Applying Artificial Intelligence to Identify Subphenotypes of Acute Kidney Injury in Mexican Patients With Severe COVID-19
试验速览
- 阶段
- 不适用
- 状态
- 已完成
- 入组人数
- 2,934
- 试验地点
- 1
- 主要终点
- Subphenotypes of acute kidney injury in patients
研究概览
简要总结
The goal of this observational study was to identify subphenotypes of acute kidney injury patients with COVID-19, and the investigators analyzed their impact on mortality. The study included demographic and clinical variables of the participants. The implementation of Machine Learning algorithms and Artificial Intelligence methods are used, and some specific implementations were designed for the analysis, where each group was characterized by traditional statistical methods.
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
- 15 Years 至 —（Child, Adult, Older Adult）
- 性别
- All
- 接受健康志愿者
- 否
入选标准
- •Patients older than 15 years old, hospitalized, and with severe acute respiratory syndrome (SARS-CoV-2) positive confirmation.
排除标准
- •Patients who did not have at least 1 creatinine measurement.
结局指标
主要结局
Subphenotypes of acute kidney injury in patients
时间窗: Through study completion, an average of one month
Number of acute kidney injury subphenotypes in patients with COVID-19
次要结局
- Length of stay of acute kidney injury patients(Through study completion, an average of one month)
- Mortality of acute kidney injury patients(Through study completion, an average of one month)
- Severity of acute kidney injury patients(Through study completion, an average of one month)
- Renal replacement therapy requirement in acute kidney injury patients(Through study completion, an average of one month)
- Non-recovery in acute kidney injury patients(Through study completion, an average of one month)
研究者
Elizabeth Santiago Del Angel
Ph D. in computer science
Instituto Nacional de Enfermedades Respiratorias