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尿失禁诊断仪器研究重点。

Research priorities for diagnostic instrumentation in urinary incontinence.

机构信息

Bristol Urological Institute, Bristol, UK.

Antwerp University Hospital, Antwerpen, Belgium.

出版信息

Proc Inst Mech Eng H. 2024 Jun;238(6):682-687. doi: 10.1177/09544119231193884. Epub 2023 Sep 5.

DOI:10.1177/09544119231193884
PMID:37667889
Abstract

The International Consultation on Incontinence (ICI) captures current evidence on incontinence. The conference 'Incontinence: The Engineering Challenge XIII' in November 2021 heard an update on the most recent ICI summary on urodynamic testing. This paper summarises the ICI recommendations for future research in urodynamics, with a view to informing engineers of issues and challenges that could benefit from engineering solutions. Engineers are encouraged to contribute to the following areas of research, which will have a direct and positive effect on patients' quality of life and overall health: (a) Urine flow measurement: home- and app-based devices, machine learning analysis of flow shape, (b) Pressure measurement: normal values for and validation of new technologies, including air-filled, non-invasive and urethral pressure reflectometry, (c) Ultrasound imaging: bladder wall biomechanics, bladder shape analysis, (d) Assess normal and abnormal value ranges, and diagnostic performance and (e) Specific trials in understudied patient groups including those with symptoms resistant to treatment, children and the frail elderly.

摘要

国际尿失禁咨询委员会(ICI)收集了关于尿失禁的最新证据。2021 年 11 月举行的“尿失禁:工程挑战 XIII 会议”听取了关于最新的尿动力学测试 ICI 摘要的最新情况。本文总结了 ICI 对未来尿动力学研究的建议,以期让工程师了解可能受益于工程解决方案的问题和挑战。鼓励工程师在以下研究领域做出贡献,这将对患者的生活质量和整体健康产生直接而积极的影响:(a) 尿流测量:家庭和应用程序设备,流量形状的机器学习分析,(b) 压力测量:正常数值和新技术的验证,包括充气、非侵入性和尿道压力反射测量,(c) 超声成像:膀胱壁生物力学,膀胱形状分析,(d) 评估正常和异常值范围、诊断性能和 (e) 在研究不足的患者群体中进行特定试验,包括对治疗有抵抗症状的患者、儿童和脆弱的老年人。

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Research priorities for diagnostic instrumentation in urinary incontinence.尿失禁诊断仪器研究重点。
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Urodynamic and ultrasound characteristics of incontinence after radical hysterectomy.根治性子宫切除术后尿失禁的尿动力学和超声特征
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Biosensors (Basel). 2025 Jul 24;15(8):481. doi: 10.3390/bios15080481.
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Improving the Accuracy of a Wearable Uroflowmeter for Incontinence Monitoring Under Dynamic Conditions: Leveraging Machine Learning Methods.提高可穿戴尿流计在动态条件下进行尿失禁监测的准确性:利用机器学习方法。
Biosensors (Basel). 2025 May 11;15(5):306. doi: 10.3390/bios15050306.