Effect of Left Atrial Wall Thickness on Radiofrequency Ablation Success.

INTRODUCTION: Radiofrequency (RF) ablation in thicker regions of the left atrium (LA) may require increased ablation energy in order to achieve effective transmural lesions. Consequently, many cases of recurrent atrial fibrillation (AF) postablation may be due to thicker-than-normal atrial tissue. The aim of this study was to test the hypotheses that patients with recurrent AF have thicker tissue overall and that electrical reconnection is more likely in regions of thicker tissue. METHODS AND RESULTS: Retrospective analysis was performed on 86 CT images acquired preoperatively from a cohort of 119 patients who had undergone RF ablation for AF. Of these, 33 patients experienced recurrence of AF within 1 year of initial treatment and 29 returned for a repeat ablation. For each patient, LA wall thickness (LAWT) was measured from the images in 12 anatomical regions using custom software. Patients with recurrent AF had larger LAWT compared to successfully treated patients (1.6 ± 0.6 mm vs. 1.5 ± 0.5 mm, P \u3c 0.001) and reconnection was found to be at regions of thicker tissue (1.6 ± 0.6 mm, P = 0.038) compared to nonreconnected regions (1.5 ± 0.5 mm). The superior right posterior wall of the LA was significantly related to both recurrence (P = 0.048) and reconnection (P = 0.014). CONCLUSION: Increased LAWT has a small but significant effect on postablation recurrence and reconnection. Measures of LAWT may facilitate appropriate dosing of RF energy, but other factors will be critical in transmural lesion formation and ablation success

How to diagnose the cause of sudden cardiac arrest

Sudden cardiac death or sudden cardiac arrest (SCA) is defined as natural death that occurs within an hour of the onset of acute symptoms or during sleep due to a primary cardiac cause. Most cases of SCA are attributable to coronary artery disease, with occult cardiomyopathy or inheritable arrhythmic syndromes accounting for a minority of SCA. Diagnosing the cause of SCA has potential implications for the patient and the family, and demands a comprehensive approach. This review summarizes the potential causes of SCA and outlines a systematic diagnostic approach to the SCA survivor. (Cardiol J 2011; 18, 2: 210-216

In Search of Black Swans: Identifying Students at Risk of Failing Licensing Examinations.

PURPOSE: To determine which admissions variables and curricular outcomes are predictive of being at risk of failing the Medical Council of Canada Qualifying Examination Part 1 (MCCQE1), how quickly student risk of failure can be predicted, and to what extent predictive modeling is possible and accurate in estimating future student risk. METHOD: Data from five graduating cohorts (2011-2015), Schulich School of Medicine & Dentistry, Western University, were collected and analyzed using hierarchical generalized linear models (HGLMs). Area under the receiver operating characteristic curve (AUC) was used to evaluate the accuracy of predictive models and determine whether they could be used to predict future risk, using the 2016 graduating cohort. Four predictive models were developed to predict student risk of failure at admissions, year 1, year 2, and pre-MCCQE1. RESULTS: The HGLM analyses identified gender, MCAT verbal reasoning score, two preclerkship course mean grades, and the year 4 summative objective structured clinical examination score as significant predictors of student risk. The predictive accuracy of the models varied. The pre-MCCQE1 model was the most accurate at predicting a student\u27s risk of failing (AUC 0.66-0.93), while the admissions model was not predictive (AUC 0.25-0.47). CONCLUSIONS: Key variables predictive of students at risk were found. The predictive models developed suggest, while it is not possible to identify student risk at admission, we can begin to identify and monitor students within the first year. Using such models, programs may be able to identify and monitor students at risk quantitatively and develop tailored intervention strategies