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Objective: To investigate the impact of acute myocardial infarction (AMI) concurrent acute kidney injury (AKI) on major adverse cardiac events (MACE) occurrence during hospitalization. Methods: A total of 625 AMI patients treated in our hospital from 2011-01 to 2014-03 were retrospectively studied. According to AKI incidence, the patients were divided into 2 groups: AKI group,n=86 and Non-AKI group,n=539. Based on AKI network (AKIN) criteria, AKI group was further divided into 3 subgroups as AKI-I subgroup,n=45, AKI-II subgroup,n=27, AKI-III subgroup,n=14; based on renal function at admission, AKI group was divided into another set of 2 subgroups as Normal renal function subgroup [(eGFR≥90 ml/(min·1.73m2)],n=61 and Renal dysfunction subgroup [(eGFR Results: The incidences of MACE in AKI group and Non-AKI group was (59.3% vs 16.9%),P0.05. Multivariate Logistic regression analysis showed that AKI was the independent risk factor for MACE occurrence in AMI patients; elevated AKI stages were accompanied with the higher incidence of MACE accordingly, compared with AKI-I subgroup, the incidences of MACE in AKI-III subgroup and AKI-II subgroup were as (OR=1.68, 95% CI 1.14-1.69),P Conclusion: AKI was closely related to MACE occurrence in AMI patients, effectively preventing AKI may improve the prognosis in relevant patients.
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Objective To investigate the risk factors for acute kidney injury (AKI) in patients with non-ST-segment elevation myocardial infarction (NSTEMI),and to establish a prediction score system for AKI.Methods Totally 296 patients with NSTEMI,who were admitted to the emergency room and further transferred to the Cardiovascular Department in Shantou Central Hospital,were enrolled during January 2011 to April 2014.All patients were divided into AKI group and non-AKI group.Demographics,clinical data and laboratory examinations were collected before and after AKI.AKI risk factors and its OR values were determined after statistically analyzed data by One-Way ANOVA,multivariate logistic regression analysis.Prediction score system for AKI was further established by area under the ROC curve and Hosmer-Lemeshow goodness of fit tests.Results For total 296 patients,the incidence of AKI was 18.4％,including 35 (64.8％) patients in stage Ⅰ,12 (22.2％) patients in stage Ⅱ and 7 (13.0％) patients in stage Ⅲ.Logistic analysis showed that age,heart function (Killip),anemia,the time to emergency department after AMI attack,and absence β-blocker were independent factors associated with AKI.Prediction score system was established which the highest score was 13.A risk score of 3.5 points was determined by Youden' s index,as the optimal cut-off for predict AKI.Patients with ≤3.0 points were considered at low risk,and ≥4.0 points were considered at high risk for AKI.The prediction score system of AKI showed adequate discrimination (area under ROC curve was 0.806) and calibration (Hosmer-Lemeshow statistic test,P =O.503).Conclusions Age,heart function (Killip),anemia,the time to emergency department after AMI attack,and absence β-blocker were independent factors associated with AKI.The clinical prediction score system may help clinicians to make pre-intervention for NSTEMI patients with high AKI risk.