Machine learning-based detection of sleep-disordered breathing in hypertrophic cardiomyopathy.

BACKGROUND: Hypertrophic cardiomyopathy (HCM) is often concomitant with sleep-disordered breathing (SDB), which can cause adverse cardiovascular events. Although an appropriate approach to SDB prevents cardiac remodelling, detection of concomitant SDB in patients with HCM remains suboptimal. Thus, we aimed to develop a machine learning-based discriminant model for SDB in HCM. METHODS: In the present multicentre study, we consecutively registered patients with HCM and performed nocturnal oximetry. The outcome was a high Oxygen Desaturation Index (ODI), defined as 3% ODI >10, which significantly correlated with the presence of moderate or severe SDB. We randomly divided the whole participants into a training set (80%) and a test set (20%). With data from the training set, we developed a random forest discriminant model for high ODI based on clinical parameters. We tested the ability of the discriminant model on the test set and compared it with a previous logistic regression model for distinguishing SDB in patients with HCM. RESULTS: Among 369 patients with HCM, 228 (61.8%) had high ODI. In the test set, the area under the receiver operating characteristic curve of the discriminant model was 0.86 (95% CI 0.77 to 0.94). The sensitivity was 0.91 (95% CI 0.79 to 0.98) and specificity was 0.68 (95% CI 0.48 to 0.84). When the test set was divided into low-probability and high-probability groups, the high-probability group had a higher prevalence of high ODI than the low-probability group (82.4% vs 17.4%, OR 20.9 (95% CI 5.3 to 105.8), Fisher's exact test p<0.001). The discriminant model significantly outperformed the previous logistic regression model (DeLong test p=0.03). CONCLUSIONS: Our study serves as the first to develop a machine learning-based discriminant model for the concomitance of SDB in patients with HCM. The discriminant model may facilitate cost-effective screening tests and treatments for SDB in the population with HCM.

Surgical repair of a pseudoaneurysm derived from a nine-year-old saphenous vein graft after coronary artery bypass.

A 57-year-old male presented intermittent pain between the left shoulder and neck. He had undergone coronary artery bypass twice and all grafts had been confirmed to be angiographically intact at three and a half years prior. Coronary angiography revealed that a pseudoaneurysm derived from around the proximal ascending aortic anastomosis of the saphenous vein graft that connected to the left anterior descending branch and #4-atrioventricular branch sequentially. The pseudoaneurysm compressed the saphenous vein graft itself. He underwent repair of the pseudoaneurysm through median sternotomy after left subclavian artery-saphenous vein graft bypass utilizing a free left radial artery without cardiopulmonary bypass through left anterolateral thoracotomy. A 7 mm length longitudinal tear in the saphenous vein graft near the proximal anastomosis had caused the pseudoaneurysm. This tear had likely been caused by perforation by a catheter during coronary arteriography three and a half years ago.