POS-191 EXTERNAL VALIDATION AND COMPARISON OF RISK PREDICTION SCORING TOOLS FOR ACUTE KIDNEY INJURY IN PATIENTS WITH MYOCARDIAL INFARCTION IN A TERTIARY HOSPITAL IN DAVAO CITY

Abstract

Patients with acute myocardial infarction are at high risk of developing acute kidney Injury (AKI). In settings where AKI biomarkers are not readily available, the use of a scoring system upon patient's admission may benefit those with high probability of developing AKI as this may allow prompt institution of renal protective measures such as avoidance of overzealous diuresis, wide variations in blood pressure, use of high volume contrast media, acute anemia from blood loss, and use of relatively nephrotoxic agents that may require renal dose adjustments and, perhaps, an early nephrology referral. From January 2015 to December 2019, a total of 384 charts were gathered based on inclusion criteria. After thorough chart review, 317 charts were excluded and 69 patient charts were included for the study. The continuous baseline characteristics of AKI and non-AKI patients in this study were analyzed using Shapiro-Wilk Test for normality. Comparison of these baseline characteristics was done using Independent Sample T-test and presented as mean and standard deviation otherwise, Mann-Whitney U Test was used and presented with mean rank. Pearson Chi Square or Fisher’s Exact Test was used to compare categorical characteristics. A p-value of <0.05 was considered statistically significant. Overall diagnostic accuracy of both scoring tools was assessed by area under the receiver operating characteristic (AUROC) curve. SPSS was used to determine the specificity, sensitivity and AUROC of all possible cut-off scores for each scoring tool. Online statistical calculators were used to calculate for the positive predictive value (PPV), negative predictive value (NPV), accuracy, and likelihood ratios. The study population consisted of 69 patients, 23 (33.3%) of whom developed acute kidney injury based on the KDIGO criteria. These patients were further categorized as having stage 1 (78.3%), stage 2 (17.4%), or stage 3 (4.3%) AKI. The two risk scoring tools used in this study to predict the occurrence of acute kidney injury in those who had an acute myocardial infarction are those of Abusaada et al and Xu et al. The cut-off scores for Abusaada’s and Xu’s tools are similar at >/= 4. Results showed a higher sensitivity analysis for Xu (91% vs 61%). However, Abusaada’s scoring tool had higher values for specificity (85% vs 7%), PPV (66.7% vs 32.8%), NPV (81.2% vs 60%), accuracy (76.8% vs 34.7%), and positive likelihood ratio (4 vs .98). For purposes of comparison, the scoring tool of Xu required adjustment to arrive at the cut-off score with the highest accuracy. After adjustment, AUROC values were calculated showing .717 (95% CI: .58-.86) for Abusaada and .764 (95% CI: .64-.89) for Xu which had no statistical difference (p-value .447). This study concluded that there is a high incidence of AKI in patients with acute myocardial infarction. Of the available recently validated risk assessment tools that can stratify patients in terms of developing AKI, between Xu et al and Abusaada et al, this study favors the use of the Abusaada scoring system because it did not require any adjustment to arrive at the highest accuracy level. This scoring can be employed immediately upon admission to aid in the preemptive management of AKI in patients with myocardial infarction. This was found to have a good predictive index for AKI occurrence in the setting of AMI.