Test-Retest Reliability and Agreement of Single Pulse Transcranial Magnetic Stimulation (TMS) for Measuring Activity in Motor Cortex in Patients With Acute Ischemic Stroke.

Background: Transcranial magnetic stimulation (TMS) is often used to examine neurophysiology. We aimed to investigate the inter-rater reliability and agreement of single pulse TMS in hospitalised acute ischemic stroke patients. Methods: Thirty-one patients with first-time acute ischemic stroke (median age 72 (IQR 64-75), 35% females) underwent TMS motor threshold (MT) assessment in 4 muscles bilaterally, conducted by 1 of 2 physiotherapists. Test-retest reliability was evaluated using a two-way random effects model (2,1) absolute agreement-type Interclass Correlation Coefficient (ICC). Standard Error of Measurement (SEM) and Smallest Detectable Change (SDC) were used to evaluate agreement. Results: Reliability, SEM, and SDC of TMS was found to be moderate in right opponens pollicis (0.78 [CI 95% 0.55-0.89], SEM: 4.51, SDC: 12.51), good in right vastus medialis and tibial anterior (0.88 [CI 95% 0.72-0.96], SEM: 2.89, SDC: 8.01 and 0.88 [CI 95% 0.76-0.94], SEM: 2.88, SDC: 7.98 respectively), and excellent in right and left biceps brachii (0.98 [CI 95% 0.96-0.99], SEM: 1.79 SDC: 4.96, and 0.94 [CI 95% 0.89-0.97], SEM: 2.17 SDC: 6.01), opponens pollicis (0.92 [CI 95% 0.83-0.96], SEM: 2.68 SDC: 8.26, vastus medialis (0.92 [CI 95% 0.84-0.96], SEM: 2.87 SDC: 7.95), and tibial anterior (0.93 [CI 95% 0.86-0.96], SEM: 2.51 SDC: 6.95). Conclusion: The TMS demonstrated moderate to excellent inter-rater reliability confirming the ability of these measures to reliably discriminate between individuals in the current study sample. Improvements of less than 4.96 to 12.51 could be a result of measurement error and may therefore not be considered a true change.

Towards a wearable multi-modal seizure detection system in epilepsy: A pilot study.

OBJECTIVE: To explore the possibilities of wearable multi-modal monitoring in epilepsy and to identify effective strategies for seizure-detection. METHODS: Thirty patients with suspected epilepsy admitted to video electroencephalography (EEG) monitoring were equipped with a wearable multi-modal setup capable of continuous recording of electrocardiography (ECG), accelerometry (ACM) and behind-the-ear EEG. A support vector machine (SVM) algorithm was trained for cross-modal automated seizure detection. Visualizations of multi-modal time series data were used to generate ideas for seizure detection strategies. RESULTS: Three patients had more than five seizures and were eligible for SVM classification. Classification of 47 focal tonic seizures in one patient found a sensitivity of 84% with a false alarm rate (FAR) of 8/24 h. In two patients each with nine focal nonmotor seizures it yielded a sensitivity of 100% and a FAR of 13/24 h and 5/24. Visual comparisons of features were used to identify strategies for seizure detection in future research. CONCLUSIONS: Multi-modal monitoring in epilepsy using wearables is feasible and automatic seizure detection may benefit from multiple modalities when compared to uni-modal EEG. SIGNIFICANCE: This study is unique in exploring a combination of wearable EEG, ECG and ACM and can help inform future research on monitoring of epilepsy.

Acute effects of brain-responsive neurostimulation in drug-resistant partial onset epilepsy.

OBJECTIVE: Understanding the acute effects of responsive stimulation (AERS) based on intracranial EEG (iEEG) recordings in ambulatory patients with drug-resistant partial epilepsy, and correlating these with changes in clinical seizure frequency, may help clinicians more efficiently optimize responsive stimulation settings. METHODS: In patients implanted with the NeuroPace® RNS® System, acute changes in iEEG spectral power following active and sham stimulation periods were quantified and compared within individual iEEG channels. Additionally, acute stimulation-induced acute iEEG changes were compared within iEEG channels before and after patients experienced substantial reductions in clinical seizure frequency. RESULTS: Responsive stimulation resulted in a 20.7% relative decrease in spectral power in the 2-4 second window following active stimulation, compared to sham stimulation. On several detection channels, the AERS features changed when clinical outcomes improved but were relatively stable otherwise. AERS change direction associated with clinical improvement was generally consistent within detection channels. CONCLUSIONS: In this retrospective analysis, patients with drug-resistant partial epilepsy treated with direct brain-responsive neurostimulation showed an acute stimulation related reduction in iEEG spectral power that was associated with reductions in clinical seizure frequency. SIGNIFICANCE: Identifying favorable stimulation related changes in iEEG activity could help physicians to more rapidly optimize stimulation settings for each patient.

Morphological Description of Frontal EEG Interictal and Ictal Discharges in an Adult Cohort of 175 Patients.

Clinical and electroencephalogram (EEG) features in frontal lobe epilepsy (FLE) vary considerably among patients, making the diagnosis a challenge. The objective of this study was to describe interictal and ictal EEG activity, identifying variables that could help to differentiate and diagnose frontal lobe epilepsy cases. A prospective cross-sectional study from patients with frontal interictal epileptiform discharges (IED) referred to the Vall d'Hebron University Hospital (Barcelona, Spain) after a clinical event compatible with epileptic seizures was designed. The interictal and ictal activity were analyzed to provide a detailed EEG description of the cases, using different statistical analyses. The morphological seizure pattern at the ictal onset remained globally unchanged over time in seizures arising from the frontal lobe for each patient. Isolated sharp waves were the most frequent waveforms in the expression of IED. Frontal lobe seizures are frequently short and sometimes appear grouped in clusters within the same recording. Often the ictal expression of the electrical activity in frontal lobe seizure is subtle and challenging to interpret. A description of the main findings is summarized to identify seizures arising from the frontal lobe and avoid false negatives findings in EEG interpretations.

Standardized EEG interpretation accurately predicts prognosis after cardiac arrest.

OBJECTIVE: To identify reliable predictors of outcome in comatose patients after cardiac arrest using a single routine EEG and standardized interpretation according to the terminology proposed by the American Clinical Neurophysiology Society. METHODS: In this cohort study, 4 EEG specialists, blinded to outcome, evaluated prospectively recorded EEGs in the Target Temperature Management trial (TTM trial) that randomized patients to 33°C vs 36°C. Routine EEG was performed in patients still comatose after rewarming. EEGs were classified into highly malignant (suppression, suppression with periodic discharges, burst-suppression), malignant (periodic or rhythmic patterns, pathological or nonreactive background), and benign EEG (absence of malignant features). Poor outcome was defined as best Cerebral Performance Category score 3-5 until 180 days. RESULTS: Eight TTM sites randomized 202 patients. EEGs were recorded in 103 patients at a median 77 hours after cardiac arrest; 37% had a highly malignant EEG and all had a poor outcome (specificity 100%, sensitivity 50%). Any malignant EEG feature had a low specificity to predict poor prognosis (48%) but if 2 malignant EEG features were present specificity increased to 96% (p < 0.001). Specificity and sensitivity were not significantly affected by targeted temperature or sedation. A benign EEG was found in 1% of the patients with a poor outcome. CONCLUSIONS: Highly malignant EEG after rewarming reliably predicted poor outcome in half of patients without false predictions. An isolated finding of a single malignant feature did not predict poor outcome whereas a benign EEG was highly predictive of a good outcome.

Interrater variability of EEG interpretation in comatose cardiac arrest patients.

OBJECTIVE: EEG is widely used to predict outcome in comatose cardiac arrest patients, but its value has been limited by lack of a uniform classification. We used the EEG terminology proposed by the American Clinical Neurophysiology Society (ACNS) to assess interrater variability in a cohort of cardiac arrest patients included in the Target Temperature Management trial. The main objective was to evaluate if malignant EEG-patterns could reliably be identified. METHODS: Full-length EEGs from 103 comatose cardiac arrest patients were interpreted by four EEG-specialists with different nationalities who were blinded for patient outcome. Percent agreement and kappa (κ) for the categories in the ACNS EEG terminology and for prespecified malignant EEG-patterns were calculated. RESULTS: There was substantial interrater agreement (κ 0.71) for highly malignant patterns and moderate agreement (κ 0.42) for malignant patterns. Substantial agreement was found for malignant periodic or rhythmic patterns (κ 0.72) while agreement for identifying an unreactive EEG was fair (κ 0.26). CONCLUSIONS: The ACNS EEG terminology can be used to identify highly malignant EEG-patterns in post cardiac arrest patients in an international context with high reliability. SIGNIFICANCE: The establishment of strict criteria with high transferability between interpreters will increase the usefulness of routine EEG to assess neurological prognosis after cardiac arrest.