Prisca Bauer

Dr. Prisca Bauer

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Research Focus & Metrics

Academic Career Length

14Years (2013-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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27 April 2021 in Neurology
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BSBushra Sultana
Bushra Sultana
MPMarie-Andrée Panzini
Marie-Andrée Panzini
ACAriane Veilleux Carpentier
Ariane Veilleux Carpentier
JCJacynthe Comtois
Jacynthe Comtois
BRBastien Rioux
Bastien Rioux
MKMark R. Keezer
Mark R. Keezer
Objective: In order to evaluate the incidence and prevalence of drug-resistant epilepsy (DRE) as well as its predictors and correlates, we conducted a systematic review and meta-analysis of observational studies. Methods: Our protocol was registered with PROSPERO and the PRISMA and MOOSE reporting standards were followed. We searched MEDLINE, Embase, and Web of Science. We used a double arcsine transformation and random-effects models to carry out our meta-analyses. We performed random-effects meta-regressions using study-level data. Results: Our search strategy identified 10,794 abstracts. Of these, 103 articles met our eligibility criteria. There was high inter-study heterogeneity and risk of bias. The cumulative incidence of DRE was 25.0 % (95% CI: 16.8, 34.3) in child studies but 14.6% (95% CI: 8.8, 21.6) in adult/mixed ages studies. The prevalence of DRE was 13.7% (95% CI: 9.2, 19.0) in population/community-based populations but 36.3% (95% CI: 30.4, 42.4) in clinic-based cohorts. Meta-regression confirmed that the prevalence of DRE was higher in clinic-based populations and in focal epilepsy. Multiple predictors and correlates of DRE were identified. The most reported of these were having a neurological deficit, an abnormal EEG, and symptomatic epilepsy. The most reported genetic predictors of DRE were polymorphisms of the ABCB1 gene. Conclusions: Our observations provide a basis for estimating the incidence and prevalence of DRE, which vary between populations. We identified numerous putative DRE predictors and correlates. These findings are important to plan epilepsy services, including epilepsy surgery, a crucial treatment option for people with disabling seizures and DRE.

28 August 2013 in Journal of Neurology, Neurosurgery & Psychiatry
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PBPrisca Bauer
Prisca Bauer
JRJohannes B Reitsma
Johannes B Reitsma
BHBernard M Houweling
Bernard M Houweling
CFCyrille H Ferrier
Cyrille H Ferrier
NRNick F Ramsey
Nick F Ramsey
Recent studies have shown that fMRI (functional magnetic resonance imaging) may be of value for pre-surgical assessment of language lateralisation. The aim of this study was to systematically review and analyse the available literature. A systematic electronic search for studies comparing fMRI with Wada testing was conducted in the PubMed database between March 2009 and November 2011. Studies involving unilateral Wada testing, study population consisting exclusively of children younger than 12 years of age or involving five patients or fewer were excluded. 22 studies (504 patients) were included. A random effects meta-analysis was conducted to obtain pooled estimates of the positive and negative predictive values of the fMRI using the Wada test as the reference standard. The impact of several study features on the performance of fMRI was assessed. The results showed that 81% of patients were correctly classified as having left or right language dominance or mixed language representation. Techniques were discordant in 19% of patients. fMRI and Wada test agreed in 94% for typical language lateralisation and in 51% for atypical language lateralisation. Language production or language comprehension tasks and different regions of interest did not yield statistically significant different results. It can be concluded that fMRI is reliable when there is strong left-lateralised language. The Wada test is warranted when fMRI fails to show clear left-lateralisation.

1 March 2018 in Epilepsy & Behavior
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RKRick R. van Koert
Rick R. van Koert
PBPrisca Bauer
Prisca Bauer
ISIlse Schuitema
Ilse Schuitema
JSJosemir W. Sander
Josemir W. Sander
GVGerhard H. Visser
Gerhard H. Visser

10 April 2018 in Neurology
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SSSharon Shmuely
Sharon Shmuely
PBPrisca Bauer
Prisca Bauer
EZErik W. van Zwet
Erik W. van Zwet
JDJ. Gert van Dijk
J. Gert van Dijk
RTRoland Thijs
Roland Thijs
Objective We assessed motor phenomena in syncope and convulsive seizures to aid differential diagnosis and understand the pathophysiologic correlates. Methods We studied video-EEG recordings of tilt-induced syncope and convulsive seizures in participants aged 15 years and older. Syncope was defined as (1) loss of consciousness (video-assessed), (2) circulatory changes (accelerating blood pressure decrease with or without bradycardia/asystole), and (3) EEG changes (“slow” or “slow-flat-slow”). We assessed myoclonic jerks and tonic postures of the arms and noted time of occurrence, laterality, synchrony, and rhythmicity (mean consecutive differences of interclonic intervals). Results Video-EEG records of 65 syncope cases and 50 convulsive seizures were included. In syncope, postures occurred in 42 cases (65%) and jerks in 33 (51%). Fewer jerks occurred in syncope (median 2, range 1–19) compared to convulsive seizures (median 48, range 20–191; p < 0.001). Jerks were more rhythmic in seizures compared to syncope (p < 0.001). Atonia was seen in all syncope cases, while this was not observed in any seizure. Jerks predominantly occurred during the slow and postures during the flat EEG phase. Conclusions Jerks and tonic postures were common in syncope, but semiology differed from convulsive seizures. The lack of overlap in the number of jerks suggests that less than 10 indicates syncope and more than 20 a convulsive seizure: the “10/20 rule.” Loss of tone strongly favors syncope. The EEG correlates imply that jerks in syncope are likely of cortical origin, whereas tonic postures may result from brainstem disinhibition.

10 January 2017 in Brain
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PBPrisca Bauer
Prisca Bauer
RTRoland Thijs
Roland Thijs
RLRobert J. Lamberts
Robert J. Lamberts
DVDemetrios N. Velis
Demetrios N. Velis
GVGerhard H. Visser
Gerhard H. Visser
SKStiliyan Kalitzin
Stiliyan Kalitzin
It is not fully understood how seizures terminate and why some seizures are followed by a period of complete brain activity suppression, postictal generalized EEG suppression. This is clinically relevant as there is a potential association between postictal generalized EEG suppression, cardiorespiratory arrest and sudden death following a seizure. We combined human encephalographic seizure data with data of a computational model of seizures to elucidate the neuronal network dynamics underlying seizure termination and the postictal generalized EEG suppression state. A multi-unit computational neural mass model of epileptic seizure termination and postictal recovery was developed. The model provided three predictions that were validated in EEG recordings of 48 convulsive seizures from 48 subjects with refractory focal epilepsy (20 females, age range 15–61 years). The duration of ictal and postictal generalized EEG suppression periods in human EEG followed a gamma probability distribution indicative of a deterministic process (shape parameter 2.6 and 1.5, respectively) as predicted by the model. In the model and in humans, the time between two clonic bursts increased exponentially from the start of the clonic phase of the seizure. The terminal interclonic interval, calculated using the projected terminal value of the log-linear fit of the clonic frequency decrease was correlated with the presence and duration of postictal suppression. The projected terminal interclonic interval explained 41% of the variation in postictal generalized EEG suppression duration (P < 0.02). Conversely, postictal generalized EEG suppression duration explained 34% of the variation in the last interclonic interval duration. Our findings suggest that postictal generalized EEG suppression is a separate brain state and that seizure termination is a plastic and autonomous process, reflected in increased duration of interclonic intervals that determine the duration of postictal generalized EEG suppression.

11 December 2014 in European Journal of Neurology
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MKM. R. Keezer
M. R. Keezer
PBPrisca Bauer
Prisca Bauer
MFM. D. Ferrari
M. D. Ferrari
JSJ. W. Sander
J. W. Sander