양극성 장애, 조증 삽화 입원 환자에서 조증 증상 경과 예측과 관련있는 임상 변인 연구Investigation of Clinical Factors Associated with the Prediction of Manic Symptom Improvement in the Hospitalized Manic Subjects with Bipolar Disorder
- Other Titles
- Investigation of Clinical Factors Associated with the Prediction of Manic Symptom Improvement in the Hospitalized Manic Subjects with Bipolar Disorder
- Authors
- 김채리; 박진완; 백두현; 이연정; 한상우; 우성일; 황재욱
- Issue Date
- 2017
- Publisher
- 대한생물치료정신의학회
- Keywords
- Bipolar disorder · Manic · Hospitalization · Clinical course.; 양극성 장애·조증 삽화·입원·임상 경과.
- Citation
- 생물치료정신의학, v.23, no.3, pp.155 - 163
- Journal Title
- 생물치료정신의학
- Volume
- 23
- Number
- 3
- Start Page
- 155
- End Page
- 163
- URI
- https://scholarworks.bwise.kr/sch/handle/2021.sw.sch/8048
- DOI
- 10.22802/jksbtp.2017.23.3.155
- ISSN
- 1225-9454
- Abstract
- Objectives:This study was aimed to investigate clinical factors associated with the prediction of symptom improvement in hospitalized patients with bipolar disorder, manic episode.
Methods:We performed a retrospective observational study based on the medical records review of 53 bipolar disorder manic patients, who had been hospitalized in the psychiatric ward. During the hospitalization, Young Mania Rating Scales(YMRS) have been measured periodically. Demographic information and clinical characteristics including medications and history of prior hospitalization have been collected in each patient. Linear mixed effect model has been used to assess the effect of clinical factors on the changes of YMRS over time. Selection of clinical factors was conducted using backward elimination with the minimization of Akaike Information Criterion.
Results:Mean days of hospitalization were 29.74±16.96. Mean YMRS at the admission was 33.64±7.57. Effective factors for the model included YMRS at baseline, combination of mood stabilizer, and the history of prior hospitalization.
Predicted YMRS at the discharge was 10.43(95% confidence interval 7.13–13.72).
Conclusion:The current findings suggest the model which may predict the clinical course of the bipolar disorder manic patients. It would be useful to establish the treatment plan for the patients.
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