The reporting quality of acupuncture-related traumatic adverse events: a systematic review of case studies in Korea.

BACKGROUND: Acupuncture is known for a harmless treatment when administered by well-trained clinicians. However, multiple case reports of traumatic adverse events (AEs) related to acupuncture treatments continue to be published in literature. In this review, we evaluated the reporting quality and conducted causality assessments of case studies that have reported acupuncture-related traumatic AEs in Korea. METHODS: Eight databases were searched from their inception to January 2024. Only Korean case studies that reported traumatic AEs following acupuncture procedures were included without any language restrictions. Reporting quality was evaluated based on patient characteristics, AEs, and acupuncture practice. Causality was assessed using the modified WHO-UMC causality criteria. RESULTS: Twenty-eight studies were included from a total of 1,154 identified studies. The quality of reporting in the included studies was low overall. While the descriptions of patient characteristics and AEs were relatively well detailed, most information on acupuncture practice was not reported at all. During the causality assessment, only three (10.7%) studies were judged to be "certain". Twelve (42.9%) studies were "unassessable" because they inadequately described the information necessary for decision-making. It was practically difficult to establish the causality between acupuncture and AEs, as well as the appropriateness of acupuncture practice. CONCLUSIONS: Insufficient and inappropriate reporting was observed in most case studies reporting acupuncture-related traumatic AEs in Korea. To overcome these limitations, we have suggested tentative guidelines in the form of a set of items that should be reported by future authors who plan to publish case studies on acupuncture-related traumatic AEs in a clinical setting.

A Hybrid Deep Learning Emotion Classification System Using Multimodal Data.

This paper proposes a hybrid deep learning emotion classification system (HDECS), a hybrid multimodal deep learning system designed for emotion classification in a specific national language. Emotion classification is important in diverse fields, including tailored corporate services, AI advancement, and more. Additionally, most sentiment classification techniques in speaking situations are based on a single modality: voice, conversational text, vital signs, etc. However, analyzing these data presents challenges because of the variations in vocal intonation, text structures, and the impact of external stimuli on physiological signals. Korean poses challenges in natural language processing, including subject omission and spacing issues. To overcome these challenges and enhance emotion classification performance, this paper presents a case study using Korean multimodal data. The case study model involves retraining two pretrained models, LSTM and CNN, until their predictions on the entire dataset reach an agreement rate exceeding 0.75. Predictions are used to generate emotional sentences appended to script data, which are further processed using BERT for final emotion prediction. The research result is evaluated by using categorical cross-entropy (CCE) to measure the difference between the model's predictions and actual labels, F1 score, and accuracy. According to the evaluation, the case model outperforms the existing KLUE/roBERTa model with improvements of 0.5 in CCE, 0.09 in accuracy, and 0.11 in F1 score. As a result, the HDECS is expected to perform well not only on Korean multimodal datasets but also on sentiment classification considering the speech characteristics of various languages and regions.

Current Characteristics of Herbal Medicine Interventions for Cancer on Clinical Databases: A Cross-Sectional Study.

BACKGROUND: The utilization of herbal medicine has been noteworthy for treating cancer; however, there is not enough information regarding the characteristics of clinical trials of herbal medicine interventions. This study aimed to evaluate the characteristic of registered trials using herbal medicine interventions for cancer. METHODS: A cross-sectional study was performed via the website ClinicalTrials.gov, ISRCTN registry, Chinese clinical trial registry, and international clinical trials registry platform to gather associated registered clinical trials using an advanced search with the developed keyword strategy as of March 26, 2023. All obtainable information from the trials was collected without any restrictions to conduct a comprehensive review. RESULTS: A total of 169 registered trials were included for evaluation. Of all trials, 102 trials were eligible for this study. Countries from Asia registered the most trials (62.75%), and hospitals sponsored most of the trials (42.16%). Randomized, Phase 2, interventional trials were dominant, and approximately 64.71% of the trials anticipated recruiting less than 100 participants. More than half of the trials were from 2016 to 2023 (53.92%). While 45 trials were completed, only 16 trials had results for further analysis. According to the completed results, the types of herbal medicines from the trials mainly focused on lung, breast, and colorectal cancer. CONCLUSION: This study is the first to explore the characteristics of clinical trials of herbal medicine for cancer registered in large clinical databases. The acquired trials had relatively informative data; however, better-designed trials may be needed for health professionals to consider herbal medicine as an option when treating cancer patients.

Integrative Korean Medicine Treatment for Obesity and Overweight in Children and Adolescents: A Multicenter Retrospective Chart Review Study.

Introduction: Integrative Korean medicine treatment (IKM), including herbal medicine (HM) and acupuncture, has been widely used for obesity and overweight in children and adolescents in South Korea. We investigated the real-world usage status and the potential effect of the IKM for obesity and overweight in children and adolescents. Methods: Multicenter medical charts were retrospectively reviewed of obese and overweight children and adolescents who visited Korean medicine institutions with the goal of weight control for the first time and received IKM, to analyze the usage status and effect of IKM. We defined IKM responders as those with an improved obesity grade on the body mass index (BMI) percentile and analyzed their characteristics. Results: Medical charts of 209 patients (183 obese and 26 overweight) with a mean age of 11.45 years were examined. Patients visited the institution a mean of 5.95 times, and HM alone and HM plus acupuncture were frequently used IKM. HM was prescribed to 205 patients, 167 of whom received an HM prescription containing Ephedrae Herba. An HM of the decoction type was prescribed to 189 patients, and the average treatment duration was 76.54 days. After IKM, the percentile and z-score of BMI and weight significantly declined and height percentile and z-score were significantly enhanced, without serious adverse events. In the IKM responders, age, and the proportion of girls and overweight were significantly higher, and the percentile and z-score of height, weight, and BMI were significantly lower. Conclusion: This is the first study to examine the real-world usage of IKM for obesity and overweight in children and adolescents. A significant improvement in obesity-related outcome measures after IKM, illustrated the potential effect of IKM.

A Customized Deep Sleep Recommender System Using Hybrid Deep Learning.

This paper proposes a recommendation system based on a hybrid learning approach for a personal deep sleep service, called the Customized Deep Sleep Recommender System (CDSRS). Sleep is one of the most important factors for human life in modern society. Optimal sleep contributes to increasing work efficiency and controlling overall well-being. Therefore, a sleep recommendation service is considered a necessary service for modern individuals. Accurate sleep analysis and data are required to provide such a personalized sleep service. However, given the variations in sleep patterns between individuals, there is currently no international standard for sleep. Additionally, service platforms face a cold start problem when dealing with new users. To address these challenges, this study utilizes K-means clustering analysis to define sleep patterns and employs a hybrid learning algorithm to evaluate recommendations by combining user-based and collaborative filtering methods. It also incorporates feedback top-N classification processing for user profile learning and recommendations. The behavior of the study model is as follows. Using personal information received through mobile devices and data, such as snoring, sleep time, movement, and noise collected through AI motion beds, we recommend sleep and receive user evaluations of recommended sleep. This assessment reconstructs the profile and, finally, makes recommendations using top-N classification. The experimental results were evaluated using two absolute error measurement methods: mean squared error (MSE) and mean absolute percentage error (MAPE). The research results regarding the hybrid learning methods show 13.2% fewer errors than collaborative filtering (CF) and 10.2% fewer errors than content-based filtering (CBF) on an MSE basis. According to the MAPE, the methods are 14.7% more accurate than the CF model and 9.2% better than the CBF model. These results demonstrate that CDSRS systems can provide more accurate recommendations and customized sleep services to users than CF, CBF, and combination models. As a result, CDSRS, a hybrid learning method, can better reflect a user's evaluation than traditional methods and can increase the accuracy of recommendations as the number of users increases.

Validity and reliability of the single camera marker less motion capture system using RGB-D sensor to measure shoulder range-of-motion: A protocol for systematic review and meta-analysis.

BACKGROUND: The range-of motion (ROM) is an essential component of joint mobility. Shoulder ROM measurement has been problematic due to its complexity. A marker less motion capture system can be a potential alternative for upper limb assessment. Currently, there is no systematic review to evaluate the validity of a marker less motion capture system for assessing shoulder ROM. This study aims to describe methods to evaluate the reliability and validity of a single camera marker less motion capture system that uses an RGB-depth sensor to measure shoulder ROM. METHODS: Studies that measured shoulder ROM with a single camera marker less motion capture system using the RGB-depth sensor and assessed the intra- and/or inter-rater reliability, and/or validity of the device will be included. The search of electronic databases, such as MEDLINE, EMBASE, Cochran library, Cumulative Index to Nursing, and Allied Health Literature via EBSCO, IEEE Xplore, China National Knowledge Infrastructure, KoreaMed, Korean studies Information Service System, and Research Information Sharing Services will be performed for all relevant articles from inception to December 2022. Two authors will independently perform quality assessments using the Consensus-based Standards for the selection of health Measurement Instruments checklist for reliability, measurement error of outcome measurement instrument, and criterion validity. The primary outcomes will be the intra- and inter-rater reliability and validity of the markerless motion capture system measuring shoulder flexion, extension, abduction, adduction, internal rotation, or external rotation. A subgroup analysis would be performed if there are sufficient data to pool to identify an influencing factor in the measurement of ROM using a marker less motion capture system. RESULTS AND CONCLUSION: These findings will present tools to utilize and evaluate single camera motion capture systems for the medical use for clinicians and healthcare experts and can aid in further clinical research using such a system for different movements and other joints.

Association between Possible Sarcopenia and Depressive Symptoms in Korean Older Adults: Results from the Korea National Health and Nutrition Examination Survey in 2018.

BACKGROUND: Despite increased clinical and research interest in sarcopenia, even in Asia, not much is known about the association between sarcopenia and depressive symptoms. Sarcopenia and depressive symptoms are associated with several health problems in older adults; therefore, we investigated the association between sarcopenia and depression in Korean older adults. METHODS: The study sample included 1,929 participants aged over 60 years (44.6% men; mean age, 69.7 years) from nationally representative data of the 2018 Korea National Health and Nutrition Examination survey. Possible sarcopenia was defined according to the diagnostic algorithm of the Asian Working Group for Sarcopenia 2019; however, we measured only hand-grip strength (kg) in this study. Patient Health Questionnaire-9 was used for screening for symptoms of depression. A cross-sectional analysis was used to examine the relationship between possible sarcopenia and depressive symptoms. RESULTS: Possible sarcopenia and depressive symptoms were identified in 538 (27.9%) and 97 (5.0%) participants, respectively. After adjusting for age, sex, and other potential covariates, possible sarcopenia was positively associated with higher odds of depressive symptoms (odds ratio, 2.06; 95% confidence interval, 1.36-3.11; P<0.001). CONCLUSION: Possible sarcopenia was significantly associated with depressive symptoms in Korean older adults. Early interventions for possible sarcopenia and depressive symptoms in routine clinical practice could help Korean older adults to have healthy aging. Future studies are required to explore any causal relationship between possible sarcopenia and depressive symptoms in Korean older adults.

The Opioid-Sparing Effect of Acupuncture After Abdominal Surgery: A Systematic Review and Meta-Analysis Protocol.

Purpose: Routine overprescribing of postoperative opioid analgesics may induce side effects and correlate with chronic opioid use following surgery. This review aims to evaluate the effectiveness and safety of acupuncture for opioid-sparing effects in patients who underwent abdominal surgery. Methods: Eleven databases in different languages, including English (Ovid MEDLINE, CENTRAL, EMBASE, CINAHL), Chinese, Korean, and Japanese, will be searched. Randomized controlled trials using acupuncture for postoperative pain control in adult patients undergoing abdominal surgery will be screened. All randomized controlled trials comparing acupuncture with no treatment, sham acupuncture, and conventional treatments will be included. The Cochrane risk of bias tool will be used to assess the risk of bias. The primary outcome will consist of a cumulative opioid consumption. Additionally, the number of cumulative opioid analgesic demands/requests, the time to initial opioid analgesic usage, postoperative pain, opioid-related side effects, and adverse events of acupuncture will be assessed. The mean differences or risk ratios with a 95% confidence interval will be calculated to estimate the pooled effect of acupuncture when it is possible to conduct a meta-analysis. Results: This study could confirm the effect of opioid-sparing on acupuncture after abdominal surgery. Conclusion: This study would evaluate the evidence on the effectiveness of acupuncture after abdominal surgery with a focus on opioid intake. It provides evidence to support decision-making on applying acupuncture for postoperative management. Registration Number: CRD42022311155.

Deep autoencoder-powered pattern identification of sleep disturbance using multi-site cross-sectional survey data.

Pattern identification (PI) is a diagnostic method used in Traditional East Asian medicine (TEAM) to select appropriate and personalized acupuncture points and herbal medicines for individual patients. Developing a reproducible PI model using clinical information is important as it would reflect the actual clinical setting and improve the effectiveness of TEAM treatment. In this paper, we suggest a novel deep learning-based PI model with feature extraction using a deep autoencoder and k-means clustering through a cross-sectional study of sleep disturbance patient data. The data were obtained from an anonymous electronic survey in the Republic of Korea Army (ROKA) members from August 16, 2021, to September 20, 2021. The survey instrument consisted of six sections: demographics, medical history, military duty, sleep-related assessments (Pittsburgh sleep quality index (PSQI), Berlin questionnaire, and sleeping environment), diet/nutrition-related assessments [dietary habit survey questionnaire and nutrition quotient (NQ)], and gastrointestinal-related assessments [gastrointestinal symptom rating scale (GSRS) and Bristol stool scale]. Principal component analysis (PCA) and a deep autoencoder were used to extract features, which were then clustered using the k-means clustering method. The Calinski-Harabasz index, silhouette coefficient, and within-cluster sum of squares were used for internal cluster validation and the final PSQI, Berlin questionnaire, GSRS, and NQ scores were used for external cluster validation. One-way analysis of variance followed by the Tukey test and chi-squared test were used for between-cluster comparisons. Among 4,869 survey responders, 2,579 patients with sleep disturbances were obtained after filtering using a PSQI score of >5. When comparing clustering performance using raw data and extracted features by PCA and the deep autoencoder, the best feature extraction method for clustering was the deep autoencoder (16 nodes for the first and third hidden layers, and two nodes for the second hidden layer). Our model could cluster three different PI types because the optimal number of clusters was determined to be three via the elbow method. After external cluster validation, three PI types were differentiated by changes in sleep quality, dietary habits, and concomitant gastrointestinal symptoms. This model may be applied to the development of artificial intelligence-based clinical decision support systems through electronic medical records and clinical trial protocols for evaluating the effectiveness of TEAM treatment.

Association between Fat Distribution and Chronic Low Back Pain among 10,606 Adults: Data from the Korean National Health and Nutrition Examination Survey.

Obesity is associated with chronic low back pain (CLBP), but the association between fat distribution and CLBP is unclear. This cross-sectional study evaluated the relationship using the Korean National Health and Nutrition Examination Survey data. A total of 10,606 adults (average age: 45.4, female: 57.1%) were included. We estimated the regional fat distribution, waist circumference, and body fat proportion, compared the values in people with and without CLBP, and stratified the estimates by sex and obesity status using a multivariable linear model. There were no statistically significant differences in the average waist circumference between the people with and without CLBP (p = 0.731) and the average fat proportion between those with and without CLBP (p = 0.731). The average regional fat distribution was significantly higher in the people with CLBP than in those without CLBP, in the upper limbs (11.4%, 95% confidence interval [CI]: [11.3, 11.5] vs. 11.2%, 95% CI: [11.1, 11.3], p < 0.05) and in the lower limbs (31.9%, 95% CI: [31.6, 32.2] vs. 31.4%, 95% CI: [31.2, 31.6], p < 0.01). More obvious among men, fat distribution in the lower limbs is higher than in people without obesity (p < 0.001). People with CLBP tend to have a higher fat distribution in the limbs than those without it and obese people with CLBP would need to reduce the fat in the lower limbs.

Acupuncture for postoperative delirium (POD): A systematic review and meta-analysis protocol.

BACKGROUND: Postoperative delirium (POD) is a form of delirium that is newly diagnosed after a surgical procedure. This study aims to examine the effectiveness and safety of acupuncture treatment for POD in patients who underwent surgery. METHODS: Randomized controlled trials for patients diagnosed with POD using validated delirium assessment scales will be included in this review. Electronic databases, such as MEDLINE, EMBASE, CENTRAL, CINAHL (English DB), CNKI, Wanfang, VIP (Chinese database), KoreaMed, RISS, KISS, DBpia, OASIS (Korean DB), and J-STAGE (Japanese DB) will be searched without language limitation from their inception to October 2020. The intervention group will include patients who have received any type of acupuncture treatment for POD. The control group will include individuals with no treatment, sham acupuncture treatment, and conventional treatment. The primary outcome is the incidence of POD in each study. Quality assessment will be performed using the Cochrane risk of bias tool. A meta-analysis will be performed to pool the estimated effect. CONCLUSION: This study will provide evidence for acupuncture as a potential treatment for POD, in researchers, patients, and policy makers. DISSEMINATION: The result of the study will be disseminated through posters, press releases, conference presentations, and peer-reviewed papers. TRIAL REGISTRATION NUMBER: OSF 2020: (https://osf.io/usvdg).

Prediction of Prolonged Length of Hospital Stay After Cancer Surgery Using Machine Learning on Electronic Health Records: Retrospective Cross-sectional Study.

BACKGROUND: Postoperative length of stay is a key indicator in the management of medical resources and an indirect predictor of the incidence of surgical complications and the degree of recovery of the patient after cancer surgery. Recently, machine learning has been used to predict complex medical outcomes, such as prolonged length of hospital stay, using extensive medical information. OBJECTIVE: The objective of this study was to develop a prediction model for prolonged length of stay after cancer surgery using a machine learning approach. METHODS: In our retrospective study, electronic health records (EHRs) from 42,751 patients who underwent primary surgery for 17 types of cancer between January 1, 2000, and December 31, 2017, were sourced from a single cancer center. The EHRs included numerous variables such as surgical factors, cancer factors, underlying diseases, functional laboratory assessments, general assessments, medications, and social factors. To predict prolonged length of stay after cancer surgery, we employed extreme gradient boosting classifier, multilayer perceptron, and logistic regression models. Prolonged postoperative length of stay for cancer was defined as bed-days of the group of patients who accounted for the top 50% of the distribution of bed-days by cancer type. RESULTS: In the prediction of prolonged length of stay after cancer surgery, extreme gradient boosting classifier models demonstrated excellent performance for kidney and bladder cancer surgeries (area under the receiver operating characteristic curve [AUC] >0.85). A moderate performance (AUC 0.70-0.85) was observed for stomach, breast, colon, thyroid, prostate, cervix uteri, corpus uteri, and oral cancers. For stomach, breast, colon, thyroid, and lung cancers, with more than 4000 cases each, the extreme gradient boosting classifier model showed slightly better performance than the logistic regression model, although the logistic regression model also performed adequately. We identified risk variables for the prediction of prolonged postoperative length of stay for each type of cancer, and the importance of the variables differed depending on the cancer type. After we added operative time to the models trained on preoperative factors, the models generally outperformed the corresponding models using only preoperative variables. CONCLUSIONS: A machine learning approach using EHRs may improve the prediction of prolonged length of hospital stay after primary cancer surgery. This algorithm may help to provide a more effective allocation of medical resources in cancer surgery.

Effects of Gambisan in overweight adults and adults with obesity: A retrospective chart review.

OBJECTIVE: A retrospective chart review was conducted to explore the effect of Gambisan, a granular extract of novel herbal medicine, for short-term (≤16 weeks) weight loss in adults who are overweight and those with obesity. METHODS: Outpatients of Kyung Hee University Korean Medicine Hospital (Seoul, Korea) who took Gambisan and underwent bioelectric impedance analysis were selected (Jan 2011 to Dec 2015); their electronic medical records and clinical charts were retrospectively reviewed. The effectiveness of Gambisan was primarily evaluated by comparing body weight (BW) at baseline and endpoint, using paired t tests; the safety of Gambisan was evaluated on the basis of adverse events (AEs) experienced by patients. RESULTS: Two hundred five patients were included in this study. The study population exhibited a significant reduction in BW (73.69 ±â€Š14.49 kg to 69.01 ±â€Š13.20 kg, P < .001) as well as percentage body fat (37.38 ±â€Š5.38% to 34.50 ±â€Š5.83%, P < .001). Moreover, 111 (54.1%) patients achieved modest weight loss (≥5%), while 35 (17.1%) achieved ≥10% weight loss. Furthermore, Gambisan induced significant reduction of BW in all subgroups (body mass index, sex, prescribed duration, and dosage). Among 139 patients with available data, 79 (56.8%) reported loss-of-appetite. In addition, 120 (mostly mild) AEs were reported in 69 (49.6%) patients, and the most frequent AEs were nausea, palpitation, and insomnia. DISCUSSION: Despite limitations in interpreting the results of this retrospective medical record review, Gambisan induced statistically and clinically meaningful weight loss with a tolerable level of AEs. Based on the findings of this review, further well-designed clinical trials are warranted.

A Smart Recommender Based on Hybrid Learning Methods for Personal Well-Being Services.

The main focus of the paper is to propose a smart recommender system based on the methods of hybrid learning for personal well-being services, called a smart recommender system of hybrid learning (SRHL). The essential health factor is considered to be personal lifestyle, with the help of a critical examination of various disciplines. Integrating the recommender system effectively contributes to the prevention of disease, and it also leads to a reduction in treatment cost, which contributes to an improvement in the quality of life. At the same time, there exist various challenges within the recommender system, mainly cold start and scalability. To effectively address the inefficiencies, we propose combined hybrid methods in regard to machine learning. The primary aim of this learning method is to integrate the most effective and efficient learning algorithms to examine how combined hybrid filtering can help to improve the cold star problem efficiently in the provision of personalized well-being in regard to health food service. These methods include: (1) switching among content-based and collaborative filtering; (2) identifying the user context with the integration of dynamic filtering; and (3) learning the profiles with the help of processing and screening of reflecting feedback loops. The experimental results were evaluated by using three absolute error measures, providing comparable results with other studies relative to machine learning domains. The effects of using the hybrid learning method are gathered with the help of the experimental results. Our experiments also show that the hybrid method improves accuracy by 14.61% of the average error predicted in the recommender systems in comparison to the collaborative methods, which mainly focus on the computation of similar entities.

Anti-cancer effect of bee venom on human MDA-MB-231 breast cancer cells using Raman spectroscopy.

We demonstrated the apoptotic effect of bee venom (BV) on human MDA-MB-231 breast cancer cells using Raman spectroscopy and principal component analysis (PCA). Biochemical changes in cancer cells were monitored following BV treatment; the results for different concentrations and treatment durations differed markedly. Significantly decreased Raman vibrations for DNA and proteins were observed for cells treated with 3.0 µg/mL BV for 48 h compared with those of control cells. These results suggest denaturation and degradation of proteins and DNA fragmentation (all cell death-related processes). The Raman spectroscopy results agreed with those of atomic force microscopy and conventional biological tests such as viability, TUNEL, and western blot assays. Therefore, Raman spectroscopy, with PCA, provides a noninvasive, label-free tool for assessment of cellular changes on the anti-cancer effect of BV.

Evaluation of bleeding-related adverse events following acupuncture treatment in patients on anticoagulant or antiplatelet drugs: A prospective observational study.

OBJECTIVE: To evaluate the risk of bleeding-related adverse events after acupuncture treatment in patients receiving anticoagulant or antiplatelet drugs. DESIGN AND SETTING: A total of 428 inpatients who received acupuncture treatment underwent two assessments for bleeding-related adverse events, such as micro-bleeding, hematoma, and ecchymosis: 1) immediately after acupuncture treatment on the first day and 2) before acupuncture treatment on the following day. Additional analyses were performed using the number of acupuncture needles as independent variables. Multivariable analysis using factors likely related to bleeding and subgroup analysis according to regions of needle insertion were also performed. RESULTS: A total of 169 patients receiving anticoagulant or antiplatelet drugs (exposure group) and 259 patients not receiving either drug (non-exposure group) were studied. Sixty-five (38.5%) patients in the exposure group and 115 (44.4%) patients in the non-exposure group had bleeding-related mild adverse events. There was no difference in the risk of bleeding-related adverse events between the two groups per sessions (relative risk (RR) 0.87, 95% confidence interval (CI), 0.69-1.10) and per needles (RR 0.89, 95% CI 0.70-1.13). In multivariable analysis, thickness of needle only increased risk of bleeding. Subgroup analysis showed that taking these drugs did not increase the risk of bleeding in any of the regions. CONCLUSION: Our findings suggest that anticoagulant and antiplatelet drugs do not increase the incidence of bleeding-related adverse events after acupuncture treatment.

The efficacy and safety of herbal medicine BHH10 in postmenopausal women with osteoporosis: study protocol for a phase II, multicenter, randomized, double-blinded, placebo-controlled clinical trial.

BACKGROUND: Osteoporosis is becoming more prevalent in aging societies worldwide, and the economic burden attributable to osteoporotic fractures is substantial. The medications presently available to treat osteoporosis have side effects, and the development of safer and more effective treatments is urgently needed. The aim of this study is to evaluate the efficacy and safety of BHH10, a traditional Korean herbal medicine, in the treatment of postmenopausal osteoporosis. METHODS/DESIGN: This is a phase II, multicenter, randomized, double-blinded, placebo-controlled clinical trial and will include 168 postmenopausal women aged 55 years and older with osteoporosis. The participants will be recruited competitively from two sites of the Acupuncture and Moxibustion Department of Kyung Hee University Hospital of Korean Medicine, either Hoegidong or Gangdong in Seoul, Korea. Participants will be assigned randomly to one of two groups, the BHH10 group or the placebo group, in a 1:1 ratio, and will have five scheduled visits. Participants will take two tablets of BHH10 or placebo three times daily for 12 weeks. The primary efficacy outcome is the change in bone mineral density at the lumbar spine (L1-4) between baseline (visit 1) and 12 weeks after randomization (visit 5). Other outcome variables include changes in bone turnover markers, the Deficiency Syndrome of the Kidney Index, EuroQol five-dimension questionnaire score, and laboratory parameters, as well as adverse events. DISCUSSION: To our knowledge, this will be the first clinical trial to assess the efficacy and safety of BHH10 in postmenopausal women with osteoporosis. It is anticipated that the results will contribute to the development of traditional herbal medicines that can be used to treat osteoporosis in postmenopausal women in Korea. If the superiority of BHH10 over placebo is demonstrated, this study could provide the foundation for a phase III clinical trial. The results of the study will be published in a peer-reviewed journal. TRIAL REGISTRATION: Clinical Research Information Service, KCT0001842 . Registered on 14 March 2016.

The efficacy and safety of the herbal medicine geonchildan for patients with active rheumatoid arthritis: study protocol for a randomized, double-blind, placebo-controlled, parallel pilot trial.

BACKGROUND: This study aims to assess the efficacy and safety of geonchildan, a Korean traditional herbal medicine, for patients with active rheumatoid arthritis (RA) and evaluate the feasibility of a large-scale confirmatory clinical trial. METHODS/DESIGN: This is a randomized, double-blind, placebo-controlled, parallel two-arm pilot trial in Seoul, Korea. Altogether, 30 patients diagnosed with RA for at least 3 months and with a Disease Activity Score for 28 joints (DAS28) ≥ 3.2 will be enrolled. Participants are randomly assigned to one of two groups, the experimental group or the placebo group, in a 1:1 ratio and will make four scheduled visits. The participants will be administered geonchildan or a placebo three times per day for 12 weeks. The change in DAS28 will be examined as the primary efficacy outcome. The secondary efficacy outcomes include the proportion of patients achieving ACR20, ACR50, ACR70, and EULAR responses; the DAS28 sub-items; the consumption of medication; Korean Health Assessment Questionnaire scores; inflammatory parameters; and the Korean medical diagnostic pattern indicator. Adverse events and laboratory test results will be recorded to evaluate safety. The process, resources used, and management of the study will also be assessed to determine the feasibility of a large-scale trial. DISCUSSION: This is the first clinical trial to explore the efficacy and safety of geonchildan in patients with active RA. If the superiority of geonchildan versus the placebo is demonstrated and the study design is feasible, this study could form the foundation for a large-scale clinical trial. The results will be published in a peer-reviewed journal. TRIAL REGISTRATION: Clinical Research Information Service, KCT0001943 . Registered on 14 June 2016.

The efficacy and safety of Hanslim for obese patients: Study protocol for a multicenter, randomized, double-blind, multi-dose, placebo-controlled, phase IIb clinical trial.

BACKGROUND: This study aims to evaluate the efficacy, safety, and appropriate dose of Hanslim, a Korean traditional herbal medicine, for obese patients, when compared to a placebo. METHODS/DESIGN: This study is a randomized, double-blinded, multicenter, multidose, placebo-controlled, phase IIb clinical trial. A total of 165 obese patients with a body mass index (BMI) of more than 30 kg/m or obese patients with a BMI of 27 to 29.9 kg/m and one or more risk factors such as hypertension, diabetes, or hyperlipidemia will be enrolled. Participants will be randomly assigned to 1 of 3 groups (high-dose, low-dose, or placebo) with a 1:1:1 allocation ratio and will have 4 scheduled visits during the 12-week treatment period. The participants will be administered 2 tablets of Hanslim or placebo, 2 times per day. The difference in the proportion of participants who lost weight by more than 5% from their baseline at 12 weeks compared to the placebo group will be examined as the primary efficacy outcome. Secondary efficacy outcomes include differences in body weight, BMI, body-fat percentage, fat mass, skeletal-muscle mass, edema index, waist circumference, hip circumference, waist-hip ratio, serum lipid, blood glucose, C-reactive protein, and total score of Korean version of obesity-related quality of life after 12 weeks of treatment. Adverse events, laboratory test results, vital sings, and electrocardiography will be recorded to evaluate safety. DISCUSSION: This is the first prospective clinical trial to explore the efficacy and safety of Hanslim for obese patients. If the results provide the appropriate dosage of Hanslim, this study would contribute to the confirmatory evidence for the use of Hanslim as a treatment for obesity needed to conduct a large-scale, phase III clinical trial. The results will be published in a peer-reviewed journal. TRIAL REGISTRATION: Clinical Research Information Service, ID: KCT0002193. Registered on January 6, 2017. https://cris.nih.go.kr/cris/search/search_result_st01_en.jsp?seq=7468.

Efficacy and safety of sofosbuvir plus ribavirin for Korean patients with hepatitis C virus genotype 2 infection: A retrospective multi-institutional study.

BACKGROUND/AIMS: Sofosbuvir plus ribavirin is a standard treatment for patients infected with chronic hepatitis C virus (HCV) genotype 2 in Korea. The purpose of this study was to examine the efficacy and safety of this treatment in Korean patients with chronic HCV genotype 2 infection. METHODS: We retrospectively analyzed clinical data of patients treated with sofosbuvir plus ribavirin for chronic HCV genotype 2 from May 2016 to December 2017 at eight hospitals located in the Daejeon-Chungcheong area. RESULTS: A total of 172 patients were treated with sofosbuvir plus ribavirin. Of them, 163 patients completed the treatment, and 162 patients were tested for sustained virologic response 12 weeks after treatment discontinuation (SVR12). Mean age was 59.6±12.3 years (27-96), and 105 (64.4%) patients were female. Of the total patients, 49 (30.1%) were diagnosed with cirrhosis, and 31 of them were treated for 16 weeks. Sofosbuvir plus ribavirin was the first-line treatment for 144 (88.3%) patients. Eleven (6.7%) patients were intolerant to previous interferon-based treatment. Eight (5.0%) patients relapsed after interferon-based treatment. HCV RNA non-detection rate at 4, 8, and 12 weeks was 97.5%, 99.1%, and 99.3%, respectively, and SVR12 was 98.8% (161/163). During treatment, 18 (11.0%) patients had to reduce their administrated dose of ribavirin because of anemia. One patient stopped the treatment because of severe anemia. Other adverse events, including dizziness, indigestion, and headache, were found in 26 (16.0%) patients. CONCLUSION: A 12-16 week treatment with sofosbuvir plus ribavirin is remarkably effective and well tolerated in Korean patients with chronic HCV genotype 2 infection.