Identifying epilepsy surgery referral candidates with natural language processing in an Australian context.

OBJECTIVE: Epilepsy surgery is known to be underutilized. Machine learning-natural language processing (ML-NLP) may be able to assist with identifying patients suitable for referral for epilepsy surgery evaluation. METHODS: Data were collected from two tertiary hospitals for patients seen in neurology outpatients for whom the diagnosis of "epilepsy" was mentioned. Individual case note review was undertaken to characterize the nature of the diagnoses discussed in these notes, and whether those with epilepsy fulfilled prespecified criteria for epilepsy surgery workup (namely focal drug refractory epilepsy without contraindications). ML-NLP algorithms were then developed using fivefold cross-validation on the first free-text clinic note for each patient to identify these criteria. RESULTS: There were 457 notes included in the study, of which 250 patients had epilepsy. There were 37 (14.8%) individuals who fulfilled the prespecified criteria for epilepsy surgery referral without described contraindications, 32 (12.8%) of whom were not referred for epilepsy surgical evaluation in the given clinic visit. In the prediction of suitability for epilepsy surgery workup using the prespecified criteria, the tested models performed similarly. For example, the random forest model returned an area under the receiver operator characteristic curve of 0.97 (95% confidence interval 0.93-1.0) for this task, sensitivity of 1.0, and specificity of 0.93. SIGNIFICANCE: This study has shown that there are patients in tertiary hospitals in South Australia who fulfill prespecified criteria for epilepsy surgery evaluation who may not have been referred for such evaluation. ML-NLP may assist with the identification of patients suitable for such referral. PLAIN LANGUAGE SUMMARY: Epilepsy surgery is a beneficial treatment for selected individuals with drug-resistant epilepsy. However, it is vastly underutilized. One reason for this underutilization is a lack of prompt referral of possible epilepsy surgery candidates to comprehensive epilepsy centers. Natural language processing, coupled with machine learning, may be able to identify possible epilepsy surgery candidates through the analysis of unstructured clinic notes. This study, conducted in two tertiary hospitals in South Australia, demonstrated that there are individuals who fulfill criteria for epilepsy surgery evaluation referral but have not yet been referred. Machine learning-natural language processing demonstrates promising results in assisting with the identification of such suitable candidates in Australia.

The efficacy and tolerability of adjunctive brivaracetam for the treatment of adult epilepsy: An Australian multi-center retrospective real-world observational cohort study.

OBJECTIVE: Assess the efficacy and tolerability of add-on therapy brivaracetam (BRV) in adult patients with epilepsy in a real-world setting. METHODS: This multi-center retrospective observational cohort study examined all adult patients who commenced on BRV at 11 Australian epilepsy centers between 2017 and 2020. Primary outcomes were seizure response (≥50% reduction in frequency) and seizure freedom 12 months post BRV commencement, and tolerability. We report three approaches to missing data (complete case analysis, CCA; last observation carried forward, LOCF; and intention to treat, ITT). Secondary outcomes included the durability of early BRV response and continuous seizure freedom from BRV initiation. Subgroup analysis examined patients with focal and generalized epilepsy and patients with refractory (≥4 prior ASMs) and highly refractory (≥7 prior ASMs) epilepsy. Outcomes were also assessed at 'personalized' seizure outcome time points based on baseline seizure frequency. RESULTS: Baseline and follow-up data were available for 228 patients. The mean age was 41.5 years (IQR 30, 50). Most had focal epilepsy (188/228, 82.5%). Median number of previous ASMs was 4 (2, 7), and concomitant ASMs 2 (2, 3). Twelve-month responder rate was: 46.3% using CCA (95% CI 34.0, 58.9); 39.5% using LOCF (33.1, 46.1); and 15.4% using ITT (10.9, 20.7). Twelve-month seizure freedom was: 23.9% using CCA (14.3, 35.9); 24.6% using LOCF (19.1, 30.7); and 7.9% using ITT (4.7, 12.1). The most frequent adverse effects were sedation or cognitive slowing (33/228, 14.5%), irritability or aggression (16/228, 7.0%), and low mood (14/228, 6.1%). Outcomes were similar using continuous outcome definitions and 'personalized' outcome assessment time points. Early responses were highly durable, with 3-month response maintained at all subsequent time points at 83%, and seizure freedom maintained at 85%. Outcomes were similar in focal (n = 187) and generalizsed (n = 25) subgroups. Outcomes were similar in refractory patients (n = 129), but lower in the highly refractory group (n = 62), however improvement with BRV was still observed with 12-month seizure freedom of 8.3% using CCA (1.0, 27), 6.5% using LOCF (1.8, 15.7); and 3.2% using ITT (0.4, 11.2). CONCLUSIONS: Meaningful real-world responder and seizure freedom rates can be still observed in a refractory epilepsy population. Brivaracetam response can occur early and appears to be maintained with minimal later relapse. The results should be interpreted with caution given the retrospective nature of the study and the quantities of missing data at later time points.

Identifying epilepsy surgery candidates with natural language processing: A systematic review.

INTRODUCTION: Epilepsy surgery is an underutilised, efficacious management strategy for selected individuals with drug-resistant epilepsy. Natural language processing (NLP) may aid in the identification of patients who are suitable to undergo evaluation for epilepsy surgery. The feasibility of this approach is yet to be determined. METHOD: In accordance with the PRISMA guidelines, a systematic review of the databases PubMed, EMBASE and Cochrane library was performed. This systematic review was prospectively registered on PROSPERO. RESULTS: 6 studies fulfilled inclusion criteria. The majority of included studies reported on datasets from only a single centre, with one study utilising data from two centres and one study six centres. The most commonly employed algorithms were support vector machines (5/6), with only one study utilising NLP strategies such as random forest models and gradient boosted machines. However, the results are promising, with all studies demonstrating moderate to high levels of performance in the identification of patients who may be suitable to undergo epilepsy surgery evaluation. Furthermore, multiple studies demonstrated that NLP could identify such patients 1-2 years prior to the treating clinicians instigating referral. However, no studies were identified that have evaluated the influence of implementing such algorithms on healthcare systems or patient outcomes. CONCLUSIONS: NLP is a promising approach to aid in the identification of patients that may be suitable to undergo epilepsy surgery evaluation. Further studies are required examining diverse datasets with additional analytical methodologies. Studies evaluating the impact of implementation of such algorithms would be beneficial.

Managing electromyogram contamination in scalp recordings: An approach identifying reliable beta and gamma EEG features of psychoses or other disorders.

OBJECTIVE: In publications on the electroencephalographic (EEG) features of psychoses and other disorders, various methods are utilized to diminish electromyogram (EMG) contamination. The extent of residual EMG contamination using these methods has not been recognized. Here, we seek to emphasize the extent of residual EMG contamination of EEG. METHODS: We compared scalp electrical recordings after applying different EMG-pruning methods with recordings of EMG-free data from 6 fully paralyzed healthy subjects. We calculated the ratio of the power of pruned, normal scalp electrical recordings in the six subjects, to the power of unpruned recordings in the same subjects when paralyzed. We produced "contamination graphs" for different pruning methods. RESULTS: EMG contamination exceeds EEG signals progressively more as frequencies exceed 25 Hz and with distance from the vertex. In contrast, Laplacian signals are spared in central scalp areas, even to 100 Hz. CONCLUSION: Given probable EMG contamination of EEG in psychiatric and other studies, few findings on beta- or gamma-frequency power can be relied upon. Based on the effectiveness of current methods of EEG de-contamination, investigators should be able to reanalyze recorded data, reevaluate conclusions from high-frequency EEG data, and be aware of limitations of the methods.

Efficacy and tolerability of adjuvant perampanel: an Australian multicenter real-world observational study in refractory focal and generalized epilepsy syndromes.

PURPOSE: To explore the efficacy and tolerability of adjuvant perampanel (PER) and their associated risk factors in late add-on drug-resistant epilepsy. METHOD: Retrospective multicenter 'real-world' observational study. Consecutively identified patients commenced on PER, with mixed epilepsy syndromes, from nine Australian epilepsy centers. Primary efficacy endpoints were at least 50% reduction in seizure frequency (responders), seizure freedom, and retention at 6 and 12 months, following a 3-month titration period. Tolerability endpoints were cessation of PER for any reason, cessation of PER due to treatment-emergent adverse events (TEAE), or cessation due to inefficacy. Outcomes were assessed for a-priori risk factors associated with efficacy and tolerability. RESULTS: Three-hundred and eighty seven adults were identified and followed up for a median of 12.1 months (IQR 7.0-25.2). Focal epilepsy accounted for 79.6% (FE), idiopathic generalized epilepsy (IGE), 10.3% and developmental epileptic encephalopathy (DEE) 10.1%, of the cohort. All patients had drug-resistant epilepsy, 71.6% had never experienced six months of seizure freedom, and the mean number of antiepileptic medications (AEDs) prior to starting PER was six. At 12 months, with missing cases classified as treatment failure, retention was 40.0%, responder 21.7%, and seizure freedom 9.0%, whereas, using last outcome carried forward (LOCF), responder and seizure freedom rates were 41.3% and 14.7%, respectively. Older age of epilepsy onset was associated with a marginal increase in the likelihood of seizure freedom at 12-month maintenance (OR 1.04, 95% CI 1.02, 1.06). Male sex (adjusted OR [aOR] 2.06 95% CI 1.33, 3.19), lower number of prior AEDs (aOR 0.84, 95% CI 0.74, 0.96) and no previous seizure-free period of at least 6-month duration (aOR 2.04 95% CI 1.21, 3.47) were associated with retention. Perampanel combined with a GABA receptor AED was associated with a lower responder rate at 12 months but reduced cessation of PER. The most common TEAEs were neuropsychiatric (18.86%), followed by dizziness (13.70%), and sleepiness (5.68%). CONCLUSIONS: Adjuvant PER treatment, even in late-add on drug-resistant epilepsy is an effective and well-tolerated treatment for drug-resistant epilepsy.

Epilepsy and Seizure-Related Hospital Admissions to an Australian Neurology Unit: A Prospective Observational Study.

This study provides contemporary data on patients admitted to a Neurology unit with seizures, the majority of whom have a diagnosis of epilepsy. There were 278 hospital presentations with seizure during the 6-month study period, with 60 admissions to the Neurology unit included for analysis. Provoking factors were identified in 40%, with poor medication adherence the commonest precipitant. CT-brain had low diagnostic yield in patients with epilepsy presenting with seizure and should be reserved for those with further indications for imaging. Patients with drug-resistant epilepsy comprised 54% of admissions suggesting management strategies in this cohort can be further optimized.

Fast and effective removal of contamination from scalp electrical recordings.

OBJECTIVE: To present a new, automated and fast artefact-removal approach which significantly reduces the effect of contamination in scalp electrical recordings. METHOD: We used spectral and temporal characteristics of different sources recorded during a typical scalp electrical recording in order to improve a fast and effective artefact removal approach. Our experiments show that correlation coefficient and spectral gradient of brain components differ from artefactual components. We trained two binary support vector machine classifiers such that one separates brain components from muscle components, and the other separates brain components from mains power and environmental components. We compared the performance of the proposed approach with seven currently used alternatives on three datasets, measuring mains power artefact reduction, muscle artefact reduction and retention of brain neurophysiological responses. RESULTS: The proposed approach significantly reduces the main power and muscle contamination from scalp electrical recording without affecting brain neurophysiological responses. None of the competitors outperformed the new approach. CONCLUSIONS: The proposed approach is the best choice for artefact reduction of scalp electrical recordings. Further improvements are possible with improved component analysis algorithms. SIGNIFICANCE: This paper provides a definitive answer to an important question: Which artefact removal algorithm should be used on scalp electrical recordings?

Potential role of cannabidiol for seizure control in a patient with recurrent glioma.

Glioma-related epilepsy significantly impact on patients' quality of life, and can often be difficult to treat. Seizures cause significant morbidity for example neurocognitive deterioration, which may result from seizures themselves or due to adverse effects from antiepileptic drugs. Management of tumour with surgery, radiotherapy and chemotherapy may contribute to seizure control, but tumour related epilepsy is often refractory despite adequate treatment with standard anti-epileptic medications. Given the increasing interest in medicinal cannabis (or cannabidiol or CBD) as an anti-epileptic drug, CBD may help with seizure control in glioma patients with treatment-refractory seizures. Here we present a case of a young lady with recurrent glioma who had refractory seizures despite multiple anti-epileptic agents, who had significant benefit with CBD.

Resting cranial and upper cervical muscle activity is increased in patients with migraine.

OBJECTIVE: To compare comprehensive measures of scalp-recorded muscle activity in migraineurs and controls. METHOD: We used whole-of-head high-density scalp electrical recordings, independent component analysis (ICA) and spectral slope of the derived components, to define muscle (electromyogram-containing) components. After projecting muscle components back to scalp, we quantified scalp spectral power in the frequency range, 52-98 Hz, reflecting muscle activation. We compared healthy subjects (n = 65) and migraineurs during a non-headache period (n = 26). We also examined effects due to migraine severity, gender, scalp-region and task (eyes-closed and eyes-open). We could not examine the effect of pre-ictal versus inter-ictal versus post-ictal as this information was not available in the pre-existing dataset. RESULTS: There was more power due to muscle activity (mean ±â€¯SEM) in migraineurs than controls (respectively, -13.61 ±â€¯0.44 dB versus -14.73 ±â€¯0.24 dB, p = 0.028). Linear regression showed no relationship between headache frequency and muscle activity in any combination of region and task. There was more power during eyes-open than eyes-closed (respectively, -13.42 ±â€¯0.34 dB versus -14.92 ±â€¯0.34 dB, p = 0.002). CONCLUSIONS: There is an increase in cranial and upper cervical muscle activity in non-ictal migraineurs versus controls. This raises questions of the role of muscle in migraine, and the possible differentiation of non-ictal phases. SIGNIFICANCE: This provides preliminary evidence to date of possible cranial muscle involvement in migraine.

Improved artefact removal from EEG using Canonical Correlation Analysis and spectral slope.

BACKGROUND: Contamination of scalp measurement by tonic muscle artefacts, even in resting positions, is an unavoidable issue in EEG recording. These artefacts add significant energy to the recorded signals, particularly at high frequencies. To enable reliable interpretation of subcortical brain activity, it is necessary to detect and discard this contamination. NEW METHOD: We introduce a new automatic muscle-removal approach based on the traditional Blind Source Separation-Canonical Correlation Analysis (BSS-CCA) method and the spectral slope of its components. We show that CCA-based muscle-removal methods can discriminate between signals with high correlation coefficients (brain, mains artefact) and signals with low correlation coefficients (white noise, muscle). We also show that typical BSS-CCA components are not purely from one source, but are mixtures from multiple sources, limiting the performance of BSS-CCA in artefact removal. We demonstrate, using our paralysis dataset, improved performance using BSS-CCA followed by spectral-slope rejection. RESULT: This muscle removal approach can reduce high-frequency muscle contamination of EEG, especially at peripheral channels, while preserving steady-state brain responses in cognitive tasks. COMPARISON WITH EXISTING METHODS: This approach is automatic and can be applied on any sample of data easily. The results show its performance is comparable with the ICA method in removing muscle contamination and has significantly lower computational complexity. CONCLUSION: We identify limitations of the traditional BSS-CCA approach to artefact removal in EEG, propose and test an extension based on spectral slope that makes it automatic and improves its performance, and results in performance comparable to competitors such as ICA-based artefact removal.

Evaluation of a minimum-norm based beamforming technique, sLORETA, for reducing tonic muscle contamination of EEG at sensor level.

BACKGROUND: Cranial and cervical muscle activity (electromyogram, EMG) contaminates the surface electroencephalogram (EEG) from frequencies below 20 through to frequencies above 100Hz. It is not possible to have a reliable measure of cognitive tasks expressed in EEG at gamma-band frequencies until the muscle contamination is removed. NEW METHOD: In the present work, we introduce a new approach of using a minimum-norm based beamforming technique (sLORETA) to reduce tonic muscle contamination at sensor level. Using a generic volume conduction model of the head, which includes three layers (brain, skull, and scalp), and sLORETA, we estimated time-series of sources distributed within the brain and scalp. The sources within the scalp were considered to be muscle and discarded in forward modelling. RESULT: (1) The method reduced EMG contamination, more strongly at peripheral channels; (2) task-induced cortical activity was retained or revealed after removing putative muscle activity. COMPARISON WITH EXISTING METHODS: This approach can decrease tonic muscle contamination in scalp measurements without relying on time-consuming processing of expensive MRI data. In addition, it is competitive to ICA in muscle reduction and can be reliably applied on any length of recorded data that captures the dynamics of the signals of interest. CONCLUSION: This study suggests that sLORETA can be used as a method to quantitate cranial muscle activity and reduce its contamination at sensor level.

EpiNet as a way of involving more physicians and patients in epilepsy research: Validation study and accreditation process.

OBJECTIVE: EpiNet was established to encourage epilepsy research. EpiNet is used for multicenter cohort studies and investigator-led trials. Physicians must be accredited to recruit patients into trials. Here, we describe the accreditation process for the EpiNet-First trials. METHODS: Physicians with an interest in epilepsy were invited to assess 30 case scenarios to determine the following: whether patients have epilepsy; the nature of the seizures (generalized, focal); and the etiology. Information was presented in two steps for 23 cases. The EpiNet steering committee determined that 21 cases had epilepsy. The steering committee determined by consensus which responses were acceptable for each case. We chose a subset of 18 cases to accredit investigators for the EpiNet-First trials. We initially focused on 12 cases; to be accredited, investigators could not diagnose epilepsy in any case that the steering committee determined did not have epilepsy. If investigators were not accredited after assessing 12 cases, 6 further cases were considered. When assessing the 18 cases, investigators could be accredited if they diagnosed one of six nonepilepsy patients as having possible epilepsy but could make no other false-positive errors and could make only one error regarding seizure classification. RESULTS: Between December 2013 and December 2014, 189 physicians assessed the 30 cases. Agreement with the steering committee regarding the diagnosis at step 1 ranged from 47% to 100%, and improved when information regarding tests was provided at step 2. One hundred five of the 189 physicians (55%) were accredited for the EpiNet-First trials. The kappa value for diagnosis of epilepsy across all 30 cases for accredited physicians was 0.70. SIGNIFICANCE: We have established criteria for accrediting physicians using EpiNet. New investigators can be accredited by assessing 18 case scenarios. We encourage physicians with an interest in epilepsy to become EpiNet-accredited and to participate in these investigator-led clinical trials.

Constitutive spectral EEG peaks in the gamma range: suppressed by sleep, reduced by mental activity and resistant to sensory stimulation.

OBJECTIVE: In a systematic study of gamma activity in neuro-psychiatric disease, we unexpectedly observed distinctive, apparently persistent, electroencephalogram (EEG) spectral peaks in the gamma range (25-100 Hz). Our objective, therefore, was to examine the incidence, distribution and some of the characteristics of these peaks. METHODS: High sample-rate, 128-channel, EEG was recorded in 603 volunteers (510 with neuropsychiatric disorders, 93 controls), whilst performing cognitive tasks, and converted to power spectra. Peaks of spectral power, including in the gamma range, were determined algorithmically for all electrodes. To determine if peaks were stable, 24-h ambulatory recordings were obtained from 16 subjects with peaks. In 10 subjects, steady-state responses to stimuli at peak frequency were compared with off-peak-frequency stimulation to determine if peaks were a feature of underlying network resonances and peaks were evaluated with easy and hard versions of oddball tasks to determine if peaks might be influenced by mental effort. RESULTS: 57% of 603 subjects exhibited peaks >2 dB above trough power at or above 25 Hz. Larger peaks (>5 dB) were present in 13% of subjects. Peaks were distributed widely over the scalp, more frequent centrally. Peaks were present through the day and were suppressed by slow-wave-sleep. Steady-state responses were the same with on- or off-peak sensory stimulation. In contrast, mental effort resulted in reductions in power and frequency of gamma peaks, although the suppression did not correlate with level of effort. CONCLUSIONS: Gamma EEG can be expressed constitutively as concentrations of power in narrow or wide frequency bands that play an, as yet, unknown role in cognitive activity. SIGNIFICANCE: These findings expand the described range of rhythmic EEG phenomena. In particular, in addition to evoked, induced and sustained gamma band activity, gamma activity can be present constitutively in spectral peaks.

Surface Laplacian of central scalp electrical signals is insensitive to muscle contamination.

The objective of this paper was to investigate the effects of surface Laplacian processing on gross and persistent electromyographic (EMG) contamination of electroencephalographic (EEG) signals in electrical scalp recordings. We made scalp recordings during passive and active tasks, on awake subjects in the absence and in the presence of complete neuromuscular blockade. Three scalp surface Laplacian estimators were compared to left ear and common average reference (CAR). Contamination was quantified by comparing power after paralysis (brain signal, B) with power before paralysis (brain plus muscle signal, B+M). Brain:Muscle (B:M) ratios for the methods were calculated using B and differences in power after paralysis to represent muscle (M). There were very small power differences after paralysis up to 600 Hz using surface Laplacian transforms (B:M > 6 above 30 Hz in central scalp leads). Scalp surface Laplacian transforms reduce muscle power in central and pericentral leads to less than one sixth of the brain signal, two to three times better signal detection than CAR. Scalp surface Laplacian transformations provide robust estimates for detecting high-frequency (gamma) activity, for assessing electrophysiological correlates of disease, and also for providing a measure of brain electrical activity for use as a standard in the development of brain/muscle signal separation methods.

Visual Experiences during Paralysis.

RATIONALE: Paralyzed human volunteers (n = 6) participated in several studies the primary one of which required full neuromuscular paralysis while awake. After the primary experiment, while still paralyzed and awake, subjects undertook studies of humor and of attempted eye-movement. The attempted eye-movements tested a central, intentional component to one's internal visual model and are the subject of this report. METHODS: Subjects reclined in a supportive chair and were ventilated after paralysis (cisatracurium, 20 mg intravenously). In illumination, subjects were requested to focus alternately on the faces of investigators standing on the left and the right within peripheral vision. In darkness, subjects were instructed to look away from a point source of light. Subjects were to report their experiences after reversal of paralysis. RESULTS: During attempted eye-movement in illumination, one subject had an illusion of environmental movement but four subjects perceived faces as clearly as if they were in central vision. In darkness, four subjects reported movement of the target light in the direction of attempted eye-movements and three could control the movement of the light at will. CONCLUSION: The hypothesis that internal visual models receive intended ocular-movement-information directly from oculomotor centers is strengthened by this evidence.

Relation of gamma oscillations in scalp recordings to muscular activity.

We recorded scalp electrical activity before and after full neuro-muscular paralysis in 5 volunteers and determined differences due to elimination of muscular activity on several standard applications of EEG. Due to paralysis, there were reductions in 'noisiness' of the standard scalp recordings which were maximal over the peripheral scalp, not explained by abolition of movement artefact, and best accounted for by sustained EMG activity in resting individuals. There was a corresponding reduction in spectral power in the gamma range. In central leads, the extent of gamma frequency coherence during a non-time-locked mental task (1 s epochs) was reduced by paralysis, likely due to a reduction in gamma-frequency coherence in widely arising EMG signals. In a time-locked mental task (auditory oddball), evoked responses were qualitatively unaffected by paralysis but 3 of 4 induced gamma responses were obscured by EMG.

Thinking activates EMG in scalp electrical recordings.

OBJECTIVE: Fast electrical rhythms in the gamma range (30-100Hz) in scalp (but not intracranial) recordings are predominantly due to electromyographic (EMG) activity. We hypothesized that increased EMG activity would be augmented by mental tasks in proportion to task difficulty and the requirement of these tasks for motor or visuo-motor output. METHODS: EEG was recorded in 98 subjects whilst performing cognitive tasks and analysed to generate power spectra. In four other subjects, neuromuscular blockade was achieved pharmacologically providing EMG-free spectra of EEG at rest and during mental tasks. RESULTS: In comparison to the paralysed condition, power of scalp electrical recordings in the gamma range varied in distribution, being maximal adjacent to cranial or cervical musculature. There were non-significant changes in mean gamma range activity due to mental tasks in paralysed subjects. In normal subjects, increases in scalp electrical activity were observed during tasks, without relationship to task difficulty, but with tasks involving limb- or eye-movement having higher power. CONCLUSIONS: Electrical rhythms in the gamma frequency range recorded from the scalp are inducible by mental activity and are largely due to EMG un-related to cognitive effort. EMG varies with requirements for somatic or ocular movement more than task difficulty. SIGNIFICANCE: Severe restrictions exist on utilizing scalp recordings for high frequency EEG.

Scalp electrical recording during paralysis: quantitative evidence that EEG frequencies above 20 Hz are contaminated by EMG.

OBJECTIVE: To identify the possible contribution of electromyogram (EMG) to scalp electroencephalogram (EEG) rhythms at rest and induced or evoked by cognitive tasks. METHODS: Scalp EEG recordings were made on two subjects in presence and absence of complete neuromuscular blockade, sparing the dominant arm. The subjects undertook cognitive tasks in both states to allow direct comparison of electrical recordings. RESULTS: EEG rhythms in the paralysed state differed significantly compared with the unparalysed state, with 10- to 200-fold differences in the power of frequencies above 20 Hz during paralysis. CONCLUSIONS: Most of the scalp EEG recording above 20 Hz is of EMG origin. Previous studies measuring gamma EEG need to be re-evaluated. SIGNIFICANCE: This has a significant impact on measurements of gamma rhythms from the scalp EEG in unparalysed humans. It is to be hoped that signal separation methods will be able to rectify this situation.

Predicting prolonged dysphagia in acute stroke: the Royal Adelaide Prognostic Index for Dysphagic Stroke (RAPIDS).

Dysphagia is common after stroke and is associated with increased morbidity and mortality. Predicting those who are likely to have significant prolonged dysphagia is not possible at present. This study was undertaken to validate the Royal Adelaide Prognostic Index for Dysphagic Stroke (RAPIDS) in the prediction of prolonged dysphagia following acute stroke using clinical and radiographic features. A prospective study of unselected, consecutive admissions to the Royal Adelaide Hospital acute stroke unit was undertaken. Clinical and radiographic features applicable to the RAPIDS test were calculated and the sensitivity, specificity, and likelihood ratio for predicting prolonged dysphagia were calculated with 95% confidence intervals (CI). Of 104 subjects admitted with acute stroke, 55 (53%) had dysphagia and 20 (19%) had dysphagia requiring nonoral feeding/hydration for 14 days or more or died while dysphagic prior to 14 days. The RAPIDS test had sensitivity of 90% (95% CI = 70-97%) and specificity of 92% (95% CI - 84-96%) for predicting this latter group of patients. We conclude that the RAPIDS test can be used early to identify patients likely to have prolonged dysphagia. This test could form a basis for selection of patients for trials of nonoral feeding methods.

The symbol of modern medicine: why one snake is more than two.

Today, two serpent motifs are commonly used to symbolize the practice and profession of medicine. Internationally, the most popular symbol of medicine is the single serpent-entwined staff of Asklepios (Latin, Aesculapius), the ancient Greco-Roman god of medicine. However, in the United States, the staff of Asklepios (the Asklepian) and a double serpent-entwined staff with surmounting wings (the caduceus) are both popular medical symbols. The latter symbol is often designated as the "medical caduceus" and is equated with the ancient caduceus, the double serpent-entwined staff of the Greco-Roman god Hermes (Latin, Mercury). Many physicians would be surprised to learn that the medical caduceus has a quite modern origin: Its design is derived not from the ancient caduceus of Hermes but from the printer's mark of a popular 19th-century medical publisher. Furthermore, this modern caduceus became a popular medical symbol only after its adoption by the U.S. Army Medical Corps at the beginning of the 20th century. This paper describes the ancient origin of the Asklepian and how a misunderstanding of ancient mythology and iconography seems to have led to the inappropriate popularization of the modern caduceus as a medical symbol.