NCT05731765进行中（未招募）不适用
Automated Detection of Spontaneous Venous Pulsations Within Fundal Videos Using Machine Learning
适应症
试验速览
- 阶段
- 不适用
- 状态
- 进行中（未招募）
- 入组人数
- 210
- 试验地点
- 1
- 主要终点
- Area-under-the receiver operating characteristic (AUROC) for spontaneous venous pulsations detection
研究概览
简要总结
This diagnostic study will use 410 retrospectively captured fundal videos to develop ML systems that detect SVPs and quantify ICP. The ground truth will be generated from the annotations of two independent, masked clinicians, with arbitration by an ophthalmology consultant in cases of disagreement.
研究设计
- 研究类型
- Observational
- 观察模型
- Cohort
- 时间视角
- Retrospective
入排标准
- 年龄范围
- 18 Years 至 —（Adult, Older Adult）
- 性别
- All
- 接受健康志愿者
- 是
入选标准
- •Patients aged ≥18 years with presumed normal ICP undergoing routine dilated OCT scans.
- •Patients undergoing a LP or continuous ICP monitoring with implanted transcranial pressure transducer devices at in- or out-patient neurology, neurosurgery or neuro-ophthalmology services.
排除标准
- •Glaucoma diagnosis or glaucoma suspects in either eye.
- •Bilateral restricted fundal view, e.g. advanced bilateral cataracts.
- •Bilateral retinal vein or artery occlusion.
结局指标
主要结局
Area-under-the receiver operating characteristic (AUROC) for spontaneous venous pulsations detection
时间窗: 1 year
Binary classification performance of the machine learning model
次要结局
- Quantification of intracranial pressure(1 year)
- Localisation of spontaneous venous pulsations(1 year)
研究者
研究点 (1)
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