Dataset Information

Value of Clinical Signs in Identifying Patients with Scans without Evidence of Dopaminergic Deficit (SWEDD).

ABSTRACT:

Background

In clinical trials that recruited patients with early Parkinson's disease (PD), 4-15% of the participants with a clinical diagnosis of PD had normal dopamine transporter single photon emission computed tomography (DAT SPECT) scans, also called "scans without evidence of dopaminergic deficit" (SWEDD).

Objective

To investigate in patients with a clinical diagnosis of PD, if specific clinical features are useful to distinguish patients with nigrostriatal degeneration from those that have no nigrostriatal degeneration.

Methods

We performed a diagnostic test accuracy study. Patients that participated in the Levodopa in Early Parkinson's disease trial, a clinical trial in patients with early PD, were asked to participate if they had not undergone DAT SPECT imaging earlier. The index tests were specific clinical features that were videotaped. A panel of six neurologists in training (NT), six general neurologists (GN), and six movement disorders experts (MDE) received a batch of ten videos consisting of all SWEDD subjects and a random sample of patients with abnormal DAT SPECT scans. The raters analyzed the videos for presence of specific signs and if they suspected the patient to have SWEDD. The reference test was visually assessed DAT SPECT imaging.

Results

Of a total of 87 participants, three subjects were SWEDDs (3.4%). The overall intraclass correlation coefficient (ICC) of the Parkinsonian signs was poor to moderate with ICCs ranging from 0.14 to 0.67. NT correctly identified 50.0% of the SWEDD subjects, GN 33.3%, and MDE 66.7%.

Conclusion

Our study suggests that the selected videotaped clinical features cannot reliably distinguish patients with a clinical diagnosis of PD and an abnormal DAT SPECT from patients with clinical PD and a SWEDD.

SUBMITTER: Suwijn SR

PROVIDER: S-EPMC7683040 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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Publications

Value of Clinical Signs in Identifying Patients with Scans without Evidence of Dopaminergic Deficit (SWEDD).

Suwijn Sven R SR Samim Hamdia H Eggers Carsten C Espay Alberto J AJ Fox Susan S Lang Anthony E AE Samuel Mike M Silverdale Monty M Verschuur Constant V M CVM Dijk Joke M JM Verberne Hein J HJ Booij Jan J de Bie Rob M A RMA

Journal of Parkinson's disease 20200101 4

<h4>Background</h4>In clinical trials that recruited patients with early Parkinson's disease (PD), 4-15% of the participants with a clinical diagnosis of PD had normal dopamine transporter single photon emission computed tomography (DAT SPECT) scans, also called "scans without evidence of dopaminergic deficit" (SWEDD).<h4>Objective</h4>To investigate in patients with a clinical diagnosis of PD, if specific clinical features are useful to distinguish patients with nigrostriatal degeneration from ...[more]

PMID: 32597819

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Project description:BackgroundA small proportion of patients with clinical parkinsonism have normal transporter-single photon emission computed tomography (DaTSPECT) which is commonly defined as scans without evidence of dopaminergic deficits (SWEDD). A better understanding of SWEDD can improve the current therapeutic options and appropriate disease monitoring.AimWe aimed to assess CSF biomarkers levels including α-synuclein (α-syn), amyloid βeta (Aβ1-42), total tau (t-tau), and phosphorylated tau (p-tau) in SWEDD and investigate the longitudinal alteration in the CSF profile.MethodsIn total, 406 early-stage PD, 58 SWEDD, and 187 healthy controls (HCs) were entered into our study from PPMI. We compared the level of CSF biomarkers at baseline, six months, one year, and two years. Furthermore, the longitudinal alteration of CSF biomarkers was explored in each group using linear mixed models.ResultsThere was no significant difference in the level of CSF α-syn Aβ1-42, t-tau, and p-tau between HCs and SWEDD at different time points. Investigating the level of CSF α-syn in PD and SWEDD showed a significant difference at one (p = 0.016) and two years (p = 0.006). Also, we observed a significant difference in the level of CSF Aβ1-42 between SWEDD and PD at one year (p = 0.012). Moreover, there was a significant difference in the level of CSF t-tau between SWEDD and PD subjects at one (p = 0.013) and two years (p = 0.017). Furthermore, there was a significant difference in the level of CSF p-tau between SWEDD and PD groups at two years visits (p = 0.030). Longitudinal analysis showed a significant decrease after one (p = 0.029) and two years (p = 0.002) from baseline in the level of CSF α-syn only in the PD group. Also, we observed that the level of CSF Aβ1-42 significantly increased after one year in SWEDD (p = 0.031) and decreased after two years from baseline in PD subjects (p = 0.005). Moreover, there was a significant increase in the level of CSF t-tau after two years (p = 0.036) and CSF p-tau after six months from baseline in SWEDD subjects (p = 0.011).ConclusionThis finding suggests a faster neurodegeneration process in PD patients compared to SWEDD at least based on these biomarkers. Future studies with longer follow-up duration and more sample sizes are necessary to validate our results.

Project description:Background: Early stage (preclinical) detection of Parkinson's disease (PD) remains challenged yet is crucial to both differentiate it from other disorders and facilitate timely administration of neuroprotective treatment as it becomes available. Objective: In a cross-validation paradigm, this work focused on two binary predictive probability analyses: classification of early PD vs. controls and classification of early PD vs. SWEDD (scans without evidence of dopamine deficit). It was hypothesized that five distinct model types using combined non-motor and biomarker features would distinguish early PD from controls with > 80% cross-validated (CV) accuracy, but that the diverse nature of the SWEDD category would reduce early PD vs. SWEDD CV classification accuracy and alter model-based feature selection. Methods: Cross-sectional, baseline data was acquired from the Parkinson's Progressive Markers Initiative (PPMI). Logistic regression, general additive (GAM), decision tree, random forest and XGBoost models were fitted using non-motor clinical and biomarker features. Randomized train and test data partitions were created. Model classification CV performance was compared using the area under the curve (AUC), sensitivity, specificity and the Kappa statistic. Results: All five models achieved >0.80 AUC CV accuracy to distinguish early PD from controls. The GAM (CV AUC 0.928, sensitivity 0.898, specificity 0.897) and XGBoost (CV AUC 0.923, sensitivity 0.875, specificity 0.897) models were the top classifiers. Performance across all models was consistently lower in the early PD/SWEDD analyses, where the highest performing models were XGBoost (CV AUC 0.863, sensitivity 0.905, specificity 0.748) and random forest (CV AUC 0.822, sensitivity 0.809, specificity 0.721). XGBoost detection of non-PD SWEDD matched 1-2 years curated diagnoses in 81.25% (13/16) cases. In both early PD/control and early PD/SWEDD analyses, and across all models, hyposmia was the single most important feature to classification; rapid eye movement behavior disorder (questionnaire) was the next most commonly high ranked feature. Alpha-synuclein was a feature of import to early PD/control but not early PD/SWEDD classification and the Epworth Sleepiness scale was antithetically important to the latter but not former. Interpretation: Non-motor clinical and biomarker variables enable high CV discrimination of early PD vs. controls but are less effective discriminating early PD from SWEDD.

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Project description:We contrasted the neuroanatomical substrates of sub-acute and chronic visuospatial deficits associated with different aspects of unilateral neglect using computed tomography scans acquired as part of routine clinical diagnosis. Voxel-wise statistical analyses were conducted on a group of 160 stroke patients scanned at a sub-acute stage. Lesion-deficit relationships were assessed across the whole brain, separately for grey and white matter. We assessed lesions that were associated with behavioural performance (i) at a sub-acute stage (within 3 months of the stroke) and (ii) at a chronic stage (after 9 months post stroke). Allocentric and egocentric neglect symptoms at the sub-acute stage were associated with lesions to dissociated regions within the frontal lobe, amongst other regions. However the frontal lesions were not associated with neglect at the chronic stage. On the other hand, lesions in the angular gyrus were associated with persistent allocentric neglect. In contrast, lesions within the superior temporal gyrus extending into the supramarginal gyrus, as well as lesions within the basal ganglia and insula, were associated with persistent egocentric neglect. Damage within the temporo-parietal junction was associated with both types of neglect at the sub-acute stage and 9 months later. Furthermore, white matter disconnections resulting from damage along the superior longitudinal fasciculus were associated with both types of neglect and critically related to both sub-acute and chronic deficits. Finally, there was a significant difference in the lesion volume between patients who recovered from neglect and patients with chronic deficits. The findings presented provide evidence that (i) the lesion location and lesion size can be used to successfully predict the outcome of neglect based on clinical CT scans, (ii) lesion location alone can serve as a critical predictor for persistent neglect symptoms, (iii) wide spread lesions are associated with neglect symptoms at the sub-acute stage but only some of these are critical for predicting whether neglect will become a chronic disorder and (iv) the severity of behavioural symptoms can be a useful predictor of recovery in the absence of neuroimaging findings on clinical scans. We discuss the implications for understanding the symptoms of the neglect syndrome, the recovery of function and the use of clinical scans to predict outcome.

Dataset Information

Value of Clinical Signs in Identifying Patients with Scans without Evidence of Dopaminergic Deficit (SWEDD).

Background

Objective

Methods

Results

Conclusion

Publications

Value of Clinical Signs in Identifying Patients with Scans without Evidence of Dopaminergic Deficit (SWEDD).

Similar Datasets

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