Left Ventricular End-Diastolic Pressure for the Prediction of Contrast-Induced Nephropathy and Clinical Outcomes in Patients With ST-Elevation Myocardial Infarction Who Underwent Primary Percutaneous Intervention (the ELEVATE Study)

Contrast-induced nephropathy (CIN) is an important complication of percutaneous coronary intervention (PCI). We investigated whether left ventricular end-diastolic pressure (LVEDP) in patients who underwent PCI might be additive to current risk stratification of CIN. Data from consecutive patients who underwent primary PCI for ST-elevation myocardial infarction between 2013 and 2018 at Western Health in Victoria, Australia were analyzed. CIN was defined as a 25% increase in serum creatinine from baseline or 44 µmol/L increase in absolute value within 48 hours of contrast administration. Compared with patients without CIN (n = 455, 93%), those who developed CIN (n = 35, 7%) were older (64 vs 58 years, p = 0.006), and had higher peak creatine kinase (2,862 [1,258 to 3,952] vs 1,341 U/L [641 to 2,613], p = 0.02). The CIN group had higher median LVEDP (30 [21-33] vs 25 mm Hg [20-30], p = 0.013) and higher median Mehran risk score (MRS) (5 [2-8] vs 2 [1-5], p <0.001). Patients with CIN had more in-hospital major adverse cardiovascular and cerebrovascular events (composite end point of death, new or recurrent myocardial infarction or stent thrombosis, target vessel revascularization or stroke) (23% vs 8.6%, p = 0.01), but similar 30-day major adverse cardiovascular and cerebrovascular events (20% vs 15%, p = 0.46). An LVEDP >30 mm Hg independently predicted CIN (odds ratio 3.4, 95% confidence interval 1.46 to 8.03, p = 0.005). The addition of LVEDP ≥30 mm Hg to MRS marginally improved risk prediction for CIN compared with MRS alone (area-under-curve, c-statistic = 0.71 vs c-statistic = 0.63, p = 0.08). In conclusion, elevated LVEDP ≥30 mm Hg during primary PCI was an independent predictor of CIN in patients treated for ST-elevation myocardial infarction. The addition of LVEDP to the MRS may improve risk prediction for CIN.