Research Article: An Explainable Machine Learning Model to Predict Acute Kidney Injury After Cardiac Surgery: A Retrospective Cohort Study
Abstract:
The impact of acute kidney injury (AKI) is up to % in patients undergoing cardiac surgery. Delayed diagnosis and intervention allow AKI to progress to more severe stages and contribute to the development of chronic kidney disease after hospital discharge. Both mortality and length of stay increase with the progressive severity of kidney injury. In clinical trials, no pharmacological or non-pharmacological prevention strategies have been shown to reduce the occurrence of AKI., Therefore, an accurate postoperative AKI risk assessment is crucial for the postoperative strategy for monitoring and disposition.
Introduction:
The impact of acute kidney injury (AKI) is up to % in patients undergoing cardiac surgery. Delayed diagnosis and intervention allow AKI to progress to more severe stages and contribute to the development of chronic kidney disease after hospital discharge. Both mortality and length of stay increase with the progressive severity of kidney injury. In clinical trials, no pharmacological or non-pharmacological prevention strategies have been shown to reduce the occurrence of AKI. , Therefore, an accurate postoperative…
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