Literature DB >> 25935890

Predictors for being offered epilepsy surgery: 5-year experience of a tertiary referral centre.

Chiara Fois1, Stjepana Kovac2, Aytakin Khalil3, Gülnur Tekgöl Uzuner4, Beate Diehl5, Tim Wehner5, John S Duncan5, Matthew C Walker5.   

Abstract

OBJECTIVES: To define factors that predict whether patients with pharmacoresistant focal epilepsy are offered epilepsy surgery (including invasive EEG) and the main reasons for not proceeding with these after non-invasive presurgical evaluation.
METHODS: We retrospectively analysed data from 612 consecutive patients with focal epilepsy admitted to a video-EEG Telemetry Unit for presurgical evaluation, and used a multivariate logistic regression model to assess the predictive value of factors for being offered potentially curative surgery.
RESULTS: In the multivariate analysis, bilateral lesions on MRI (OR: 0.10; 95% CI 0.03 to 0.24), no lesion (OR: 0.33; 95% CI 0.22 to 0.49) or extratemporal lobe epilepsy (OR: 0.30; 95% CI 0.20 to 0.45) were the only factors that significantly reduced the probability of being offered surgery. 32% of patients who were offered epilepsy surgery decided against proceeding.
CONCLUSIONS: There was a low chance (<10%) of being offered surgery if there were bilateral lesions on MRI and extratemporal lobe epilepsy. Patients should be given advice on the risk/benefit ratio and of realistic outcomes of epilepsy surgery; this may help reduce the number of patients who refuse surgery after comprehensive workup. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/

Entities:  

Keywords:  EPILEPSY, SURGERY; NEUROSURGERY; TELEMETRY

Mesh:

Year:  2015        PMID: 25935890     DOI: 10.1136/jnnp-2014-310148

Source DB:  PubMed          Journal:  J Neurol Neurosurg Psychiatry        ISSN: 0022-3050            Impact factor:   10.154


  6 in total

1.  Prospective validation of a machine learning model that uses provider notes to identify candidates for resective epilepsy surgery.

Authors:  Benjamin D Wissel; Hansel M Greiner; Tracy A Glauser; Katherine D Holland-Bouley; Francesco T Mangano; Daniel Santel; Robert Faist; Nanhua Zhang; John P Pestian; Rhonda D Szczesniak; Judith W Dexheimer
Journal:  Epilepsia       Date:  2019-11-29       Impact factor: 5.864

2.  Estimation of brain network ictogenicity predicts outcome from epilepsy surgery.

Authors:  M Goodfellow; C Rummel; E Abela; M P Richardson; K Schindler; J R Terry
Journal:  Sci Rep       Date:  2016-07-07       Impact factor: 4.379

3.  Quantification and Selection of Ictogenic Zones in Epilepsy Surgery.

Authors:  Petroula Laiou; Eleftherios Avramidis; Marinho A Lopes; Eugenio Abela; Michael Müller; Ozgur E Akman; Mark P Richardson; Christian Rummel; Kaspar Schindler; Marc Goodfellow
Journal:  Front Neurol       Date:  2019-10-01       Impact factor: 4.003

4.  The role that choice of model plays in predictions for epilepsy surgery.

Authors:  Leandro Junges; Marinho A Lopes; John R Terry; Marc Goodfellow
Journal:  Sci Rep       Date:  2019-05-14       Impact factor: 4.379

5.  Addressing the epilepsy surgery gap: Impact of community/tertiary epilepsy center collaboration.

Authors:  Keyan Peterson; Suzette LaRoche; Tiffany Cummings; Valerie Woodard; Anna-Marieta Moise; Heidi Munger Clary
Journal:  Epilepsy Behav Rep       Date:  2020-10-29

6.  Presurgical video-EEG monitoring with foramen ovale and epidural peg electrodes: a 25-year perspective.

Authors:  Gadi Miron; Christoph Dehnicke; Heinz-Joachim Meencke; Julia Onken; Martin Holtkamp
Journal:  J Neurol       Date:  2022-06-15       Impact factor: 6.682

  6 in total

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