Neuropsychiatric Symptoms and Quality of Life in Patients With Adult-Onset Idiopathic Focal Dystonia and Essential Tremor

Treatment patterns in essential tremor: Real-world evidence from a United Kingdom and France primary care database

BACKGROUND AND PURPOSE

Essential tremor (ET) is one of the most common neurological disorders, but information on treatment pattern is still scant. The aim of this study was to describe the demographic and clinical characteristics, treatment patterns, and determinants of drug use in patients with newly diagnosed ET in France and the United Kingdom.

METHODS

Incident cases of ET diagnosed between January 1, 2015 and December 31, 2018 with 2 years of follow-up were identified by using The Health Improvement Network (THIN®) general practice database. During the follow-up, we assessed the daily prevalence of use and potential switches from first-line to second-line treatment or other lines of treatment. Logistic regression models were conducted to assess the effect of demographic and clinical characteristics on the likelihood of receiving ET treatment.

RESULTS

A total of 2957 and 3249 patients were selected in the United Kingdom and France, respectively. Among ET patients, drug use increased from 12 months to 1 month prior the date of index diagnosis (ID). After ID, nearly 40% of patients received at least one ET treatment, but during follow-up drug use decreased and at the end of the follow-up approximately 20% of patients were still on treatment. Among treated patients, ≤10% maintained the same treatment throughout the entire follow-up, nearly 20% switched, and 40%-75% interrupted any treatment. Results from the multivariate analysis revealed that, both in France and the United Kingdom, patients receiving multiple concomitant therapies and affected by psychiatric conditions were more likely to receive an ET medication.

CONCLUSION

This study shows that ET is an undertreated disease with a lower-than-expected number of patients receiving and maintaining pharmacological treatment. Misclassification of ET diagnosis should be acknowledged; thus, results require cautious interpretation.

Evaluation of non-motor symptoms in cervical dystonia, hemifacial spasm, and blepharospasm patients and their correlation with motor symptoms

BACKGROUND

Awareness of non-motor symptoms has been increasing in recent years, but there are still few studies on this topic.

OBJECTIVE

Our aim was to evaluate various non-motor symptoms, especially psychiatric disorders, cognitive status, and sleep, in cervical dystonia (CD), hemifacial spasm (HFS), and blepharospasm (BPS) patients and to investigate whether these symptoms are related to the severity of motor symptoms.

METHODS

This was a single-center cross-sectional, observational, case-control study. Motor severity scales were used to determine disease severity. We evaluated non-motor symptoms with commonly used scales. A total of 73 patients and 73 control groups participated.

RESULTS

In CD patients, the MoCA total score, 'language', 'abstraction', and 'orientation' scores were statistically significantly lower; PSQI, ESS, and NMSQ scores were statistically significantly higher than controls. In the BPS group, the MoCA total score and the 'language' score were significantly lower, and the NMSQ score was statistically significantly higher than the controls. In the HFS group, MoCA total score, 'executive functions', 'language', and 'abstraction' scores were statistically significantly lower; PSQI scores are statistically significantly higher than controls. There was a positive correlation between the severity score and the PSQI score in the CD group and between the severity score and the NMSQ score in the BPS group. All three groups had significant cognitive impairments.

CONCLUSIONS

In CD, BPS, and HFS, non-motor symptoms are apparent with undeniable frequency in addition to common motor symptoms. Importantly, these NMS may cause significant deterioration in the quality of life of the patients.

Multiple Comorbidities, Psychiatric Disorders, Healthcare Resource Utilization and Costs Among Adults with Essential Tremor: A Retrospective Observational Study in a Large US Commercially Insured and Medicare Advantage Population

Background: Essential tremor (ET), the most common movement disorder, often impairs patients' ability to perform activities of daily living, mental health, and quality of life. Objectives: To assess comorbidities, psychiatric disorders, healthcare resource utilization (HCRU), and costs among patients with ET compared with patients without ET. Methods: This retrospective observational study was conducted using a large US administrative claims database. Patients with ET were identified during the study period (1/1/2017-12/31/2019). The earliest claim date with ET diagnosis was identified as the index date. An index date was assigned randomly for each non-ET patient. Patients had to be at least 22 years old and be enrolled in the health plan for at least 6 months before and at least 12 months after the index date. Patients with and those without ET were matched 1:1 on age, gender, payer type, and first 3 digits of their ZIP code. Comorbidities were assessed using data within 6 months prior to the index date. Psychiatric disorders, HCRU, and costs were examined using data within 12 months after the index date. Results: The mean (SD) age of ET patients (n = 5286) was 70.8 (11.8) years, 49.1% were female, and 82.9% were Medicare Advantage members. In the 12 months following the index date, 26.0% of patients had no insurance claims for ET-related pharmacotherapy or invasive therapies. Patients with ET had a higher number of comorbidities than non-ET patients (5.3 [3.2] vs 4.0 [3.3]); a higher prevalence of psychiatric disorders (depression: 25.6% vs 15.3%; adjusted odds ratio (AOR) [95% CI], 1.56 [1.41-1.73]; anxiety: 27.7% vs 15.5%, AOR: 1.78 [1.61-1.96]); and higher total healthcare costs: $17 560 [$39 972] vs $13 237 [$27 098], adjusted cost ratio [95% CI]: 1.11 [1.06-1.16]; all P<.0001. Discussion: Highly prevalent multiple comorbidities and psychiatric disorders should be considered in the context of clinical decision-making to optimize ET management. Conclusions: This study represents the largest observational study to report ET disease and economic burdens in a real-world setting. The data demonstrate increased comorbidity, mental health, and healthcare cost burdens among ET patients compared with matched non-ET patients. These findings underscore the need for innovative care for this complex population.

Combined Intrinsic Local Functional Connectivity With Multivariate Pattern Analysis to Identify Depressed Essential Tremor

Background

Although depression is one of the most common neuropsychiatric symptoms in essential tremor (ET), the diagnosis biomarker and intrinsic brain activity remain unclear. We aimed to combine multivariate pattern analysis (MVPA) with local brain functional connectivity to identify depressed ET.

Methods

Based on individual voxel-level local brain functional connectivity (regional homogeneity, ReHo) mapping from 41 depressed ET, 43 non-depressed ET, and 45 healthy controls (HCs), the binary support vector machine (BSVM) and multiclass Gaussian Process Classification (MGPC) algorithms were used to identify depressed ET patients from non-depressed ET and HCs, the accuracy and permutations test were used to assess the classification performance.

Results

The MGPC algorithm was able to classify the three groups (depressed ET, non-depressed ET, and HCs) with a total accuracy of 84.5%. The BSVM algorithm achieved a better classification performance with total accuracy of 90.7, 88.64, and 90.48% for depressed ET vs. HCs, non-depressed ET vs. HCs, and depressed ET vs. non-depressed ET, and the sensitivity for them at 80.49, 76.64, and 80.49%, respectively. The significant discriminative features of depressed ET vs. HCs were primarily located in the cerebellar-motor-prefrontal gyrus-anterior cingulate cortex pathway, and for depressed ET vs. non-depressed ET located in the cerebellar-prefrontal gyrus-anterior cingulate cortex circuits. The partial correlation showed that the ReHo values in the bilateral middle prefrontal gyrus (positive) and the bilateral cerebellum XI (negative) were significantly correlated with clinical depression severity.

Conclusion

Our findings suggested that combined individual ReHo maps with MVPA not only could be used to identify depressed ET but also help to reveal the intrinsic brain activity changes and further act as the potential diagnosis biomarker in depressed ET patients.

Imaging Tremor Quantification for Neurological Disease Diagnosis

In this paper, we introduce a simple method based on image analysis and deep learning that can be used in the objective assessment and measurement of tremors. A tremor is a neurological disorder that causes involuntary and rhythmic movements in a human body part or parts. There are many types of tremors, depending on their amplitude and frequency type. Appropriate treatment is only possible when there is an accurate diagnosis. Thus, a need exists for a technique to analyze tremors. In this paper, we propose a hybrid approach using imaging technology and machine learning techniques for quantification and extraction of the parameters associated with tremors. These extracted parameters are used to classify the tremor for subsequent identification of the disease. In particular, we focus on essential tremor and cerebellar disorders by monitoring the finger–nose–finger test. First of all, test results obtained from both patients and healthy individuals are analyzed using image processing techniques. Next, data were grouped in order to determine classes of typical responses. A machine learning method using a support vector machine is used to perform an unsupervised clustering. Experimental results showed the highest internal evaluation for distribution into three clusters, which could be used to differentiate the responses of healthy subjects, patients with essential tremor and patients with cerebellar disorders.