Overview
Primary objectives of this study is to develop and validate a predictive model for acute kidney injury after non-cardiac surgery based on machine learning. Secondary objectives of this study is to incorporate frailty assessment as a new predictor into the model and measure its incremental value was measured.
Description
The data of this study are divided into two parts: retrospective and prospective. The retrospective data were from the electronic medical records of adult patients who underwent non-cardiac surgery during hospitalization from July 2015 to June 2025. The ratio of the training set, the internal validation set and the test set was 7:1:2. The prospective data is an external (temporal) validation set. Data collection began in July 2025 and is expected to end in February 2026
Eligibility
Inclusion Criteria:
- 18 years old or above
- Undergo non-cardiac surgery
Exclusion Criteria:
- At least one measurement of serum creatinine (SCr) was not conducted before and after the operation
- End-stage renal disease (ESRD) that has received dialysis within the past year
- Baseline SCr ≥ 4.5 mg/dl (because the clinical criteria for AKI based on elevated SCr may not be applicable to these patients)
- Acute kidney injury occurred within 7 days before the operation
- The operation time is less than 2 hours