Quality Of Life In Epilepsy Inventory-31 Research Articles

Effects of stigma on the quality of life in patients with epilepsy

BackgroundThis study was aimed to evaluate the stigma and quality of life (QoL) in adult patients with epilepsy (PWEs) and explore the relationship between stigma and QoL.MethodsTwo hundred and ninety-eight PWEs admitted to the Epilepsy Center of the First Affiliated Hospital of Chongqing Medical University during September 2020 and March 2021 were enrolled in this study. All participants completed self-reported questionnaires including the Stigma Scale for Epilepsy and the Quality of Life in Epilepsy Inventory-31 (QOLIE-31).ResultsA total of 146 (49%) PWEs reported an experience of stigma. The total score of QOLIE-31 and the individual scores of seven subscales (worry about new seizures, emotion, well-being, energy and fatigue, cognitive impairment, medication effect, and social function) were significantly decreased in these patients (P < 0.001). Multivariate stepwise linear regression analysis showed that the annual household income per capita, the number of antiseizure medications and stigma had statistically significant effects on QoL (P < 0.05). Among them, stigma had the most significant negative effect.ConclusionsNearly half of PWEs have experienced stigma. Stigma, lower household income per capita, and polypharmacy treatment are associated with poorer QoL. Stigma has the most obvious negative impact.

First epileptic seizure and quality of life – A prospective study

ObjectiveImpaired QoL and depression are common in patients with chronic epilepsies; however, data on the impact of a first seizure on QoL are sparse. According to the current ILAE-definition of epilepsy, patients may be diagnosed with epilepsy immediately after the first seizure, if EEG and/or imaging findings are abnormal. Patients with normal findings in imaging and EEG are not diagnosed as having epilepsy. We investigated QoL in patients after a first seizure with and without a consecutive diagnosis of epilepsy to detect differences between groups within the first year after seizure. MethodsWe examined patients (n = 152) after a first epileptic seizure and six and 12 months thereafter using demographic, clinical and QoL-related questionnaire data (Short Form-36 Health Survey (SF-36), Quality of Life in Epilepsy Inventory-31 (QOLIE-31), Beck’s depression inventory II (BDI-II)). ResultsPatients diagnosed with epilepsy after the first seizure showed a tendency of reduced mental health-related QoL six (p =.098) and 12 months (p =.092) after the first seizure compared to patients who were not diagnosed with epilepsy, but were diagnosed as having had a single first seizure. There were no significant differences between the two groups in physical health-related QoL. Multiple regression analyses showed that especially depressive symptoms explained 22.0 – 48.7 % of the variance in mental health-related QoL six (p <.001) and 12 months (p <.001) after the first seizure. Physical health-related QoL was especially predicted by age (p <.001), group (p =.002) and recurrent seizures (p = < 0.001). In PWE, there was a statistical trend with improving QOLIE-31 overall scores from six to 12 months (p =.086). ConclusionOur results suggest that QoL may be impaired in patients diagnosed with epilepsy early, immediately after the onset of disease. Early follow-up monitoring from the beginning of patient career is important for possible interventions and to improve patients' daily life in the long term.

Patient-reported outcomes in epilepsy: a case study exploring their usage and impact.

This study aimed to obtain insights from epilepsy specialists on the use of Patient-Reported Outcome (PRO) measures and how they can affect the management of people with epilepsy and healthcare resource utilization. The heads of two referral units for people with epilepsy at one tertiary care hospital were invited to respond to a structured survey. Paper-based questionnaires and face-to-face interviews were the main modalities used to measure the quality of life of people with epilepsy. The Quality of Life in Epilepsy Inventory-31 (QOLIE-31), the Adverse Event Profile (adult centre), the Generalized Anxiety Disorder-7, Short-Form Health Survey 36, PSY-Flex, SAFA and Child Behavior Checklist (paediatric centre) were the most used scales. There was consensus about the favourable impact of PRO upon patient management, disease management and measurement of the success of a treatment. Both respondents considered the PRO as important as other main indicators like efficacy and tolerability of the treatment. Lack of time, personnel and economic resources was identified as a barrier on the use of PRO. The PRO could reduce the number of visits, exams and treatments, and increase the time spent on each patient and the number of neuropsychological, psychological and rehabilitation services. The standardized use of PRO was considered useful and the increase in human resources was considered a priority to achieve this goal. Despite the heterogeneity in the actual collection of PRO, there was a uniform perception about their role to optimize the care of people with epilepsy.

The effect of sleep disorders on quality of life in patients with epilepsy: A multicenter study from Turkey

ObjectiveWe aimed to investigate sleep disorders in patients with epilepsy (PWE) and to investigate the effects of sleep disorders on quality of life. MethodsIn our multicenter study conducted in Turkey, 1358 PWE were evaluated. The demographic and clinical data of the patients were recorded. The Insomnia Severity Index (ISI), Epworth Sleepiness Scale (ESS), Pittsburgh Sleep Quality Index (PSQI), Beck Depression Inventory (BDI), and Quality of Life in Epilepsy Inventory-10 (QOLIE-10) were administered. ResultsThe mean age of 1358 patients was 35.92 ± 14.11 (range, 18–89) years. Seven hundred fifty-one (55.30 %) were women. Some 12.7 % of the patients had insomnia (ISI > 14), 9.6 % had excessive daytime sleepiness (ESS > 10), 46.5 % had poor sleep quality (PSQI > 5), and 354 patients (26.1 %) had depressive symptoms (BDI > 16). The mean QOLIE-10 score was 22.82 ± 8.14 (10–48). Resistant epilepsy was evaluated as the parameter with the highest risk affecting quality of life Adjusted odds ratio (AOR = 3.714; 95 % confidence interval (CI): [2.440–5.652] < 0.001)). ISI (AOR = 1.184; 95 % CI: [1.128–1.243]; p < 0.001), ESS (AOR = 1.081; 95 % CI: [1.034–1.130]; p < 0.001), PSQI (AOR = 0.928; 95 % CI: [0.867 – 0.994]; p = 0.034), BDI (AOR = 1.106; 95 % CI: [1.084–1.129]; p < 0.001), epilepsy duration (AOR = 1.023; 95 % CI: [1.004–1.041]; p = 0.014), were determined as factors affecting quality of life. SignificanceSleep disorders are common in PWE and impair their quality of life. Quality of life can be improved by controlling the factors that may cause sleep disorders such as good seizure control, avoiding polypharmacy, and correcting the underlying mood disorders in patients with epilepsy.

Evaluation of quality of life's prognostic factors in people with functional seizures

AimsFunctional non-epileptic seizures significantly impact the quality of life of patients. We aimed to identify prognostic factors associated with the quality of life in individuals with functional non-epileptic seizures. Subjects and methodsAdult patients diagnosed with definite or documented functional seizures based on LaFrance's criteria (n=72) were enrolled at the time of diagnosis. Quality of life was assessed using the Quality of Life in Epilepsy Inventory-31 (QOLIE-31) at diagnosis and at a six-month follow-up. Demographic and medical information was collected, and psychiatric comorbidities were evaluated using validated scales. ResultsComparisons between diagnosis and follow-up did not reveal any factors associated with improvement in quality of life at six months after diagnosis. However, multivariable analysis, adjusted for age, sex, diagnosis delay, and frequency of functional seizures showed a significant cross-sectional relationship with a QOLIE-31 score decrease of 0.66 [95% CI −0.93;−0.39], −0.32 [−0.61; −0.03], and −0.22 [−0.42; −0.02] for an increase of 1 point of BDI-2 score, BAI score, and CTQ score respectively. ConclusionPsychiatric comorbidities, particularly depression and anxiety, are associated with worse quality of life in patients with functional seizures. This underscores the crucial importance of multidisciplinary care involving both neurological and psychiatric expertise when managing individuals with functional seizures.

Quality of life in epilepsy: comparison between Indonesian version of QOLIE-10 and QOLIE-31

Quality of Life in Epilepsy Inventory 10 (QOLIE-10) and QOLIE-31 is used to measure patient’s quality of life. While longer version of QOLIE-31 is thought to have higher validity and reliability, QOLIE-10 is shorter and more practical to use in clinical setting. This study aimed to compare Indonesian version of QOLIE-10 and QOLIE-31. This was a cross sectional study conducted at Dr. Moewardi General Hospital, Surakarta, Indonesia. Participant were asked to complete the Indonesian version of QOLIE-10 and QOLIE-31, and data obtained then analysed to find the correlation between QOLIE-10 and QOLIE-31. A total of 51 epilepsy patients were included on this study. We observed correlation of 0.41 to 0.84 (p&amp;lt;0.05) for each item of QOLIE-10 with their respective QOLIE-31 subscale. We also found correlation value of 0.898 (p=.000) between total score of QOLIE-10 and QOLIE-31 showing strong positive correlation of two questionnaire. Independent T-sample test on QOLIE-10 and QOLIE-31 T-score result of p=.361, showing no statistical difference between two questionnaires. Frequency of seizure is correlated with patients’ quality of life. QOLIE-10 has strong positive correlation to QOLIE-31, which make it a useful tool to assess epilepsy patients’ quality of life.

Quality of life of persons with epilepsy in Mahenge, an onchocerciasis-endemic area in Tanzania: A cross-sectional study

ObjectiveThis study investigated the quality of life (QoL) of adults with epilepsy living in Mahenge, an onchocerciasis-endemic area in Tanzania with a high prevalence of onchocerciasis-associated epilepsy (OAE). MethodsBetween February and December 2020, persons with epilepsy (PWE) were recruited from four rural villages in Mahenge: Mdindo, Msogezi, Mzelezi, and Sali. For PWE who could not answer the questionnaire due to their mental or physical disability, a family member was asked to answer the questions instead. The Quality of Life in Epilepsy Inventory-31 (QOLIE-31) questionnaire used contained seven domains. The raw domain scores were transformed to 0–100% subscales, with higher scores indicating better QoL. The global QoL was calculated from the subscales using the overall QOLIE-31 score formula. ResultsIn total, 96 PWE were enrolled in the study with a median age of 28 (range: 18–60) years, of whom 45 (47%) were male. The questionnaires were answered by PWE (54.8%) or one of their family members (45.2%). Most PWE were single (81%), and half never attended school. About two-thirds (65%) of PWE were suspected of having OAE, and a third (31%) had a history of head nodding seizures. Most PWE were treated with phenobarbital (85.4%) and had high treatment adherence (96.9%). Still, the number of seizures per week ranged from 0 to 7, with a median of one. The mean global QOLIE-31 score was 66.9 (range: 38.3–92.1) out of 100.0. Predictors of lower QoL were living in Sali Village and experiencing seizures the week before the interview. In contrast, completing primary school and switching to second-line anti-seizure medication were predictors of higher QoL. ConclusionIn order to improve the QoL of PWE in Mahenge, it is vital to optimize anti-seizure medication regimens to decrease the frequency of seizures and to increase the schooling of PWE.

Validity and reliability of the Indonesian version of QOLIE-10

Background: Epilepsy could result in disability and lowered patient's quality of life. Quality of Life in Epilepsy Inventory 10 (QOLIE-10) is a questionnaire to assess epilepsy patients' quality of life, but it has not been translated into Indonesian yet. This study aims to translate QOLIE-10 into Indonesian and analyze its validity and reliability. Methods: This was a cross sectional study conducted at Neurology Clinic, Universitas Sebelas Maret, Surakarta. The translation process consists of two steps, a forward and backward process; each is done by two independent translators. Participants recruited were then asked to complete the Indonesian version of QOLIE-10 twice, with an interval of approximately one month. Results: From the data obtained, we observed an r-value ranging from 0.247 to 0.669 on the pretest and post-test, greater than the critical r-value of 0.235 (p&lt;0.05). We also observed Cronbach's alpha coefficient of 0.938 and 0.909 (p&lt;0.05) for the pretest and post-test, respectively, and the test-retest reliability with r=0.871 (p=0.000). Conclusion: Indonesian version of QOLIE-10 is understandable to Indonesian native speakers, valid, and reliable.

Physical activity in adults with epilepsy: clinical aspects and relationship with cognition and quality of life.

To assess the relationship between the regular practice of PA with clinical and cognitive variables and quality of life (QoL) in PWEs. Habitual Physical Activity Questionnaire (HPAQ) was related to clinical variables, scores on the Mini-Mental State Examination (MMSE), on the Brief Cognitive Battery-Edu (BCB-Edu), on the Satisfaction Scale for Physical Activity (SSPA), and on the Quality of Life in Epilepsy Inventory (QOLIE)-31 in 60 PWEs, with a significance level of p<0.05. The PWEs had a mean age of 42.4±13.6 years, 50% of whom were female. Longer length of epilepsy correlated with lower PA in leisure time (Pearson correlation [r]= -0.276; p-value [p]=0.036). The occupational physical activity scores of the HPAQ correlated positively with perception (r=0.300; p=0.021), memory (r=0.381; p=0.003), semantic verbal fluency test (SVF) (r=0.427; p=0.001), and with the total score in the MMSE (r=0.327; p=0.012). The total HPAQ score correlated with the SVF (r=0.336; p=0.009) and with the MMSE (r=0.254; p=0.049). There was no correlation among the QOLIE-31, the HPAQ, and the SSPA. Longer duration of epilepsy was associated with the lower practice of PA. Physical activity was associated with better performance in aspects of cognition. There was no relationship between QoL and practice and satisfaction with PA, suggesting different psychosocial aspects involved.

Somatic symptoms and related disorders in a large cohort of people with epilepsy: A cohort study.

This study was undertaken to characterize somatic symptoms and related disorders (SSD) in epilepsy. Adults with epilepsy under active follow-up at a tertiary epilepsy center were consecutively enrolled. The diagnosis of SSD was performed by an experienced psychologist based on the structured clinical interview for Statistical Manual of Mental Disorders, 5th edition. Detailed social/demographic data, epilepsy features, psychiatric features, life quality, disability, and economic burden were collected and compared between people with SSD and those without. Bodily distress syndrome checklist, Somatic Symptom Disorder-B Criteria Scale, Patient Health Questionnaire-9, and Generalized Anxiety Disorder seven-item scale (GAD-7) were used to evaluate SSD individuals' somatic symptoms, symptom-related psychological distress, and depressive and anxious symptoms. Quality of life and disability were assessed by Quality of Life in Epilepsy Inventory 31 (QOLIE-31) and World Health Organization Disability Assessment Schedule V.2.0 (WHO DAS 2.0). A risk prediction nomogram was generated using least absolute shrinkage and selection operator (LASSO) analysis and validated. One hundred fifty of 631 participants (24%) were diagnosed with SSD. In people with SSD, the top three most common somatic symptoms were memory impairment, headache, and dizziness (85%, 80%, and 78%, respectively), and multiple systems were involved in most (82%) people with SSD. Compared with people without SSD, those with SSD had lower QOLIE-31 total scores, and higher WHO DAS 2.0 scores and disease economic burdens. LASSO analysis suggested that a history of severe traumatic brain injury, hippocampal sclerosis, low seizure worry and medication effects scores on QOLIE-31, multiple systems affected by somatic symptoms, and a high GAD-7 score were risk factors of SSD. The nomogram was validated for good accuracy in the training and testing cohorts. SSD are likely to be a common comorbidity in epilepsy and harm epilepsy prognosis. Our risk prediction nomogram was successfully developed but needs further validation in larger cohorts.

Determinants of medication adherence in people with epilepsy: A multicenter, cross-sectional survey

ObjectivesPoor medication adherence in people with epilepsy (PwE) increases mortality, hospitalization, and poor quality of life, representing a critical challenge for clinicians. Several demographic, clinical, and neuropsychological factors were singularly found associated with medication adherence in several studies, but the literature lacks a comprehensive study simultaneously assessing all these variables. MethodsWe performed a multicenter and cross-sectional study using online questionnaires with the following clinical scales: Morisky Medication Adherence Scale (MMAS-8), Quality of Life in Epilepsy Inventory 31 (QoLIE-31), Beck Depression Inventory-II (BDI-II), Generalized Anxiety Disorder-7 (GAD-7) and 14-item Resilience scale (RES14) in a population of 200 PwE. We used the ANOVA test and Spearman’s correlation to evaluate the relationship between medication adherence and demographic, clinical (seizure frequency, number of anti-seizure medications), and neuropsychological characteristics. We trained separate machine learning models (logistic regression, random forest, support vector machine) to classify patients with medium–high adherence (MMAS-8 ≥ 6) and poor adherence (MMAS-8 < 6) and to identify the main features that influence adherence. ResultsWomen were more adherent to medication (p-value = 0.035). Morisky Medication Adherence Scale -8 showed a direct correlation with RES14 (p-value = 0.001) and age (p-value = 0.001), while was inversely correlated with BDI-II (p-value = 0.001) and GAD-7 (p-value = 0.001). In our model, the variables mostly predicting treatment adherence were QoLIE-31 subitems, followed by age, resilience, anxiety, years of school, and disease duration. ConclusionOur study confirms that gender, age, and neuropsychological traits are relevant factors in predicting medication adherence to PwE. Furthermore, our data provided the first evidence that machine learning on multidimensional self-report questionnaires could help to develop a decisional support system in outpatient epilepsy clinics.

Anti-seizure medications and quality of life in person with epilepsy

ObjectiveThe goal of this study was to determine the effects of mono-, bi-, and polytherapy anti-seizure medications (ASMs) in terms of seizure reduction and quality of life (QOL) in persons with epilepsy (PWE). MethodsA cross-sectional observational study was conducted. All PWE with age <75 years were recruited and further classified into two groups: responders and non-responders, based on the response of the ASMs to the treatments for reduced seizure frequency since the last one year. Other demographic and clinical data such as seizure frequency, type of seizures, age at onset of seizures, and information about ASMs with their daily doses were assessed for the descriptive analysis. The quality of life was assessed in randomly selected PWE (n = 100) using the quality of life in epilepsy inventory-31 (QOLIE-31) in adults. ResultsWith a total of 486 PWE, the median age (years) was comparable in both groups. Out of these the non-responders group was found to be significantly higher (77.8%) than the responders group (22.2%). In the responders group, the percentage of PWE who were on monotherapy was significantly higher (51.85 %) than those who were on polytherapy (17.59%), whereas in the non-responders group, 21.16% of PWE were on monotherapy and 44.86% were on polytherapy. The duration of epilepsy was similar in both groups, but the average seizure frequency was significantly higher in the non-responders. In QOL assessments, 43% of PWE were observed in the responders group, whereas 57% of PWE were found in the non-responders group. The overall comparative QOL scores were also significantly higher (p < 0.0001) in the responders group as compared to the non-responders group. ConclusionOur findings revealed that those PWE who were on monotherapy showed better reduction in seizure frequency and improved QOL in responder groups as compared to non-responder groups.

Self-perceived burden and associated factors in Chinese adult epilepsy patients: A cross-sectional study.

ObjectivesEpilepsy requires long-term or lifelong treatment, and patients are prone to financial, emotional and psychological burdens that can cause psychological changes during the treatment process. This study aimed to describe the prevalence and associated factors of Self-Perceived Burden (SPB) in Chinese adult epilepsy patients, informing the treatment and nursing of epilepsy.MethodsA total of 143 adult epilepsy patients were included in this study, and the clinical questionnaire survey was conducted at the Third Xiangya Hospital of Central South University in Hunan, China, from March 2022 to June 2022. The sociodemographic and clinical characteristics of adult epilepsy patients were collected using a self-developed questionnaire, and the data on SPB, stigma and quality of life were collected through the Self-Perceived Burden Scale (SPBS), Kilifi Stigma Scale for Epilepsy (KSSE) and Quality of Life in Epilepsy Inventory-31 (QOLIE-31). Multiple linear regression analysis was used to determine the associated factors influencing SPB in adult epilepsy patients.ResultsThe average score of SPBS for the 143 adult epilepsy patients was 30.77 (SD = 9.06), and 89.5% of them had obvious SPB. The results of the univariate analysis showed that residence, monthly household income, duration of epilepsy, type of medication and electroencephalogram finding were associated with SPB (P < 0.05). In Spearman correlation analysis indicated that SPBS score were positively correlated with KSSE score (r = 0.510, P < 0.05) while negatively correlated with QOLIE-31 score (r = −0.506, P < 0.05). Multiple linear regression analysis revealed that factors such as KSSE, type of medication, residence and electroencephalogram finding accounted for 32.8% of the factors influencing SPB in adult epilepsy patients.Conclusion89.5% of adult epilepsy patients have varying degrees of SPB, which is associated with high stigma and poor quality of life. Therefore, during the treatment and nursing of adult epilepsy patients, clinical staff should pay attention to the psychological status of patients, help them reduce their psychological burden, and guide them to develop a healthy lifestyle.

Effects of insomnia and levels of depression and anxiety symptoms on quality of life in people with epilepsy

ObjectivesThe association between insomnia and quality of life (QOL) in epilepsy is poorly understood and may involve interactive variables. We aimed to investigate whether and how insomnia, levels of depression and anxiety symptoms interact to influence QOL in people with epilepsy (PWE).MethodsA consecutive cohort of 179 PWE was enrolled. We collected data on insomnia, levels of depression and anxiety symptoms, and QOL. The Insomnia Severity Index (ISI), Depression Inventory for Epilepsy (NDDI-E), Generalized Anxiety Disorder-7 (GAD-7), and QOL in Epilepsy Inventory (QOLIE-31) were used. The direct, indirect, and total effects of insomnia on QOL were estimated based on a moderated mediation model.ResultsDepression symptom levels mediated the association between insomnia and QOL (B = 0.09 SE = 0.03, p = 0.01). Depression symptom levels accounted for 34.7% of the total effect of insomnia on QOL. The mediating effect of depression symptom levels was positively moderated by anxiety symptom levels (B = 0.09, SE = 0.03, p = 0.01).ConclusionThe effect of insomnia on QOL can be partially explained by the mediation of depression symptom levels. Additionally, improving anxiety symptoms may attenuate the indirect effect of insomnia on QOL through depression symptom levels.

Lack of association between generic brittleness and neuropsychiatric measures in patients with epilepsy

PurposeIn a prior bioequivalence study, generic brittle (GB) patients with epilepsy who were considered at risk of worsened seizures or drug side effects from switching antiepileptic drug (AED) formulations demonstrated no significant difference in their drug levels when switched between a brand and generic AED. An alternative basis for being GB may relate to having a personality or mindset that predisposes to poor outcomes from a formulation switch. The objective of this study was to explore whether GB patients with epilepsy could be differentiated from not GB patients based on standardized measures of personality, mood, outlook, and beliefs. MethodsThis was an exploratory, observational, case-control, non-therapeutic study in patients with epilepsy. Patient interviews were conducted, and histories were collected, yielding each patient (n = 148) to be determined as GB or not GB. Eight neuropsychiatry tests were administered to n = 127 of these patients. Tests included Neuroticism Extraversion Openness Personality Inventory 3 (NEO-PI 3), Life Orientation Test-Revised (LOT-R), Quality of Life in Epilepsy Inventory-89 (QOLIE-89), Adverse Childhood Experiences Score (ACE), Physical Symptoms Questionnaire or Patient Health Questionnaire-15 (PHQ-15), Beck Depression Inventory II (BDI-II), Beck Anxiety Inventory (BAI), and the Beliefs About Medicines Questionnaire Epilepsy (BMQ-Epilepsy). A total of 23 Chi squared analyses, along with logistical regression, were performed to assess which tests and sub-elements associated with GB status. ResultsNone of the neuropsychiatry tests or their sub-elements differentiated GB patients from not GB patients. Results implicate that standardized measures of personality, mood, outlook, and beliefs about their healthcare do not differ between GB and not GB patients with epilepsy, possibly because generic brittleness is caused by factors that neuropsychiatry tests do not measure. ConclusionsWe hypothesized that being GB may relate to having a personality or mindset that predisposes patients to attributing poor outcomes to a formulation switch. However, findings here in patients with epilepsy did not uncover neuropsychiatric factors that predict which patients were GB and which were not GB.

Quality of life for patients with psychogenic nonepilepsy seizures in comparison with age- and gender-matched patients with epilepsy – Cross-sectional study

AimsPatients with psychogenic nonepileptic seizures (PNES), and age- and gender-matched patients with epilepsy (PWE) who utilized an out-patient service were compared regarding quality of life (QoL) and self-reported symptoms of depression. Additionally, the impact of miscellaneous clinical variables including symptoms of depression on QoL in patients with PNES and PWE in real-world settings was assessed. Subjects and methodsAdult patients who had a diagnosis of definite or documented PNES based on LaFrance’s criteria (PNES group, n = 62), or of epilepsy based on results of clinical and EEG procedures (Epilepsy group, n = 61) were enrolled. To assess QoL and evaluate depression, the Quality of Life in Epilepsy Inventory-10 (QOLIE-10) and Neurological Disorders Depression Inventory for Epilepsy (NDDI-E), respectively, were administered. ResultsComparisons between the groups revealed a shorter duration of illness and fewer number of attacks in patients with PNES as compared to the Epilepsy group (p < 0.0001; p = 0.0003, respectively). There was no significant difference between the groups revealed by the QOLIE-10 (p = 0.141), while the patients with PNES tended to have higher NDDI-E scores (p = 0.068). Multiple regression analysis of QOLIE-10 results in the PNES group revealed that NDDI-E score was the sole significant contributor (β = −0.425 p = 0.001). In contrast, NDDI-E score as well as attack frequency had a significant impact on QOLIE-10 results in the Epilepsy group (β = −0.283 p = 0.026; β = −0.272 p = 0.031, respectively). ConclusionIn PWE and patients with PNES who utilized an out-patient service, QoL did not differ significantly between those groups. For treating PNES, psychosocial factors may be a more appropriate indicator of therapeutic goal than attack frequency.

Psychometric evaluation of Persian version of Seizure Severity Questionnaire

Background and purposeSeizure severity has been increasingly gaining attention as a complementary assessment to seizure frequency for the measurement of treatment responses. This study aimed to assess the reliability and external validity and of the Persian version of the Seizure Severity Questionnaire (SSQ). MethodsThe study sample was recruited from 126 patients with epilepsy who attended the neurology outpatient clinic at Imam Khomeini and Roozbeh hospitals, Tehran, Iran. The Forward-Backward technique was applied to translate the questionnaire. The reliability of SSQ was assessed by Cronbach’s alpha coefficient. The external validity of SSQ was assessed by correlating SSQ scores with Quality of Life in Epilepsy Inventory-31 (QOLIE-31) subscales. ResultsThe sample comprised 63 women (50%) and 63 men (50%) aged 13–76 years. The mean scores of SSQ items ranged from 3.46 to 5.48. Distribution was skewed for all component scores, with a tendency for the item scores to concentrate toward the highest scores. Reliability for almost all domains were moderate to good, with Cronbach’s alpha ranging from 0.615 to 0.770. Component B to D and total score of SSQ had weak-to-moderate inverse correlation with QOLIE-31 subscale scores. However, the result showed no significant correlation with age, sex, or education. ConclusionWith some limitations, the Persian version of the SSQ shows relatively good reliability and content validity, supporting its use as a specific measure of seizure severity in epilepsy in Iran.

Utility of mental health and sleep screening questionnaires for patients admitted to a seizure monitoring unit

RationalePatients with seizure disorders have relatively high rates of comorbid psychological and sleep disorders. Because these can profoundly affect quality of life, early recognition and treatment are of potential benefit. As a quality improvement project, we evaluated the performance and utility of a set of mental health and sleep quality screening questionnaires in patients admitted to a VA seizure monitoring unit (SMU). MethodsQuestionnaires, including the Beck Depression Inventory-II (BDI-II), the post-traumatic stress disorder (PTSD) checklist (PCL), the Quality of Life in Epilepsy Inventory-31 (QOLIE-31), and the Pittsburgh Sleep Quality Index (PSQI), were administered to 100 patients admitted to the Portland VAMC SMU. Scored results were entered into the electronic medical record (EMR) within 72 h of hospital admission. We assessed how many patients exceeded questionnaire cutoff scores, and whether these patients had prior mental health or sleep diagnoses or evaluations within the six months preceding admission. Following hospital discharge, providers completed a survey regarding the utility of the questionnaire results. We also reviewed EMR documented mental health and sleep visits during the six months following the SMU admission. ResultsForty-seven patients (47.5%) exceeded the cutoff score for the BDI-II, including 15 without an admission diagnosis of depression, and 14 who had not seen a mental health provider in the previous six months. Similarly, 33 patients (33.3%) exceeded the cutoff score for the PCL, including nine without a diagnosis of PTSD. Scores on the BDI-II and PCL were highly correlated with the QOLIE-31 total score (r = 0.7). Seventy patients (70.7%) exceeded the cutoff score for poor sleep quality, and 37 did not have a sleep disorder diagnosis. Providers indicated that the questionnaire results were moderately or very helpful in most cases and influenced discharge recommendations to patients and referring providers in more than 50% of cases. Discharge recommendations for mental health or sleep follow-up were associated with EMR documented consultations within the six months following SMU admission. ConclusionsThe results suggest that a standard set of screening questionnaires can identify SMU patients at risk for mental health and sleep disorders, including patients not currently diagnosed or recently evaluated. Questionnaire results were perceived as helpful by providers and influenced discharge recommendations. Given that these disorders are treatable and have a major influence on health-related quality of life, the effort to collect and document this information is well justified.

Felt stigma in seizure-free persons with epilepsy: Associated factors and its impact on health-related quality of life

PurposeWe investigated felt stigma in seizure-free persons with epilepsy with regard to associated factors and its impact on health-related quality of life (HRQoL). MethodsThis cross-sectional study included 81 patients who had been seizure free for at least 2 years and 52 controls who had only had one seizure in the last 2 years. All patients completed the Stigma Scale, Quality of Life in Epilepsy Inventory-31 (QOLIE-31), short form of the Eysenck Personality Questionnaire-Revised (EPQ-RS), Hospital Anxiety Depression Scale (HADS), Rosenberg Self-esteem Scale, and the enacted stigma questionnaire. ResultsThe proportion of felt stigma was not significantly different between controls (25%) and patients in seizure remission (21%). A stepwise logistic regression analysis revealed that enacted stigma and higher EPQ-RS Neuroticism scores were more likely to be associated with felt stigma of patients in remission. Quality of Life in Epilepsy Inventory-31 scores were significantly higher in patients in seizure remission than in controls. In the stepwise linear regression analysis, felt stigma was not associated with the total QOILE-31 scores. Sobel tests showed that felt stigma had indirect effects on the QOLIE-31 scores through EPQ-RS Neuroticism scores, but its statistical significance was lost after controlling for the presence of enacted stigma, anxiety, and depressive symptoms. ConclusionOne-fifth of seizure-free patients continued to feel stigmatized, even though they had not had a seizure in more than 2 years. Experience of enacted stigma and a neurotic personality trait were the most important correlates of felt stigma for these patients. Health-related quality of life was significantly better in patients in remission than in patients with rare seizures. Felt stigma was not a significant or independent factor associated with worse HRQoL in patients in remission.

Relationship between sleep quality and cognitive performance in patients with epilepsy

PurposeTo investigate the relationship between self-reported sleep quality and cognitive function in patients with epilepsy (PWE), as well as anxiety and depressive symptoms and patient quality of life (QoL). MethodsThis multicenter cross-sectional study included PWE aged ≥12 years who were receiving ≥1 anti-seizure medication (ASM) and had not been diagnosed with a sleep disorder. Patients completed the Pittsburgh Sleep Quality Index (PSQI), the Epworth Sleepiness Scale (ESS), the Montreal Cognitive Assessment test (MoCA), the Hospital Anxiety and Depression Scale (HADS), and the Quality of Life in Epilepsy Inventory-10 (QOLIE-10). ResultsThe study enrolled 150 patients aged 16–83 years, mean age (standard deviation [SD]) 40.6 (15.2) years; 58.7% were female and 75.3% had focal epilepsy. Mean (SD) PSQI score was 4.71 (3.08), 44.4% of patients had impaired sleep quality (PSQI score ≥5), 19.9% had pathologic excessive daytime sleepiness (ESS score >12), and 32.7% had mild cognitive impairment (MoCA score <26). Within the PSQI, sleep disturbance (P = 0.036) and use of sleep medication (P = 0.006) scores were significantly higher in patients with mild cognitive impairment. Multiple regression analysis showed older age (regression coefficient [B], −0.086; 95% confidence interval [CI], −0.127, −0.045; P < 0.001) and the use of sleep medication component of the PSQI [B, −1.157; 95% CI, −2.064, −0.220; P = 0.013) were independently associated with lower MoCA score. Poor sleep quality was associated with probable anxiety and depression symptoms, and directly correlated with reduced QoL. ConclusionsIn PWE, sleep quality was not significantly independently associated with mild cognitive impairment, although poor sleep quality had a negative effect on mood and QoL.