Detecting psychiatric comorbidity in patients with epilepsy or non epileptic attack disorder at a specialist neuropsychiatry tertiary referral centre: a clinical audit.

R. Goggins, F. Pattison, M. Upton and J. M. Bird.

Aims and methods

Examining our hospital database we identified psychiatric comorbidity in patients suffering with epilepsy or non epileptic attack disorder. To improve detection in successive audit cycles, patients were assessed using a standardised questionnaire (SCL-90-R) and a structured interview following formal training in SCAN 2.1.

Results

From the database 78 patients (14%) out of a total of 549 were identified as having an ICD-10 psychiatric diagnosis. For inpatients, in two successive audit cycles, the detection rate was 58% and 48% respectively. The SCL-90-R had high sensitivity and specificity in predicting ICD-10 diagnoses.

Clinical implications

Psychiatric comorbidity is common in patients suffering with epilepsy or non epileptic attack disorder. The SCL-90-R questionnaire can be used as a useful tool in screening such patients for psychiatric comorbidity.

Key words: Non-epileptic attack disorder, detection, prognosis

Introduction

An audit, approved by the local audit committee, was conducted at The Burden Centre. This is a specialist neuropsychiatry tertiary referral centre, with a long history of managing patients with complicated epilepsy and non epileptic attack disorder.

Psychiatric comorbidity is common in patients with seizures (Trimble 1991). In specialty referral clinics for epilepsy, the prevalence is thought to be 25% to 50% (Stevens JR 1988). Of note, approximately 20% of patients attending specialist epilepsy centres do not have epilepsy (McDade and Brown 1992) but are suffering with non-epileptic attack disorder. To complicate matters the percentage of patients suffering with non epileptic attack disorder that also have epilepsy is of the order of 25% (Betts and Boden, 1992).

Detecting and treating psychiatric comorbidity can improve prognosis in both epilepsy and non epileptic attack disorder (Wolf 1997, Hermann 2000, Muller 2001).

Method

The aim of the audit was firstly to establish the detection rate of psychiatric comorbidity in patients assessed at the Burden Centre presenting with a history of epilepsy or non epileptic attack disorder. We then aimed to improve the detection rate by using a standardised questionnaire and interview schedules.

The first cycle of the audit was conducted by analysing data on all patients with epilepsy or non epileptic attack disorder that had been assessed at the Burden Centre over a one year period. This was achieved by scrutinising The Burden Neuropsychiatric Database. This is a comprehensive relational database written in Access 2 designed and built with a view to collating a wide range of data from all the patients assessed at the Burden Centre. The data includes seizure semiology, neuropsychiatric aetiology and history, drug history, investigation results and appointment details including medication, seizure frequency and an impact of epilepsy scale. From the database the rate of detection of psychiatric comorbidity was established (Table 1).

In order to see if the detection rate could be improved (Audit Cycle 2), 33 patients consecutively admitted with epilepsy or non epileptic attack disorder were prospectively assessed using a standardised interview (Schedules for Clinical Assessment in Neuropsychiatry Version 2.1 (SCAN 2.1 Wing et al. 1990)) and a self-report questionnaire, (the Symptom Checklist-90-Revised (SCL-90-R Derogatis 1994). SCAN 2.1 is a structured clinical interview schedule with semi-standardized probes aimed at assessing, measuring and classifying the psychopathology and behaviour associated with the major psychiatric disorders of adult life. Administration time varies between 60 and 90 minutes. A resident clinician was formally trained in SCAN 2.1. The SCL-90-R is a 90-item self-report symptom inventory designed to reflect the psychological symptom patterns of community, medical and psychiatric respondents. Each item is rated on a 5-point scale of distress. The SCL-90-R has high validity and reliability in neuropsychiatric population (Derogatis 1994). It has 9 primary symptom dimensions including: Somatisation, Obsessive-Compulsive, Interpersonal Sensitivity, Depression, Anxiety, Hostility, Phobic Anxiety, Paranoid Ideation and Psychotism. Raw scores are converted to t scores for each dimension.

One month later a third audit cycle was conducted prospectively on a further 21 consecutive inpatients using the SCL-90-R questionnaire with SCAN 2.1. All patients in cycles 2 and 3 completed the audit. Psychiatric diagnoses were formulated in accordance with ICD-10 diagnostic criteria.

Patients with significant psychiatric symptoms not fulfilling an ICD-10 diagnosis were classified under the category 'symptoms not diagnostic' in Cycle 1.

Patients were divided into 3 groups: patients with epilepsy, patients with non epileptic attack disorder and patients where the seizure type was unclassified at the time of the assessment. Those with epilepsy were classified in accordance with the classification system proposed by the International League Against Epilepsy (ILAE 1981).

Results

1158 patients were identified on the Burden Neurological Database. Of these 549 had a diagnosis of epilepsy, non epileptic attack disorder or a seizure type unclassified. 34 (6%) were identified as having significant psychiatric symptoms and a further 78 (14%) fulfilled criteria for a psychiatric disorder. 13% of patients with epilepsy suffered with psychiatric comorbidity (8% fulfilling criteria for an ICD-10 diagnosis). For the non epileptic attack disorder and unclassified groups, 5% and 2.2% respectively, were recorded as having psychiatric comorbidity. For audit cycles 2 and 3, 67 and 57% respectively suffered with psychiatric comorbidity (Table 3).

Table 1. Psychiatric comorbidity in cycle 1.

Groups Symptoms not diagnostic ICD-10 diagnosis Total comorbidity
n (%) n (%) n (%) n (%)
Audit Cycle 1 (Retrospective) 549 34 (6%) 78 (14%) 112 (20%)
Epilepsy
398 (72%)
27 (5%) 45 (8%) 72 (13%)
Non epileptic attack disorder 105 (19%) 6 (1%) 22 (4%) 28 (5%)
Seizure type Unclassified Disorder 46 (8%) 1 (0.2%) 11 (2%) 12 (2.2%)


Table 2. Psychiatric comorbidity in cycle 2.

Groups Symptoms not diagnostic ICD-10 Diagnosis Total comorbidity
n (%) n (%) n (%) n (%)
Audit Cycle 2
(Prospective) 33
2 (6%) 19 (58%) 22 (67%)
Epilepsy 15 (46%) 1 (3%) 6 (18%) 7 (21%)
Non epileptic attack disorder
10 (30%)
1 (3%) 9 (27%) 10 (30%)
Seizure type Unclassified
8 (24%)
0 3 (9%) 3 (9%)

Table 3. Psychiatric comorbidity in cycle 3.

Groups Symptoms not diagnostic ICD-10 Diagnosis Total comorbidity
n (%) n (%) n (%) n (%)
Audit Cycle 3 (Prospective) 21 1 (5%) 11 (52%) 12 (57%)
Epilepsy 9 (43%) 0 4 (19%) 4 (19%)
Non epileptic attack disorder
8 (38%)
2 (9.5%) 5 (23.8%) 7 (33%)
Seizure type Unclassified
4 (19%)
0 1 (5%) 1 (5%)


A t score greater than 62 from at least two of the nine dimensions on the SCL-90-R correlated with diagnoses established by SCAN 2.1 with a sensitivity of 75% and a specificity of 69%. The positive predictive value was 79% (Table 4). The SCL-90-R correlated more accurately with SCAN 2.1 in audit cycle 3 with scores of 80%, 91% and 89% respectively (Table 5).


Table 4. SCL-90-R: a screening tool for psychiatric diagnoses.

SCL-90-R
(2 t scores >62)
ICD-10 Psychiatric diagnosis present ICD-10 Psychiatric diagnosis absent Total
Positive 15 4 19
Negative 5 9 14
Total 20 13 33


Table 5. SCL-90-R: a screening tool for psychiatric diagnoses.

SCL-90-R
(2 t scores >62)
ICD-10 Psychiatric diagnosis present ICD-10 Psychiatric diagnosis absent Total
Positive 8 1 9
Negative 2 10 12
Total 10 11 21

The most common seizures classified were complex partial seizures with secondary generalisation accounting for 31% of the total. The most common ICD-10 diagnoses were alcohol and substance abuse (22%), depressive disorders (16.5%), neurotic and somatoform disorders (16%) and learning disability (32%).

Discussion

From the results above, 2 t scores greater than 62 from at least 2 dimensions on the SCL-90-R was predictive of psychiatric diagnoses with relatively high sensitivity and specificity. It therefore may be an effective and simple tool in improving detection rates of psychiatric comorbidity in patients with epilepsy or non epileptic attack disorder.

Table 1 displays rates of psychiatric comorbidity for both inpatients and outpatients. Detection rates are much lower than for later cycles. This is expected as cycles 2 and 3 evaluate inpatients only. For cycles 2 and 3, 90% and 62.5% of patients with non epileptic attack disorder respectively fulfilled criteria for an ICD-10 diagnosis. Non epileptic attack disorder was defined broadly and was not taken to imply dissociative seizures only. They involve "a sudden, usually disruptive, change in a person's behaviour, perception, thinking, or feeling which is usually time limited and which resembles, or is mistaken for, epilepsy but which does not have the characteristic electrophysiological changes detectable by electroencephalography which accompanies a true epileptic seizure" (Betts and Boden, 1991). Although the cause cannot always be identified, there are many different conditions that can cause non epileptic attack disorder. These can be grouped into four main categories:

neurological, cardiovascular, psychological, and other causes.

Conclusion

There are a number of limitations to the audit. Only comparisons between the second and third groups are admissible as the first cycle includes both inpatients and outpatients while the second and third cohorts are based on inpatient series only. In addition the samples are independent and the numbers are relatively small. However the results are not intended to provide evidence of statistical significance, rather to highlight methods of improving detection rates of psychiatric comorbidity.

Authors

First author: Dr Ray Goggins, Specialist Registrar in Old Age Psychiatry, Southmead Hospital, Westbury-on-Trym, Bristol, BS10 5NB.

Dr Fiona Pattison, Clinical Assistant, The Burden Centre, Frenchay Hospital, Frenchay Park Road, Bristol, BS16 1JB.

Dr Mark Upton, Consultant Psychiatrist, Pyrland House, Cheddon Road, Taunton, Somerset TA2 7AU.

Dr Jonathan Bird, Consultant Neuropsychiatrist, The Burden Centre, Frenchay Hospital, Frenchay Park Road, Bristol, BS16 1JB.

References

Betts T, Boden S. 1991. Pseudoseizures. In: Women and Epilepsy, M. Trimble (Ed.) pp.243-259. Wiley, Chichester.

Derogatis L. R. 1994 SCL-90-R: Administration, Scoring and Procedures Manual. National Computer Systems, Inc., Minneapolis.

Hermann BP, Seidenberg M, Bell B. Psychiatric comorbidity in chronic epilepsy: identification, consequences, and treatment of major depression.
Epilepsia. 2000;41 Suppl 2:S31-41.

Muller B. 2001. Psychological approaches to the prevention and inhibition of nocturnal epileptic seizures: A meta-analysis of 70 case studies. Seizure 2001; 10: 13-33.

Sheehan DV, Lecrubier Y. 2002 M.I.N.I. Plus Medical Outcomes Systems.

Stevens JR. Psychiatric aspects of epilepsy. J Clin Psychiatry 1988 Apr;49 Suppl:49-57.

Trimble 1991. The psychoses of epilepsy. New York: Raven Press.

Wing, J.K., Babor, T., Brugha, T., Burke, J., Cooper, J.E., Giel, R., Jablensky, A., Regier, D., Sartorius, N. (1990) SCAN: Schedules for clinical assessment in neuropsychiatry. Arch Gen Psych. 47, 589-593.

Wolf P 1997. Behavioural therapy. In: Epilepsy: A Comprehensive Textbook, (Eds J. Engel and T.A. Pedley) pp.1359-1364. Lippincott-Raven Publishers, Philadelphia.

Acknowledgement
Special thanks to the nursing staff at the Burden Centre for their kind assistance.

Declaration of Interest-nil

First Published July 2003

 


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