MetaLAB-HOI: Template standardization of health outcomes enable massive and accurate detection of adverse drug reactions from electronic health records.

PURPOSE: This study aimed to advance the MetaLAB algorithm and verify its performance with multicenter data to effectively detect major adverse drug reactions (ADRs), including drug-induced liver injury. METHODS: Based on MetaLAB, we created an optimal scenario for detecting ADRs by considering demographic and clinical records. MetaLAB-HOI was developed to identify ADR signals using common model-based multicenter electronic health record (EHR) data from the clinical health outcomes of interest (HOI) template and design for drug-exposed and nonexposed groups. In this study, we calculated the odds ratio of 101 drugs for HOI in Konyang University Hospital, Seoul National University Hospital, Chungbuk National University Hospital, and Seoul National University Bundang Hospital. RESULTS: The overlapping drugs in four medical centers are amlodipine, aspirin, bisoprolol, carvedilol, clopidogrel, clozapine, digoxin, diltiazem, methotrexate, and rosuvastatin. We developed MetaLAB-HOI, an algorithm that can detect ADRs more efficiently using EHR. We compared the detection results of four medical centers, with drug-induced liver injuries as representative ADRs. CONCLUSIONS: MetaLAB-HOI's strength lies in fully utilizing the patient's clinical information, such as prescription, procedure, and laboratory results, to detect ADR signals. Considering changes in the patient's condition over time, we created an algorithm based on a scenario that accounted for each drug exposure and onset period supervised by specialists for HOI. We determined that when a template capable of detecting ADR based on clinical evidence is developed and manualized, it can be applied in medical centers for new drugs with insufficient data.

Development and Application of an Active Pharmacovigilance Framework Based on Electronic Healthcare Records from Multiple Centers in Korea.

INTRODUCTION: With the availability of retrospective pharmacovigilance data, the common data model (CDM) has been identified as an efficient approach towards anonymized multicenter analysis; however, the establishment of a suitable model for individual medical systems and applications supporting their analysis is a challenge. OBJECTIVE: The aim of this study was to construct a specialized Korean CDM (K-CDM) for pharmacovigilance systems based on a clinical scenario to detect adverse drug reactions (ADRs). METHODS: De-identified patient records (n = 5,402,129) from 13 institutions were converted to the K-CDM. From 2005 to 2017, 37,698,535 visits, 39,910,849 conditions, 259,594,727 drug exposures, and 30,176,929 procedures were recorded. The K-CDM, which comprises three layers, is compatible with existing models and is potentially adaptable to extended clinical research. Local codes for electronic medical records (EMRs), including diagnosis, drug prescriptions, and procedures, were mapped using standard vocabulary. Distributed queries based on clinical scenarios were developed and applied to K-CDM through decentralized or distributed networks. RESULTS: Meta-analysis of drug relative risk ratios from ten institutions revealed that non-steroidal anti-inflammatory drugs (NSAIDs) increased the risk of gastrointestinal hemorrhage by twofold compared with aspirin, and non-vitamin K anticoagulants decreased cerebrovascular bleeding risk by 0.18-fold compared with warfarin. CONCLUSION: These results are similar to those from previous studies and are conducive for new research, thereby demonstrating the feasibility of K-CDM for pharmacovigilance. However, the low quality of original EMR data, incomplete mapping, and heterogeneity between institutions reduced the validity of the analysis, thus necessitating continuous calibration among researchers, clinicians, and the government.

A Data-Driven Reference Standard for Adverse Drug Reaction (RS-ADR) Signal Assessment: Development and Validation.

BACKGROUND: Pharmacovigilance using real-world data (RWD), such as multicenter electronic health records (EHRs), yields massively parallel adverse drug reaction (ADR) signals. However, proper validation of computationally detected ADR signals is not possible due to the lack of a reference standard for positive and negative associations. OBJECTIVE: This study aimed to develop a reference standard for ADR (RS-ADR) to streamline the systematic detection, assessment, and understanding of almost all drug-ADR associations suggested by RWD analyses. METHODS: We integrated well-known reference sets for drug-ADR pairs, including Side Effect Resource, Observational Medical Outcomes Partnership, and EU-ADR. We created a pharmacovigilance dictionary using controlled vocabularies and systematically annotated EHR data. Drug-ADR associations computed from MetaLAB and MetaNurse analyses of multicenter EHRs and extracted from the Food and Drug Administration Adverse Event Reporting System were integrated as "empirically determined" positive and negative reference sets by means of cross-validation between institutions. RESULTS: The RS-ADR consisted of 1344 drugs, 4485 ADRs, and 6,027,840 drug-ADR pairs with positive and negative consensus votes as pharmacovigilance reference sets. After the curation of the initial version of RS-ADR, novel ADR signals such as "famotidine-hepatic function abnormal" were detected and reasonably validated by RS-ADR. Although the validation of the entire reference standard is challenging, especially with this initial version, the reference standard will improve as more RWD participate in the consensus voting with advanced pharmacovigilance dictionaries and analytic algorithms. One can check if a drug-ADR pair has been reported by our web-based search interface for RS-ADRs. CONCLUSIONS: RS-ADRs enriched with the pharmacovigilance dictionary, ADR knowledge, and real-world evidence from EHRs may streamline the systematic detection, evaluation, and causality assessment of computationally detected ADR signals.

srBERT: automatic article classification model for systematic review using BERT.

BACKGROUND: Systematic reviews (SRs) are recognized as reliable evidence, which enables evidence-based medicine to be applied to clinical practice. However, owing to the significant efforts required for an SR, its creation is time-consuming, which often leads to out-of-date results. To support SR tasks, tools for automating these SR tasks have been considered; however, applying a general natural language processing model to domain-specific articles and insufficient text data for training poses challenges. METHODS: The research objective is to automate the classification of included articles using the Bidirectional Encoder Representations from Transformers (BERT) algorithm. In particular, srBERT models based on the BERT algorithm are pre-trained using abstracts of articles from two types of datasets, and the resulting model is then fine-tuned using the article titles. The performances of our proposed models are compared with those of existing general machine-learning models. RESULTS: Our results indicate that the proposed srBERTmy model, pre-trained with abstracts of articles and a generated vocabulary, achieved state-of-the-art performance in both classification and relation-extraction tasks; for the first task, it achieved an accuracy of 94.35% (89.38%), F1 score of 66.12 (78.64), and area under the receiver operating characteristic curve of 0.77 (0.9) on the original and (generated) datasets, respectively. In the second task, the model achieved an accuracy of 93.5% with a loss of 27%, thereby outperforming the other evaluated models, including the original BERT model. CONCLUSIONS: Our research shows the possibility of automatic article classification using machine-learning approaches to support SR tasks and its broad applicability. However, because the performance of our model depends on the size and class ratio of the training dataset, it is important to secure a dataset of sufficient quality, which may pose challenges.

Carthami Semen Pharmacopuncture Combined with Electroacupuncture on Carpal Tunnel Syndrome: A Retrospective Case Series Study.

While carpal tunnel syndrome (CTS) is the most common entrapment neuropathy affecting the wrist, resulting in substantial physical, psychological, and economic effects, there is no gold standard therapy for CTS. In this case series study, we aimed to report CTS patients treated with Carthami Semen Pharmacopuncture (CSP) and electroacupuncture (EA) showing improvements in their symptoms, and the combinatorial effects of CSP and EA. We collected medical records of CTS outpatients who received CSP and EA at Chuk-u Acupuncture & Moxibustion Korean Medicine Clinic from August 2017 to September 2018. The outcome measures were the visual analog scale (VAS) for pain, paresthesia, the Korean version of the Boston carpal tunnel questionnaire (K-BCTQ) score, and changes in nocturnal pain, Tinel sign, and Phalen's test. We included patient satisfaction at the completion of all treatments. 17 patients were included for this case series study. After treatment, VAS for pain decreased significantly from 50.41 ± 16.19 to 9.59 ± 9.46, VAS for paresthesia also decreased significantly from 63.50 ± 11.49 to 14.75 ± 12.97, and K-BCTQ symptom severity scale decreased from 2.48 ± 0.68 to 1.89 ± 0.70 (all p < 0.001). Nocturnal pain, Tinel signs, and Phalen's test showed improvements after all the treatments. All the patients reported favorable overall satisfaction with the treatments, and 69.23% wanted future pharmacopuncture treatments if CTS recurred. No complications were detected. The combination of CSP and EA could be an effective and safe option in treating CTS.

Moxibustion for cognitive impairment: a systematic review and meta-analysis of animal studies.

BACKGROUND: Cognitive impairment is an age-dependent chronic disorder that exponentially worsens with age; however, its treatment is mostly symptomatic. Moxibustion is widely accepted in East Asia as a treatment for cognitive impairment. This systematic review aimed to verify the efficacy and underlying mechanism of moxibustion in treating cognitive impairment. METHODS: Sixteen trials involving 324 animals obtained from MEDLINE (PubMed), EMBASE, the Cochrane library, the Chinese National Knowledge Infrastructure, Wan-Fang, Cqvip, the Korean Studies Information Service System, and the Oriental Medicine Advanced Searching Integrated System met the inclusion criteria. We extracted the results of behavioral tests and immunohistochemical biomarkers from the included articles and evaluated the risk of bias and reporting quality. RESULTS: The moxibustion group showed significantly decreased escape latency, increased crossing times, and prolonged dwelling times in the Morris water maze test. There was a significantly enhanced latency period and reduced error time in the step-down test and nerve behavior score. The effects of moxibustion were found to be mediated by suppression of oxidative stress and apoptosis, modulation of inflammation and Aß genesis activation of vascular endothelial growth factor, and adjustment of metabolites in the tricarboxylic acid cycle and fatty acid metabolism. CONCLUSION: Our results demonstrated the therapeutic efficacy of moxibustion on cognitive impairment and suggested the putative mechanism. However, considering the small number of included studies, high bias risk, low reporting quality, and the limitations of animal experimentation, our results need to be confirmed by more detailed studies.

Scolopendra Pharmacopuncture Combined with Electroacupuncture for the Treatment of Ganglion Cysts: A Retrospective Study.

OBJECTIVES: Ganglion cysts require a sustainable treatment that suppresses their frequent recurrence. This study aimed to explore the clinical effects of Scolopendra pharmacopuncture (SP) and electroacupuncture on ganglion cysts. METHODS: We retrospectively reviewed the patient records and follow-up reports for 20 patients with wrist ganglion cysts who received SP and electroacupuncture from April 2016 to March 2017. The cyst diameter, recurrence, visual analog scale (VAS) scores for pain, the Korean version of the disabilities of arm, shoulder, and hand (K-DASH) score, and the Korean version of the patient-rated wrist evaluation (K-PRWE) score before and after treatment were noted. RESULTS: After treatment, the cyst diameter decreased significantly from 13.61 ± 6.41 mm to 5.15 ± 6.18 mm (p < 0.001), and VAS score for pain decreased from 1.31 ± 1.77 to 0.41 ± 0.33 (p = 0.021). Further, the K-DASH score decreased significantly from 8.97 ± 12.66 to 2.21 ± 7.39 (p = 0.016), and score for the function subscale of K-PRWE decreased from 11.37 ± 4.48 to 9.1 ± 3.67 (p = 0.046). No recurrences were reported from the followed-up patients. Any complication related to SP or electroacupuncture was not observed, except mild rash, itching, and swelling at the injection site in four patients. CONCLUSION: Combination of SP and electroacupuncture may be effective in treating ganglion cysts; further prospective studies with large population are needed to clarify the effect of SP and electroacupuncture.

The Efficacy and Underlying Mechanism of Moxibustion in Preventing Cognitive Impairment: A Systematic Review of Animal Studies.

Cognitive impairment is age-related and manageable only with early diagnosis and prevention. Moxibustion is widely accepted in East Asia as useful for preventing cognitive impairment. This systematic review of animal studies was conducted to verify the efficacy of moxibustion in preventing cognitive impairment and to elucidate the underlying mechanism. Randomized controlled animal trials that established the efficacy of moxibustion in preventing cognitive impairment were included in the analysis. Results of behavioral tests and the signaling pathways elucidated were extracted and a meta-analysis was conducted with the behavioral test results. The risk of bias was evaluated using 9 items, and reporting quality was evaluated using the ARRIVE (Animal Research: Reporting In Vivo Experiments) Guidelines Checklist. Ten trials involving 410 animals met the inclusion criteria. All studies reported the benefit of moxibustion in preventing cognitive deficits caused by Alzheimer's disease (AD). Among five studies using the Morris water maze test, a significant effect of moxibustion in decreasing the escape time was reported in three studies, increasing the crossing times in four studies, and prolonging the dwelling time in two studies. The effects of moxibustion were demonstrated to be mediated by an increase in the activity of neurotrophins and heat shock protein, modulation of the cell cycle, and suppression of apoptosis and inflammation. However, considering the small number of included studies, the lack of studies investigating entire signaling pathways, and a high risk of bias and low reporting quality, our results need to be confirmed through more detailed studies.

Reproducibility of Facial Soft Tissue Thickness Measurements Using Cone-Beam CT Images According to the Measurement Methods.

The purpose of this study was to establish the reproducibility of facial soft tissue (ST) thickness measurements by comparing three different measurement methods applied at 32 landmarks on three-dimensional cone-beam computed tomography (CBCT) images. Two observers carried out the measurements of facial ST thickness of 20 adult subjects using CBCT scan data, and inter- and intra-observer reproducibilities were evaluated. The measurement method of "perpendicular to bone" resulted in high inter- and intra-observer reproducibility at all 32 landmarks. In contrast, the "perpendicular to skin" method and "direct" method, which measures a distance between one point on bone and the other point on skin, presented low reproducibility. The results indicate that reproducibility could be increased by identifying the landmarks on hard tissue images, rather than on ST images, and the landmark description used in this study can be used in the establishment of reliable tissue depth data using CBCT images.