A computerized algorithm for arousal detection in healthy adults and patients with Parkinson disease.

J Clin Neurophysiol. 2012 Feb;29(1):58-64.

Sorensen GL, Jennum P, Kempfner J, Zoetmulder M, Sorensen HB.

Abstract

SUMMARY: Arousals occur from all sleep stages and can be identified as abrupt electroencephalogram (EEG) and electromyogram (EMG) changes. Manual scoring of arousals is time consuming with low interscore agreement. The aim of this study was to design an arousal detection algorithm capable of detecting arousals from non-rapid eye movement (REM) and REM sleep, independent of the subject's age and disease. The proposed algorithm uses features from EEG, EMG, and the manual sleep stage scoring as input to a feed-forward artificial neural network (ANN). The performance of the algorithm has been assessed using polysomnographic (PSG) recordings from a total of 24 subjects. Eight of the subjects were diagnosed with Parkinson disease (PD) and the rest (16) were healthy adults in various ages. The performance of the algorithm was validated in 3 settings: testing on the 8 patients with PD using the leave-one-out method, testing on the 16 healthy adults using the leave-one-out method, and finally testing on all 24 subjects using a 4-fold crossvalidation. For these 3 validations, the sensitivities were 89.8%, 90.3%, and 89.4%, and the positive predictive values (PPVs) were 88.8%, 89.4%, and 86.1%. These results are high compared with those of previously presented arousal detection algorithms and especially compared with the high interscore variability of manual scorings.

Rapid eye movement sleep behavior disorder and risk of dementia in Parkinson's disease: A prospective study.

Mov Disord. 2012 Feb 9. doi: 10.1002/mds.24939. [Epub ahead of print]

Postuma RB, Bertrand JA, Montplaisir J, Desjardins C, Vendette M, Rios Romenets S, Panisset M, Gagnon JF.

Source

Department of Neurology, McGill University, Montreal General Hospital, Montreal, Québec, Canada; Centre d'Études Avancées en Médecine du Sommeil, Hôpital du Sacré-Coeur de Montréal, Montréal, Québec, Canada.

Abstract

One of the most devastating nonmotor manifestations of PD is dementia. There are few established predictors of dementia in PD. In numerous cross-sectional studies, patients with rapid eye movement (REM) sleep behavior disorder (RBD) have increased cognitive impairment on neuropsychological testing, but no prospective studies have assessed whether RBD can predict Parkinson's dementia. PD patients who were free of dementia were enrolled in a prospective follow-up of a previously published cross-sectional study. All patients had a polysomnogram at baseline. Over a mean 4-year follow-up, the incidence of dementia was assessed in those with or without RBD at baseline using regression analysis, adjusting for age, sex, disease duration, and follow-up duration. Of 61 eligible patients, 45 (74%) were assessed and 42 were included in a full analysis. Twenty-seven patients had baseline RBD, and 15 did not. Four years after the initial evaluation, 48% with RBD developed dementia, compared to 0% of those without (P-adjusted = 0.014). All 13 patients who developed dementia had mild cognitive impairment on baseline examination. Baseline REM sleep atonia loss predicted development of dementia (% tonic REM = 73.2 ± 26.7 with dementia, 40.8 ± 34.5 without; P = 0.029). RBD at baseline also predicted the new development of hallucinations and cognitive fluctuations. In this prospective study, RBD was associated with increased risk of dementia. This indicates that RBD may be a marker of a relatively diffuse, complex subtype of PD. 

(123)I-MIBG myocardial scintigraphy for differentiating Parkinson's disease from other neurodegenerative parkinsonism: A systematic review and meta-analysis.

Parkinsonism Relat Disord. 2012 Feb 7. [Epub ahead of print]

Orimo S, Suzuki M, Inaba A, Mizusawa H.

Source

Department of Neurology, Kanto Central Hospital, 6-25-1 Kami-Yoga, Setagaya-ku 158-8531, Tokyo, Japan.

Abstract

OBJECTIVES:

Differential diagnosis of Parkinson's disease (PD) and other neurodegenerative parkinsonism by clinical consensus criteria and diagnostic imaging is often difficult. (123)I-meta-iodobenzylguanidine ((123)I-MIBG) myocardial scintigraphy is a useful imaging tool for differentiating PD from other parkinsonism. The purpose of the present study is to systematically review and perform a meta-analysis of studies on the diagnostic performance of (123)I-MIBG myocardial scintigraphy for the differential diagnosis of PD and other neurodegenerative parkinsonism, specifically multiple system atrophy, progressive supranuclear palsy, and corticobasal degeneration.

METHODS:

A computer literature search of the PubMED/MEDLINE database was conducted to find relevant published articles on (123)I-MIBG myocardial scintigraphy for the differential diagnosis of PD and other neurodegenerative parkinsonism. We used the bivariate random-effects model to obtain the pooled estimates of the sensitivity and specificity and the corresponding 95% confidence intervals.

RESULTS:

Thirteen studies comprising 845 patients including 625 PD and 220 other neurodegenerative parkinsonism were analyzed. The pooled sensitivity and specificity to differentiate PD from other neurodegenerative parkinsonism by the early heart-to-mediastinum (H/M) ratio were 82.6% and 89.2%, respectively, and those by the delayed H/M ratio were 89.7% and 82.6%, respectively. When PD was limited to early stage (Hoehn-Yahr stage 1 or 2), the pooled sensitivity and specificity by the delayed H/M ratio were 94.1% and 80.2%, respectively.

CONCLUSIONS:

The present meta-analysis confirmed high sensitivity and specificity of (123)I-MIBG myocardial scintigraphy for differentiating PD from other neurodegenerative parkinsonism in both early and delayed imaging phases. Furthermore, (123)I-MIBG myocardial scintigraphy was highly effective for distinguishing early PD.

Role of DaTSCAN and clinical diagnosis in Parkinson disease.

Neurology. 2012 Feb 8. [Epub ahead of print]

de la Fuente-Fernández R.

Abstract

OBJECTIVE:

To assess the role of DaTSCAN in the diagnosis of Parkinson disease (PD).

METHODS:

Using the sensitivity and specificity values obtained in the 2 studies that recently led the US Food and Drug Administration to approve the use of DaTSCAN for the diagnosis of PD, calculations were carried out to estimate the accuracy of the clinical diagnosis taking DaTSCAN findings as the standard of truth.

RESULTS:

In early PD, a clinical diagnosis of "possible" or "probable" PD has a sensitivity of 98% and a specificity of 67%. The specificity increases to 94% once the clinical diagnosis becomes established. The overall accuracy of the clinical diagnosis is 84% in early PD and 98% at later stages. The clinical diagnostic accuracy is mathematically identical to the diagnostic accuracy of DaTSCAN imaging.

CONCLUSIONS:

In the absence of neuropathologic validation, the overall accuracy of a clinical diagnosis of PD is very high and mathematically identical to the accuracy of DaTSCAN imaging, which calls into question the use of radiotracer neuroimaging as a diagnostic tool in clinical practice.