Automated external defibrillators (AEDs) and implantable cardioverter defibrillators (ICDs) are used to treat life-threatening arrhythmias. AEDs and ICDs use shock advice algorithms to classify ECG tracings as shockable or non-shockable rhythms in clinical practice. Machine learning algorithms have recently been assessed for shock decision classification with increasing accuracy. Outside of rhythm classification alone, they have been evaluated in diagnosis of causes of cardiac arrest, prediction of success of defibrillation and rhythm classification without the need to interrupt cardiopulmonary resuscitation. This review explores the many applications of machine learning in AEDs and ICDs. While these technologies are exciting areas of research, there remain limitations to their widespread use including high processing power, cost and the ‘black-box’ phenomenon.
Objective: To assess cardiovascular (CV) safety of erenumab in clinical trial patients associated with degree of CV risk.Background: Hypertension has been considered a theoretical risk associated with the inhibition of the calcitonin gene-related peptide pathway in migraine management, particularly in a patient population with pre-existing CV risk factors.Methods: Data pooled from four double-blind, randomized trials were used to assess blood pressure (BP) changes and CV safety in patients grouped based on 10-year risk of cardiac, cerebrovascular, and peripheral artery disease as no-risk-factors, low-risk (>0% to ≤10%), moderate-risk (>10% to ≤20%), and high-risk (>20%) categories. CV safety was assessed as ischemic cardiovascular and cerebrovascular adverse events (ICCAE).
Results: There was no apparent difference between placebo-(N = 1032) and erenumabtreatment groups (70 mg, N = 885; 140 mg, N = 504) in clinical worsening of BP category from baseline to Months 1-3 (14% [143/1032] placebo vs. 13% [114/885] and 14% [71/504] for erenumab 70 and 140 mg, respectively) regardless of baseline BP category. The adverse event (AE) profile of erenumab was similar across CV risk categories throughout the long-term analysis. Erenumab-treated patients with high and moderate 10-year CV risk (N = 107) did not experience any ICCAEs during the double-blind treatment period; there was a single ICCAE (a cerebral dural venous sinus thrombosis) observed in the low-risk erenumab group (N = 273). There were no increases in AEs during the long-term extensions of up to 5 years (N = 2499; 3482 patient-years of exposure to erenumab) with exposure-adjusted incidence rates of cardio/cerebrovascular disorder AEs of 0.4, 0.5, 0.0, and 1.1 (per 100 patient-years) for no risk factor (N = 1805), low (N = 492), moderate (N = 121), and high (N = 81) 10-year CV risk groups, respectively.
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