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- Title
Using a smartphone-based self-management platform to study sex differences in Parkinson's disease: multicenter, cross-sectional pilot study.
- Authors
Xu, Zhiheng; Jin, Lirong; Chen, Weijie; Hu, Tianyu; Li, Shiyu; Liang, Xiaoniu; Han, Xixi; Chen, Yi; Tang, Yilin; Wang, Jian; Wu, Danhong
- Abstract
Background: Patient-reported outcome (PRO) is a distinct and indispensable dimension of clinical characteristics and recent advances have made remote PRO measurement possible. Sex difference in PRO of Parkinson's disease (PD) is hardly extensively researched. Methods: A smartphone-based self-management platform, offering remote PRO measurement for PD patients, has been developed. A total of 1828 PD patients, including 1001 male patients and 827 female patients, were enrolled and completed their PRO submission through this platform. Results: Sex differences in PROs have been identified. The female group had a significantly lower height, weight, and body mass index (BMI) than the male group (P < 0.001). For motor symptoms, a higher proportion of patients reporting dyskinesia was observed in the female group. For non-motor symptoms, there is a higher percentage (P < 0.001) as well as severity (P = 0.016) of depression in the female group. More male patients reported hyposmia, lisp, drooling, dysuria, frequent urination, hypersexuality, impotence, daytime sleepiness, and apathy than females (P < 0.05). In contrast, more female patients reported headache, palpation, body pain, anorexia, nausea, urinal incontinence, anxiety, insomnia (P < 0.05) than males. Conclusions: We provide evidence for sex differences in PD through the data collected from our platform. These results highlighted the importance of gender in clinical decision-making, and also support the feasibility of remote PRO measurement through a smartphone-based self-management platform in patients with PD.
- Subjects
PARKINSON'S disease; SMARTPHONES; DROWSINESS; DROOLING; PATIENTS; SUMATRIPTAN; BODY mass index; PILOT projects
- Publication
BMC Medical Informatics & Decision Making, 2024, Vol 24, Issue 1, p1
- ISSN
1472-6947
- Publication type
Article
- DOI
10.1186/s12911-024-02569-1