Identifying glaucoma patients by applying multivariate analyses of cardiovascular signals.

Glaucoma is a disease that damages the eye's optic nerve. However, the exact cause of this optic nerve damage is not yet fully understood. Besides the factors of age, genetics and others, such as obesity, medication and migraines, a vascular dysfunction is believed to be a significant factor leading to glaucoma. This study's objective was to investigate whether these vascular dysfunctions could be recognized by analyzing cardiovascular regulation in glaucoma patients. Linear and nonlinear methods were applied to the extracted heart rate (HR), and systolic/ diastolic blood pressure (DBP) time series to discriminate between 35 healthy controls and 20 glaucoma patients. The combination of indices from 30-min analysis of time domain (Renyi entropy of systolic blood pressure) and nonlinear dynamics (segmented Poincare plot analysis of DBP, high-resolution joint symbolic dynamics of DBP/ HR) were able to differentiate between controls and patients with a specificity and sensitivity of > 95%. Since changes in short-term blood pressure regulation patterns and heart-rate coupling are clear signs of a vascular dysfunction, this approach could be useful for providing an earlier diagnosis of glaucoma in clinical practice.