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1.
Healthcare Informatics Research ; : 246-255, 2023.
Article in English | WPRIM | ID: wpr-1000440

ABSTRACT

Objectives@#The objective of this study was to develop and validate a multicenter-based, multi-model, time-series deep learning model for predicting drug-induced liver injury (DILI) in patients taking angiotensin receptor blockers (ARBs). The study leveraged a national-level multicenter approach, utilizing electronic health records (EHRs) from six hospitals in Korea. @*Methods@#A retrospective cohort analysis was conducted using EHRs from six hospitals in Korea, comprising a total of 10,852 patients whose data were converted to the Common Data Model. The study assessed the incidence rate of DILI among patients taking ARBs and compared it to a control group. Temporal patterns of important variables were analyzed using an interpretable timeseries model. @*Results@#The overall incidence rate of DILI among patients taking ARBs was found to be 1.09%. The incidence rates varied for each specific ARB drug and institution, with valsartan having the highest rate (1.24%) and olmesartan having the lowest rate (0.83%). The DILI prediction models showed varying performance, measured by the average area under the receiver operating characteristic curve, with telmisartan (0.93), losartan (0.92), and irbesartan (0.90) exhibiting higher classification performance. The aggregated attention scores from the models highlighted the importance of variables such as hematocrit, albumin, prothrombin time, and lymphocytes in predicting DILI. @*Conclusions@#Implementing a multicenter-based timeseries classification model provided evidence that could be valuable to clinicians regarding temporal patterns associated with DILI in ARB users. This information supports informed decisions regarding appropriate drug use and treatment strategies.

2.
Brain & Neurorehabilitation ; : 48-55, 2016.
Article in English | WPRIM | ID: wpr-211310

ABSTRACT

OBJECTIVE: Authors conducted the pilot trial to evaluate whether the virtual reality using mirror therapy induces analgesia and functional improvement to the patients of rheumatoid wrist arthritis. METHOD: Three patients with no symptom or sign of active phase at both wrists were recruited. Voluntary range of motion (ROM) of each wrist over as far as possible was recorded and then the same movement was recorded only over 60% of the previous one after break of 5 minutes. For the virtual reality treatment, the second recorded motion was reconstructed into the another one of as same ROM and spent time as the first one, providing confusing visual information to the patients while patients were instructed to reach only the red flags (60% ROM of 1st one). This exercise was repeated for 5 days. Numerous scales such as VAS, ROM, Michigan Hand Outcomes Questionaire (MHQ), Performance and Satisfaction in Activities of Daily Living (PS-ADL), patient-rated wrist evaluation (PRWE) were evaluated before and after repetition. RESULTS: The increased satisfaction with their hands (satisfaction score of MHQ; 5.8 ± 2.3, [6-30]), improved ADL performances (PS-ADL score: 5.0 ± 3.5, [0-117]), and no side effect were noticed. CONCLUSION: The virtual reality using mirror therapy may be safe and has some analgesic effect, which warrants a clinical trial in the future for the patients of rheumatoid wrist arthritis.


Subject(s)
Humans , Activities of Daily Living , Analgesia , Arthritis , Arthritis, Rheumatoid , Hand , Michigan , Range of Motion, Articular , Virtual Reality Exposure Therapy , Weights and Measures , Wrist
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