Development of Interpretable Machine Learning Models for Prediction of Acute Kidney Injury After Noncardiac Surgery
试验速览
- 阶段
- 不适用
- 状态
- 已完成
- 发起方
- 入组人数
- 88,367
- 试验地点
- 1
- 主要终点
- Postoperative acute kidney injury
研究概览
简要总结
Acute kidney injury (AKI) is a common surgical complication characterized by a rapid decline in renal function. Patients with AKI are at an increased risk of developing chronic kidney disease and end-stage renal disease, which has been associated with an increased risk of morbidity, mortality and financial burdens. Identifying high-risk patients for postoperative AKI early can facilitate the development of preventive and therapeutic management strategies, and prediction models can be helpful in this regard.
The goal of this retrospective study is to develop prediction models for postoperative AKI in noncardiac surgery using machine learning algorithms, and to simplify the models by including only preoperative variables or only important predictors.
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
- 否
入选标准
- •Adult patients (age ≥ 18 years) who had a serum creatinine measurement within 10 days before surgery and at least one measurement within 7 days after surgery.
- •Eligible surgeries encompassed general, thoracic, orthopedic, obstetric, gynecology, and neurosurgery procedures lasting longer than 1 hour
排除标准
- •Patients with concurrent cardiac, vascular, urological, or transplant surgeries.
- •Patients with an American Society of Anesthesiologists (ASA) physical status V.
- •Patients with end-stage renal disease (i.e., a glomerular filtration rate [eGFR] of 15 mL/min/1.73 m² or receiving hemodialysis).
结局指标
主要结局
Postoperative acute kidney injury
时间窗: Within 7 days after surgery
In accordance with the KDIGO creatinine criteria: a serum creatinine increases of 26.5 mmol/L within 48 hours or 1.5 times baseline within 7 days after surgery.
次要结局
未报告次要终点
研究者
Rao Sun
Associate chief physician
Tongji Hospital