifically and is still considered an unproven treatment for PD. Therefore, there is an urgent need for acupuncture to be studied, validated and used for PD. Thus, our study’s aim is to examine how many acupuncture studies in PD are registered and reported in Korea. METHODS: The registries Clinicaltrials.gov and the Clinical Research Information Service (CRIS) and the search engine PubMed were searched to find relevant human clinical studies involving acupuncture therapy in PD patients. We examined the registration of trials, the posting and publication of results, and whether published articles were registered. RESULTS: In Clinicaltrials.gov, one completed trial was found with published results. In CRIS, one completed trial was found with published results. A total of 6 publications were found in our study: 2 articles were registered, but only 1 had the registered trial number listed in the article. CONCLUSION: Acupuncture is popular among the PD population in Korea regardless of its unproven safety and efficacy. Despite the pressing need for clinical trials, the number of studies listed in the registries was small, and only a few publications were registered. More effort and rigor are needed to validate the efficacy and safety of acupuncture for PD.
Acupuncture Therapy ; Acupuncture* ; Complementary Therapies ; Hope ; Humans ; Information Services ; Korea* ; Parkinson Disease* ; Publications ; Registries ; Search Engine

BACKGROUND AND PURPOSE: Research on stem cells (SC) is growing rapidly in neurology, but clinical applications of SC for neurological disorders remain to be proven effective and safe. Human clinical trials need to be registered in registries in order to reduce publication bias and selective reporting. METHODS: We searched three databases—clinicaltrials.gov, the Clinical Research Information System (CRIS), and PubMed—for neurologically relevant SC-based human trials and articles in Korea. The registration of trials, posting and publication of results, and registration of published SC articles were examined. RESULTS: There were 17 completed trials registered at clinicaltrials.gov and the CRIS website, with results articles having been published for 5 of them. Our study found 16 publications, of which 1 was a review article, 1 was a protocol article, and 8 contained registered trial information. CONCLUSIONS: Many registered SC trials related to neurological disorders are not reported, while many SC-related publications are not registered in a public registry. These results support the presence of biased reporting and publication bias in SC trials related to neurological disorders in Korea.
Bias (Epidemiology) ; Humans ; Information Systems ; Korea ; Nervous System Diseases* ; Neurology ; Publication Bias ; Publications ; Registries ; Stem Cells*

Previously, we defined DRD as a syndrome of selective nigrostriatal dopamine deficiency caused by genetic defects in the dopamine synthetic pathway without nigral cell loss. DRD-plus also has the same etiologic background with DRD, but DRD-plus patients have more severe features that are not seen in DRD because of the severity of the genetic defect. However, there have been many reports of dystonia responsive to dopaminergic drugs that do not fit into DRD or DRD-plus (genetic defects in the dopamine synthetic pathway without nigral cell loss). We reframed the concept of DRD/DRD-plus and proposed the concept of DRD look-alike to include the additional cases described above. Examples of dystonia that is responsive to dopaminergic drugs include the following: transportopathies (dopamine transporter deficiency; vesicular monoamine transporter 2 deficiency); SOX6 mutation resulting in a developmentally decreased number of nigral cells; degenerative disorders with progressive loss of nigral cells (juvenile Parkinson's disease; pallidopyramidal syndrome; spinocerebellar ataxia type 3), and disorders that are not known to affect the nigrostriatal dopaminergic system (DYT1; GLUT1 deficiency; myoclonus-dystonia; ataxia telangiectasia). This classification will help with an etiologic diagnosis as well as planning the work up and guiding the therapy.
Ataxia ; Classification ; Diagnosis ; Dopamine ; Dopamine Agents ; Dystonia* ; Humans ; Parkinson Disease ; Spinocerebellar Ataxias ; Vesicular Monoamine Transport Proteins

We aimed to determine normal reference ranges for prostate volume (PV) and annual PV change rate in a Korean nationwide screening population. Data from men who underwent a routine health check-up were collected from 13 university hospitals. The cohort comprised men aged > or =40 yr who had undergone 2 or more serial transrectal ultrasonographies. Men with initial PV>100 mL; serum PSA level>10 ng/mL; PV reduction>20% compared with initial PV, or who had history of prostate cancer or prostate surgery, were excluded. Linear regression and mixed effects regression analyses were used to predict mean PV and longitudinal change in PV over time. A total of 2,967 men formed the study cohort. Age, body mass index (BMI), and serum prostate-specific antigen (PSA) level were found to be significant predictors of PV. A predicted PV table, with a 95% confidence interval (CIs), was developed after adjusting for these 3 variables. Annual PV change rate was 0.51 mL/year (95% CI, 0.47-0.55). Annual PV change rate according to age was 0.68 mL/year, 0.84 mL/year, 1.09 mL/year, and 0.50 mL/year for subjects in their 40s, 50s, 60s, and > or =70 yr, respectively. Predicted annual PV change rate differed depending on age, BMI, serum PSA level and baseline PV. From a nationwide screening database, we established age-, PSA-, and BMI-specific reference ranges for PV and annual PV change rate in Korean men. Our newly established reference ranges for PV and annual PV change rate will be valuable in interpreting PV data in Korean men.
Adult ; Aged ; Aged, 80 and over ; Aging/*pathology ; Humans ; Male ; Mass Screening/*standards ; Middle Aged ; Organ Size ; Prostate/*anatomy & histology/ultrasonography ; Reference Values ; Reproducibility of Results ; Republic of Korea ; Sensitivity and Specificity ; Ultrasonography/*standards ; Urology/*standards

Background: and PurposeThis study aimed to determine the updated 10-year prevalence of Huntington’s disease (HD) in South Korea and the medical and economic burdens across the duration of the disease. Methods: Data from the National Health Insurance database during 2010–2019 were analyzed. We identified HD cases using predefined criteria. Information on age at diagnosis, sex, and common nonneurological comorbidities were collected. We analyzed individual patterns of the use of medical services and yearly medical expenditure. Incidence rates, 10-year prevalence rates, and longitudinal medical expenditure changes were assessed. Results: New patients with HD (average=152.10) were detected every year, with an annual incidence of 0.29 per 100,000. The estimated 10-year prevalence of HD was 2.2 per 100,000. The most common ages at the time of diagnosis were 50–59 years (23.3%). In 2019, 56.4% of patients with HD were followed-up at referral or general hospitals, and 32.2% were managed at long-term-care hospitals. The annual medical cost for an individual was KRW 6,569,341±895,097 (mean±SD) (mean≈USD 5,653). Medical expenditure was the highest in those aged 60–79 years, and lowest in those younger than 30 years. However, in all age groups, the annual medical expenditure was highest during the 9 years following a diagnosis. Conclusions This study found that the actual prevalence of HD in South Korea was higher than previously thought and that patients are in a situation with high medical expenditure that persists over time.

Forced-air warming is commonly utilized to prevent perioperative hypothermia. Underbody warming blankets are often employed to secure a larger area for patient warming. While forced-air warming systems are generally regarded as safe, improper usage poses a risk of cutaneous complications. Additionally, the influence of underbody blankets on cutaneous complications remains uncertain. We present a case of cutaneous complications resulting from the improper utilization of a forced-air warming device and an underbody blanket. A 79-year-old man presented to the hospital for robotic proctectomy under general anesthesia. The surgery lasted for 7 hours, and the forced-air warming device with underbody blanket operated continuously for 5 hours intraoperatively. The surgery was completed without any incidents. However, first-degree burns on the patient’s back, along with superficial decubitus ulcers on his right scapula, were observed after surgery. To prevent cutaneous complications, clinicians must adhere to the manufacturer's guidelines when utilizing a forced-air warming system. Compared to overbody blankets, underbody blankets have limitations in monitoring cutaneous responses. Ensuring patient safety requires selecting an appropriate blanket for scheduled operations.

Background: Time-of-flight (TOF) magnetic resonance angiography (MRA) is widely used to identify aneurysm in human brain. Various deep learning models have been developed to help TOF-MRA reading in the field. The performance of those TOF-MRA analysis tools, however, faces several limitations in cerebral aneurysm detection. These challenges primarily come from the fact that cerebral aneurysms occupy less than 0.1% of the total TOF-MRA voxel size. This study aims to improve the efficiency of cerebral aneurysm detection by developing a landmark-based semi-supervised deep learning method, a technology that automatically generates landmark boxes in areas with a high probability of cerebral aneurysm occurrence. Methods: We used data from a total of 500 aneurysm-positive and 50 aneurysm-negative subjects. The aneurysm detection model was developed using clustering and a dilated residual network. Results: When the number of landmarks was ten and their size was 36 mm3, the best performance was achieved in our experiment. Although landmark occupies a small portion of the entire image, up to 98.2% of landmarks were cerebral aneurysms. The sensitivity of the model for cerebral aneurysm detection was 83.0%, with a false positive rate of 3.4%. Conclusions This study developed a deep learning model using TOF-MRA image. This model generates the most suitable landmarks for each individual, excluding unnecessary areas for cerebral aneurysm detection, which makes it possible to focus on areas with a high probability of occurrence. This model is expected to enhance the efficiency and accuracy of cerebral aneurysm detection in the field.

Background: Time-of-flight (TOF) magnetic resonance angiography (MRA) is widely used to identify aneurysm in human brain. Various deep learning models have been developed to help TOF-MRA reading in the field. The performance of those TOF-MRA analysis tools, however, faces several limitations in cerebral aneurysm detection. These challenges primarily come from the fact that cerebral aneurysms occupy less than 0.1% of the total TOF-MRA voxel size. This study aims to improve the efficiency of cerebral aneurysm detection by developing a landmark-based semi-supervised deep learning method, a technology that automatically generates landmark boxes in areas with a high probability of cerebral aneurysm occurrence. Methods: We used data from a total of 500 aneurysm-positive and 50 aneurysm-negative subjects. The aneurysm detection model was developed using clustering and a dilated residual network. Results: When the number of landmarks was ten and their size was 36 mm3, the best performance was achieved in our experiment. Although landmark occupies a small portion of the entire image, up to 98.2% of landmarks were cerebral aneurysms. The sensitivity of the model for cerebral aneurysm detection was 83.0%, with a false positive rate of 3.4%. Conclusions This study developed a deep learning model using TOF-MRA image. This model generates the most suitable landmarks for each individual, excluding unnecessary areas for cerebral aneurysm detection, which makes it possible to focus on areas with a high probability of occurrence. This model is expected to enhance the efficiency and accuracy of cerebral aneurysm detection in the field.