Factors Associated with Quality of Life in Adult Epilepsy Patients: a Hospital Based Study from South India

Introduction

Quality of life research has been performed in almost all areas of medicine, historically beginning with oncology and reaching also the field of neurology. Quality of life in epilepsy has become a critical measure in health care (Cramer 1994) due to the increased use in clinical research and practice (Hermann, 1993& Jacoby, 1992).

Quality of life had given rise to numerous discussions and debates in health care since late 1980 throughout the world. QOL had under gone a marked change from well-being of patients with chronic health care problems to an important outcome measure. (Vickrey, 1993-94 & Mihara, 1994).

Seizures in 70-80% of people who develop epilepsy are well controlled by antiepileptic drug (AED); treatment is clearly shown in epidemiological studies (Sander, 1993) and research shows that quality of life does not diminish very greatly in groups of well controlled epilepsy (Jacoby, 1992). In other 20-30% of groups whose seizures are chronic and intractable, the QOL may be less positive. However, it has been reported previously that there is a clear relationship between the severity of epilepsy and QOL; the impact of epilepsy on QOL is complex and may be mediated by a number of different factors (Collings, SJ. 1990 & Collings, JA 1990) including patients own perceptions of themselves, their condition and its treatment. 

The studies on factors influencing quality of life showed seizure frequency (Guekht. et al., 2007 & Tlusta, et al., 2009) to be one of the most important factors along with comorbid psychiatric conditions (Tlusta, et al., 2009) and symptoms of depression  (Canuet et al 2009) . Other determinants of quality of life were seizure worry (Loring, et al 2004) duration of disease (Canuet et al 2009) and employment (Tlusta, et al., 2009).

The importance on the application of quality of life assessment in research concerning epidemiology, clinical trials, quality assurance, and individual patient care are well investigated .In terms of epidemiology, the description of the quality of life of representative population samples helped in identifying poor QOL in a clinical population in comparison to a healthy reference group. In clinical studies, the effects of interventions in longitudinal and randomized cohort studies on QOL were investigated. In quality assurance programmes the use of QOL assessments was to capture the benefits of the care strategy in order to assess the QOL delivered and to improve the overall treatment of the patient in an institution.   In individual care QOL helped to plan ,monitor and evaluate individual care for that patient taking account the perceptions ,wishes and priorities of the patient.     

This study attempts to investigate factors associated with quality of life in adult epilepsy patients, also focusing in particular on the uses of QOL as an out-come measure on different dimensions of socio-demographic, type and treatment of epilepsy.  The intention is to identify factors which cause good and poor quality of life and aims to provide useful information to improve their well-being.

Method and Materials
         
Design and Sample

A cross-sectional study was performed to examine quality of life in 560 adult epilepsy patients. Non Random consecutive sampling method was adopted. This group consisted of 337 males and 223 females (age range 18-50). Each patient was interviewed and assessed by a clinical psychologist and neurologist. Informed consent was taken from all participants.

–    Inclusion Criteria: Age between 18-55years and having a definite diagnosis of epilepsy.

–    Exclusion Criteria: Patients who had malignant epilepsy syndromes accompanied by a mental handicap, family history of psychiatry, psychosis, presence of severe psychiatric disturbances and non-epileptic attacks in epilepsy patients were excluded.

Procedure and Instruments

They were assessed on clinical, sociodemographic data, details on epilepsy, AED whether monotherapy or polytherapy. All the patients were interviewed on psychiatric problems and diagnosed according to the International Statistical Classification of Diseases and Related Health Problems 10th Revision (ICD-10) for Mental and Behavioral disorders. The psychiatric diagnosis was made clinically by a qualified clinical psychologist for anxiety and depressive disorders. Clinical details of epilepsy were given by the neurologist. We used QOLIE -31 scale of quality of life which is a modified version of QOLIE-89(Quality of life in epilepsy).QOLIE-31 (Cramer, J.A., et al 1998) consists of 31 questions divided into 7groups (subscales). Liverpool seizure severity scale (LSSS) (Baker, G.A., et. al., 1991) was used to assess seizure severity. The scale assesses perception of seizure control and ictal postictal effects in two subscales.     

In Quality of Life, the subscales which were assessed are seizure worry, overall quality of life (overall QOL), emotional wellbeing, Energy/fatigue, cognitive functioning, medication effects and social functioning. In the present study we considered the score of the each subscale and total score; higher score indicates better quality of life. The patients were divided into two groups separated by median 50(0-100 scale) into >50 as good outcome and <50 as poor outcome on quality of life. This Division is an accepted procedure where cutoffs on an instrument are not given.  

Statistical Tests Used

Descriptive statistics was done for socio-demographic data, seizure type, AEDs, QOLIE and psychiatric diagnosis. Analysis of variance (ANOVA’s) one way was done for comparing the changes in seizure type and QOLIE subscale’s.  Multiple logistic regression analysis with step-down procedure was employed in data analysis. For ANOVA P value less than 0.01 was taken as significant and for Logistic Regression Odds Ratio with 95% confidence interval were considered. SPSS package was used for analysis.

Results

Study population comprised of 337 males and 223 females with mean age of 29.78(18-55) years. According to demographic data most of them were males, married residing in urban areas. The study shows patients were mostly educated either students or working nonprofessionals (Table I). Duration of epilepsy (mean value 9.36 years and SD – 8.) and Liverpool seizure severity scale (mean value of severity score 32.1 and SD-25.1) are continuous variables ranging from zero to maximum hence mean and standard deviations are given.

Most of epilepsy patients had no family history, on single AED, well controlled and partial (focal, local) seizures. Frequency of seizures were categorized into three groups, well controlled on AED(, refractory seizures (Refractory epilepsy may be defined as failure of adequate trials of two tolerated and appropriately chosen and used AED schedules to achieve sustained seizure freedom.) and nil seizures not on AEDs. Most of the patients show well controlled seizures 322 (57.5%). (Table II).

Psychiatric diagnosis was present in 36% of our study population. Most of psychiatric problems were depression and anxiety. Depression is a major condition in 105(18.75%) epilepsy patients in this study. Out of 560 cases, 205 patients had psychiatric conditions out of these 45(22%) cases had poor QOLIE (Table III). One way analysis of variance was done on seven sub scales of QOLIE i.e. seizure worry, overall QOLIE emotional well-being, energy/fatigue, cognitive functioning, medication effects, social functioning and seizure type.  On ANOVA no significant difference was found between subscales and seizure frequency mainly on refractory seizures as shown in Table IV. 

Predictors of good QOLIE were single anti-epileptic medication (AED) and absence of psychiatric diagnosis on Univariate analysis. (Table V). Male sex indicated Odds ratio (OR) 1.17 but 95% confidence intervals of OR (0.75, 1.84) were not significant similarly on marital status (single) indicated Odds ratio (1.495) significant but confidence intervals of Odds ratio (1.029 -0.174) were not significant. On multiple logistic regression steps down procedure, factors which are found to be significantly associated with poor quality of life were multiple AEDs and presence of a psychiatric diagnosis at step 8. Psychiatric diagnosis was the major predicting factor for poor QOLIE (Table VI).