Abstracts

Rationale: The importance of accessible, structured clinical data for effective patient care, research and service evaluation is increasingly recognised. Electronic data capture (EDC) systems can improve clinical data accessibility, quality and analysis. Here we explore EDC use to characterise a cohort of patients evaluated for epilepsy surgery discussed in a multi-disciplinary team (MDT) meeting. Methods: An EDC system based on a portable document format (PDF) pro forma was developed to record weekly epilepsy surgery MDT meetings in a tertiary referral centre, replacing the paper-based system. The PDF pro forma compromised structured and free text fields to capture data including patient demographics, antecedent history, history of status epilepticus, injuries, investigations and outcome. Dynamic PDF features including menus were used to capture current and previous drugs and seizure semiology using the semiological seizure classification (1).  A pro forma was completed for each case, reviewed and locked after each meeting by the meeting chairperson. Software was developed to automatically extract and summarise data across the collection of PDF files. Results: From July 2011 to June 2017, data for 841 case discussions (2.7 cases/week) were summarised automatically. 731 individual patients were presented (some cases were re-discussions). The following characteristics emerged: age 36.8 ± 11.6 years (mean ± s.d., range 17-85), 53.2% male, 86.4% right-handed, 41.3% with one or more epilepsy risk factor and 14.6% with a history of status epilepticus. The prevalence of anxiety was 13.8% and depression 25.7%. The number of seizure types was 2.0 ± 1.0. The three most frequent seizure types were automotor (52.4% of patients), secondarily generalised tonic-clonic (GTC, 49.5%) and dialeptic seizures (29.8%). Patients were currently prescribed 2.5 ± 1.3 anti-epileptic drugs, having been previously prescribed 3.8 ± 2.9 other drugs. The three most frequent current drugs were levetiracetam (43.9%), lamotrigine (31.9%), and clobazam (31.5%). Investigations reviewed included video telemetry (87.6% abnormal, 2.6% normal, 9.9% not done), structural MRI (66.2% abnormal, 28.6% normal, 4.9% not done), 18F-fluorodeoxyglucose PET (27.9% abnormal, 14.6% normal, 57.5% not done), language fMRI (71.6% of patients), and neuropsychiatry (78.9%) and neuropsychology assessment (93.1%).  The meeting conclusion was recorded as offer resection (19%), intracranial EEG (23%), further non-invasive investigation (23%), not for resection (19%), and other (15%). Conclusions: A PDF-based EDC system for epilepsy surgery multi-disciplinary team meetings facilitated data capture and service evaluation. Benefits of EDC included integrity, completeness and accessibility of data. The EDC system facilitated characterisation of this drug refractory cohort, revealing a high percentage with GTCs and psychiatric co-morbidities.  Only ~20% were judged to be able to immediately progress to resection, whereas ~25% required intracranial EEG. References: (1) Lüders et al. Semiological seizure classification. Epilepsia. 1998 Sep;39(9):1006-13 Funding: This work was undertaken at UCLH/UCL who receives a proportion of funding from the Department of Health’s NIHR Biomedical Research Centres funding scheme.