Probabilistic classification of acute myocardial infarction from multiple cardiac markers

Logistic regression and Gaussian mixture model (GMM) classifiers have been trained to estimate the probability of acute myocardial infarction (AMI) in patients based upon the concentrations of a panel of cardiac markers. The panel consists of two new markers, fatty acid binding protein (FABP) and glycogen phosphorylase BB (GPBB), in addition to the traditional cardiac troponin I (cTnI), creatine kinase MB (CKMB) and myoglobin. The effect of using principal component analysis (PCA) and Fisher discriminant analysis (FDA) to preprocess the marker concentrations was also investigated. The need for classifiers to give an accurate estimate of the probability of AMI is argued and three categories of performance measure are described, namely discriminatory ability, sharpness, and reliability. Numerical performance measures for each category are given and applied. The optimum classifier, based solely upon the samples take on admission, was the logistic regression classifier using FDA preprocessing. This gave an accuracy of 0.85 (95% confidence interval: 0.78-0.91) and a normalised Brier score of 0.89. When samples at both admission and a further time, 1-6 h later, were included, the performance increased significantly, showing that logistic regression classifiers can indeed use the information from the five cardiac markers to accurately and reliably estimate the probability AMI. © Springer-Verlag London Limited 2008.

The Impact of Engagement Processes on the First Appointment Attendance Rate at a Regional Outpatient Psychological Trauma Service.

The effectiveness of simple measures to increase attendance at first appointments is briefly reviewed. The Family Trauma Centre’s remit and pre-study engagement process are described. The perceived idiosyncratic aspects of inviting people suffering from psychological trauma to attend a clinical service are noted as contributory factors in initially tolerating a high first appointment DNA rate. Three new initial engagement processes are then described and results of their application to 30 referrals in total are presented. The overwhelming finding is that paying close attention to any of the three initial engagement processes significantly increases first appointment attendance. Based on these findings the Centre developed a new initial engagement protocol.. The principle that services should pay more attention to their engagement processes than on the characteristics of their client groups when seeking to reduce first appointment DNA rates is supported.