Distinct psychopathology profiles in patients with epileptic seizures compared to non-epileptic psychogenic seizures

被引:17
|
作者
Wang, Albert D. [1 ]
Leong, Michelle [1 ]
Johnstone, Benjamin [2 ]
Rayner, Genevieve [3 ,4 ,5 ,6 ]
Kalincik, Tomas [1 ,7 ]
Roos, Izanne [1 ,7 ]
Kwan, Patrick [2 ,5 ,6 ,7 ]
O'Brien, Terence J. [2 ,5 ,6 ,7 ]
Velakoulis, Dennis [8 ,9 ]
Malpas, Charles B. [1 ,3 ,5 ,6 ,7 ]
机构
[1] Univ Melbourne, Royal Melbourne Hosp, Dept Med, Clin Outcomes Res Unit CORe, Melbourne, Vic 3010, Australia
[2] Univ Melbourne, Royal Melbourne Hosp, Dept Med, Melbourne, Vic, Australia
[3] Univ Melbourne, Melbourne Sch Psychol Sci, Melbourne, Vic, Australia
[4] Univ Melbourne, Dept Med, Austin Hlth, Melbourne, Vic, Australia
[5] Monash Univ, Clayton, Vic, Australia
[6] Alfred Hlth, Dept Neurol, Melbourne, Vic, Australia
[7] Royal Melbourne Hosp, Dept Neurol, Melbourne, Vic, Australia
[8] Royal Melbourne Hosp, Dept Psychiat, Melbourne, Vic, Australia
[9] Univ Melbourne, Dept Psychiat, Melbourne, Vic, Australia
关键词
Epilepsy; Epileptic seizures; Psychogenic non-epileptic seizures; Psychiatric comorbidity; Psychopathology; Machine learning; PERSONALITY-ASSESSMENT INVENTORY; PSYCHIATRIC COMORBIDITY; DEPRESSION; DISORDERS; PACKAGE; STRESS; SAMPLE; MMPI; TOOL; EEG;
D O I
10.1016/j.eplepsyres.2019.106234
中图分类号
R74 [神经病学与精神病学];
学科分类号
摘要
Objective: Similarities in clinical presentations between epileptic seizures (ES) and psychogenic non-epileptic seizures (PNES) produces a risk of misdiagnosis. Video-EEG monitoring (VEM) is the diagnostic gold standard, but involves significant cost and time commitment, suggesting a need for efficient screening tools. Methods: 628 patients were recruited from an inpatient VEM unit; 293 patients with ES, 158 with PNES, 31 both ES and PNES, and 146 non-diagnostic. Patients completed the SCL-90-R, a standardised 90-item psychopathology instrument. Bayesian linear models were computed to investigate whether SCL-90-R domain scores or the overall psychopathology factor p differed between groups. Receiver operating characteristic (ROC) curves were computed to investigate the PNES classification accuracy of each domain score and p. A machine learning algorithm was also used to determine which subset of SCL-90-R items produced the greatest classification accuracy. Results: Evidence was found for elevated scores in PNES compared to ES groups in the symptom domains of anxiety (b = 0.47, 95%HDI = [0.10, 0.80]), phobic anxiety (b = 1.32, 95%HDI = [0.98, 1.69]), somatisation (b = 0.84, 95%HDI = [0.49, 1.20]), and the general psychopathology factor p (b = 1.35, 95%HDI = [0.86, 1.82]). Of the SCL-90-R domain scores, somatisation produced the highest classification accuracy (AUC = 0.74, 95%CI = [0.69, 0.79]). The genetic algorithm produced a 6-item subset from the SCL-90-R, which produced comparable classification accuracy to the somatisation scores (AUC = 0.73, 95%CI = [0.64, 0.82]). Significance: Compared to patients with ES, patients with PNES report greater symptoms of somatisation, general anxiety, and phobic anxiety against a background of generally elevated psychopathology. While self-reported psychopathology scores are not accurate enough for diagnosis in isolation, elevated psychopathology in these domains should raise the suspicion of PNES in clinical settings.
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页数:8
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