Video-based training improves the accuracy of seizure diagnosis. Issue 4 (8th January 2014)

• Record Type: Journal Article
• Authors: Seneviratne, Udaya; Ding, Catherine; Bower, Simon; Craig, Simon; Leech, Michelle; Phan, Thanh G
• Is Part Of: Journal of neurology, neurosurgery and psychiatry. Volume 85:Issue 4(2014)
• Page Start: 466
• Page End: 470
• Publication Date: 2014-01-08
• Subjects: Neurology -- Periodicals; Nervous system -- Surgery -- Periodicals; Psychiatry -- Periodicals; 616.8
• DOI: 10.1136/jnnp-2013-306618
• Languages: English
• ISSNs: 0022-3050

Abstract

Abstract : Background and aim: The difficulties in differentiating epileptic seizures (ES) from psychogenic non-epileptic seizures (PNES) are well known. However, interventions to enhance diagnostic accuracy have not been well studied. We sought to evaluate the accuracy of discrimination between ES and PNES before and after targeted training among medical students. Methods: A teaching module incorporating videos of typical ES and PNES was used for training. Typical ES and PNES, 10 each, were shown in a random mix. The participants were asked to make a diagnosis as the baseline test, followed by a detailed discussion on videos. One month later, a 1 h lecture was delivered on the diagnosis and classification of seizures, followed by two more tests 3 and 6 months later, using a similar format, but different videos. A group of emergency medicine trainees also went through the preteaching test for comparison. We used summary receiver operating characteristic curves and area under the curve (AUC) to quantify the discriminating ability and z scores to assess the differences between AUC between different stages of training. Results: In medical students, the AUC improved significantly from 0.52 (95% CI 0.49 to 0.55) at the baseline to 0.64 (95% CI 0.59 to 0.69, p<0.001) at 3 months and 0.63 (95% CI 0.57 to 0.69, p<0.001) at 6 months. At 3 and 6 months testing, they achieved results similar to that of emergency medicine trainees (p=0.5). Conclusions: Targeted video-based training increases the accuracy of visual discrimination of seizures short-term and medium-term.