Physiology of dystonia: Human studies.

In this chapter, we discuss neurophysiological techniques that have been used in the study of dystonia. We examine traditional disease models such as inhibition and excessive plasticity and review the evidence that these play a causal role in pathophysiology. We then review the evidence for sensory and peripheral influences within pathophysiology and look at an emergent literature that tries to probe how oscillatory brain activity may be linked to dystonia pathophysiology.

Diving into the subcortex: The potential of chronic subcortical sensing for unravelling basal ganglia function and optimization of deep brain stimulation.

Subcortical structures are a relative neurophysiological 'terra incognita' owing to their location within the skull. While perioperative subcortical sensing has been performed for more than 20 years, the neurophysiology of the basal ganglia in the home setting has remained almost unexplored. However, with the recent advent of implantable pulse generators (IPG) that are able to record neural activity, the opportunity to chronically record local field potentials (LFPs) directly from electrodes implanted for deep brain stimulation opens up. This allows for a breakthrough of chronic subcortical sensing into fundamental research and clinical practice. In this review an extensive overview of the current state of subcortical sensing is provided. The widespread potential of chronic subcortical sensing for investigational and clinical use is discussed. Finally, status and future perspectives of the most promising application of chronic subcortical sensing -i.e., adaptive deep brain stimulation (aDBS)- are discussed in the context of movement disorders. The development of aDBS based on both chronic subcortical and cortical sensing has the potential to dramatically change clinical practice and the life of patients with movement disorders. However, several barriers still stand in the way of clinical implementation. Advancements regarding IPG and lead technology, physiomarkers, and aDBS algorithms as well as harnessing artificial intelligence, multimodality and sensing in the naturalistic setting are needed to bring aDBS to clinical practice.

Predicting mortality of individual patients with COVID-19: a multicentre Dutch cohort.

OBJECTIVE: Develop and validate models that predict mortality of patients diagnosed with COVID-19 admitted to the hospital. DESIGN: Retrospective cohort study. SETTING: A multicentre cohort across 10 Dutch hospitals including patients from 27 February to 8 June 2020. PARTICIPANTS: SARS-CoV-2 positive patients (age ≥18) admitted to the hospital. MAIN OUTCOME MEASURES: 21-day all-cause mortality evaluated by the area under the receiver operator curve (AUC), sensitivity, specificity, positive predictive value and negative predictive value. The predictive value of age was explored by comparison with age-based rules used in practice and by excluding age from the analysis. RESULTS: 2273 patients were included, of whom 516 had died or discharged to palliative care within 21 days after admission. Five feature sets, including premorbid, clinical presentation and laboratory and radiology values, were derived from 80 features. Additionally, an Analysis of Variance (ANOVA)-based data-driven feature selection selected the 10 features with the highest F values: age, number of home medications, urea nitrogen, lactate dehydrogenase, albumin, oxygen saturation (%), oxygen saturation is measured on room air, oxygen saturation is measured on oxygen therapy, blood gas pH and history of chronic cardiac disease. A linear logistic regression and non-linear tree-based gradient boosting algorithm fitted the data with an AUC of 0.81 (95% CI 0.77 to 0.85) and 0.82 (0.79 to 0.85), respectively, using the 10 selected features. Both models outperformed age-based decision rules used in practice (AUC of 0.69, 0.65 to 0.74 for age >70). Furthermore, performance remained stable when excluding age as predictor (AUC of 0.78, 0.75 to 0.81). CONCLUSION: Both models showed good performance and had better test characteristics than age-based decision rules, using 10 admission features readily available in Dutch hospitals. The models hold promise to aid decision-making during a hospital bed shortage.

Embedded adaptive deep brain stimulation for cervical dystonia controlled by motor cortex theta oscillations.

Dystonia is a disabling movement disorder characterized by excessive muscle contraction for which the underlying pathophysiology is incompletely understood and treatment interventions limited in efficacy. Here we utilize a novel, sensing-enabled, deep brain stimulator device, implanted in a patient with cervical dystonia, to record local field potentials from chronically implanted electrodes in the sensorimotor cortex and subthalamic nuclei bilaterally. This rechargeable device was able to record large volumes of neural data at home, in the naturalistic environment, during unconstrained activity. We confirmed the presence of theta (3-7 Hz) oscillatory activity, which was coherent throughout the cortico-subthalamic circuit and specifically suppressed by high-frequency stimulation. Stimulation also reduced the duration, rate and height of theta bursts. These findings motivated a proof-of-principle trial of a new form of adaptive deep brain stimulation - triggered by theta-burst activity recorded from the motor cortex. This facilitated increased peak stimulation amplitudes without induction of dyskinesias and demonstrated improved blinded clinical ratings compared to continuous DBS, despite reduced total electrical energy delivered. These results further strengthen the pathophysiological role of low frequency (theta) oscillations in dystonia and demonstrate the potential for novel adaptive stimulation strategies linked to cortico-basal theta bursts.

[Clinical course of COVID-19 in the Netherlands: an overview of 2607 patients in hospital during the first wave]. / Klinisch beloop van covid-19 in Nederland.

OBJECTIVE: To systematically collect clinical data from patients with a proven COVID-19 infection in the Netherlands. DESIGN: Data from 2579 patients with COVID-19 admitted to 10 Dutch centers in the period February to July 2020 are described. The clinical data are based on the WHO COVID case record form (CRF) and supplemented with patient characteristics of which recently an association disease severity has been reported. METHODS: Survival analyses were performed as primary statistical analysis. These Kaplan-Meier curves for time to (early) death (3 weeks) have been determined for pre-morbid patient characteristics and clinical, radiological and laboratory data at hospital admission. RESULTS: Total in-hospital mortality after 3 weeks was 22.2% (95% CI: 20.7% - 23.9%), hospital mortality within 21 days was significantly higher for elderly patients (> 70 years; 35, 0% (95% CI: 32.4% - 37.8%) and patients who died during the 21 days and were admitted to the intensive care (36.5% (95% CI: 32.1% - 41.3%)). Apart from that, in this Dutch population we also see a risk of early death in patients with co-morbidities (such as chronic neurological, nephrological and cardiac disorders and hypertension), and in patients with more home medication and / or with increased urea and creatinine levels. CONCLUSION: Early death due to a COVID-19 infection in the Netherlands appears to be associated with demographic variables (e.g. age), comorbidity (e.g. cardiovascular disease) but also disease char-acteristics at admission.

Acute effects of adaptive Deep Brain Stimulation in Parkinson's disease.

BACKGROUND: Beta-based adaptive Deep Brain Stimulation (aDBS) is effective in Parkinson's disease (PD), when assessed in the immediate post-implantation phase. However, the potential benefits of aDBS in patients with electrodes chronically implanted, in whom changes due to the microlesion effect have disappeared, are yet to be assessed. METHODS: To determine the acute effectiveness and side-effect profile of aDBS in PD compared to conventional continuous DBS (cDBS) and no stimulation (NoStim), years after DBS implantation, 13 PD patients undergoing battery replacement were pseudo-randomised in a crossover fashion, into three conditions (NoStim, aDBS or cDBS), with a 2-min interval between them. Patient videos were blindly evaluated using a short version of the Unified Parkinson's Disease Rating Scale (subUPDRS), and the Speech Intelligibility Test (SIT). RESULTS: Mean disease duration was 16 years, and the mean time since DBS-implantation was 6.9 years. subUPDRS scores (11 patients tested) were significantly lower both in aDBS (p=<.001), and cDBS (p = .001), when compared to NoStim. Bradykinesia subscores were significantly lower in aDBS (p = .002), and did not achieve significance during cDBS (p = .08), when compared to NoStim. Two patients demonstrated re-emerging tremor during aDBS. SIT scores of patients who presented stimulation-induced dysarthria significantly worsened in cDBS (p = .009), but not in aDBS (p = .407), when compared to NoStim. Overall, stimulation was applied 48.8% of the time during aDBS. CONCLUSION: Beta-based aDBS is effective in PD patients with bradykinetic phenotypes, delivers less stimulation than cDBS, and potentially has a more favourable speech side-effect profile. Patients with prominent tremor may require a modified adaptive strategy.

Adaptive deep brain stimulation as advanced Parkinson's disease treatment (ADAPT study): protocol for a pseudo-randomised clinical study.

INTRODUCTION: Adaptive deep brain stimulation (aDBS), based on the detection of increased beta oscillations in the subthalamic nucleus (STN), has been assessed in patients with Parkinson's disease (PD) during the immediate postoperative setting. In these studies, aDBS was shown to be at least as effective as conventional DBS (cDBS), while stimulation time and side effects were reduced. However, the effect of aDBS on motor symptoms and stimulation-induced side effects during the chronically implanted phase (after the stun effect of DBS placement has disappeared) has not yet been determined. METHODS AND ANALYSIS: This protocol describes a single-centre clinical study in which aDBS will be tested in 12 patients with PD undergoing battery replacement, with electrodes implanted in the STN, and as a proof of concept in the internal globus pallidus. Patients included will be allocated in a pseudo-randomised fashion to a three-condition (no stimulation/cDBS/ aDBS), cross-over design. A battery of tests will be conducted and recorded during each condition, which aim to measure the severity of motor symptoms and side effects. These tests include a tablet-based tapping test, a subscale of the Movement Disorder Society-unified Parkinson's disease rating scale (subMDS-UPDRS), the Speech Intelligibility Test (SIT) and a tablet-based version of the Stroop test. SubMDS-UPDRS and SIT recordings will be blindly assessed by independent raters. Data will be analysed using a linear mixed-effects model. ETHICS AND DISSEMINATION: This protocol was approved by the Ethical Committee of the University Medical Centre Groningen, where the study will be carried out. Data management and compliance to research policies and standards of our centre, including data privacy, storage and veracity, will be controlled by an independent monitor. All the scientific findings derived from this protocol are aimed to be made public through publication of articles in international journals. TRIAL REGISTRATION NUMBER: NTR 5456; Pre-results.

Accuracy of Intraoperative Computed Tomography in Deep Brain Stimulation-A Prospective Noninferiority Study.

INTRODUCTION: Clinical response to deep brain stimulation (DBS) strongly depends on the appropriate placement of the electrode in the targeted structure. Postoperative MRI is recognized as the gold standard to verify the DBS-electrode position in relation to the intended anatomical target. However, intraoperative computed tomography (iCT) might be a feasible alternative to MRI. MATERIALS AND METHODS: In this prospective noninferiority study, we compared iCT with postoperative MRI (24-72 hours after surgery) in 29 consecutive patients undergoing placement of 58 DBS electrodes. The primary outcome was defined as the difference in Euclidean distance between lead tip coordinates as determined on both imaging modalities, using the lead tip depicted on MRI as reference. Secondary outcomes were difference in radial error and depth, as well as difference in accuracy relative to target. RESULTS: The mean difference between the lead tips was 0.98 ± 0.49 mm (0.97 ± 0.47 mm for the left-sided electrodes and 1.00 ± 0.53 mm for the right-sided electrodes). The upper confidence interval (95% CI, 0.851 to 1.112) did not exceed the noninferiority margin established. The average radial error between lead tips was 0.74 ± 0.48 mm and the average depth error was determined to be 0.53 ± 0.40 mm. The linear Deming regression indicated a good agreement between both imaging modalities regarding accuracy relative to target. CONCLUSIONS: Intraoperative CT is noninferior to MRI for the verification of the DBS-electrode position. CT and MRI have their specific benefits, but both should be considered equally suitable for assessing accuracy.

The characteristics of pallidal low-frequency and beta bursts could help implementing adaptive brain stimulation in the parkinsonian and dystonic internal globus pallidus.

INTRODUCTION: Adaptive deep brain stimulation (aDBS) has been applied in Parkinson's disease (PD), based on the presence of brief high-amplitude beta (13-35 Hz) oscillation bursts in the subthalamic nucleus (STN), which correlate with symptom severity. Analogously, average low-frequency (LF) oscillatory power (4-12 Hz) in the internal globus pallidus (GPi) correlates with dystonic symptoms and might be a suitable physiomarker for aDBS in dystonia. Characterization of pallidal bursts could facilitate the implementation of aDBS in the GPi of PD and dystonia patients. OBJECTIVE AND METHODS: We aimed to describe the bursting behaviour of LF and beta oscillations in a cohort of five GPi-DBS PD patients and compare their amplitude and length with those of a cohort of seven GPi-DBS dystonia, and six STN-DBS PD patients (n electrodes = 34). Furthermore, we used the information obtained to set up aDBS and test it in the GPi of both a dystonia and a PD patient (n = 2), using either LF (dystonia) or beta oscillations (PD) as feedback signals. RESULTS: LF and beta oscillations in the dystonic and parkinsonian GPi occur as phasic, short-lived bursts, similarly to the parkinsonian STN. The amplitude profile of such bursts, however, differed significantly. Dystonia showed higher LF burst amplitudes, while PD presented higher beta burst amplitudes. Burst characteristics in the parkinsonian GPi and STN were similar. Furthermore, aDBS applied in the GPi was feasible and well tolerated in both diseases. CONCLUSION: Pallidal LF and beta burst amplitudes have different characteristics in PD and dystonia. The presence of increased burst amplitudes could be employed as feedback for GPi-aDBS.

Toward adaptive deep brain stimulation for dystonia.

The presence of abnormal neural oscillations within the cortico-basal ganglia-thalamo-cortical (CBGTC) network has emerged as one of the current principal theories to explain the pathophysiology of movement disorders. In theory, these oscillations can be used as biomarkers and thereby serve as a feedback signal to control the delivery of deep brain stimulation (DBS). This new form of DBS, dependent on different characteristics of pathological oscillations, is called adaptive DBS (aDBS), and it has already been applied in patients with Parkinson's disease. In this review, the authors summarize the scientific research to date on pathological oscillations in dystonia and address potential biomarkers that might be used as a feedback signal for controlling aDBS in patients with dystonia.

[Prevalence of neuropsychiatric disorders in drug-naive subjects with Parkinson's disease (PD)]. / Prevalencia de trastornos neuropsiquiátricos en pacientes con enfermedad de Parkinson (EP) no tratados.

INTRODUCTION: Parkinson's disease is characterized by a broad spectrum of neuropsychiatric manifestations. Its pathophysiology has been associated with the disease itself as well as with the dopaminergic treatment. MATERIAL AND METHODS: A cross-sectional study was conducted in drug-naive patients with early Parkinson's disease. All participants were evaluated through a set of scales for specific neuropsychiatric symptoms including: cognition, depression, anxiety, apathy, psychosis, and impulse control disorder. RESULTS: A total of 63 patients with Parkinson were included, of whom 26 (41.3%) subjects had some degree of cognitive impairment; seven (11.1%) had depression and 11 (15.8%) subjects had anxiety. Regarding the other symptoms, a total of 12 (19%) patients showed apathy, seven (11.1%) had psychosis, and eight (12.6%) patients had symptoms related to impulse control disorders. CONCLUSION: Neuropsychiatric disorders are common in drug-naive patients with early Parkinson's disease. Given the impact of these symptoms on quality of life, identification and proper treatment is essential.

Independent Validation of the SEND-PD and Correlation with the MDS-UPDRS Part IA.

Introduction. Neuropsychiatric symptoms in Parkinson's disease can be assessed by the MDS-UPDRS part IA. The Scale for Evaluation of Neuropsychiatric Disorders in Parkinson's disease (SEND-PD) has been recently developed to assess the severity of some neuropsychiatric symptoms. The objective of this study is to compare the performance of the SEND-PD with the corresponding items of the MDS-UPDRS part IA. Methods. Patients with Parkinson's disease were evaluated using the MDS-UPDRS and the SEND-PD by independent raters. Partial SEND-PD and neuropsychiatric MDS-UPDRS part IA were constructed with equivalent items for comparison. Results. A total of 260 consecutive patients were included. Overall, 61.2% of the patients did not report any psychotic symptom and 83.5% did not report any ICD symptom. On the other hand, 78.5% of the patients did report at least one symptom related to apathy, depression, or anxiety. The partial SEND-PD score was 2.9 ± 3.1 (range from 0 to 16). The neuropsychiatric MDS-UPDRS part IA score was 2.9 ± 3 (range from 0 to 14). The correlation coefficient between corresponding items ranged from 0.67 to 0.98 and between both summary indexes was r s = 0.93 (all, P < 0.001). Conclusion. A high association between equivalent items of the SEND-PD and the MDS-UPDRS was found.