The greatest loss of unpleasant smells may be related to the risk of more severe PD symptoms.

Background: Limited research has explored the relationship between the valence of olfactory dysfunction and PD clinical symptoms. This study aimed to investigate correlations between the emotional valence of olfactory impairment and different domains of PD symptoms. Methods: PD patients who fulfilled the clinically probable PD diagnostic criteria of the International Parkinson and Movement Disorder Society Clinical Diagnostic Criteria for Parkinson's Disease were recruited from the Center for Parkinson and Movement Disorders at Taichung Veterans General Hospital between October 2016 and April 2022. Demographic data and serial clinical assessments were collected, including the traditional Chinese version of the University of Pennsylvania Smell Identification Test (UPSIT-TC) and Movement Disorder Society-sponsored revision of the Unified Parkinson's Disease Rating Scale (MDS-UPDRS). Thirty-five odors from the UPSIT-TC were classified into neutral, pleasant or unpleasant groups. Group comparisons, correlation analyses, and linear regression analyses were conducted to examine the relationship between olfactory impairment of UPSIT-TC odors, considering emotional valence, and MDS-UPDRS subscores across various domains. Results: A total of 176 PD patients were recruited for analysis. Patients in the predominantly neutral/unpleasant odor impairment groups had higher MDS-UPDRS part III scores compared to those in the predominantly pleasant odor impairment group (pleasant vs. neutral vs. unpleasant odor impairment groups: 26.79 ± 13.59 vs. 35.33 ± 16.36 vs. 31.57 ± 12.37, p = 0.009). This trend was also noted in MDS-UPDRS rigidity, bradykinesia, and akinetic-rigid subscores (p = 0.003, p = 0.012, and p = 0.001, respectively). Correlation analysis revealed a weak but significant correlation between rigidity/akinetic-rigid subscores and misidentification numbers for neutral/unpleasant odors (all p < 0.05), with age, gender, LEDD, and disease duration as covariates. All significances were retained in the linear regression analysis. Conclusion: Our results emphasize the link between olfactory impairment of specific emotional valence, neutral/unpleasant odors, and PD severity, particularly with respect to akinetic-rigid symptoms. A concise olfactory test that focuses on both neutral and unpleasant odors may offer deeper insights into PD symptoms.

Exploring obstructive sleep apnea and sleep architecture in Parkinson's disease motor subtypes.

INTRODUCTION: Parkinson's disease (PD) can be divided into motor subtypes: postural instability/gait difficulty (PIGD), tremor dominant, and indeterminate. This study aimed to assess differences in sleep structure and obstructive sleep apnea (OSA) between the PIGD and non-PIGD subtypes. METHODS: PD participants with or without OSA (defined as apnea-hypopnea index (AHI) ≥ 15 events/hour on overnight polysomnography) were included. Patients were separated into two groups: PIGD and non-PIGD. Linear regression was used to explore differences in sleep, AHI, and other respiratory parameters between groups (adjusted for variables determined a priori). Logistic regression adjusted for the same variables was used to determine if the proportion of patients with OSA differed across groups. Subset analyses were performed: subset 1 excluding patients on psychoactive medication; subset 2 excluding patients taking levodopa or dopaminergic agonists (DAs) at nighttime and subset 3 excluding patients on either of the abovementioned drugs. RESULTS: 146 participants were studied. The non-PIGD group had less N3 sleep compared to the PIGD group (12.4% vs 16.9% p = 0.06), reaching significance in subsets 1 and 3. The AHI was significantly lower in the PIGD group (p = 0.047), including when medication effects were removed (p < 0.05). OSA was more frequent in the non-PIGD group, but only significantly in subset 3 (adjusted OR 0.3, p = 0.04). CONCLUSION: OSA may be more severe in non-PIGD subtypes, and more frequent, in a subset free of psychoactive medication, and of levodopa and DAs, possibly owing to motor complications and dyskinesia. Future studies are required to confirm this.

An interactive web application to identify early Parkinsonian non-tremor-dominant subtypes.

BACKGROUND: Parkinson's disease (PD) patients with tremor-dominant (TD) and non-tremor-dominant (NTD) subtypes exhibit heterogeneity. Rapid identification of different motor subtypes may help to develop personalized treatment plans. METHODS: The data were acquired from the Parkinson's Disease Progression Marker Initiative (PPMI). Following the identification of predictors utilizing recursive feature elimination (RFE), seven classical machine learning (ML) models, including logistic regression, support vector machine, decision tree, random forest, extreme gradient boosting, etc., were trained to predict patients' motor subtypes, evaluating the performance of models through the area under the receiver operating characteristic curve (AUC) and validating by the follow-up data. RESULTS: The feature subset engendered by RFE encompassed 20 features, comprising some clinical assessments and cerebrospinal fluid α-synuclein (CSF α-syn). ML models fitted in the RFE subset performed better in the test and validation sets. The best performing model was support vector machines with the polynomial kernel (P-SVM), achieving an AUC of 0.898. Five-fold repeated cross-validation showed the P-SVM model with CSF α-syn performed better than the model without CSF α-syn (P = 0.034). The Shapley additive explanation plot (SHAP) illustrated that how the levels of each feature affect the predicted probability as NTD subtypes. CONCLUSION: An interactive web application was developed based on the P-SVM model constructed from feature subset by RFE. It can identify the current motor subtypes of PD patients, making it easier to understand the status of patients and develop personalized treatment plans.

Does the Etiology, Phenomenology and Motor Subtype of Delirium Differ When It Occurs in Patients With An Underlying Dementia?: A Multi-Site, International Study.

OBJECTIVES: To compare the etiology, phenomenology and motor subtype of delirium in patients with and without an underlying dementia. METHODS: A combined dataset (n = 992) was collated from two databases of older adults (>65 years) from liaison psychiatry and palliative care populations in Ireland and India. Phenomenology and severity of delirium were analysed using the Delirium Symptom Rating Scale Revised (DRS-R98) and contributory etiologies for the delirium groups were ascertained using the Delirium Etiology Checklist (DEC). Delirium motor subtype was documented using the abbreviated version of the Delirium Motor Subtype Scale (DMSS4). RESULTS: Delirium superimposed on dementia (DSD) showed greater impairment in short term memory, long term memory and visuospatial ability than the delirium group but showed significantly less perceptual disturbance, temporal onset and fluctuation. Systemic infection, cerebrovascular and other Central nervous system etiology were associated with DSD while metabolic disturbance, organ insufficiency and intracranial neoplasm were associated with the delirium only group. CONCLUSION: The etiology and phenomenology of delirium differs when it occurs in the patient with an underlying dementia. We discuss the implications in terms of identification and management of this complex condition.

Neuroimaging correlates of postural instability in Parkinson's disease.

BACKGROUND: Postural instability (PI) is a common disabling symptom in Parkinson's disease (PD), but little is known on its pathophysiological basis. OBJECTIVE: In this study, we aimed to identify the brain structures associated with PI in PD patients, using different MRI approaches. METHODS: We consecutively enrolled 142 PD patients and 45 control subjects. PI was assessed using the MDS-UPDRS-III pull-test item (PT). A whole-brain regression analysis identified brain areas where grey matter (GM) volume correlated with the PT score in PD patients. Voxel-based morphometry (VBM) and Tract-Based Spatial Statistics (TBSS) were also used to compare unsteady (PT ≥ 1) and steady (PT = 0) PD patients. Associations between GM volume in regions of interest (ROI) and several clinical features were then investigated using LASSO regression analysis. RESULTS: PI was present in 44.4% of PD patients. The whole-brain approach identified the bilateral inferior frontal gyrus (IFG) and superior temporal gyrus (STG) as the only regions associated with the presence of postural instability. VBM analysis showed reduced GM volume in fronto-temporal areas (superior, middle, medial and inferior frontal gyrus, and STG) in unsteady compared with steady PD patients, and the GM volume of these regions was selectively associated with the PT score and not with any other motor or non-motor symptom. CONCLUSIONS: This study demonstrates a significant atrophy of fronto-temporal regions in unsteady PD patients, suggesting that these brain areas may play a role in the pathophysiological mechanisms underlying postural instability in PD. This result paves the way for further studies on postural instability in Parkinsonism.

Auto-Classification of Parkinson's Disease with Different Motor Subtypes Using Arterial Spin Labelling MRI Based on Machine Learning.

The purpose of this study was to automatically classify different motor subtypes of Parkinson's disease (PD) on arterial spin labelling magnetic resonance imaging (ASL-MRI) data using support vector machine (SVM). This study included 38 subjects: 21 PD patients and 17 normal controls (NCs). Based on the Unified Parkinson's Disease Rating Scale (UPDRS) subscores, patients were divided into the tremor-dominant (TD) subtype and the postural instability gait difficulty (PIGD) subtype. The subjects were in a resting state during the acquisition of ASL-MRI data. The automated anatomical atlas 3 (AAL3) template was registered to obtain an ASL image of the same size and shape. We obtained the voxel values of 170 brain regions by considering the location coordinates of these regions and then normalized the data. The length of the feature vector depended on the number of voxel values in each brain region. Three binary classification models were utilized for classifying subjects' data, and we applied SVM to classify voxels in the brain regions. The left subgenual anterior cingulate cortex (ACC_sub_L) was clearly distinguished in both NCs and PD patients using SVM, and we obtained satisfactory diagnostic rates (accuracy = 92.31%, specificity = 96.97%, sensitivity = 84.21%, and AUCmax = 0.9585). For the right supramarginal gyrus (SupraMarginal_R), SVM distinguished the TD group from the other groups with satisfactory diagnostic rates (accuracy = 84.21%, sensitivity = 63.64%, specificity = 92.59%, and AUCmax = 0.9192). For the right intralaminar of thalamus (Thal_IL_R), SVM distinguished the PIGD group from the other groups with satisfactory diagnostic rates (accuracy = 89.47%, sensitivity = 70.00%, specificity = 6.43%, and AUCmax = 0.9464). These results are consistent with the changes in blood perfusion related to PD subtypes. In addition, the sensitive brain regions of the TD group and PIGD group involve the brain regions where the cerebellothalamocortical (CTC) and the striatal thalamocortical (STC) loops are located. Therefore, it is suggested that the blood perfusion patterns of the two loops may be different. These characteristic brain regions could become potential imaging markers of cerebral blood flow to distinguish TD from PIGD. Meanwhile, our findings provide an imaging basis for personalised treatment, thereby optimising clinical diagnostic and treatment approaches.

Classifying Tremor Dominant and Postural Instability and Gait Difficulty Subtypes of Parkinson's Disease from Full-Body Kinematics.

Characterizing motor subtypes of Parkinson's disease (PD) is an important aspect of clinical care that is useful for prognosis and medical management. Although all PD cases involve the loss of dopaminergic neurons in the brain, individual cases may present with different combinations of motor signs, which may indicate differences in underlying pathology and potential response to treatment. However, the conventional method for distinguishing PD motor subtypes involves resource-intensive physical examination by a movement disorders specialist. Moreover, the standardized rating scales for PD rely on subjective observation, which requires specialized training and unavoidable inter-rater variability. In this work, we propose a system that uses machine learning models to automatically and objectively identify some PD motor subtypes, specifically Tremor-Dominant (TD) and Postural Instability and Gait Difficulty (PIGD), from 3D kinematic data recorded during walking tasks for patients with PD (MDS-UPDRS-III Score, 34.7 ± 10.5, average disease duration 7.5 ± 4.5 years). This study demonstrates a machine learning model utilizing kinematic data that identifies PD motor subtypes with a 79.6% F1 score (N = 55 patients with parkinsonism). This significantly outperformed a comparison model using classification based on gait features (19.8% F1 score). Variants of our model trained to individual patients achieved a 95.4% F1 score. This analysis revealed that both temporal, spectral, and statistical features from lower body movements are helpful in distinguishing motor subtypes. Automatically assessing PD motor subtypes simply from walking may reduce the time and resources required from specialists, thereby improving patient care for PD treatments. Furthermore, this system can provide objective assessments to track the changes in PD motor subtypes over time to implement and modify appropriate treatment plans for individual patients as needed.

Sudomotor deficits in Parkinson's disease with special reference to motor subtypes.

INTRODUCTION: Parkinson's disease which shows clinically heterogeneous motor derangement may also accompany various autonomic disorders, but results of previous research on incidence and degree of each autonomic dysfunction have been inconsistent. As for sudomotor dysfunction, some investigators emphasize hypo- or anhidrois, whereas others stress hyperhidrosis. SUBJECTS AND METHODS: To elucidate sudomotor dysfunctions in Parkinson's disease (PD) with respect to subtypes, 225 clinically probable patients PD patients were stratified by motor phenotype (tremor-dominant group: 33; mixed group: 105; and akinesia-rigidity group: 87) and subjected to thermal and acetylcholine-induced (focal) sweating tests. Thermal sweating was qualitatively assessed with a modified version of Minor's colorimetric methods. Thermoregulatory and acetylcholine-induced focal sweat rates were measured with capacitance hydrometers. RESULTS: Thermoregulatory sweating was almost normal without anhidrotic area in 29.8% of PD patients, slightly defective in 38.7%, with anhidrotic area across <1/4 of the body surface, moderately defective in 22.2% with anhidrotic area across approximately 1/2 of the body surface, and extremely defective in 9.3% with anhidrotic area across more than 3/4 of the body surface. Patchy sweating was observed in 104 patients, implicating involvement of the hypothalamo-spinal and/or preganglionic systems in the disease process. Hyperhidrosis was seen in 15% of patients. Tremor-dominant group showed least impairment. CONCLUSION: This study suggests that PD is associated with various patterns and degree of sudomotor abnormalities, and that sudomotor sympathetic deficits may be related with the pathophysiology of akinesia and rigidity rather than that of resting tremor.

Structural and functional differences of the thalamus between drug-naïve Parkinson's disease motor subtypes.

Objective: The thalamus is an integrative hub of motor circuits in Parkinson's disease (PD). This study aimed to investigate the alterations of structure and functional connectivity (FC) of the thalamic subregions in the tremor-dominant (TD) subtype and the postural instability and gait difficulty (PIGD) subtype in PD. Methods: A total of 59 drug-naïve patients (24 TD and 35 PIGD) and 37 healthy controls were recruited. The volumes of the thalamus and the thalamic subregions were calculated using FreeSurfer. Functional connectivity (FC) analysis of the resting-state functional MRI (rsfMRI) was conducted on the thalamic subregions. Finally, the altered structure and FC were used for correlation analysis with clinical motor scores and for further motor subtypes differentiation. Results: The volumes of the left posterior parietal thalamus (PPtha) in TD patients were significantly lower than those of PIGD patients. Compared with PIGD patients, TD patients exhibited higher FC between the thalamic subregions, the left middle temporal gyrus (MTG), the right dorsolateral superior frontal gyrus (SFGdl), the left middle occipital gyrus (MOG), and the right superior temporal gyrus (STG). Compared with HCs, TD patients showed higher FC between the thalamic subregions and the right SFGdl, as well as the left MOG. Compared with HCs, PIGD patients showed lower FC between the thalamic subregions and the left MTG. In addition, the altered FC was closely related to clinical symptoms and performed high-discriminative power in differentiating the motor subtypes. Conclusion: Increased FC between the thalamic subregions and the sensory cortices in TD patients may indicate a better compensatory capacity for impairment of sensory information integration than that in PIGD patients. The altered FC between the thalamus and the MTG was a potential biomarker for the distinction of the PD motor subtypes.

The severity of corneal nerve loss differentiates motor subtypes in patients with Parkinson's disease.

Background: Parkinson's disease (PD) is a heterogeneous movement disorder with patients manifesting with either tremor-dominant (TD) or postural instability and gait disturbance (PIGD) motor subtypes. Small nerve fiber damage occurs in patients with PD and may predict motor progression, but it is not known whether it differs between patients with different motor subtypes. Objective: The aim of this study was to explore whether there was an association between the extent of corneal nerve loss and different motor subtypes. Methods: Patients with PD classified as TD, PIGD, or mixed subtype underwent detailed clinical and neurological evaluation and corneal confocal microscopy (CCM). Corneal nerve fiber density (CNFD), corneal nerve branch density (CNBD), and corneal nerve fiber length (CNFL) were compared between groups, and the association between corneal nerve fiber loss and motor subtypes was investigated. Results: Of the 73 patients studied, 29 (40%) had TD, 34 (46%) had PIGD, and 10 (14%) had a mixed subtype. CNFD (no./mm2, 24.09 ± 4.58 versus 28.66 ± 4.27; p < 0.001), CNBD (no./mm2, 28.22 ± 11.11 versus 37.37 ± 12.76; p = 0.015), and CNFL (mm/mm2, 13.11 ± 2.79 versus 16.17 ± 2.37; p < 0.001) were significantly lower in the PIGD group compared with the TD group. Multivariate logistic regression showed that higher CNFD (OR = 1.265, p = 0.019) and CNFL (OR = 1.7060, p = 0.003) were significantly associated with the TD motor subtype. The receiver operating characteristic (ROC) analysis demonstrated that combined corneal nerve metrics showed excellent discrimination between TD and PIGD, with an area under the curve (AUC) of 0.832. Conclusion: Greater corneal nerve loss occurs in patients with PIGD compared with TD, and patients with a higher CNFD or CNFL were more likely to have the TD subtype. CCM may have clinical utility in differentiating different motor subtypes in PD.

Incidence, Subtypes, Risk factors, and Outcome of Delirium: A Prospective Observational Study from Indian Intensive Care Unit.

Background: Delirium is a common, under-recognized, and often fatal condition in critically ill patients, characterized by acute disorder of attention and cognition. The global prevalence varies with a negative impact on outcomes. A paucity of Indian studies exists that have systematically assessed delirium. Objective: A prospective observational study designed to determine the incidence, subtypes, risk factors, complications, and outcome of delirium in Indian intensive care units (ICUs). Patients and methods: Among 1198 adult patients screened during the study period (December 2019-September 2021), 936 patients were included. The confusion assessment method score (CAM-ICU) and Richmond agitation sedation scale (RASS) were used, with additional confirmation of delirium by the psychiatrist/neurophysician. Risk factors and related complications were compared with a control group. Results: Delirium occurred in 22.11% of critically ill patients. The hypoactive subtype was the most common (44.9%). The risk factors recognized were higher age, increased acute physiology and chronic health evaluation (APACHE-II) score, hyperuricemia, raised creatinine, hypoalbuminemia, hyperbilirubinemia, alcoholism, and smoking. Precipitating factors included patients admitted on noncubicle beds, proximity to the nursing station, requiring ventilation, as well as the use of sedatives, steroids, anticonvulsants, and vasopressors. Complications observed in the delirium group were unintentional removal of catheters (35.7%), aspiration (19.8%), need for reintubation (10.6%), decubitus ulcer formation (18.4%), and high mortality (21.3% vs 5%). Conclusion: Delirium is common in Indian ICUs with a potential effect on length of stay and mortality. Identification of incidence, subtype, and risk factors is the first step toward prevention of this important cognitive dysfunction in the ICU. How to cite this article: Tiwari AM, Zirpe KG, Khan AZ, Gurav SK, Deshmukh AM, Suryawanshi PB, et al. Incidence, Subtypes, Risk factors, and Outcome of Delirium: A Prospective Observational Study from Indian Intensive Care Unit. Indian J Crit Care Med 2023;27(2):111-118.

Nigral neuropathology of Parkinson's motor subtypes coincide with circuitopathies: a scoping review.

The neuropathological substrates of Parkinson's disease (PD) patients with motor subtypes tremor-dominance (TD), non-tremor dominance (nTD), postural instability and gait difficulty (PIGD), and akinetic-rigid (AR) are not completely differentiated. While extensive pathological research has been conducted on neuronal tissue of PD patients, data have not been discussed in the context of mechanistic circuitry theories differentiating motor subtypes. It is, therefore, expected that a more specific and tailored management of PD symptoms can be accomplished by understanding symptom-specific neuropathological mechanisms with the detail histology can provide. This scoping review gives an overview of the literature comparing TD and nTD PD motor subtypes by clarify observed pathology with underlying physiological circuitry theories. Studies using an array of pathological examination techniques have shown significant differences between TD and nTD PD subtypes. nTD PD patients show higher neuronal loss, gliosis, extraneuronal melanin deposits, and neuroaxonal dystrophy in multiple subregions of the substantia nigra (SN) related to the overactivity of the indirect motor loop. TD patients show more severe cell loss specifically in medial SN subdivisions, and have damage in the retrorubral field A-8 that projects to the dorsolateral striatum and ventromedial thalamus in the direct motor loop. Pathological studies are consistent with neuroimaging data and support contemporary mechanistic circuitry theories of PD motor symptom genesis. Further multimodal neuroimaging and histological studies are required to validate and expand upon these findings.

Differential Effects of Subthalamic Nucleus and Globus Pallidus Internus Deep Brain Stimulation on Motor Subtypes in Parkinson's Disease.

OBJECTIVE: We investigated the differences in motor symptom change outcomes after bilateral subthalamic nucleus (STN) and globus pallidus internus (GPi) deep brain stimulation (DBS) in well-defined motor subtypes of Parkinson's disease (PD) to improve clinical decision making. METHODS: We included 114 patients who had undergone STN-DBS and 65 patients who had undergone GPi-DBS. The patients were classified as having akinetic-rigid type (ART), tremor-dominant type (TDT), and mixed type (MT) using the preoperative Movement Disorder Society Unified Parkinson's Disease Rating Scale part III (MDS-UPDRS-III) scores in the no-medication state. The outcome measures included the no-medication MDS-UPDRS-III scores and subscore changes at the last follow-up after surgery. The outcomes were compared among the different motor subtypes and between STN-DBS and GPi-DBS. RESULTS: At the last follow-up (14.92 ± 8.35 months), the TDT patients had had a greater median overall motor improvement in the no-medication MDS-UPDRS-III scores compared with the ART patients (62.90% vs. 46.67%; P < 0.001), regardless of the stimulation target. The ART patients showed greater improvement after STN-DBS than after GPi-DBS (54.44% vs. 37.21%; P < 0.001), with improvements in rigidity, akinesia, and posture and gait disorders accounting for the difference. CONCLUSIONS: Our results suggest that the different PD motor subtypes will have differential responses to STN-DBS and GPi-DBS, that TDT patients will experience greater improvement than ART patients, and that STN-DBS provides better effects for ART patients than does GPi-DBS. In addition, different motor symptoms among the different motor subtypes might respond differently to STN-DBS than to GPi-DBS. All these factors could reflect the heterogeneity of PD. Longer-term outcomes across the different motor subtypes and stimulation targets should be studied further.

Subtypes of delirium after ischaemic stroke-predisposing factors and outcomes: a prospective observational study (PROPOLIS).

BACKGROUND AND PURPOSE: Delirium is a serious complication after stroke. It remains unclear whether different motor subtypes of delirium are associated with diverse risk factors and outcomes. The aim was to investigate if delirium subtypes differ in predisposing factors, clinical characteristics and outcomes. METHODS: In all, 698 patients with ischaemic stroke or transient ischaemic attack (median age 73 years; 53.7% female) were prospectively included. Core features of delirium during the first 7 days after admission were examined. The Diagnostic and Statistical Manual of Mental Disorders (DSM-5) criteria for delirium were used. Pre-stroke characteristics were compared between different delirium subtypes and logistic regression and Cox proportional hazard models were used to explore the association between delirium, functional outcome and death. RESULTS: Hyperactive, hypoactive and mixed delirium were diagnosed in 28, 75 and 66 patients, respectively. Patients with hyperactive delirium had less severe neurological deficit on admission and more often had transient ischaemic attack compared with patients with hypoactive and mixed delirium. Compared with patients with hypoactive delirium, those with hyperactive delirium more often suffered from irritability/lability prior to stroke. Hyperactive and hypoactive delirium did not differ in age, sex, comorbidities, pre-stroke dependency, cognitive decline and severity of delirium. Hyperactive, hypoactive and mixed delirium were associated with an increased risk of poor 3- and 12-month functional outcome compared with patients without delirium. Moreover, patients with hypoactive and mixed delirium had an elevated risk of death. CONCLUSIONS: Hyperactive delirium is associated with less severe stroke and higher scores of pre-existing irritability/lability. All three motor subtypes of delirium are associated with poor outcome, although hyperactive delirium seems to have a less unfavourable prognosis.

Relationship between perivascular space enlargement and cognitive and motor longitudinal changes in patients with Parkinson′s disease / 中华神经科杂志

Objective:To investigate the correlation between basal ganglia (BG) enlarged perivascular space (EPVS; BG-EPVS) and cognitive and motor longitudinal changes in patients with newly diagnosed Parkinson′s disease and its different motor subtypes [tremor dominant (TD), postural instability and gait disorder (PIGD)].Methods:A total of 131 Parkinson′s disease patients from the Parkinson Progression Markers Initiative (PPMI) database were screened and their clinical data were collected at baseline, 1 year and 2 years of follow-up. The number of EPVS in different brain regions was assessed on axial T 2-weighted images by cranial imaging data, and they were divided into two groups according to the degree of EPVS: BG-EPVS- and BG-EPVS+. Parkinson′s disease patients were divided into TD and PIGD groups by Movement Disorder Society Unified Parkinson′s Disease Rating Scale (MDS-UPDRS) score, and the number and clinical data of EPVS were compared between the two groups, and the correlation between the number and degree of BG-EPVS at baseline and longitudinal changes in clinical outcome measures of Parkinson′s disease and its different motor subtypes (TD, PIGD) was analyzed. Results:BG-EPVS was positively correlated with age ( r=0.32, P<0.01), Hoehn & Yahr stage ( r=0.21, P<0.05), serum neurofilament light chain ( r=0.18, P<0.05) and Epworth Sleepiness Scale score ( r=0.20, P<0.05) in all Parkinson′s disease patients. At baseline and 2 years, the number of BG-EPVS was more in the PIGD group than in the TD group (11.0±4.2 vs 9.0±3.8, t=2.18, P=0.03; 16.3±6.7 vs 12.6±4.6 , t=2.71 , P=0.007;after correction).At baseline, more BG-EPVS in patients with Parkinson′s disease and its motor subtypes (TD, PIGD) was significantly associated with baseline motor outcomes ( β=0.66, P=0.01; β=0.64, P=0.008; β=0.91, P=0.009), but not with cognitive outcomes. By linear mixed effects model analysis, BG-EPVS numbers and moderate to severe BG-EPVS were positively correlated with motor outcomes over time in patients with Parkinson′s disease and its motor subtypes (TD, PIGD) ( β=0.51, P=0.008; β=0.59, P=0.025; β=0.80, P=0.038). After dividing BG-EPVS in Parkinson′s disease patients into different degrees, moderate to severe BG-EPVS was positively correlated with motor outcomes over time ( β=3.30, P=0.031). Conclusion:In this longitudinal study, bigger baseline BG-EPVS numbers were found to be positively associated with longitudinal changes in dyskinesia severity in Parkinson′s disease patients, not with cognitive changes, and be able to predict decline in motor function over a 2-year follow-up period.

Distinct hippocampal subfield atrophy in Parkinson's disease regarding motor subtypes.

INTRODUCTION: Global hippocampal atrophy has been repeatedly reported in patients with Parkinson's disease (PD). However, there is limited literature on the differential involvement of hippocampal subfields among PD motor subtypes. This study aimed to investigate hippocampal subfield alterations in patients with PD based on their predominant symptoms. METHOD: We enrolled 31 PD patients with the tremor-dominant (TD) subtype, 27 PD patients with postural instability and gait disturbance-dominant (PIGD) subtype, and 40 healthy controls (HCs). All participants underwent high-spatial-resolution T1-weighted magnetic resonance imaging. The volume of hippocampal subfields was measured using FreeSurfer software, compared across groups, and correlated with clinical features. RESULTS: We found volumetric reductions in the hippocampal subfield in both patient subtypes compared to HCs, which were more pronounced in the PIGD subtype. The PIGD subtype had accelerated age-related alterations in the hippocampus compared to the TD subtype. Bilateral hippocampal volumes were positively associated with cognitive performance levels, but not with disease severity and duration in patients. CONCLUSIONS: Alterations in the hippocampal subfields of patients with PD differed based on their predominant symptoms. These findings are of relevance for understanding the pathophysiology of the increased risk of cognitive impairment in PIGD.

Use of machine learning method on automatic classification of motor subtype of Parkinson's disease based on multilevel indices of rs-fMRI.

OBJECTIVE: This study aimed to develop an automatic classifier to distinguish different motor subtypes of Parkinson's disease (PD) based on multilevel indices of resting-state functional magnetic resonance imaging (rs-fMRI). METHODS: Ninety-six PD patients, which included thirty-nine postural instability and gait difficulty (PIGD) subtype and fifty-seven tremor-dominant (TD) subtype, were enrolled and allocated to training and validation datasets with a ratio of 7:3. A total of five types of index, consisting of mean regional homogeneity (mReHo), mean amplitude of low-frequency fluctuation (mALFF), degree of centrality (DC), voxel-mirrored homotopic connectivity (VMHC), and functional connectivity (FC), were extracted. The features were then selected using a two-sample t-test, the least absolute shrinkage and selection operator (LASSO), and Spearman's rank correlation coefficient. Finally, support vector machine (SVM) models based on the separate index and multilevel indices were built, and the performance of models was assessed via the area under the receiver operating characteristic curve (AUC). Feature importance was evaluated using Shapley additive explanation (SHAP) values. RESULTS: The optimal SVM model was obtained based on multilevel rs-fMRI indices, with an AUC of 0.934 in the training dataset and an AUC of 0.917 in the validation dataset. The AUCs of the models based on the separate index were ranged from 0.783 to 0.858 for the training dataset and from 0.713 to 0.792 for the validation dataset. SHAP analysis revealed that functional activity and connectivity in frontal lobe and cerebellum were important features for differentiating PD subtypes. CONCLUSIONS: Our findings demonstrated multilevel rs-fMRI indices could provide more comprehensive information on brain functionalteration. Furthermore, the machine learning method based on multilevel rs-fMRI indices might be served as an alternative approach for automatically classifying clinical subtypes in PD at the individual level.

Consistency and Stability of Motor Subtype Classifications in Patients With de novo Parkinson's Disease.

OBJECTIVE: Patients with Parkinson's disease (PD) are commonly classified into subtypes based on motor symptoms. The aims of the present study were to determine the consistency between PD motor subtypes, to assess the stability of PD motor subtypes over time, and to explore the variables influencing PD motor subtype stability. METHODS: This study was part of a longitudinal study of de novo PD patients at a single center. Based on three different motor subtype classification systems proposed by Jankovic, Schiess, and Kang, patients were respectively categorized as tremor-dominant/indeterminate/postural instability and gait difficulty (TD/indeterminate/PIGD), TD S /mixed S /akinetic-rigid S (ARS), or TD K /mixed K /AR K at baseline evaluation and then re-assessed 1 month later. Demographic and clinical characteristics were recorded at each evaluation. The consistency between subtypes at baseline evaluation was assessed using Cohen's kappa coefficient (κ). Additional variables were compared between PD subtype groups using the two-sample t-test, Mann-Whitney U-test or Chi-squared test. RESULTS: Of 283 newly diagnosed, untreated PD patients, 79 were followed up at 1 month. There was fair agreement between the Jankovic, Schiess, and Kang classification systems (κ S = 0.383 ± 0.044, κ K = 0.360 ± 0.042, κ SK = 0.368 ± 0.038). Among the three classification systems, the Schiess classification was the most stable and the Jankovic classification was the most unstable. The non-motor symptoms questionnaire (NMSQuest) scores differed significantly between PD patients with stable and unstable subtypes based on the Jankovic classification (p = 0.008), and patients with a consistent subtype had more severe NMSQuest scores than patients with an inconsistent subtype. CONCLUSION: Fair consistency was observed between the Jankovic, Schiess, and Kang classification systems. For the first time, non-motor symptoms (NMSs) scores were found to influence the stability of the TD/indeterminate/PIGD classification. Our findings support combining NMSs with motor symptoms to increase the effectiveness of PD subtypes.

Substantia nigra neuromelanin magnetic resonance imaging in patients with different subtypes of Parkinson disease.

Neuromelanin (NM) is a dark pigment that mainly exists in neurons of the substantia nigra pars compacta (SNc). In Parkinson disease (PD) patients, NM concentration decreases gradually with degeneration and necrosis of dopamine neurons, suggesting potential use as a PD biomarker. We aimed to evaluate associations between NM concentration in in vivo SN and PD progression and different motor subtypes using NM magnetic resonance imaging (NM-MRI). Fifty-four patients with idiopathic PD were enrolled. Patients were divided into groups by subtypes with different clinical symptoms: tremor dominant (TD) group and postural instability and gait difficulty (PIGD) group. Fifteen healthy age-matched volunteers were enrolled as controls. All subjects underwent clinical assessment and NM-MRI examination. PD patients showed significantly decreased contrast-to-noise ratio (CNR) values in medial and lateral SN (P < 0.05) compared to controls. CNR values in lateral SN region decreased linearly with PD progression (P = 0.001). PIGD patients showed significant decreases in CNR mean values in lateral SN compared to TD patients (P = 0.004). Diagnostic accuracy of using lateral substantia nigra (SN) in TD and PIGD groups was 79% (sensitivity 76.5%, specificity 78.6%). NM concentration in PD patients decreases gradually during disease progression and differs significantly between PD subtypes. NM may be a reliable biomarker for PD severity and subtype identification.

Neuroimaging Detectable Differences between Parkinson's Disease Motor Subtypes: A Systematic Review.

BACKGROUND: The neuroanatomical substrates of Parkinson's disease (PD) with tremor-dominance (TD) and those with non-tremor dominance (nTD), postural instability and gait difficulty (PIGD), and akinetic-rigid (AR) are not fully differentiated. A better understanding of symptom specific pathoanatomical markers of PD subtypes may result in earlier diagnosis and more tailored treatment. Here, we aim to give an overview of the neuroimaging literature that compared PD motor subtypes. METHODS: A systematic literature review on neuroimaging studies of PD subtypes was conducted according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Search terms submitted to the PubMed database included: "Parkinson's disease", "MRI" and "motor subtypes" (TD, nTD, PIGD, AR). The results are first discussed from macro to micro level of organization (i.e., (1) structural; (2) functional; and (3) molecular) and then by applied imaging methodology. FINDINGS: Several neuroimaging methods including diffusion imaging and positron emission tomography (PET) distinguish specific PD motor subtypes well, although findings are mixed. Furthermore, our review demonstrates that nTD-PD patients have more severe neuroalterations compared to TD-PD patients. More specifically, nTD-PD patients have deficits within striato-thalamo-cortical (STC) circuitry and other thalamocortical projections related to cognitive and sensorimotor function, while TD-PD patients tend to have greater cerebello-thalamo-cortical (CTC) circuitry dysfunction. CONCLUSIONS: Based on the literature, STC and CTC circuitry deficits seem to be the key features of PD and the subtypes. Future research should make greater use of multimodal neuroimaging and techniques that have higher sensitivity in delineating subcortical structures involved in motor diseases.