A new algorithm is able to identify stroke patients who are most likely to experience atrial fibrillation (AF) and are thus at higher risk of a second stroke.
While it is recommended that patients undergo 30 days of heart rhythm monitoring to detect AF within six months of an initial stroke, the reality is that many patients are not monitored once they are discharged from the hospital setting.
To try to address this, the authors of a new study set out to identify the patients who were most likely to develop AF, by examining data from almost 10,000 patients with post-cryptogenic stroke (CS) or transient ischemic attack (TIA) patients included.
Age (≥75 years), obesity, congestive heart failure, hypertension, coronary artery disease, peripheral vascular disease, and valve disease, were all significant risk factors for the development of AF. The authors combined these variables to develop the HAVOC score, which demonstrated an area under the curve of 0.77 for predicting AF.
Writing in Cardiology , the authors said the scoring system successfully stratified patients into three risk groups, with good model discrimination and may be used to select patients for extended rhythm monitoring.