Discriminative power of different nonmotor signs in early Parkinson's disease. A case-control study

Abstract

The objective of this study was to evaluate the discriminative power of different nonmotor signs for early diagnosis of Parkinson's disease (PD). Thirty patients with PD with <or=3 years of disease duration were compared with 30 healthy controls. Six deficit domains (DD) were defined: hyposmia, sleep abnormalities, dysautonomia, visual deficits, executive dysfunction, and depression. Plotting of Receiver operating characteristic (ROC) curves and exact conditional logistic modeling, followed by manual stepwise descending procedure were used to identify a model for nonmotor signs that detects early PD. Patients with PD and controls did not differ in terms of age, gender, and educational level. Several DD discriminated patients with PD from healthy controls. Visual deficits showed the largest area under the ROC curve (0.83), followed by hyposmia (0.81) and dysautonomia (0.80). When combining the DD visual deficits and dysautonomia, the best residual model was obtained; it maximized both sensitivity and specificity for PD at a level of 0.77. At an early disease stage, several nonmotor domains were already able to discriminate patients with PD from healthy controls. Visual deficits had the best discriminatory power. Being brief and inexpensive, visual tests should be further investigated in larger cohorts as potential screening tool for early PD.

Visual Contrast Sensitivity in Early-Stage Parkinson's Disease

“…44 Many parts of the visual system have been implicated as the cause for visual deficits, such as the retina, where thinning of the inner retinal nerve fiber layer and decreased dopamine concentration seem to mirror the loss of dopaminergic neurons in the basal ganglia. 2,45,46 Pattern electroretinogram studies in PD subjects have shown significant loss at midspatial frequencies of 4 cyc/deg, corroborating our findings. 47 With the addition of motion, both PD and control subjects improved their contrast sensitivity at low spatial frequencies.…”

“…It is critical for many daily activities 1 and is impaired in patients with neurodegenerative diseases such as Parkinson's disease. [2][3][4][5] Conventionally, contrast sensitivity has been measured in the laboratory as a function of an object's richness in texture, its spatial frequency. We define spatial contrast sensitivity as the ability to distinguish static stimuli, and spatiotemporal contrast sensitivity as the ability to detect moving stimuli while tracking them with smooth pursuit eye movements.…”

Non-motor features of Parkinson’s disease in a nested case–control study of US men

“…Colour vision has been reported to be significantly impaired in patients with PD compared with controls,26 including among patients with early PD (≤3years since onset)27 and patients with de novo PD 28. Retinal dopamine levels have been found to be reduced in patients with PD 29.…”

Approaches to the Diagnosis of Parkinson’s Disease during the Pre-motor Phase

“…In a recent study, non-motor signs across six different domains were explored in patients with early motor PD. 39 Tests addressed visual deficits tested by color discrimination, contrast sensitivity, and spatial discrimination; olfactory function; sleep abnormalities by Parkinson's Disease Sleep Scale rating and documentation of loss of muscle atonia during REM sleep on polysomnography; dysautonomia as reported on two self-completed questionnaires; executive dysfunction; and depression.…”

“…Across all domains, patients with PD performed worse than the control group, with statistically significant differences in visual deficits, sleep abnormalities, hyposmia, dysautonomia, and depression; the most marked distinction between the test and control groups emerged in visual deficits, hyposmia, and dysautonomia. 39 By combining the results of the Farnsworth-Munsell color discrimination test and the non-motor symptom questionnaire (NMSQuest), the sensitivity and specificity for detection of PD peaked at 0.77, suggesting a relatively simple model for predicting PD.…”