A Novel Nomogram to Predict Severity of COVID-19
试验速览
- 阶段
- 不适用
- 状态
- 已完成
- 发起方
- 入组人数
- 1,000
- 试验地点
- 1
- 主要终点
- the consistency of predicted severe rate and observed severe rate of COVID-19 patients
研究概览
简要总结
Investigators use clinical data from a large sample of COVID-19 disease patients to screen out biomarkers associated with disease severity. Then, a novel nomogram model will be established to predict covid-19 disease severity, which could provide important assistance and supplement for clinical work. In the case of extremely shortage of front-line medical resources, patients with potential severe diseases will be timely treated with the help of the novel nomogram model.
研究设计
- 研究类型
- Observational
- 观察模型
- Case Only
- 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
- 否
入选标准
- •COVID-19 disease patients confirmed by virus nucleic acid RT-PCR and CT
排除标准
- •unconfirmed suspected cases
- •Patients during pregnancy and lactation
- •incomplete clinical data
- •investigators considered patients ineligible for the trial
- •Child patients
结局指标
主要结局
the consistency of predicted severe rate and observed severe rate of COVID-19 patients
时间窗: up to 3 months
We aim to use the clinical data of COVID-19 patients to construct a nomogram model to predict the severe rate of each patient, then the the consistency of predicted severe rate and observed severe rate will be evaluated by calibration plot.
Duration of severe illness
时间窗: up to 3 months
the duration of severe illness of each patient will evaluated
次要结局
未报告次要终点
研究者
Jianguo Sun
Deputy Director,Head of Oncology department, Principal Investigator, Clinical Professor
Xinqiao Hospital of Chongqing