Abstract
Abnormalities of oculometric measures (OM) are widely described in people with Parkinson's disease (PD). However, knowledge of correlations between abnormal OM, disease severity and clinical assessment in PD patients is still lacking. To evaluate these correlations, PD patients (215 patients, mean age 69 ± 9.1 years, 79 females) with severe (H&Y > 3) and mild to moderate (H&Y ≤ 2) disease, and 215 age-matched healthy subjects were enrolled. All patients were evaluated using MDS-UPDRS and an oculometric test using computer vision and deep learning algorithms. Comparisons of OM between groups and correlations between OM and MDS-UPDRS scores were calculated. Saccadic latency (ms) was prolonged in patients with severe compared with mild to moderate disease (pro-saccades: 267 ± 69 vs. 238 ± 53, p = 0.0011; anti-saccades: 386 ± 119 vs. 352 ± 106, p = 0.0393) and in patients with mild to moderate disease versus healthy subjects (pro-saccades: 238 ± 53 vs. 220 ± 45, p = 0.0003; anti-saccades: 352 ± 106 vs. 289 ± 71, p < 0.0001). Error rate (%) was higher among patients with severe (64.06 ± 23.08) versus mild to moderate disease (49.84 ± 24.81, p = 0.0001), and versus healthy subjects (49.84 ± 24.81 vs. 28.31 ± 21.72, p = 0.00001). Response accuracy (%) was lower for patients with severe (75.66 ± 13.11) versus mild to moderate disease (79.66 ± 13.56, p = 0.0462), and versus healthy subjects (79.66 ± 13.56 vs. 90.27 ± 8.79, p < 0.0001). Pro- and anti-saccadic latency, error rate and accuracy were correlated with MDS-UPDRS scores (r = 0.32, 0.28, 0.36 and -0.30, respectively, p < 0.0001) and similar correlations were found with its axial subscore (R = 0.38, 0.29, 0.44, and -0.30, respectively, p < 0.0001). Several OM were different in patients under levodopa treatment. OM worsened as PD severity increases, and were correlated with MDS-UPDRS scores. Using OM can be implemented for PD patients' assessment as a tool to follow disease progression.