인문학
사회과학
자연과학
공학
의약학
농수해양학
예술체육학
복합학
DBpia AI
AI 에이전트
AI 아이디어
AI 리더
AI 뷰어
Citeasy
크롬 서지관리 다운로드
지원사업
학술연구/단체지원/교육 등 연구자 활동을 지속하도록 DBpia가 지원하고 있어요.
커뮤니티
연구자들이 자신의 연구와 전문성을 널리 알리고, 새로운 협력의 기회를 만들 수 있는 네트워킹 공간이에요.
초록·키워드
Comparative studies assessing outcomes with the three device-assisted therapies could help to individualise treatment for patients living with Parkinson's disease. We designed a single-centre non-randomised prospective observational study assessing the quality of life (QoL), motor and non-motor outcomes at 6 and 12-months in patients treated with subcutaneous apomorphine continuous 16-hours infusion (APO), levodopa-carbidopa intestinal gel (LCIG) or subthalamic nucleus deep brain stimulation (STN-DBS). In this study, 66 patients were included (13 APO; 19 LCIG; 34 STN-DBS). At baseline, cognitive, non-motor and motor scores were significantly less severe in the STN-DBS group, whereas the LCIG group had a longer disease duration and higher non-motor scores. In the APO group, there were no statistically significant changes in non-motor, motor and QoL scales. The LCIG group had significant changes in QoL and motor scales that were significant after multiple comparison analysis at 6 and 12-months. The STN-DBS group showed improvement in QoL scores and non-motor and motor scores at 6 and 12-months after multiple comparison analysis. In this real-life prospective study, device-assisted therapies showed differences in their effects on QoL and motor and non-motor function at 12-months. However, there were also differences in baseline characteristics of the patient groups that were not based on pre-determined selection criteria. Differences in characteristics of patients offered and/or treatment with different device-assisted therapies may reflect within-centre biases that may, in turn, influence perceptions of treatment efficacy or outcomes. Treatment centres should be aware of this potential confounder when assessing and offering device-assisted treatment options to their patients and potential baseline differences need to be taken into consideration when comparing the results of non-randomised studies.
인공지능 문자 인식 모델을 통해 추출된 텍스트로, 일부 오타나 오류가 포함될 수 있으나 지속적으로 개선 중입니다.
오류를 발견하셨다면 해당 부분을 드래그한 후 ' 를 통해 신고해주세요.
오류를 발견하셨다면 해당 부분을 드래그한 후 ' 를 통해 신고해주세요.
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