Postural Instability And Gait Difficulty Research Articles

The Analysis of relation to brain iron deposition of Parkinson’s Disease using Quantitative Susceptibility Mapping

Objectives: This study aimed to investigate the levels of brain iron deposition in Parkinson's disease (PD) patients using Quantitative Susceptibility Mapping (QSM) and to determine whether distinctions compared to the general population exist. Furthermore, we examined potential variations in iron deposition among different PD subtypes.Methods: Structural brain imaging was conducted on 75 participants at Gangdong Kyung Hee University Hospital between August 2017 and May 2020. PD patients were categorized into Tremor Dominant (TD) and Postural Instability and Gait Difficulty (PIGD) subtypes. Voxel-based morphometry and QSM were employed to compare voxel-wise magnetic susceptibility across the entire brain between Normal Controls (NC) and PD groups. Subsequently, QSM values were compared between TD and PIGD groups.Results: QSM values were compared among 46 PD patients and 23 normal controls, as well as between TD (n=22) and PIGD (n=24) groups. Voxel-based QSM analysis revealed no significant differences between groups. Similarly, ROI-based QSM analysis showed no significant distinctions.Conclusions: No significant variations were observed between the PD patient group, NC group, or PD subtypes. This study systematically compared QSM values across a broad range of brain regions potentially linked to PD pathology. Additionally, the subdivision of the PD group into TD and PIGD subtypes for QSM-based iron deposition analysis represents a meaningful and innovative approach.

Utility of serum neurofilament light chain and glial fibrillary acidic protein as diagnostic biomarkers of freezing of gait in Parkinson’s disease

Freezing of gait (FOG) is one of the most distressing features of Parkinson’s disease (PD), increasing the risks of fractures and seriously affecting patients’ quality of life. We aimed to examine the potential diagnostic roles of serum neurofilament light chain (NFL) and glial fibrillary acidic protein (GFAP) in PD patients with FOG (PD-FOG). We included 99 patients, comprising 54 PD patients without FOG (PD-NoFOG), 45 PD-FOG and 37 healthy controls (HCs). Our results indicated serum markers were significantly higher in PD-FOG and postural instability and gait difficulty (PIGD) motor subtype patients than in PD-NoFOG and non-PIGD subtype patients (P < 0.05), respectively. Patients with high concentrations of the markers NFL and GFAP had higher PIGD scores and greater FOG severity than those with low concentrations. Moreover, serum levels of both NFL and GFAP were significantly positively associated with age, FOG severity, PD-FOG status, and negatively associated with Mini-Mental State Examination (MMSE) scores. Logistic regression analysis identified serum levels of NFL and GFAP as independent risk factors for PD-FOG. Mediation analysis revealed that MMSE scores fully mediated the relationship between serum GFAP levels and FOG-Q scores, accounting for 33.33% of the total effects (indirect effect = 0.01, 95% CI 0.01–0.02). NFL levels differentiated PD-FOG from PD-NoFOG with reliable diagnostic accuracy (AUC 0.75, 95% CI 0.66–0.84), and the combination of NFL, GFAP, duration and MMSE scores demonstrated high accuracy (AUC 0.84, 95% CI 0.76–0.91). Our findings support the notion that NFL and GFAP may be potential biomarkers for the diagnosis of PD-FOG.

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.

Regional homogeneity and functional connectivity of freezing of gait conversion in Parkinson's disease.

Freezing of gait (FOG) is common in the late stage of Parkinson's disease (PD), which can lead to disability and impacts the quality of life. Therefore, early recognition is crucial for therapeutic intervention. We aimed to explore the abnormal regional homogeneity (ReHo) and functional connectivity (FC) in FOG converters and evaluate their diagnostic values. The data downloaded from the Parkinson's Disease Progression Markers Project (PPMI) cohort was subdivided into PD-FOG converters (n = 16) and non-converters (n = 17) based on whether FOG appeared during the 3-year follow-up; 16 healthy controls were well-matched. ReHo and FC analyses were used to explore the variations in spontaneous activity and interactions between significant regions among three groups of baseline data. Correlations between clinical variables and the altered ReHo values were assessed in FOG converter group. Last, logistic regression and receiver operating characteristic curve (ROC) were used to predict diagnostic value. Compared with the non-converters, FOG converters had reduced ReHo in the bilateral medial superior frontal gyrus (SFGmed), which was negatively correlated with the postural instability and gait difficulty (PIGD) score. ReHo within left amygdala/olfactory cortex/putamen (AMYG/OLF/PUT) was decreased, which was correlated with anxiety and autonomic dysfunction. Also, increased ReHo in the left supplementary motor area/paracentral lobule was positively correlated with the rapid eye movement sleep behavior disorder screening questionnaire. FOG converters exhibited diminished FC in the basal ganglia, limbic area, and cognitive control cortex, as compared with non-converters. The prediction model combined ReHo of basal ganglia and limbic area, with PIGD score was the best predictor of FOG conversion. The current results suggested that abnormal ReHo and FC in the basal ganglia, limbic area, and cognitive control cortex may occur in the early stage of FOG. Basal ganglia and limbic area dysfunction combined with higher PIGD score are useful for the early recognition of FOG conversion.

Do motor subtypes of Parkinson’s disease impact the learning of motor tasks?

BACKGROUND:Previous studies have demonstrated that people with Parkinson's disease (PD) can acquire postural control skills even with the degeneration of motor areas responsible for consolidation of the representation regarding the learned motor skill in long-term memory. However, these findings have not considered the PD motor subtypes – tremor-dominant (TD), and postural instability and gait difficulty (PIGD). Although there is considerable heterogeneity in motor and non-motor symptoms between TD and PIGD, no study has addressed the effect of the PD subtype on learning postural control skills. AIM:We investigated the influence of PD motor subtypes on the learning of tasks with different postural control demands. METHOD:Fourteen individuals with PD (7 TD, 7 PIGD) practiced four motor tasks with high postural and cognitive demands. Participants completed 13 one-hour sessions (2x/week for 7 weeks). We considered the first and last practice sessions, pre-test and post-test, respectively. Also, we conducted one-week and one-month retention tests to assess performance persistence (motor learning). We assessed motor performance through the scores achieved on each motor task. RESULTS:Both groups demonstrated improvement in performance during the acquisition phase. However, the TD group outperformed the PIGD group in all motor tasks, despite both groups showing improvement in motor performance when comparing the results of pre-test with the post-test, and the improved performance was maintained in retention tests. The performance differences between groups are dissipated during consolidation, and they did not directly affect motor learning. INTERPRETATION: The TD and PIGD motor subtypes learned postural control tasks with different motor and cognitive demands.

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

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. 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. 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. 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.

Effectiveness of Center of Pressure Trajectory as Anticipatory Postural Adjustment Measurement in Parkinson’s Disease With Freezing of Gait History

Background Evidence showed that patients with Parkinson’s disease (PD) who have a history of freezing of gait (FOG) have hypometric anticipatory postural adjustment (APA) during gait initiation (GI) compared to PD without FOG. Objectives This study aimed to test the feasibility of center of pressure (COP) displacement during GI as the measure of APA in PD with and without a history of FOG. Methods Patients with PD underwent COP trajectory measurements, including duration, length, velocity, and acceleration in different phases of APA (APA1, APA2a, APA2, and LOC), as well as evaluation of New Freezing of Gait Questionnaire (NFOG-Q), Tinetti balance and gait score, and Postural Instability and Gait Difficulty (PIGD) score in the on and off medication states. Results The duration (seconds) of APA2a, APA2b, and LOC were highest while velocity in mediolateral direction (X) (m/s), including APA1, APA2a, APA2b, and LOC showed lowest in PD with FOG. Velocity in the mediolateral direction in different phases of APA increased in patients with FOG after dopaminergic therapy. APA2a (seconds) and APA2b (X) (m/s) were significantly associated with NFOG-Q part II, APA2b (X) (m/s) was significantly associated with NFOG-Q part III, and APA2a (seconds) was significantly associated with Tinetti balance and gait and PIGD score. Conclusions PD with FOG history showed a favorable response of APAs to dopaminergic replacement. The APA parameters by COP trajectory, especially lateral COP shift toward the stance foot (APA2b (X) (m/s) and APA2a (seconds)) are surrogate markers to assess PD with FOG history.

Characteristics of fatigue in Parkinson's disease: A longitudinal cohort study.

To assess the prevalence, evolution, clinical characteristics, correlates and predictors of fatigue as well as to investigate the influence of comorbid fatigue on the longitudinal changes in motor and non-motor symptoms over a 2-year longitudinal follow-up period in a large cohort of patients with Parkinson's disease (PD). A total of 2,100 PD patients were enrolled from the Parkinson's Disease & Movement Disorders Multicenter Database and Collaborative Network in China (PD-MDCNC), and their motor and non-motor symptoms were assessed biennially using comprehensive scales, including the 16-item Parkinson Fatigue Scale (PFS-16). Each PD patient was categorized as PD with or without fatigue on the basis of a cut-off mean PFS-16 score of 3.3. The prevalence of fatigue in our cohort was 36.8%. Compared to PD patients without fatigue, PD patients with fatigue were more likely to be older, have a longer disease duration, and higher baseline levodopa equivalent daily dose (all p < 0.05). Moreover, PD patients with fatigue showed more severe motor and non-motor phenotypes than those without fatigue. Overall, high total Unified Parkinson's Disease Rating Scale (UPDRS) score (odds ratio [OR] = 1.016, 95% confidence interval [CI]: 1.009-1.024), Non-Motor Symptoms Scale score (OR = 1.022, 95% CI: 1.015-1.029), postural instability and gait difficulty (PIGD) subtype (OR = 1.586, 95% CI: 1.211-2.079), presence of excessive daytime sleepiness (EDS; OR = 1.343, 95% CI: 1.083-1.666), and wearing-off (OR = 1.282, 95% CI: 1.023-1.607) were significantly associated with fatigue in PD patients (all p < 0.05). High total UPDRS score at baseline (OR = 1.014, 95% CI: 1.002-1.027, p = 0.028) increased the risk of developing fatigue during follow-up. Although significant, the odds ratios were low and confidence intervals were narrow. Analysis of disease progression showed significant group differences in motor and non-motor symptoms. In comparison with the never-fatigue group, the persistent-fatigue group showed significantly greater progression in motor, autonomic dysfunction, sleep, depression and cognitive symptoms (all p < 0.05). Increased disease severity, presence of the PIGD subtype, EDS, and wearing-off were associated with fatigue in PD patients. Significant subgroup-level differences were observed in the progression of motor and non-motor symptoms across different fatigue subgroups of PD patients.

Bilateral globus pallidus interna deep brain stimulation in Parkinson's disease: Therapeutic effects and motor outcomes prediction in a short-term follow up.

We aimed to compare the motor effect of bilateral globus pallidus interna (GPi) deep brain stimulation (DBS) on motor subtypes of Parkinson's disease (PD) patients and identify preoperative predictive factors of short-term motor outcome. We retrospectively investigated bilateral GPi DBS clinical outcomes in 55 PD patients in 1 year follow up. Motor outcome was measured by the Movement Disorder Society Unified Parkinson's Disease Rating Scale (MDS-UPDRS) part III before and 1 year after surgery. Clinical outcomes were compared among different motor subtypes. Preoperative predictors of motor outcome were assessed by performing univariate and multivariate linear regression and logistic regression analyses. At 1 year following implantation, GPi DBS significantly improved the off-medication MDS-UPDRS III scores in all motor subtype cohorts, with prominent improvement in tremor. No significant difference of postoperative motor symptoms changes was found except greater tremor improvement achieved in both the tremor-dominant (TD) and indeterminate (IND) patients compared to the postural instability and gait difficulty (PIGD) patients. High percentage of PIGD patients were weak responders to DBS. Better levodopa responsiveness and more severe tremor predicted greater overall improvement of motor function in the entire cohort. Similarly, both levodopa responsiveness and tremor improvement were confirmed as predictors for motor improvement in PIGD patients. Bilateral GPi DBS could effectively improve motor outcomes in PD patients regardless of motor subtypes. Both TD and IND patients obtained larger tremor improvement. The intensity of levodopa responsiveness and the severity of tremor could serve as predictors of motor improvement 1 year after GPi DBS.

Istradefylline effects on tremor dominance (TD) and postural instability and gait difficulty (PIGD)

BackgroundIn patients with Parkinson’s Disease (PD), two distinct motor subtypes, tremor dominant (TD) and postural instability and gait difficulty (PIGD), can be differentiated using Unified Parkinson’s Disease Rating Scale (UPDRS) sub-scores. This post hoc analysis of pooled data from eight pivotal studies examined the effect of treatment with istradefylline, a selective adenosine A2A receptor antagonist, on these subtypes. MethodsIn eight randomized, placebo-controlled phase 2b/3 trials, patients on levodopa with carbidopa/benserazide experiencing motor complications received istradefylline (20 or 40 mg/day) or placebo for 12 or 16 weeks. TD subtype was defined by the UPDRS II/III items kinetic and postural tremor in right/left hand and (resting) tremor in the face, lips, chin, hands, or feet; PIGD items were freezing, walking, posture, gait, and postural instability. The ratio of mean scores from TD:PIGD items determined subtype (TD [TD:PIGD ratio ≥ 1.5], PIGD [TD:PIGD ratio ≤ 1.0], mixed-type [ratio 1–1.5]). ResultsIn total, 2719 patients were included (PIGD, n = 2165; TD, n = 118; mixed-type, n = 188; not evaluable, n = 248). Among TD subtype patients, the least-squares mean change from baseline versus placebo in UPDRS II/III TD-related total score was significant at 20 mg/day istradefylline (−2.21; 95 % CI, −4.05 to −0.36; p = 0.02). For PIGD subtype patients, there was a significant difference from placebo in UPDRS II/III PIGD-related total score at 40 mg/day istradefylline (−0.25; −0.43 to −0.06; p = 0.01). ConclusionsThe data from this analysis of UPDRS-based motor subtypes suggest that istradefylline can improve motor disability in PD patients with motor fluctuations regardless of PD subtype. Future research should characterize the effects of istradefylline on tremor.

The Importance of Early Identification for Parkinson's Disease Patients with Postural Instability and Gait Disturbance.

More and more evidence-based medicine has proved that Parkinson's disease (PD) patients of tremor-dominant (TD) and postural instability and gait difficulty (PIGD) subtype express great individual differences and heterogeneity. Early identification of different subtypes may be an important way to delay disease progression and improve patients' prognosis. The study aimed to compare the spectrum of motor symptoms (MS) and nonmotor symptoms (NMS) between TD and PIGD dominant in the early and middle stages of PD, and determine predictive factors that are associated with different motor subtypes. 292 PD patients in this study were divided into TD-PD and PIGD-PD, and the clinical characteristics between different motor subtypes were compared based on scales related to sleep, mood, and autonomic function. Univariate and multivariate ordered logistic regression analyses were used to analyze the independent influencing factors of disease severity between different motor subtypes. Through the establishment of binary logistic regression model, the potential independent risk factors for distinguishing TD-PD and PIGD-PD were studied. Compared with TD subtype, patients with PIGD subtype have longer course of disease, higher disease severity, and higher daily dosage of levodopa. The severity of nontremor motor symptoms in PIGD-PD is greater than that of TD subtype. Only PIGD score was independently associated with disease severity for the two motor subtypes. Meanwhile, high scores (LED, total UPDRS, PIGD score, gastrointestinal, thermoregulatory, RBDSQ) and low tremor scores were the potential independent risk factors for distinguishing PIGD-PD from TD-PD. Specific nonmotor symptoms (RBD, gastrointestinal function and thermoregulation function) were associated with the PIGD subtype. Prompt detection and early treatment of NMSs related to the PIGD subtype based on the treatment of motor symptoms may improve patient outcomes.

Olfactory dysfunction and striatal dopamine transporter binding in motor subtypes of Parkinson's disease.

Olfactory dysfunction is one of the earliest non-motor symptoms (NMS) in Parkinson's disease (PD). There are contradictory results regarding the association of olfactory dysfunction and dopamine uptake in striatal nuclei among PD patients. It has been suggested that different motor subtypes of PD vary in the disease pathophysiology and progression. Thus, we hypothesized that there might be different associations between olfactory dysfunction and striatal dopaminergic neuronal loss among three motor subtypes of PD, namely, indeterminate, postural instability and gait difficulty (PIGD), and tremor-dominant (TD). We recruited 162 healthy controls (HCs) and 464 drug-naïve PD patients from PPMI who underwent common PD scaling tests. Striatal binding ratios (SBRs) of DaTSCAN images in caudate and putamen nuclei were calculated. To assess the olfactory function, the University of Pennsylvania Smell Identification Test (UPSIT) was carried out. The UPSIT score was significantly correlated with MDS-UPDRS part I (p value: 0.002, correlation coefficient: - 0.160), MDS-UPDRS part III (p value: 0.000, correlation coefficient: - 0.248), and SBR score in right (p value: 0.000, correlation coefficient: 0.240) and left caudate (p value: 0.000, correlation coefficient: 0.221) and right (p value: 0.000, correlation coefficient: 0.323) and left putamen (p value: 0.000, correlation coefficient: 0.335) nucleus in TD subtype. There were no significant correlations in HC, PIGD, and indeterminate subjects. The olfactory dysfunction was correlated with dopamine transporter activity in striatal nuclei only in the TD subtype. Therefore, the olfactory dysfunction in PIGD and indeterminate subtype may not be a predictive factor for the future decrease in dopamine uptake.

Parkinson's Disease Motor Subtypes Change with the Progression of the Disease: Results from the COPPADIS Cohort at 2-Year Follow-Up.

Motor phenotype (MP) can be associated with a different prognosis in Parkinson's disease (PD), but it is not fixed and can change over time. Our aim was to analyze how the MP changed over time and to identify factors associated with the changes in PD patients from a multicenter Spanish PD cohort. PD patients who were recruited from January-2016 to November-2017 (baseline visit; V0) and evaluated again at a 2-year±30 days follow-up (V2) from 35 centers of Spain from the COPPADIS cohort, were included in this study.MP was calculated at both visits based on Jankovic classification in TD (tremor dominant), IND (indeterminate), or PIGD (postural instability and gait difficulty). Sociodemographic and clinical data were collected, including serum biomarkers. Five hundred eleven patients (62.57±8.59 years old; 59.2%males) were included in the study. At V0, MP was: 47.4%(242/511) TD; 36.6%(187/511) PIGD; 16%(82/511) IND. Up to 38%(194/511) of the patients changed their phenotype from V0 to V2, being the most frequent from TD to IND (8.4%) and from TD to PIGD (6.7%). A worse cognitive status (OR = 0.966) and less autonomy for activities of daily living (OR = 0.937) at V0 and a greater increase in the globalNMS burden (OR = 1.011) from V0 to V2 were associated with changing from TD to another phenotype after 2-year follow-up. The MP in PD can change over time. With disease progression, the percentage of cases with non-tremoric MP increases. PD patients who changed from TD to postural instability and gait difficulty increased NMS burden significantly.

Olfactory dysfunction is associated with motor function only in tremor-dominant Parkinson's disease.

The prevalence of olfactory impairment in patients with Parkinson's disease (PD) is 50-90%, and therefore, olfactory dysfunction is one of the most prevalent non-motor symptoms (NMSs) in patients with PD. Numerous studies have evaluated the association between motor and non-motor symptoms and olfactory dysfunction in PD. In this study, we investigated the relationship between olfactory dysfunction, which is measured using the UPSIT test, with other motor and non-motor symptoms separately in three motor subtypes of PD, including tremor dominant (TD), postural instability and gait difficulty (PIGD), and indeterminate and healthy subjects. We recruited 487 early-stage PD patients (43 PIGD, 406 TD, and 38 indeterminate) and healthy controls (HCs) (n = 197) from the Parkinson Progression Markers Initiative (PPMI). All participants completed motor and non-motor tests at baseline visit and after 4years of follow-up. Subjects underwent common PD scaling tests. Olfactory dysfunction was significantly correlated with declined motor functions only in the TD subtype. Also, significant correlations were noticed between olfactory dysfunction and speed-attention processing and executive function in the HCs as well. Finally, no significant or meaningful association was observed in the PIGD and indeterminate subtype. Anosmia and hyposmia subjects in the TD group had the worse motor and non-motor scores compared to normosmia subjects after 4years. Olfactory dysfunction was significantly correlated with declined motor functions in the TD subtype. This is indicating that olfactory dysfunction may be an early motor and non-motor biomarker only in the TD subtype. However, it is possible that the involvement of olfactory function in other subtypes is not strong enough to make it a useful marker of diseases progression.

An inertial sensor-based algorithm for turning detection during gait.

Patients with Parkinson's disease (PD) can be divided into two subtypes based on clinical features, namely tremor-dominant (TD) and postural instability and gait difficulty (PIGD). Detection of PIGD symptoms is crucial for early diagnosis of PD and timely clinical intervention. However, patients at the early stage may not exhibit obvious motor dysfunctions during normal straight walking leading to difficulties in PD identification. Researchers have found that patients would show significant motor deteriorations in turning due to their cognition limitation. Therefore, turning detection is essential for quantitative motion analysis in the gait assessment of PD patients. In this study, we proposed a novel inertial-sensor-based algorithm for turning detection. Ten healthy young participants were enrolled in the experiment where they were required to walk along a 7-meter pathway with two 180 degree turns at their comfortable walking speed. Five inertial sensors were attached to the upper trunk, the shank and the foot of both legs. The algorithm performance was validated using an optical motion capture system for reference and two sensor combination options (upper trunk and shank sensors, upper trunk and foot sensors) were compared. The results showed that the proposed algorithm achieved accuracy over 98% for identifying the turning state of both legs. The integration of the upper trunk and foot sensors had no significant effect on the detection accuracy compared to that with the use of the upper trunk and shank sensors. Our algorithm has the potential to be implemented in the motion analysis model for complicated gait tasks, which has great potential in the early diagnosis of PIGD.

Surrogates for rigidity and PIGD MDS-UPDRS subscores using wearable sensors

BackgroundTelemedicine has the advantage of expanding access to care for patients with Parkinson’s Disease (PD). However, rigidity and postural instability in PD are difficult to measure remotely, and are important measures of functional impairment and fall risk. Research questionCan measures from wearable sensors be used as future surrogates for the MDS-UPDRS rigidity and Postural Instability and Gait Difficulty (PIGD) subscores? MethodsThirty-one individuals with mild to moderate PD wore 3 inertial sensors at home for one week to measure quantity and quality of gait and turning in daily life. Separately, we performed a clinical assessment and balance characterization of postural sway with the same wearable sensors in the laboratory (On medication). We then first performed a traditional correlation analysis between clinical scores and objective measures of gait and balance followed by multivariable linear regression employing a best subset selection strategy. ResultsThe number of walking bouts and turns correlated significantly with the rigidity subscore, while the number of turns, foot pitch angle, and sway area while standing correlated significantly with the PIGD subscore (p < 0.05). The multivariable linear regression showed that rigidity subscore was best predicted by the number of walking bouts while the PIGD subscore was best predicted by a combination of number of walking bouts, gait speed, and postural sway. SignificanceThe correlation between objective sensor data and MDS-UPDRS rigidity and PIGD scores paves the way for future larger studies that evaluate use of objective sensor data to supplement remote MDS-UPDRS assessment.

Assessment of Force Production in Parkinson's Disease Subtypes.

Muscle weakness is a secondary motor symptom of Parkinson’s disease (PD), especially in the subtype characterized by postural instability and gait difficulty (PIGD). Since the PIGD subtype also presents worse bradykinesia, we hypothesized that it also shows a decreased rate of force development, which is linked to an increased risk of falling in PD. Therefore, we investigated the effects of PD and PD subtypes on a force production profile and correlated the force production outcomes with clinical symptoms for each PD subtype. We assessed three groups of participants: 14 healthy older adults (OA), 10 people with PD composing the PIGD group, and 14 people with PD composing the tremor-dominant group. Three knee extension maximum voluntary isometric contractions were performed in a leg extension machine equipped with a load cell to assess the force production. The outcome measures were: peak force and rate of force development (RFD) at 50 ms (RFD50), 100 ms (RFD100), and 200 ms (RFD200). We observed lower peak force, RFD50, RFD100, and RFD200 in people with PD, regardless of subtypes, compared with the OA group (p < 0.05 for all comparisons). Together, our results indicated that PD affects the capacity to produce maximal and rapid force. Therefore, future interventions should consider rehabilitation programs for people with PD based on muscle power and fast-force production, and consequently reduce the likelihood of people with PD falling from balance-related events, such as from an unsuccessful attempt to avoid a tripping hazard or a poor and slower stepping response.

Stability of MDS-UPDRS Motor Subtypes Over Three Years in Early Parkinson's Disease.

Background: Various classifications have been proposed to subtype Parkinson's disease (PD) based on their motor phenotypes. However, the stability of these subtypes has not been properly evaluated.Objective: The goal of this study was to understand the distribution of PD motor subtypes, their stability over time, and baseline factors that predicted subtype stability.Methods: Participants (n = 170) from two prospective cohorts were included: the Early PD Longitudinal Singapore (PALS) study and the National Neuroscience Institute Movement Disorders Database. Early PD patients were classified into tremor-dominant (TD), postural instability and gait difficulty (PIGD), and indeterminate subtypes according to the Movement Disorder Society's Unified PD Rating Scale (MDS-UPDRS) criteria and clinically evaluated for three consecutive years.Results: At baseline, 60.6% patients were TD, 12.4% patients were indeterminate, and 27.1% patients were PIGD subtypes (p < 0.05). After 3 years, only 62% of patients in TD and 50% of patients in PIGD subtypes remained stable. The mean levodopa equivalent daily dose (LEDD) was higher in the PIGD subtype (276.92 ± 232.91 mg; p = 0.01). Lower LEDD [p < 0.05, odds ratio (OR) 0.99, 95% confidence interval (CI): 0.98–0.99] and higher TD/PIGD ratios (p < 0.05, OR 1.77, 95% CI: 1.29–2.43) were independent predictors of stability of TD subtype with an area under the curve (AUC) of 0.787 (95%CI: 0.669–0.876), sensitivity = 57.8%, and specificity = 89.7%.Conclusion: Only 50–62% of PD motor subtypes as defined by MDS-UPDRS remained stable over 3 years. TD/PIGD ratio and baseline LEDD were independent predictors for TD subtype stability over 3 years.

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

ObjectiveThis 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). MethodsNinety-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. ResultsThe 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. ConclusionsOur 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.

The effect of levodopa on bilateral coordination and gait asymmetry in Parkinson\u2019s disease using inertial sensor

This study aimed to evaluate the effect of levodopa on the phase coordination index (PCI) and gait asymmetry (GA) of patients with Parkinson’s disease (PD) and to investigate correlations between the severity of motor symptoms and gait parameters measured using an inertial sensor. Twenty-six patients with mild-to-moderate-stage PD who were taking levodopa participated in this study. The Unified Parkinson’s Disease Rating Scale part III (UPDRS III) was used to assess the severity of motor impairment. The Postural Instability and Gait Difficulty (PIGD) subscore was calculated from UPDRS III. Patients were assessed while walking a 20-m corridor in both “OFF” and “ON” levodopa medication states, and gait analysis was performed using inertial sensors. We investigated the changes in gait parameters after taking levodopa and the correlations between UPDRS III, PIGD, and gait parameters. There was a significant improvement in PCI after taking levodopa. No significant effect of levodopa on GA was found. In “OFF” state, PCI and GA were not correlated with UPDRS III and PIGD. However, in “ON” state, PCI was the only gait parameter correlating with UPDRS III, and it was also highly correlated with PIGD compared to other gait parameters. Significant improvement in bilateral-phase coordination was identified in patients with PD after taking levodopa, without significant change in gait symmetricity. Considering the high correlation with UDPRS III and PIGD in “ON” states, PCI may be a useful and quantitative parameter to measure the severity of motor symptoms in PD patients who are on medication.