Identification of Thoracic CT Scan Biomarkers by Deep Learning for Evaluating the Prognosis of Patients With COVID-19 Disease
试验速览
- 阶段
- 不适用
- 状态
- 撤回
- 发起方
- 入组人数
- 1,000
- 试验地点
- 6
- 主要终点
- Patient requiring more than 3 liters of oxygen to maintain a saturation >95% (intensive care unit or resuscitation department)
研究概览
简要总结
The study hypothesis is that low-dose computed tomography (LDCT) coupled with artificial intelligence by deep learning would generate imaging biomarkers linked to the patient's short- and medium-term prognosis.
The purpose of this study is to rapidly make available an early decision-making tool (from the first hospital consultation of the patient with symptoms related to SARS-CoV-2) based on the integration of several biomarkers (clinical, biological, imaging by thoracic scanner) allowing both personalized medicine and better anticipation of the patient's evolution in terms of care organization.
研究设计
- 研究类型
- Observational
- 观察模型
- Case Only
- 时间视角
- Retrospective
入排标准
- 性别
- All
- 接受健康志愿者
- 否
入选标准
- •Patients positive for SARS-CoV-2 according to RT-PCR test between 1st March and 31st May 2020
- •Patients undergoing low dose CT scan to establish Covid-19 lung damage
- •Available for at least 8 days follow-up
排除标准
- •Patients opposing the retrospective use of their data
结局指标
主要结局
Patient requiring more than 3 liters of oxygen to maintain a saturation >95% (intensive care unit or resuscitation department)
时间窗: Day 8
Yes/no
Percentage of lung affected by condensation on scan
时间窗: Day 0
% calculated by deep learning
Percentage of lung affected by ground glass opacity on scan
时间窗: Day 0
% calculated by deep learning
Vital status
时间窗: Day 8
Dead/alive
Percentage of lung affected on CT
时间窗: Day 0
% ground glass and condensation calculated by deep learning
次要结局
- rehospitalization(Day 30)
- Duration of intubation(Day 30)
- D Dimers level(Admission Day 0)
- Time between RT-PCR positive results and first scan(Admission Day 0)
- Medical history of cardiovascular disease(Admission Day 0)
- Percentage of lung affected on CT(Day 16)
- C-reactive protein levels(Admission Day 0)
- Time until onset of symptoms(Admission Day 0)
- BMI> 30(Admission Day 0)
- lymphocytemia(Admission Day 0)
- Diabetes(Admission Day 0)
- Medical history of immunosuppressed condition(Admission Day 0)
- Vital status(Day 30)
- Length of hospitalization(Maximum 30 days)
- Percentage of lung affected by ground glass opacity on scan(Day 16)
- Percentage of lung affected by condensation on scan(Day 16)
- Software operating time(End of study (August 2020))
- Calculate a prognostic score from clinical, biological and CT parameters(Day 8)
- lactate dehydrogenase(Admission Day 0)
- Calculate a prognostic score from clinical and biological parameters only(Day 8)
- Medical history of respiratory disease(Admission Day 0)
- Age(Admission Day 0)
- Current or previous history of smoking(Admission Day 0)
- Compare receiver operating curves of prognostic scores with and without CT parameters(Day 8)