Xu FB, Cheng H, Yue T, Ye N, Zhang HJ, Chen YP. Derivation and validation of a prediction score for acute kidney injury secondary to acute myocardial infarction in Chinese patients.
BMC Nephrol 2019;
20:195. [PMID:
31146701 PMCID:
PMC6543657 DOI:
10.1186/s12882-019-1379-x]
[Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2018] [Accepted: 05/13/2019] [Indexed: 12/16/2022] Open
Abstract
Background
Acute kidney injury (AKI) is a major complication of acute myocardial infarction(AMI), which can significantly increase mortality. This study is to analyze the related risk factors and establish a prediction score of acute kidney injury in order to take early measurement for prevention.
Methods
The medical records of 6014 hospitalized patients with AMI in Beijing Anzhen Hospital from January 2010 to December 2016 were retrospectively analyzed. These patients were randomly assigned into two cohorts: one was for the derivation of prediction score (n = 4252) and another for validation (n = 1762). The criterion for AKI was defined as an increase in serum creatinine of ≥ 0.3 mg/dL or ≥ 50% from baseline within 48 h. On the basis of odds ratio obtained from multivariate logistic regression analysis, a prediction score of acute kidney injury after AMI was built up.
Results
In this prediction score, risk score 1 point included hypertension history, heart rate > 100 bpm on admission, peak serum troponin I ≥ 100 μg/L, and time from admission to coronary reperfusion > 120 min; risks score 2 points included Killip classification ≥ class 3 on admission; and maximum dosage of intravenous furosemide ≥ 60 mg/d; risks score 3 points only included shock during hospitalization. In addition, when baseline estimated glomerular filtration rate (eGFR) was less than 90 ml/min·1.73 m2, every 10 ml/min·1.73 m2 reduction of eGFR increased risk score 1 point. Youden index showed that the best cut-off value for prediction of AKI was 3 points with a sensitivity of 71.1% and specificity 74.2%. The datasets of derivation and validation both displayed adequate discrimination (an area under the ROC curve, 0.79 and 0.81, respectively) and satisfactory calibration (Hosmer–Lemeshow statistic test, P = 0.63 and P = 0.60, respectively).
Conclusions
In conclusion, a prediction score for AKI secondary to AMI in Chinese patients was established, which may help to prevent AKI early.
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