Patients and data variables
AKI
DISEASES, DISEASE, CHRONIC RENAL FAILURE, KIDNEY DISEASE
Data were extracted using Structured Query Language (SQL) programming in PostgreSQL (version 14.0), and the SQL script codes used to extract patients' information were obtained from the GitHub website (Using the International Classification of Diseases (ICD), ninth revision (ICD-9, code 577.0) and tenth revision (ICD-10, code K85%), we identified the patients diagnosed with AP from the MIMIC-IV v1.0 database. The exclusion criteria were age less than 18 years old and intensive care unit (ICU) stay < 24 h and patients with a history of chronic renal failure, including a previous history of a kidney transplant. For patients who had multiple admissions to the ICU, data were only obtained from the first admission.After identifying eligible patients, we collected AP patient’s baseline parameters immediately after admission to the ICU, including demographic information, previous medical history, vital signs, laboratory indicators, injury factors, interventions, and disease severity scores. The vital signs and laboratory indicators are the first value within the first 24 h after ICU, and intervention measures and the severity scores of the disease are evaluated within the first 24 h after ICU.The outcome measure was determined as the development of AKI within seven days of admission to the ICU. A diagnosis of AKI was based on the 2012 Kidney Disease: Improving Global Outcomes (KIDGO) guidelines as follows: elevated serum creatinine (SCr) after 48 h by ≥26.5 μmol/L (0.3 mg/dl); or ≥50% of the baseline SCr value (increased by 1.5 times), or a urine output of more than six hours of <0.5 mL/kg/h [