Risk Assessment of Postoperative Acute Kidney Injury and Personalized Intraoperative Hypotension Threshold Prediction Based on Blood Pressure Components in Non-Cardiac Surgery Patients
试验速览
- 阶段
- 不适用
- 状态
- 进行中（未招募）
- 发起方
- 入组人数
- 44,504
- 试验地点
- 1
- 主要终点
- Postoperative AKI
研究概览
简要总结
Postoperative acute kidney injury (AKI) is a serious complication often linked to low blood pressure during surgery. This study aims to better protect patients' kidneys by personalizing how blood pressure is managed during an operation.
The project has two main goals:
First, researchers will analyze data from over 44,000 past surgeries to identify which specific blood pressure measurements are the most critical warning signs for kidney damage.
Second, using this knowledge, they will build a smart tool (a machine learning model) to predict a unique, safe blood pressure target for each individual patient before their surgery begins.
This personalized approach is intended to give doctors a specific target to maintain during surgery, helping to prevent kidney injury and improve patient safety.
详细描述
- Study Rationale Postoperative Acute Kidney Injury (AKI) is a common and severe complication following non-cardiac surgery, leading to prolonged hospital stays, increased medical costs, and a higher risk of persistent kidney failure or death. Intraoperative hypotension (abnormally low blood pressure during surgery) is recognized as a significant contributor to AKI, as it can reduce blood flow and oxygen supply to the kidneys.
Currently, there is no clinical consensus on which component of blood pressure-such as systolic (SBP), diastolic (DBP), or mean arterial pressure (MAP)-is the most critical to monitor for preventing organ injury. Furthermore, current guidelines often recommend a universal "one-size-fits-all" threshold for hypotension (e.g., MAP < 65 mmHg). This approach fails to account for individual patient differences, such as baseline blood pressure and co-existing health conditions, which may mean that the optimal blood pressure target varies significantly from person to person.
This study aims to address these gaps by using a large, multi-center dataset to first identify the most critical blood pressure components linked to AKI and then to develop a tool that predicts a personalized, optimal blood pressure threshold for individual patients. 2. Study Objectives
This study is divided into two parts:
Part 1: Risk Assessment and Blood Pressure Component Analysis
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
- •Patients undergoing non-cardiac surgery
- •Access to intraoperatively available invasive/noninvasive blood pressure monitoring data
排除标准
- •Patients for Age < 18 yr
- •Patients without preoperative or postoperative creatinine records
- •Patients undergoing urinary surgeries
- •Patients with chronic kidney injury before surgery
- •ASA grade > 5 class
- •Anesthesia duration < 60 min
- •Patients for non-available lowest blood pressure data during surgery
- •Hemodynamic records loss more than 25% of the total anesthesia duration
- •Patients for categorical variables records missing
结局指标
主要结局
Postoperative AKI
时间窗: Within 7 days post-op
KDIGO criteria for diagnosis (≥0.3 mg/dL or ≥1.5-fold increase in creatinine value)
Individualized Optimal Intraoperative Hypotension Threshold.
时间窗: preoperative period
A patient-specific blood pressure threshold predicted by a dynamic machine learning model. This threshold is identified as the blood pressure value at which the model-predicted risk of postoperative Acute Kidney Injury (AKI) falls below 10%.
次要结局
- Postoperative AKD(Within 8-90 days post-op)
- length of hospital stay(Through hospital discharge, an average of 1 weak)
- Predicted Risk of Postoperative AKI.(preoperative period)
- Predicted Lowest Intraoperative Blood Pressure.(preoperative period)
研究者
Lanyue Zhu
Attending Physician
Zhongda Hospital