Prediction of 30-day mortality in older patients with a first acute myocardial infarction

This study sought predictors of mortality in patients aged >or=75 years with a first ST-segment elevation myocardial infarction (STEMI) and evaluated the validity of the GUSTO-I and TIMI risk models. Clinical variables, treatment and mortality data from 433 consecutive patients were collected. Univariable and multivariable logistic regression analyses were applied to identify baseline factors associated with 30-day mortality. Subsequently a model predicting 30-day mortality was created and compared with the performance of the GUSTO-I and TIMI models. After adjustment, a higher Killip class was the most important predictor (OR 16.1; 95% CI 5.7-45.6). Elevated heart rate, longer time delay to admission, hyperglycemia and older age were also associated with increased risk. Patients with hypercholesterolemia had a significantly lower risk (OR 0.46; 95% CI 0.24-0.86). Discrimination (c-statistic 0.79, 95% CI 0.75-0.84) and calibration (Hosmer-Lemeshow 6, p = 0.5) of our model were good. The GUSTO-I and TIMI risk scores produced adequate discrimination within our dataset (c-statistic 0.76, 95% CI 0.71-0.81, and c-statistic 0.77, 95% CI 0.72-0.82, respectively), but calibration was not satisfactory (HL 21.8, p = 0.005 for GUSTO-I, and HL 20.6, p = 0.008 for TIMI). In conclusion, short-term mortality in elderly patients with a first STEMI depends most importantly on initial clinical and hemodynamic status. The GUSTO-I and TIMI models are insufficiently adequate for providing an exact estimate of 30-day mortality risk.

Effects of fibrosis morphology on reentrant ventricular tachycardia inducibility and simulation fidelity in patient-derived models

Myocardial fibrosis detected via delayed-enhanced magnetic resonance imaging (MRI) has been shown to be a strong indicator for ventricular tachycardia (VT) inducibility. However, little is known regarding how inducibility is affected by the details of the fibrosis extent, morphology, and border zone configuration. The objective of this article is to systematically study the arrhythmogenic effects of fibrosis geometry and extent, specifically on VT inducibility and maintenance. We present a set of methods for constructing patient-specific computational models of human ventricles using in vivo MRI data for patients suffering from hypertension, hypercholesterolemia, and chronic myocardial infarction. Additional synthesized models with morphologically varied extents of fibrosis and gray zone (GZ) distribution were derived to study the alterations in the arrhythmia induction and reentry patterns. Detailed electrophysiological simulations demonstrated that (1) VT morphology was highly dependent on the extent of fibrosis, which acts as a structural substrate, (2) reentry tended to be anchored to the fibrosis edges and showed transmural conduction of activations through narrow channels formed within fibrosis, and (3) increasing the extent of GZ within fibrosis tended to destabilize the structural reentry sites and aggravate the VT as compared to fibrotic regions of the same size and shape but with lower or no GZ. The approach and findings represent a significant step toward patient-specific cardiac modeling as a reliable tool for VT prediction and management of the patient. Sensitivities to approximation nuances in the modeling of structural pathology by image-based reconstruction techniques are also implicated.