Objective:To analyze the risk factors of major adverse kidney events within 30 days (MAKE30) in patients with acute pancreatitis (AP).Methods:A retrospective cohort study was conducted. A total of 162 patients who were first diagnosed with AP in the First Affiliated Hospital of Soochow University from June 2019 to June 2021 and the onset time was less than 72 hours were enrolled. Patients were divided into MAKE30 group and non-MAKE30 group according to the occurrence of MAKE30 after hospitalization. MAKE30 was defined as death from any cause, new renal replacement therapy (RRT), and persistent renal insufficiency (PRD). The clinical data of the two groups at admission were compared. The independent risk factors of MAKE30 were analyzed by multivariate Logistic regression method, and a regression equation was established as a quantitative prediction model of MAKE30. Receiver operator characteristic curve (ROC curve) was drawn to analyze the prediction of the quantitative prediction model value.Results:All 162 patients were included in the final analysis, including 32 in the MAKE30 group and 130 in the non-MAKE30 group. Univariate analysis showed that compared with the non-MAKE30 group, the body mass index (BMI), the proportion of severe AP, and the acute physiology and chronic health evaluation Ⅱ (APACHEⅡ) score, the sequential organ failure assessment (SOFA) score, blood urea nitrogen (BUN), serum creatinine (SCr), C-reactive protein (CRP), HCO 3-, Cl - levels and the proportion of hyperchloremia at admission in the MAKE30 group were significantly increased. Multivariate Logistic regression analysis showed that APACHE Ⅱ score at admission [odds ratio ( OR) = 1.659, 95% confidence interval (95% CI) was 1.426-1.956, P = 0.009], SOFA score ( OR = 1.501, 95% CI was 1.236-1.840, P = 0.014) and hyperchloremia ( OR = 1.858, 95% CI was 1.564-2.231, P = 0.004) were independent risk factors for MAKE30 in AP patients. The MAKE30 regression equation was established by the above risk factors [Logit( P) = 0.063+0.525×APACHEⅡ score+0.328×SOFA score+0.895×hyperchloremia], which was used as the MAKE30 quantitative prediction model. ROC curve analysis showed that the area under the ROC curve (AUC) of the model for predicting MAKE30 was 0.846 (95% CI was 0.774-0.923, P = 0.001). The patients were divided into two subgroups with hyperchloremia (Cl -≥110 mmol/L, n = 19) and non-hyperchloremia (Cl - < 110 mmol/L, n = 143) according to the blood Cl - level at admission. The incidence of MAKE30 and acute kidney injury (AKI) in the hyperchloremia group was significantly increased (MAKE30: 68.4% vs. 13.3%, AKI: 89.5% vs. 43.4%), and the levels of BUN and SCr at admission were significantly increased [BUN (mmol/L): 9.3±2.5 vs. 5.9±1.1, SCr (μmol/L): 162.3±26.4 vs. 78.6±9.2], the total length of hospital stay and length of intensive care unit (ICU) stay were significantly longer [total length of hospital stay (days): 10.2±1.6 vs. 5.6±1.2, length of ICU stay (days): 6.2±1.0 vs. 3.1±0.6], the cumulative intravenous infusion volume increased significantly at 48 hours and 72 hours (mL: 7 235.9±1 025.3 vs. 5 659.6±956.7 at 48 hours, 11 052.6±1 659.8 vs. 7 156.9±1 052.4 at 72 hours), differences were statistically significant (all P < 0.01). Conclusions:MAKE30 can be used as an important indicator to evaluate the short-term clinical prognosis of AP patients. APACHEⅡ score, SOFA score and hyperchloremia at admission are the main risk factors. The risk model of MAKE30 based on these three indicators has good predictive performance. AP patients with hyperchloremia are at high risk of developing MAKE30, which should be highly regarded in clinical practice.