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Predicting verbal memory decline following temporal lobe resection for epilepsy

Journal article
Authors Sofia Ljunggren
Lena Andersson-Roswall
Henrik Imberg
Hans Samuelsson
Kristina Malmgren
Published in Acta Neurologica Scandinavica
Volume 140
Issue 5
Pages 312-319
ISSN 0001-6314
Publication year 2019
Published at Department of Mathematical Sciences
Department of Psychology
Institute of Neuroscience and Physiology, Department of Clinical Neuroscience
Pages 312-319
Language en
Keywords epilepsy surgery, penalized regression, temporal lobe resection, verbal memory decline, neuropsychological assessment, surgery, lobectomy, performance, cognition, seizures
Subject categories Neurology


Objectives The aim of the study was to develop a prediction model for verbal memory decline after temporal lobe resection (TLR) for epilepsy. The model will be used in the preoperative counselling of patients to give individualized information about risk for verbal memory decline. Materials and Methods A sample of 110 consecutive patients who underwent TLR for epilepsy at Sahlgrenska University Hospital between 1987 and 2011 constituted the basis for the prediction model. They had all gone through a formal neuropsychological assessment before surgery and 2 years after. Penalized regression and 20 x 10-fold cross-validation were used in order to build a reliable model for predicting individual risks. Results The final model included four predictors: side of surgery; inclusion or not of the hippocampus in the resection; preoperative verbal memory function; and presence/absence of focal to bilateral tonic-clonic seizures (TCS) the last year prior to the presurgical investigation. The impact of a history of TCS is a new finding which we interpret as a sign of a more widespread network disease which influences neuropsychological function and the cognitive reserve. The model correctly identified 82% of patients with post-operative decline in verbal memory, and the overall accuracy was 70%-85% depending on choice of risk thresholds. Conclusions The model makes it possible to provide patients with individualized prediction regarding the risk of verbal memory decline following TLR. This will help them make more informed decisions regarding treatment, and it will also enable the epilepsy surgery team to prepare them better for the rehabilitation process.

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