Quantitative electroencephalography in cerebral amyloid angiopathy.

OBJECTIVE: We investigated whether quantitative electroencephalography (qEEG) correlates with cognition and cortical superficial siderosis (cSS) in cerebral amyloid angiopathy. METHODS: We included patients with sporadic (sCAA) and hereditary Dutch-type CAA (D-CAA). Spectral measures and the phase lag index (PLI) were analyzed on qEEG. Cognition was assessed with the MoCA and cSS presence was scored on 3T-MRI. Linear regression analyses were performed to investigate these qEEG measures and cognition. Independent samples T-tests were used to analyze the qEEG measure differences between participants with and without cSS. RESULTS: We included 92 participants (44 D-CAA; 48 sCAA). A lower average peak frequency (ß[95 %CI] = 0.986[0.252-1.721]; P = 0.009) and a higher spectral ratio (ß[95 %CI] = -0.918[-1.761--0.075]; P = 0.033) on qEEG correlated with a lower MoCA score, irrespective of a history of symptomatic intracerebral hemorrhage (sICH). The PLI showed no correlation to the MoCA. qEEG slowing was not different in those with or without cSS. CONCLUSIONS: Spectral qEEG (but not PLI) reflects cognitive performance in patients with CAA with and without a history of sICH. We found no association between qEEG slowing and cSS. SIGNIFICANCE: qEEG could be a valuable biomarker, especially in challenging cognitive testing situations in CAA, and a potential predictive tool in future studies.

Distinguishing normal, neuropathic and myopathic EMG with an automated machine learning approach.

OBJECTIVE: Distinguishing normal, neuropathic and myopathic electromyography (EMG) traces can be challenging. We aimed to create an automated time series classification algorithm. METHODS: EMGs of healthy controls (HC, n = 25), patients with amyotrophic lateral sclerosis (ALS, n = 20) and inclusion body myositis (IBM, n = 20), were retrospectively selected based on longitudinal clinical follow-up data (ALS and HC) or muscle biopsy (IBM). A machine learning pipeline was applied based on 5-second EMG fragments of each muscle. Diagnostic yield expressed as area under the curve (AUC) of a receiver-operator characteristics curve, accuracy, sensitivity, and specificity were determined per muscle (muscle-level) and per patient (patient-level). RESULTS: Diagnostic yield of the classification ALS vs. HC was: AUC 0.834 ± 0.014 at muscle-level and 0.856 ± 0.009 at patient-level. For the classification HC vs. IBM, AUC was 0.744 ± 0.043 at muscle-level and 0.735 ± 0.029 at patient-level. For the classification ALS vs. IBM, AUC was 0.569 ± 0.024 at muscle-level and 0.689 ± 0.035 at patient-level. CONCLUSIONS: An automated time series classification algorithm can distinguish EMGs from healthy individuals from those of patients with ALS with a high diagnostic yield. Using longer EMG fragments with different levels of muscle activation may improve performance. SIGNIFICANCE: In the future, machine learning algorithms may help improve the diagnostic accuracy of EMG examinations.

Systematic Review - Combining Neuroprotection With Reperfusion in Acute Ischemic Stroke.

Background: Clinical trials of neuroprotection in acute ischemic stroke (AIS) have provided disappointing results. Reperfusion may be a necessary condition for positive effects of neuroprotective treatments. This systematic review provides an overview of efficacy of neuroprotective agents in combination with reperfusion therapy in AIS. Methods: A literature search was performed on the following databases, namely PubMed, Embase, Web of Science, Cochrane Library, Emcare. All databases were searched up to September 23rd 2021. All randomized controlled trials in which patients were treated with neuroprotective strategies within 12 h of stroke onset in combination with intravenous thrombolysis (IVT), endovascular therapy (EVT), or both were included. Results: We screened 1,764 titles/abstracts and included 30 full reports of unique studies with a total of 16,160 patients. In 15 studies neuroprotectants were tested for clinical efficacy, where all patients had to receive reperfusion therapies, either IVT and/or EVT. Heterogeneity in reported outcome measures was observed. Treatment was associated with improved clinical outcome for: 1) uric acid in patients treated with EVT and IVT, 2) nerinetide in patients who underwent EVT without IVT, 3) imatinib in stroke patients treated with IVT with or without EVT, 4) remote ischemic perconditioning and IVT, and 5) high-flow normobaric oxygen treatment after EVT, with or without IVT. Conclusion: Studies specifically testing effects of neuroprotective agents in addition to IVT and/or EVT are scarce. Future neuroprotection studies should report standardized functional outcome measures and combine neuroprotective agents with reperfusion therapies in AIS or aim to include prespecified subgroup analyses for treatment with IVT and/or EVT.

Machine learning for automated EEG-based biomarkers of cognitive impairment during Deep Brain Stimulation screening in patients with Parkinson's Disease.

OBJECTIVE: A downside of Deep Brain Stimulation (DBS) for Parkinson's Disease (PD) is that cognitive function may deteriorate postoperatively. Electroencephalography (EEG) was explored as biomarker of cognition using a Machine Learning (ML) pipeline. METHODS: A fully automated ML pipeline was applied to 112 PD patients, taking EEG time-series as input and predicted class-labels as output. The most extreme cognitive scores were selected for class differentiation, i.e. best vs. worst cognitive performance (n = 20 per group). 16,674 features were extracted per patient; feature-selection was performed using a Boruta algorithm. A random forest classifier was modelled; 10-fold cross-validation with Bayesian optimization was performed to ensure generalizability. The predicted class-probabilities of the entire cohort were compared to actual cognitive performance. RESULTS: Both groups were differentiated with a mean accuracy of 0.92; using only occipital peak frequency yielded an accuracy of 0.67. Class-probabilities and actual cognitive performance were negatively linearly correlated (ß = -0.23 (95% confidence interval (-0.29, -0.18))). CONCLUSIONS: Particularly high accuracies were achieved using a compound of automatically extracted EEG biomarkers to classify PD patients according to cognition, rather than a single spectral EEG feature. SIGNIFICANCE: Automated EEG assessment may have utility for cognitive profiling of PD patients during the DBS screening.

What predicts quality of life after subthalamic deep brain stimulation in Parkinson's disease? A systematic review.

BACKGROUND AND PURPOSE: Subthalamic deep brain stimulation (STN DBS) is an effective therapy against medication-refractory motor complications in patients with Parkinson's disease. However, it remains difficult to predict which baseline patient characteristics are associated with quality of life (QoL) after surgery. The objective was to identify preoperative factors associated with QoL after STN DBS by systematically reviewing publications of sufficient methodological quality. METHODS: Main databases were systematically searched up to March 2019 to identify studies that investigated factors associated with QoL after STN DBS in patients with idiopathic Parkinson's disease. RESULTS: In all, 869 studies were identified, of which 18 fulfilled the inclusion criteria. Higher QoL after DBS appears to be associated with a large preoperative difference between ON and OFF motor function in some studies, although there was no clear association of severity of motor function or motor complications with postoperative QoL. Lower severity of dyskinesias was associated with greater postoperative QoL improvement but has been insufficiently studied. Higher baseline QoL was suggestive of higher postoperative QoL. Four studies suggested that older age at surgery is associated with a lower improvement, although six other studies reported no association. No or limited evidence was found for cognitive impairment or psychiatric dysfunction. CONCLUSION: Various relative contraindications for STN DBS such as cognitive impairment and psychiatric dysfunction appear to be unrelated to postoperative QoL. However, the lack of clear correlations with disease-related variables suggests that QoL may be individually influenced by other factors, indicating that an ideal preoperative patient profile with regard to QoL improvement cannot be readily provided.

Stimulation challenge test after STN DBS improves satisfaction in Parkinson's disease patients.

OBJECTIVE: Although subthalamic Deep Brain Stimulation (STN DBS) is proven effective in improving symptoms of Parkinson's Disease (PD), previous literature demonstrates a discrepancy between objective improvement and patients' perception thereof. We aimed to examine whether postoperative stimulation challenge tests (SCT) alters patients' satisfaction after STN DBS for PD. METHODS: Fifty-four PD patients underwent preoperative levodopa challenge tests and were routinely invited for SCT 1-2 years postoperatively. SEverity of predominantly Nondopaminergic Symptoms in PD (SENS-PD) scores quantified non-dopaminergic disease severity. Motor functioning was quantified using Movement Disorders Society Unified Parkinson's Disease Rating Scale (MDS-UPDRS) III scores; a ratio between conditions ON and OFF (preoperative Med-ON vs. Med-OFF, and postoperative Med-ON/Stim-ON vs. Med-OFF/Stim-OFF) reflected treatment benefit. 'Global Impression of Change' (GIC) and 'Global Satisfaction with Surgery' (GSS) Likert scales were filled out before and immediately after SCT. RESULTS: Postoperative Med-ON/Stim-ON severity was lower than preoperative ON severity. Disease severity scores were not different between assessments. GIC and GSS scores were higher after SCT versus before (GIC: Z = -3.80, r = 0.37, subjects indicating maximum scores before SCT: 32.1%, after SCT: 57.1%; GSS: Z = -3.69, r = 0.35, maximum scores before SCT: 25.0%, after SCT: 46.4%). Higher non-dopaminergic disease severity was associated with lower GIC and GSS scores (GIC: OR 1.2 (95%CI 1.0-1.3); GSS: OR 1.2 (95%CI 1.1-1.3), while motor-scores and magnitude of DBS-effects were not. CONCLUSION: SCT improves patients' satisfaction and is recommended especially in case of suboptimal subjective valuations. This information should be considered in clinical practice and in the context of clinical trials.

Selecting candidates for Deep Brain Stimulation in Parkinson's disease: the role of patients' expectations.

Patients with advanced Parkinson's Disease (PD) may be eligible for Deep Brain Stimulation (DBS) in case of medication-related motor fluctuations or tremor refractory to oral medication. However, several PD symptoms are unresponsive to DBS and constitute relative contra-indications for DBS. Patients referred for DBS undergo an eligibility screening during which motor functioning and contra-indications for surgery are assessed. During this pre-screening the potential benefits and drawbacks of surgery are discussed, together with patients' expectations of the results of DBS. Unrealistic expectations on the benefits of DBS may contribute to reduced patient satisfaction and poor clinical outcomes after surgery. The aim of this multicenter study (289 patients) was to assess the reasons for rejection after an outpatient-based pre-screening visit for DBS referrals, with particular emphasis on the role of patient expectations of DBS. The most frequent reason contributing to rejection was suboptimal oral treatment or satisfying symptom-control with oral medication (50% of rejections). Unrealistic expectations were identified in 38% of rejected patients and were the singular reason for rejection in 4%. Incorporating the assessment of unrealistic expectations increased the accuracy (Area Under the Curve) of determining DBS eligibility from 0.92 ((95% confidence interval (95%CI) 0.88-0.97) to 0.97 (95%CI 0.96-0.99). Patients' expectations of DBS are easily checked, and better education of patients and treating neurologists with regard to unrealistic expectations of this procedure may improve efficiency of referrals and avoid unnecessary stress and disappointments during screening.

Intraoperative test stimulation of the subthalamic nucleus aids postoperative programming of chronic stimulation settings in Parkinson's disease.

BACKGROUND: It is unknown whether intraoperative testing during awake Deep Brain Stimulation (DBS) of the subthalamic nucleus (STN) can be used to postoperatively identify the best settings for chronic stimulation. OBJECTIVE: To determine whether intraoperative test stimulation is indicative of postoperative stimulation results. METHODS: Records of consecutive Parkinson's Disease patients who received STN DBS between September 2012 and December 2017 were retrospectively analyzed. The best depth identified after intraoperative stimulation via the microelectrode's stimulation tip was compared with the depth of the contact selected for chronic stimulation after a standard monopolar contact review. Moreover, thresholds for induction of clinical effects (optimal improvement of rigidity and induction of side-effects) were compared between stimulation at the postoperatively selected contact and at the corresponding intraoperative depth. RESULTS: Records of 119 patients were analyzed (mean (SD) age 60.5 (6.5) years, 31.9% female, 238 STNs). In 75% of cases, the postoperatively selected contact corresponded with the intraoperative depth with the largest therapeutic window or was immediately dorsal to it. Higher stimulation intensities were required postoperatively than intraoperatively to relieve rigidity (p = 0.002) and induce capsular side-effects (p = 0.016). CONCLUSION: In the majority of cases, the postoperative contact for chronic stimulation was at a similar level or immediately dorsal with respect to the identified best intraoperative depth. Postoperatively, relief of rigidity and induction of capsular side-effects occur at higher stimulation intensities than during intraoperative test stimulation.