Manolitsis Ioannis, Feretzakis Georgios, Tzelves Lazaros, Anastasiou Athanasios, Koumpouros Yiannis, Verykios Vassilios S, Katsimperis Stamatios, Bellos Themistoklis, Lazarou Lazaros, Varkarakis Ioannis
Second Department of Urology, Sismanoglio General Hospital, National and Kapodistrian University of Athens, 15126 Athens, Greece.
School of Science and Technology, Hellenic Open University, 26335 Patras, Greece.
Healthcare (Basel). 2024 Sep 11;12(18):1817. doi: 10.3390/healthcare12181817.
The ASCAPE project aims to improve the health-related quality of life of cancer patients using artificial intelligence (AI)-driven solutions. The current study employs a comprehensive dataset to evaluate sleep and urinary incontinence, thus enabling the development of personalized interventions.
This study focuses on prostate cancer patients eligible for curative treatment with surgery. Forty-two participants were enrolled following their diagnosis and were followed up at baseline and 3, 6, 9, and 12 months after surgical treatment. The data collection process involved a combination of standardized questionnaires and wearable devices, providing a holistic view of patients' QoL and health outcomes. The dataset is systematically organized and stored in a centralized database, with advanced statistical and AI techniques being employed to reveal correlations, patterns, and predictive markers that can ultimately lead to implementing personalized intervention strategies, ultimately enhancing patient QoL outcomes.
The correlation analysis between sleep quality and urinary symptoms post-surgery revealed a moderate positive correlation between baseline insomnia and baseline urinary symptoms (r = 0.407, = 0.011), a positive correlation between baseline insomnia and urinary symptoms at 3 months (r = 0.321, = 0.049), and significant correlations between insomnia at 12 months and urinary symptoms at 3 months (r = 0.396, = 0.014) and at 6 months (r = 0.384, = 0.017). Furthermore, modeling the relationship between baseline insomnia and baseline urinary symptoms showed that baseline insomnia is significantly associated with baseline urinary symptoms (coef = 0.222, = 0.036).
The investigation of sleep quality and urinary incontinence via data analysis through the ASCAPE project suggests that better sleep quality could improve urinary disorders.
ASCAPE项目旨在利用人工智能驱动的解决方案提高癌症患者的健康相关生活质量。当前研究采用综合数据集来评估睡眠和尿失禁情况，从而能够制定个性化干预措施。
本研究聚焦于适合手术根治性治疗的前列腺癌患者。42名参与者在确诊后入组，并在手术治疗后的基线以及3、6、9和12个月进行随访。数据收集过程涉及标准化问卷和可穿戴设备的结合，提供了患者生活质量和健康结果的全面视图。数据集经过系统整理并存储在中央数据库中，采用先进的统计和人工智能技术来揭示相关性、模式和预测标志物，最终可用于实施个性化干预策略，从而提高患者的生活质量结果。
术后睡眠质量与泌尿症状的相关性分析显示，基线失眠与基线泌尿症状之间存在中度正相关（r = 0.407，P = 0.011），基线失眠与3个月时的泌尿症状之间存在正相关（r = 0.321，P = 0.049），12个月时的失眠与3个月（r = 0.396，P = 0.014）和6个月（r = 0.384，P = 0.017）时的泌尿症状之间存在显著相关性。此外，对基线失眠与基线泌尿症状之间的关系进行建模显示，基线失眠与基线泌尿症状显著相关（系数 = 0.222，P = 0.036）。
通过ASCAPE项目进行数据分析对睡眠质量和尿失禁的调查表明，更好的睡眠质量可能改善泌尿疾病。
