Accelerated Cognitive Ageing in Epilepsy: A Neuropsychological Evaluation of Cognitive Deterioration

Accelerated Cognitive Ageing in Epilepsy: A Neuropsychological Evaluation of Cognitive Deterioration Abstract Objective Shed light on cognitive deterioration in Accelerated Cognitive Ageing (ACA) in epilepsy from a neuropsychological point of view in order to improve clinical diagnostics. Methods We compared the IQ-profile including GAI, OPIE IV-premorbid IQ and deterioration-scores of 21 epilepsy patients with ACA with 21 matched epilepsy patients without ACA (Epilepsy Controls) and 16 age- and education-matched Healthy Controls. Memory was also evaluated. Results Premorbid IQs were equal in all groups. Deterioration was apparent in the ACA-group in the WAIS-IV FSIQ and PRI, whereas no deterioration was found in the two control groups. PSI was impaired in both epilepsy groups, though with more impairment seen in the ACA-group. The VCI remained unimpaired. The FSIQ–GAI discrepancy was equal in both patient groups and significantly larger than in the Healthy Controls. WMS-IV memory indices were of average level in all groups. Memory impairment in ACA was not statistically different from the Epilepsy Controls. 85.7% of ACA-patients could be correctly classified through factors DET_FSIQ and PSI. Conclusions Cognitive deterioration in ACA is characterized by an average drop of 19 IQ-points in FSIQ and PRI. Verbal abilities remain unimpaired. Impairments in fluid functions compromise cognitive abilities in epilepsy, but only partially contribute to cognitive deterioration in ACA. PSI proved to have some diagnostic value in differentiating epilepsy patients from healthy controls, but fails to differentiate between ACA and Epilepsy Controls. A comparison made between OPIE-IV equations and obtained IQs leads to a significant better detection of cognitive deterioration in epilepsy than the use of GAI–FSIQ discrepancies alone. Accelerated Cognitive Ageing, Cognitive deterioration, Epilepsy, IQ, Wechsler-Adult Intelligence Scale-Fourth Edition, General Ability Index Introduction Cognitive impairment is a common comorbidity in epilepsy. It is recently estimated that up to 65% of all patients show cognitive impairment, accounting for about half of the burden of disease (Helmstaedter et al., 2014). For a long time research has focused on impairments in specific cognitive domains, such as memory impairment in temporal lobe epilepsy or impairment of the executive functions in frontal lobe epilepsy. More recently, fMRI studies brought to light that these impairments are a consequence of aberrant neuronal networks covering wide brain areas, i.e. not just limited to the site of the epileptic area (Besseling et al., 2013; Braakman et al., 2012, 2013; Vaessen et al., 2013, 2014). In addition to these aforementioned specific cognitive impairments, also global cognitive decline has been a long-standing concern and an important topic of interest. In 1889, Gowers introduced the concept of “epileptic dementia” (in: Rose, 2010). Information merely based on case reports suggests that this type of cognitive deterioration almost exclusively occurs in the context of childhood-onset chronic and often refractory epilepsies. In these conditions, accumulation of medication effects and (tonic–clonic) seizures over decades leads to gradual decline of the higher cognitive functions. The final cognitive outcome of this “chronic accumulation model” of decline can be similar to the cognitive outcome in some forms of dementia. However, in daily clinical practice clinicians also encounter another form of cognitive decline that is less well described in the literature. In a subgroup of adult patients with epilepsy who complain about cognition and a quite sudden inability to meet the demands of daily (working) life, cognitive functioning appears to be globally deteriorated. These patients do not fulfill the neuropsychological or clinical diagnostic criteria of epileptic dementia or a progressive neurological disease such as Alzheimer’s. The majority of these patients have an adult-onset epilepsy, so that they do not fit into the aforementioned “chronic accumulation model” of decline either. In a recent review, we concluded that there may exist another pattern of cognitive deterioration (Breuer et al., 2016a). We hypothesize that in a subgroup of adult patients with epilepsy, cognitive deterioration may be “cascadic” rather than progressive, thus: deterioration takes place in a relatively short period of time, and not as a consequence of chronicity. Cognitive deterioration in this subgroup develops in a stepwise “second hit model” when epilepsy affects an already vulnerable brain. The model predicts loss of cognitive reserve capacity due to e.g. traumatic brain injury (TBI) or old age, leading to a cascade of events after a second hit, i.e. epilepsy. “Ageing” is a very important factor in this process since cognitive reserve capacity decreases with age and the ageing brain might be less able to functionally compensate for additional interference, i.e. the pathogenic effects of epilepsy or comorbid diseases. The ageing adult population with an adult- or geriatric-onset epilepsy is at particular risk for this type of deterioration, taking into account that many factors converge in these late-onset epilepsies: comorbidity (especially stroke and other (cardio)vascular diseases), metabolic disturbances, increased inflammatory response to seizures, and the use of polypharmacy (Baram, 2012; Brodie, Elder & Kwan, 2009; Leppik & Birnbaum, 2010; Palop & Mucke, 2009; Stefan et al., 2014; Trinka, 2003). All these conditions, in conjunction with ageing and the associated decrease of the brain’s neuronal plasticity, increase cerebral vulnerability and lead to irreversible loss of functional reserve capacity, eventually resulting in cascadic deterioration and acceleration of cognitive ageing. We use the term “Accelerated Cognitive Ageing” for this process. Fig. 1 graphically represents the second hit model and the process of cognitive deterioration. Fig. 1. View largeDownload slide Graphical representation of Accelerated Cognitive Ageing (ACA). The dashed blue line represents the cognitive ageing trajectory without pathology. With increasing age, cognitive functioning is declining until the minimal cognitive threshold is reached. Two alternative cognitive ageing trajectories are shown. The yellow line depicts the cognitive trajectory after one hit (e.g. TBI). There is decline in cognitive function which recovers. Recovery is, however, not complete and results in a loss of functional reserve. This is followed by a normal rate of subsequent ageing. The solid red line represents ACA in the second-hit model. After a second hit (e.g. epilepsy), cascadic deterioration takes place and does not recover due to the diminished cognitive reserve capacity. In combination and interaction with the expected changes of normal ageing, cognitive ageing is accelerated and the patient’s cognitive profile resembles that of an older individual. Published in: Breuer et al., 2016a. Fig. 1. View largeDownload slide Graphical representation of Accelerated Cognitive Ageing (ACA). The dashed blue line represents the cognitive ageing trajectory without pathology. With increasing age, cognitive functioning is declining until the minimal cognitive threshold is reached. Two alternative cognitive ageing trajectories are shown. The yellow line depicts the cognitive trajectory after one hit (e.g. TBI). There is decline in cognitive function which recovers. Recovery is, however, not complete and results in a loss of functional reserve. This is followed by a normal rate of subsequent ageing. The solid red line represents ACA in the second-hit model. After a second hit (e.g. epilepsy), cascadic deterioration takes place and does not recover due to the diminished cognitive reserve capacity. In combination and interaction with the expected changes of normal ageing, cognitive ageing is accelerated and the patient’s cognitive profile resembles that of an older individual. Published in: Breuer et al., 2016a. In a previous study, we described the clinical characteristics in a series of patients with a focal epilepsy and this hypothesized cascadic cognitive deterioration (Breuer et al., 2016b). The key neuropsychological characteristics are significant cognitive deterioration in Full Scale and Performance IQ but with preservation of the higher order cognitive functions (Verbal IQ and memory). The purpose of the current study is to shed light on this cognitive deterioration from a neuropsychological point of view by comparing the IQ-profile of ACA-patients with that of matched epilepsy patients without ACA and healthy controls, in order to elucidate the classification of this type of cognitive deterioration and improve clinical diagnostics. Methods Study Population Included in this study are outpatients with a confirmed diagnosis of epilepsy, referred to a leading Dutch tertiary care centre for epilepsy (Kempenhaeghe, Heeze). In total, 201 adult epilepsy patients with subjectively reported cognitive impairment underwent a neuropsychological assessment in the period Jan. 2016–July 2017. Patients aged 18–80 with intellectual deterioration were evaluated for inclusion in our study. Intellectual deterioration was defined as ≥1 SD discrepancy between the actual WAIS-IV FSIQ and the estimated premorbid FSIQ. Exclusion criteria were mental retardation (FSIQ < 70 before the age of 18), progressive epileptic syndromes, psychiatric disease at the time of the study (e.g. schizophrenia, psychotic episodes, major depression), and a history of epilepsy-related brain surgery. Patients with neurological or psychiatric diseases that could underlie this cognitive decline (≥1 SD discrepancy between the actual WAIS-IV FSIQ and the estimated premorbid FSIQ), or progressive neurological disorders (suspicion of) neurodegenerative diseases, or other causes of aforementioned cognitive decline were also excluded. A total of 21 patients met the inclusion criterion of significant intellectual deterioration without a known or suspected cause (ACA Group). They were consecutively matched with 21 other epilepsy patients without ACA with age, educational level, type of epilepsy and duration of epilepsy as matching factors (Epilepsy Controls). Our second control group consisted of 16 age- and education-matched healthy controls (Healthy Controls). A detailed medical history as well as demographic and clinical details were obtained. All subjects signed informed consent and gave permission to use the obtained clinical data for scientific purposes. Premorbid Intelligence, Intellectual Deterioration, General Ability Index and Other Cognitive Measures Intelligence was measured using the Dutch version of the WAIS-IV (Wechsler, 2008a). For an estimation of the premorbid intelligence, the Oklahoma Premorbid Intelligence Estimate (OPIE-IV) formula was applied. The OPIE-IV equations are derived from hierarchical regression models using raw scores of two WAIS-IV subtests (Vocabulary (V) and Matrix Reasoning (MR)), age, education, sex, and ethnicity (Holdnack, Schoenberg, Lange & Iverson, 2013). OPIE-IV predictions were derived for the FSIQ, verbal intelligence (Verbal Comprehension Index (VCI)) and performance abilities (Perceptual Reasoning Index (PRI)), resulting in OPIE IV_FSIQ, OPIE IV_VCI and OPIE IV_PRI scores, respectively. There was a significant (strong) correlation between the WAIS-IV FSIQ and the OPIE IV_FSIQ in norm group Healthy Controls (r = .81, p = < .001). Similar effects were found for VCI and OPIE IV_VCI (r = .89, p = < .001) and PRI and OPIE IV_PRI (r = .72, p = .002), comparable to findings of Holdnack et al. (2013) in the normal population. Deterioration scores were calculated by subtracting the estimated premorbid IQs (OPIE IV_scores) from the actual obtained IQs, resulting in three IQ-deterioration scores: DET_FSIQ, DET_VCI, and DET_PRI. Subsequently, the WAIS-IV General Ability Index (GAI), a composite score derived from the six core subtests of the VCI and PRI, was calculated for all subjects. The GAI provides a measure of general intellectual ability and is described to serve as more of a “hold measure” since it minimizes processing speed and working memory demands, and is therefore considered to be less susceptible to cognitive decline after neurological disease than the FSIQ (Tulsky, Saklofke, Wilkins, & Weiss, 2001). The discrepancy between the GAI and the obtained FSIQ was calculated by subtracting the GAI from the FSIQ (FSIQ–GAI). The discrepancy between the GAI and the estimated premorbid FSIQ was derived in a similar manner (OPIE IV_FSIQ–GAI). The Dutch translation of the Wechsler Memory Scale Fourth Edition (WMS-IV; Wechsler, 2009) was used for measurement of memory functions. Also the Dutch version of the WMS-IV Brief Cognitive Status Exam, a valid screening instrument for brief screening of cognitive impairment in dementia (similar to the widely used Mini Mental State Examination (MMSE)), was applied. The cut-off score for rough detection of dementia was set at 42, following Bouman, Hendriks, Aldenkamp, and Kessels (2015). Data Analysis Data was analyzed using statistical software (SPSS version 24.0). Results of exploratory analyses are reported in mean (M) and standard deviation (SD). One-way ANOVAs or unpaired t-tests were used to determine whether subject groups differed on demographic and clinical variables. A multivariate analysis of variance was performed on all IQ- and cognitive deterioration measures (MANOVA using Pillai’s trace including: obtained FSIQ/VCI/PRI/WMI/PSI, OPIE-IV_scores, DET_scores, and GAI-scores). Post-hoc univariate tests with Bonferroni correction were then performed to compare each subject group to the other two subject groups on all aforementioned dependent variables. The MANOVA was followed up with a stepwise discriminant analysis. Correct classification rates were obtained using a standard and a cross-validation procedure in which each case is classified successively by the functions derived from all other cases (leave-one out classification). This method leads to more conservative estimates of the correct classification rate. A comparable result in the standard and cross-validation procedure generally attests of the stability of the classification model (Rainville, Bechara, Naqvi, & Damasio, 2006). Results Main demographic and clinical data are shown in Table 1. Table 1. Demographic and clinical characteristics of all included subjects ACA Epilepsy Controls Healthy Controls Age in years M (SD) + range 57.5 (11.6) 57.5 (11.5) 61.4 (9.4) 30–78 y 29–77 y 47–79 y Gender 42.9% male 43.8% male 57.1% male Handedness 90.5% right-handed 100% right-handed 87.5% right-handed Highest educational level 14.3% < vocational training 14.3% < vocational training 12.5% < vocational training 42.9% vocational training 42.9% vocational training 50.0% vocational training 42.9% bachelor’s degree 42.9% bachelor’s degree 37.5% bachelor’s degree 0% master’s degree 0% master’s degree 0% master’s degree Age at epilepsy onset M (SD) + range 38.2 (16.3) 32.6 (19.2) — 12–71 y 1–74 y Duration of epilepsy M (SD) + range 17.2 (15.1) 22.7 (18.3) — 1–50 y 1–54 y Type of epilepsy 61.9% cryptogenic localization-related 61.9% cryptogenic localization-related — 28.6% symptomatic 38.1% symptomatic 9.5% idiopathic 0% idiopathic Dominant seizure typea 19.0% simple partial 4.8% simple partial — 33.3% complex partial 47.6% complex partial 9.5% absence 0% absence 0% tonic–clonic 28.6% tonic–clonic 38.1% seizure free 19.0% seizure free Status epilepticus 33.3% yes 4.8% yes Seizure frequency 38.1% seizure (sz) free 19.0% seizure (sz) free — 4.8% < 1 sz/y 9.5% < 1 sz/y 19.0% 1–5 sz/y 28.6% 1–5 sz/y 14.3% 1 sz per 2 months 4.8% 1 sz per 2 months 9.5% monthly sz 14.3% monthly sz 14.3% weekly sz 19.0% weekly sz 0% daily sz 4.8% daily sz Drug loadb 1.4 (0.5) 1.5 (0.9) — Comorbid disease 81.0% has at least one comorbid disease, of which; 47.6% has at least one comorbid disease, of which; 25.0% has at least one medical condition, of which; 58.8% cardiovascular 70.0% cardiovascular 25% cardiovascular 23.5% cerebrovascular 10% cerebrovascular 0% cerebrovascular 17.6% TBI 10% TBI 0% TBI 35.3% other (i.e. immunologic, inflammatory) 50.0% other (i.e. immunologic, inflammatory) 75% other (i.e. immunologic, inflammatory) ACA Epilepsy Controls Healthy Controls Age in years M (SD) + range 57.5 (11.6) 57.5 (11.5) 61.4 (9.4) 30–78 y 29–77 y 47–79 y Gender 42.9% male 43.8% male 57.1% male Handedness 90.5% right-handed 100% right-handed 87.5% right-handed Highest educational level 14.3% < vocational training 14.3% < vocational training 12.5% < vocational training 42.9% vocational training 42.9% vocational training 50.0% vocational training 42.9% bachelor’s degree 42.9% bachelor’s degree 37.5% bachelor’s degree 0% master’s degree 0% master’s degree 0% master’s degree Age at epilepsy onset M (SD) + range 38.2 (16.3) 32.6 (19.2) — 12–71 y 1–74 y Duration of epilepsy M (SD) + range 17.2 (15.1) 22.7 (18.3) — 1–50 y 1–54 y Type of epilepsy 61.9% cryptogenic localization-related 61.9% cryptogenic localization-related — 28.6% symptomatic 38.1% symptomatic 9.5% idiopathic 0% idiopathic Dominant seizure typea 19.0% simple partial 4.8% simple partial — 33.3% complex partial 47.6% complex partial 9.5% absence 0% absence 0% tonic–clonic 28.6% tonic–clonic 38.1% seizure free 19.0% seizure free Status epilepticus 33.3% yes 4.8% yes Seizure frequency 38.1% seizure (sz) free 19.0% seizure (sz) free — 4.8% < 1 sz/y 9.5% < 1 sz/y 19.0% 1–5 sz/y 28.6% 1–5 sz/y 14.3% 1 sz per 2 months 4.8% 1 sz per 2 months 9.5% monthly sz 14.3% monthly sz 14.3% weekly sz 19.0% weekly sz 0% daily sz 4.8% daily sz Drug loadb 1.4 (0.5) 1.5 (0.9) — Comorbid disease 81.0% has at least one comorbid disease, of which; 47.6% has at least one comorbid disease, of which; 25.0% has at least one medical condition, of which; 58.8% cardiovascular 70.0% cardiovascular 25% cardiovascular 23.5% cerebrovascular 10% cerebrovascular 0% cerebrovascular 17.6% TBI 10% TBI 0% TBI 35.3% other (i.e. immunologic, inflammatory) 50.0% other (i.e. immunologic, inflammatory) 75% other (i.e. immunologic, inflammatory) Note: * = p < 0.01. aDominant seizure type is determined for the two years preceding neuropsychological assessment. bThe prescribed daily dose of antiepileptic medication divided by the defined daily dose (Lammers et al., 1995). Table 1. Demographic and clinical characteristics of all included subjects ACA Epilepsy Controls Healthy Controls Age in years M (SD) + range 57.5 (11.6) 57.5 (11.5) 61.4 (9.4) 30–78 y 29–77 y 47–79 y Gender 42.9% male 43.8% male 57.1% male Handedness 90.5% right-handed 100% right-handed 87.5% right-handed Highest educational level 14.3% < vocational training 14.3% < vocational training 12.5% < vocational training 42.9% vocational training 42.9% vocational training 50.0% vocational training 42.9% bachelor’s degree 42.9% bachelor’s degree 37.5% bachelor’s degree 0% master’s degree 0% master’s degree 0% master’s degree Age at epilepsy onset M (SD) + range 38.2 (16.3) 32.6 (19.2) — 12–71 y 1–74 y Duration of epilepsy M (SD) + range 17.2 (15.1) 22.7 (18.3) — 1–50 y 1–54 y Type of epilepsy 61.9% cryptogenic localization-related 61.9% cryptogenic localization-related — 28.6% symptomatic 38.1% symptomatic 9.5% idiopathic 0% idiopathic Dominant seizure typea 19.0% simple partial 4.8% simple partial — 33.3% complex partial 47.6% complex partial 9.5% absence 0% absence 0% tonic–clonic 28.6% tonic–clonic 38.1% seizure free 19.0% seizure free Status epilepticus 33.3% yes 4.8% yes Seizure frequency 38.1% seizure (sz) free 19.0% seizure (sz) free — 4.8% < 1 sz/y 9.5% < 1 sz/y 19.0% 1–5 sz/y 28.6% 1–5 sz/y 14.3% 1 sz per 2 months 4.8% 1 sz per 2 months 9.5% monthly sz 14.3% monthly sz 14.3% weekly sz 19.0% weekly sz 0% daily sz 4.8% daily sz Drug loadb 1.4 (0.5) 1.5 (0.9) — Comorbid disease 81.0% has at least one comorbid disease, of which; 47.6% has at least one comorbid disease, of which; 25.0% has at least one medical condition, of which; 58.8% cardiovascular 70.0% cardiovascular 25% cardiovascular 23.5% cerebrovascular 10% cerebrovascular 0% cerebrovascular 17.6% TBI 10% TBI 0% TBI 35.3% other (i.e. immunologic, inflammatory) 50.0% other (i.e. immunologic, inflammatory) 75% other (i.e. immunologic, inflammatory) ACA Epilepsy Controls Healthy Controls Age in years M (SD) + range 57.5 (11.6) 57.5 (11.5) 61.4 (9.4) 30–78 y 29–77 y 47–79 y Gender 42.9% male 43.8% male 57.1% male Handedness 90.5% right-handed 100% right-handed 87.5% right-handed Highest educational level 14.3% < vocational training 14.3% < vocational training 12.5% < vocational training 42.9% vocational training 42.9% vocational training 50.0% vocational training 42.9% bachelor’s degree 42.9% bachelor’s degree 37.5% bachelor’s degree 0% master’s degree 0% master’s degree 0% master’s degree Age at epilepsy onset M (SD) + range 38.2 (16.3) 32.6 (19.2) — 12–71 y 1–74 y Duration of epilepsy M (SD) + range 17.2 (15.1) 22.7 (18.3) — 1–50 y 1–54 y Type of epilepsy 61.9% cryptogenic localization-related 61.9% cryptogenic localization-related — 28.6% symptomatic 38.1% symptomatic 9.5% idiopathic 0% idiopathic Dominant seizure typea 19.0% simple partial 4.8% simple partial — 33.3% complex partial 47.6% complex partial 9.5% absence 0% absence 0% tonic–clonic 28.6% tonic–clonic 38.1% seizure free 19.0% seizure free Status epilepticus 33.3% yes 4.8% yes Seizure frequency 38.1% seizure (sz) free 19.0% seizure (sz) free — 4.8% < 1 sz/y 9.5% < 1 sz/y 19.0% 1–5 sz/y 28.6% 1–5 sz/y 14.3% 1 sz per 2 months 4.8% 1 sz per 2 months 9.5% monthly sz 14.3% monthly sz 14.3% weekly sz 19.0% weekly sz 0% daily sz 4.8% daily sz Drug loadb 1.4 (0.5) 1.5 (0.9) — Comorbid disease 81.0% has at least one comorbid disease, of which; 47.6% has at least one comorbid disease, of which; 25.0% has at least one medical condition, of which; 58.8% cardiovascular 70.0% cardiovascular 25% cardiovascular 23.5% cerebrovascular 10% cerebrovascular 0% cerebrovascular 17.6% TBI 10% TBI 0% TBI 35.3% other (i.e. immunologic, inflammatory) 50.0% other (i.e. immunologic, inflammatory) 75% other (i.e. immunologic, inflammatory) Note: * = p < 0.01. aDominant seizure type is determined for the two years preceding neuropsychological assessment. bThe prescribed daily dose of antiepileptic medication divided by the defined daily dose (Lammers et al., 1995). Mean age was not statistically significant different in all subject groups. There was an almost equal gender distribution within and between groups. The mean age at epilepsy onset was equal in both patient groups, though with a larger range in the Epilepsy Controls. In the ACA-group, none of the patients had an age at onset in early childhood. In fact, more than 85% of ACA-patients had an age at onset over 18 years with almost 67% of patients having an age at onset over 30 years. There was no significant difference in duration of disease among the two groups. Most epilepsy patients suffer from a cryptogenic localization-related epilepsy. In line with this, partial seizures were the most common dominant seizure type in both patient groups. More than one-third of ACA-patients have had no seizures for the past 2 years compared to nearly one-fifth in the Epilepsy Controls. Almost 29% of patients in the latter group had tonic–clonic seizures as their current dominant seizure type whereas this was the case in none of the ACA-patients. Status epilepticus (SE) was a quite common phenomenon in ACA, but not in the Epilepsy Controls (more than 33% of ACA-patients had at least one SE versus less than 5% in the Epilepsy control group). Seizure frequency in general seemed to be somewhat higher in the Epilepsy Controls than in the ACA-group. Over 14% in the ACA-group had a high seizure frequency (weekly or daily seizures) versus 23.8% in the Epilepsy Control group. Drug load in both patient groups was equal. A noteworthy difference between all three subject groups lied in the fact that no less than 81.0% of ACA-patients had at least one comorbid disease versus 47.6% in Epilepsy Controls and only 25% in the Healthy Controls. The origin of these comorbid diseases in ACA was rather diverse, but mostly (58.8%) cardiovascular. IQ-, Deterioration-, and Other Cognitive Measures (Multivariate Tests and Discriminant Analysis) Means and SDs of WAIS-IV IQs, OPIE-IV_scores, DET_scores, and GAI-scores, as well as the results of the multivariate and post-hoc univariate tests are presented in Table 2. Using Pillai’s trace, there was a significant effect of “Group” on the aforementioned cognitive measures in multivariate analysis, V = 0.96, F (26, 88) = 3.14, p = < .001. Table 2. Multivariate and univariate comparisons on cognitive measures per subject group ACA M (SD) Epilepsy M (SD) Healthy M (SD) Fa p ACA vs. H ACA vs. E E vs. H WAIS-IV indexes  FSIQ 81.1 (13.7) 99.1 (11.9) 107.8 (13.8) 20.38 .000 .000 .000 NS  VCI 95.5 (15.2) 101.3 (12.5) 106.1 (11.7) 2.94 .061 NS NS NS  PRI 80.0 (11.5) 100.5 (12.7) 102.8 (14.3) 19.10 .000 .000 .000 NS  WMI 82.1 (13.3) 93.4 (24.4) 104.6 (13.4) 7.07 .002 .001 NS NS  PSI 75.5 (18.0) 96.3 (9.6) 113.5 (9.6) 30.99 .000 .000 .000 .003 OPIE-IV scores  OPIE IV_FSIQ 100.6 (13.2) 105.4 (10.9) 109.6 (12.1) 2.58 .085 NS NS NS  OPIE IV_VCI 96.1 (15.5) 101.0 (13.3) 105.1 (14.3) 1.77 .179 NS NS NS  OPIE IV_PRI 97.7 (11.5) 101.9 (11.0) 103.7 (12.2) 1.34 .271 NS NS NS Deterioration scores  DET_FSIQ –19.4 (5.5) –6.5 (6.9) –1.8 (8.2) 34.44 .000 .000 .000 NS  DET_VCI –0.7 (6.4) 0,1 (6.3) 0.8 (5.9) 0.24 .786 NS NS NS  DET_PRI –17.7 (6.7) –1.3 (8.4) –0.9 (10.0) 26.65 .000 .000 .000 NS GAI discrepancies  GAI 86.6 (14.2) 101.2 (11.2) 105.3 (13.7) 11.04 .000 .000 .002 NS  FSIQ–GAI –5.4 (3.8) –2.1 (6.0) 2.6 (3.0) 14.18 .000 .000 NS .008  OPIE IV_FSIQ–GAI 14.0 (4.6) 4.1 (5.4) 4.4 (7.1) 19.84 .000 .000 .000 NS ACA M (SD) Epilepsy M (SD) Healthy M (SD) Fa p ACA vs. H ACA vs. E E vs. H WAIS-IV indexes  FSIQ 81.1 (13.7) 99.1 (11.9) 107.8 (13.8) 20.38 .000 .000 .000 NS  VCI 95.5 (15.2) 101.3 (12.5) 106.1 (11.7) 2.94 .061 NS NS NS  PRI 80.0 (11.5) 100.5 (12.7) 102.8 (14.3) 19.10 .000 .000 .000 NS  WMI 82.1 (13.3) 93.4 (24.4) 104.6 (13.4) 7.07 .002 .001 NS NS  PSI 75.5 (18.0) 96.3 (9.6) 113.5 (9.6) 30.99 .000 .000 .000 .003 OPIE-IV scores  OPIE IV_FSIQ 100.6 (13.2) 105.4 (10.9) 109.6 (12.1) 2.58 .085 NS NS NS  OPIE IV_VCI 96.1 (15.5) 101.0 (13.3) 105.1 (14.3) 1.77 .179 NS NS NS  OPIE IV_PRI 97.7 (11.5) 101.9 (11.0) 103.7 (12.2) 1.34 .271 NS NS NS Deterioration scores  DET_FSIQ –19.4 (5.5) –6.5 (6.9) –1.8 (8.2) 34.44 .000 .000 .000 NS  DET_VCI –0.7 (6.4) 0,1 (6.3) 0.8 (5.9) 0.24 .786 NS NS NS  DET_PRI –17.7 (6.7) –1.3 (8.4) –0.9 (10.0) 26.65 .000 .000 .000 NS GAI discrepancies  GAI 86.6 (14.2) 101.2 (11.2) 105.3 (13.7) 11.04 .000 .000 .002 NS  FSIQ–GAI –5.4 (3.8) –2.1 (6.0) 2.6 (3.0) 14.18 .000 .000 NS .008  OPIE IV_FSIQ–GAI 14.0 (4.6) 4.1 (5.4) 4.4 (7.1) 19.84 .000 .000 .000 NS adf = 2, 55. ACA = ACA-group. Epilepsy/E = Epilepsy Controls. Healthy/H = Healthy Controls. In pairwise comparisons, p-values are given for significant contrasts based on Bonferroni-correction. NS = non-significant. Table 2. Multivariate and univariate comparisons on cognitive measures per subject group ACA M (SD) Epilepsy M (SD) Healthy M (SD) Fa p ACA vs. H ACA vs. E E vs. H WAIS-IV indexes  FSIQ 81.1 (13.7) 99.1 (11.9) 107.8 (13.8) 20.38 .000 .000 .000 NS  VCI 95.5 (15.2) 101.3 (12.5) 106.1 (11.7) 2.94 .061 NS NS NS  PRI 80.0 (11.5) 100.5 (12.7) 102.8 (14.3) 19.10 .000 .000 .000 NS  WMI 82.1 (13.3) 93.4 (24.4) 104.6 (13.4) 7.07 .002 .001 NS NS  PSI 75.5 (18.0) 96.3 (9.6) 113.5 (9.6) 30.99 .000 .000 .000 .003 OPIE-IV scores  OPIE IV_FSIQ 100.6 (13.2) 105.4 (10.9) 109.6 (12.1) 2.58 .085 NS NS NS  OPIE IV_VCI 96.1 (15.5) 101.0 (13.3) 105.1 (14.3) 1.77 .179 NS NS NS  OPIE IV_PRI 97.7 (11.5) 101.9 (11.0) 103.7 (12.2) 1.34 .271 NS NS NS Deterioration scores  DET_FSIQ –19.4 (5.5) –6.5 (6.9) –1.8 (8.2) 34.44 .000 .000 .000 NS  DET_VCI –0.7 (6.4) 0,1 (6.3) 0.8 (5.9) 0.24 .786 NS NS NS  DET_PRI –17.7 (6.7) –1.3 (8.4) –0.9 (10.0) 26.65 .000 .000 .000 NS GAI discrepancies  GAI 86.6 (14.2) 101.2 (11.2) 105.3 (13.7) 11.04 .000 .000 .002 NS  FSIQ–GAI –5.4 (3.8) –2.1 (6.0) 2.6 (3.0) 14.18 .000 .000 NS .008  OPIE IV_FSIQ–GAI 14.0 (4.6) 4.1 (5.4) 4.4 (7.1) 19.84 .000 .000 .000 NS ACA M (SD) Epilepsy M (SD) Healthy M (SD) Fa p ACA vs. H ACA vs. E E vs. H WAIS-IV indexes  FSIQ 81.1 (13.7) 99.1 (11.9) 107.8 (13.8) 20.38 .000 .000 .000 NS  VCI 95.5 (15.2) 101.3 (12.5) 106.1 (11.7) 2.94 .061 NS NS NS  PRI 80.0 (11.5) 100.5 (12.7) 102.8 (14.3) 19.10 .000 .000 .000 NS  WMI 82.1 (13.3) 93.4 (24.4) 104.6 (13.4) 7.07 .002 .001 NS NS  PSI 75.5 (18.0) 96.3 (9.6) 113.5 (9.6) 30.99 .000 .000 .000 .003 OPIE-IV scores  OPIE IV_FSIQ 100.6 (13.2) 105.4 (10.9) 109.6 (12.1) 2.58 .085 NS NS NS  OPIE IV_VCI 96.1 (15.5) 101.0 (13.3) 105.1 (14.3) 1.77 .179 NS NS NS  OPIE IV_PRI 97.7 (11.5) 101.9 (11.0) 103.7 (12.2) 1.34 .271 NS NS NS Deterioration scores  DET_FSIQ –19.4 (5.5) –6.5 (6.9) –1.8 (8.2) 34.44 .000 .000 .000 NS  DET_VCI –0.7 (6.4) 0,1 (6.3) 0.8 (5.9) 0.24 .786 NS NS NS  DET_PRI –17.7 (6.7) –1.3 (8.4) –0.9 (10.0) 26.65 .000 .000 .000 NS GAI discrepancies  GAI 86.6 (14.2) 101.2 (11.2) 105.3 (13.7) 11.04 .000 .000 .002 NS  FSIQ–GAI –5.4 (3.8) –2.1 (6.0) 2.6 (3.0) 14.18 .000 .000 NS .008  OPIE IV_FSIQ–GAI 14.0 (4.6) 4.1 (5.4) 4.4 (7.1) 19.84 .000 .000 .000 NS adf = 2, 55. ACA = ACA-group. Epilepsy/E = Epilepsy Controls. Healthy/H = Healthy Controls. In pairwise comparisons, p-values are given for significant contrasts based on Bonferroni-correction. NS = non-significant. As listed in Table 2, the premorbid IQ-indices (OPIE-IV scores) were estimated at an average level in all three subject groups, suggesting all subjects had a comparable level of intelligence before onset of disease, in line with the matched educational levels. When comparing the obtained WAIS-IV intelligence-indices however, the FSIQ, PRI, and PSI in the ACA-group were in a significantly lower range than in the Epilepsy and Healthy Controls, whereas the VCI remained unimpaired. Verbal working memory in ACA was impaired relative to the Healthy Controls, but at the same level as the Epilepsy Control group. Information processing speed was impaired in both epilepsy patient groups, though with significantly more impairment seen in the ACA-patients. This was confirmed when comparing deterioration scores among subject groups. In the ACA-group, significant deterioration was apparent in the FSIQ and PRI, whereas no deterioration took place in the two control groups. The mean GAI was, in accordance with the above, in a significantly lower range in the ACA-group than it was in the other two subject groups. The FSIQ–GAI discrepancy was equal in both patient groups and in both cases significantly larger than in the Healthy Controls. In the ACA-group, a total of 28.6% had a clinically significant GAI > FSIQ discrepancy as determined via the base rate for the overall normative sample, which only slightly differed from the total of 23.8% of clinically significant GAI > FSIQ discrepancies in the Epilepsy Controls. In the Epilepsy control-group, only two subjects had a clinically significant discrepancy in the other direction (GAI < FSIQ) versus none in the ACA-group. In the Healthy Controls, only one subject had a clinically significant GAI–FSIQ discrepancy (GAI < FSIQ). The discrepancy between the premorbid IQ (OPIE IV_FSIQ) and the GAI was comparable in both control groups, but significantly larger in ACA-patients. Analysis of memory scores (listed in Table 3) revealed all WMS-IV memory indices to be of average level in all three subject groups. Compared to the Healthy Controls, memory scores in ACA were significantly lower, though not statistically different from the Epilepsy Controls. Auditory Memory as well as Delayed Memory were both significantly impaired in all epilepsy patients compared to the Healthy Controls. Table 3. Univariate comparisons on WMS-IV memory indexes per subject group ACA M (SD) Epilepsy M (SD) Healthy M (SD) Fa p ACA vs. H ACA vs. E E vs. H WMS-IV indexes  Auditory M. 96.0 (12.5) 93.0 (16.6) 108.8 (12.5) 5.86 .005 .037 NS .006  Visual M. 91.6 (10.4) 98.8 (12.9) 102.8 (12.8) 3.64 .034 .033 NS NS  Visual Working M. 94.3 (12.2) 107.5 (14.1) 112.6 (13.9) 5.10 .012 .012 NS NS  Immediate M. 92.6 (12.1) 96.6 (15.6) 108.4 (15.0) 5.42 .008 .008 NS NS  Delayed M. 93.1 (12.0) 93.0 (13.2) 106.1 (12.3) 5.98 .005 .013 NS .011 ACA M (SD) Epilepsy M (SD) Healthy M (SD) Fa p ACA vs. H ACA vs. E E vs. H WMS-IV indexes  Auditory M. 96.0 (12.5) 93.0 (16.6) 108.8 (12.5) 5.86 .005 .037 NS .006  Visual M. 91.6 (10.4) 98.8 (12.9) 102.8 (12.8) 3.64 .034 .033 NS NS  Visual Working M. 94.3 (12.2) 107.5 (14.1) 112.6 (13.9) 5.10 .012 .012 NS NS  Immediate M. 92.6 (12.1) 96.6 (15.6) 108.4 (15.0) 5.42 .008 .008 NS NS  Delayed M. 93.1 (12.0) 93.0 (13.2) 106.1 (12.3) 5.98 .005 .013 NS .011 adf = 2, 48 for Auditory M(emory), Visual M(emory), Immediate M(emory) and Delayed M(emory). df = 2, 32 for Visual Working M(emory). ACA = ACA-group. Epilepsy/E = Epilepsy Controls. Healthy/H = Healthy Controls. In pairwise comparisons, p-values are given for significant contrasts based on Bonferroni-correction. NS = non-significant. Table 3. Univariate comparisons on WMS-IV memory indexes per subject group ACA M (SD) Epilepsy M (SD) Healthy M (SD) Fa p ACA vs. H ACA vs. E E vs. H WMS-IV indexes  Auditory M. 96.0 (12.5) 93.0 (16.6) 108.8 (12.5) 5.86 .005 .037 NS .006  Visual M. 91.6 (10.4) 98.8 (12.9) 102.8 (12.8) 3.64 .034 .033 NS NS  Visual Working M. 94.3 (12.2) 107.5 (14.1) 112.6 (13.9) 5.10 .012 .012 NS NS  Immediate M. 92.6 (12.1) 96.6 (15.6) 108.4 (15.0) 5.42 .008 .008 NS NS  Delayed M. 93.1 (12.0) 93.0 (13.2) 106.1 (12.3) 5.98 .005 .013 NS .011 ACA M (SD) Epilepsy M (SD) Healthy M (SD) Fa p ACA vs. H ACA vs. E E vs. H WMS-IV indexes  Auditory M. 96.0 (12.5) 93.0 (16.6) 108.8 (12.5) 5.86 .005 .037 NS .006  Visual M. 91.6 (10.4) 98.8 (12.9) 102.8 (12.8) 3.64 .034 .033 NS NS  Visual Working M. 94.3 (12.2) 107.5 (14.1) 112.6 (13.9) 5.10 .012 .012 NS NS  Immediate M. 92.6 (12.1) 96.6 (15.6) 108.4 (15.0) 5.42 .008 .008 NS NS  Delayed M. 93.1 (12.0) 93.0 (13.2) 106.1 (12.3) 5.98 .005 .013 NS .011 adf = 2, 48 for Auditory M(emory), Visual M(emory), Immediate M(emory) and Delayed M(emory). df = 2, 32 for Visual Working M(emory). ACA = ACA-group. Epilepsy/E = Epilepsy Controls. Healthy/H = Healthy Controls. In pairwise comparisons, p-values are given for significant contrasts based on Bonferroni-correction. NS = non-significant. The average score on the Dutch version of the WMS-IV Brief Cognitive Status Exam (not in table), a valid screening instrument for the detection of cognitive impairment in dementia, was well above the cut-off point of 42 in all three groups (Mean and SD 48.3 (6.3), 51.5 (5.7), and 51.7 (10.2) in the ACA-group, Epilepsy Controls, and Healthy Controls, respectively). The possibility to discriminate between the three subject groups based on all cognitive measures in Table 2 was further tested in a stepwise discriminant analysis. This analysis revealed two discriminant functions of which the first (DET_FSIQ) explained 96.7% of variance (canonical R2 = .61), whereas the second (PSI) explained 3.3% of variance (canonical R2 = .05). In combination, these discriminant functions significantly differentiated between the subject groups (Λ = 0.37, χ2 (4) = 54.29, p = < .0005), but removing the first function learned that the second function alone did not significantly differentiate between the three groups (Λ = 0.95, χ2 (1) = 2.85, p = .092). The discriminant function plot showed that the function DET_FSIQ discriminated the ACA-group from the two control groups, whereas the PSI differentiated between the epilepsy control-group and the Healthy Controls. The overall successful ACA-classification rate was 85.7% in both the original classification-method and the more conservative cross-validation procedure, whereas 52.4% and 62.5% of Epilepsy and Healthy Controls respectively could be successfully classified in the cross-validation procedure (Table 4). Table 4. Classification results and predicted group membership ACA Healthy Controls Epilepsy Controls Original % ACA 85.7 4.8 9.5 Healthy controls .0 68.8 31.3 Epilepsy controls 23.8 19.0 57.1 Cross-validated % ACA 85.7 4.8 9.5 Healthy controls .0 62.5 37.5 Epilepsy controls 28.6 19.0 52.4 ACA Healthy Controls Epilepsy Controls Original % ACA 85.7 4.8 9.5 Healthy controls .0 68.8 31.3 Epilepsy controls 23.8 19.0 57.1 Cross-validated % ACA 85.7 4.8 9.5 Healthy controls .0 62.5 37.5 Epilepsy controls 28.6 19.0 52.4 Table 4. Classification results and predicted group membership ACA Healthy Controls Epilepsy Controls Original % ACA 85.7 4.8 9.5 Healthy controls .0 68.8 31.3 Epilepsy controls 23.8 19.0 57.1 Cross-validated % ACA 85.7 4.8 9.5 Healthy controls .0 62.5 37.5 Epilepsy controls 28.6 19.0 52.4 ACA Healthy Controls Epilepsy Controls Original % ACA 85.7 4.8 9.5 Healthy controls .0 68.8 31.3 Epilepsy controls 23.8 19.0 57.1 Cross-validated % ACA 85.7 4.8 9.5 Healthy controls .0 62.5 37.5 Epilepsy controls 28.6 19.0 52.4 Discussion Results from an increasing number of studies have indicated that the cognitive ageing trajectory in patients with epilepsy differs from the pattern observed in healthy ageing (Helmstaedter & Elger, 2009; Hermann et al., 2006b, 2008). In our previous work, we described two models of aberrant cognitive ageing, with on the one hand “epileptic dementia” as proposed by Gowers in the past; i.e. slow and gradual cognitive deterioration due to accumulation of negative effects of seizures, treatment, and other epilepsy-related factors in early-onset, chronic and often drug-resistant epilepsy. On the other hand and in addition to this “chronic accumulation model”, cognitive deterioration may develop in a shorter period of time and in a stepwise “second hit model”, where cascadic deterioration takes places as a consequence of irreversible loss of cognitive reserve capacity due to first and second hits to the brain in combination and interaction with the normal ageing process and loss of brain plasticity inherent to ageing. The ageing adult population with an adult- or geriatric-onset epilepsy is at particular risk for this Accelerated Cognitive Ageing (ACA), taking into account that many factors converge in these late-onset epilepsies: comorbidity (especially stroke and other (cardio)vascular disease), metabolic disturbances, increased inflammatory response to seizures, and the use of polypharmacy (Baram, 2012; Brodie et al., 2009; Leppik & Birnbaum, 2010; Palop & Mucke, 2009; Stefan et al., 2014; Trinka, 2003). Especially in this group, however, underdetection may lurk as deteriorated cognition may be attributed to “normal ageing effects” or, in case of severe deterioration, to a form of dementia. The purpose of the current study was to shed light on this cognitive deterioration from a neuropsychological point of view by comparing the IQ-profile of 21 ACA-patients with that of matched healthy controls and epilepsy patients without ACA, in order to elucidate the classification of this type of cognitive deterioration and hopefully improve clinical diagnostics by reducing underdetection. Cognitive deterioration in our patient group is characterized by an average discrepancy score of more than 15 IQ-points (>1 SD) in FSIQ and PRI compared to the estimated premorbid intelligence levels as derived from the OPIE-IV equations. Verbal abilities remain virtually unimpaired. Working memory and in particular information processing speed were impaired in all patients with epilepsy, though with more impairment seen in the ACA-group. Since it is known that intellectual ability in epilepsy is often compromised by an impaired working memory and reduced processing speed, one might hypothesize that the reduction, as seen in the FSIQ and PRI, is in fact just a consequence of selective impairments in working memory and processing speed, rather than a loss of general cognitive ability. To assess the effects of impairments in aforementioned fluid functions on the expression of underlying intellectual abilities, the GAI was obtained and compared to the FSIQ. According to the WAIS-IV Technical and Interpretive Manual, the GAI is comparable to the FSIQ in the normal healthy population with a GAI–FSIQ discrepancy of eight points or more considered to be clinically significant with a rate of 5.2% in the general population (Baxendale, McGrath, & Thompson, 2014; Wechsler, 2008b). In our sample, the GAI–FSIQ discrepancy was significantly larger in all epilepsy patients compared to healthy controls with clinically significant GAI > FSIQ discrepancies in 23.8–28.6% of cases. This suggests that, in accordance with findings of Baxendale and colleagues (2014), the rates of discrepancies between GAI and FSIQ are substantially larger in epilepsy patients than in the general population. However, there was no significant difference in GAI > FSIQ discrepancy between both patient groups, suggesting impairments in fluid functions do compromise cognitive abilities in epilepsy, but only partially contribute to cognitive deterioration as seen in ACA. Reduced processing speed (but not working memory) accounted for 37% of variance in cognitive deterioration scores in the epilepsy control group, versus a relatively modest 22% in the ACA-group. In accordance with this, the WAIS-IV PSI proved to have some diagnostic value in differentiating epilepsy patients from healthy controls, but fails to differentiate between the neuropsychological profile of ACA-patients and the general epilepsy population. In our sample, more than 85% of ACA-patients could be correctly classified based on their (extended) IQ-profile and deterioration scores specifically (accounting for almost 97% of variance in a discriminant analysis). The discrepancy between predicted premorbid ability and current test performance appears to be highly reliable in differentiating between ACA- and non-ACA patients with an average discrepancy of more than 19 IQ-points between the obtained FSIQ and predicted OPIE IV-FSIQ in ACA, which is nearly three times as much as the OPIE IV FSIQ- obtained FSIQ discrepancy of 6.5 points observed in our general epilepsy population. The clinical value of this comparison between the estimated premorbid level of intellectual functioning and current neuropsychological performance has been shown in other neurological populations as well, such as in TBI (Langeluddecke & Lucas, 2004, OPIE-III) and mixed clinical samples with among others stroke, Alzheimer’s disease, Parkinson’s disease, and Huntington’s disease (Schoenberg, Duff, Scott, & Adams, 2003; Scott, Krull, Williamson, Adams, & Iverson, 1997, both OPIE-III). From a clinical perspective it is known that ACA might be mistaken for dementia. Decline in memory function in dementia is significantly correlated with decline in global cognition. In other words: more impaired global cognition is suggestive of greater discrepancies between premorbid and current memory functioning (Duff, Chelune, & Dennett, 2011). In our ACA-sample, despite the fact that severe global cognitive deterioration took place, memory functions were relatively preserved at an average functioning level (mean WMS-IV indexes varying from 91.6 to 96.0), compatible with the assumed premorbid intelligence level. Memory impairment can be present in ACA-patients, but is comparable to the level of memory functioning of the general epilepsy population. There was no significant correlation between cognitive deterioration and any of the memory scores. This seems to be in clear distinction with the most common types of dementia. Furthermore, results of a short cognitive screening with a clinically valid MMSE-like instrument for (rough) detection of cognitive impairment in dementia yielded no indications for such impairment in our ACA-group. In fact, scores in ACA-patients were equal to those observed in healthy controls. To our knowledge, no studies have been published applying OPIE-IV equations in dementia. Studies in which the neuropsychological profiles of ACA and dementia are being compared are therefore needed to further explore methods and instruments in order to make a reliable differentiation between both neurological conditions. Utilization of longitudinal data is required to monitor the process of cognitive deterioration, i.e. to confirm ACA is characterized by a cascadic drop in IQ-scores that stabilizes over time, how deterioration develops time-wise after a second hit, and whether (MRI-)biomarkers can be identified to confine or even prevent this significant and invalidating cognitive deterioration. In conclusion, a typical ACA-patient can be portrayed as a person somewhat older (50+), with an onset of epilepsy in adulthood, and a history of cardiovascular disease and/or status epilepticus. He or she complains about memory and a quite sudden inability to meet the demands of daily (working) life. The FSIQ and PRI appear to be deteriorated by an average drop of more than 15 IQ-points, which can be easily missed when only memory is evaluated in neuropsychological assessment. In contrast to most patients with dementia, memory and other higher order functions (such as verbal abilities) as well as social skills and decorum are rather preserved. A comparison made between OPIE-IV equations on the estimated premorbid intellectual functioning level and obtained IQs leads to a significant better detection of cognitive deterioration in epilepsy than the use of GAI–FSIQ discrepancies alone. Conflict of Interest Authors report no conflicts of interest. Acknowledgements None. References Baram , T. Z. ( 2012 ). The brain, seizures and epilepsy throughout life: Understanding a moving target . Epilepsy Currents , 12 , 7 – 12 . Google Scholar CrossRef Search ADS PubMed Baxendale , S. , McGrath , K. , & Thompson , P. J. ( 2014 ). 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Accelerated Cognitive Ageing in Epilepsy: A Neuropsychological Evaluation of Cognitive Deterioration

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Abstract

Abstract Objective Shed light on cognitive deterioration in Accelerated Cognitive Ageing (ACA) in epilepsy from a neuropsychological point of view in order to improve clinical diagnostics. Methods We compared the IQ-profile including GAI, OPIE IV-premorbid IQ and deterioration-scores of 21 epilepsy patients with ACA with 21 matched epilepsy patients without ACA (Epilepsy Controls) and 16 age- and education-matched Healthy Controls. Memory was also evaluated. Results Premorbid IQs were equal in all groups. Deterioration was apparent in the ACA-group in the WAIS-IV FSIQ and PRI, whereas no deterioration was found in the two control groups. PSI was impaired in both epilepsy groups, though with more impairment seen in the ACA-group. The VCI remained unimpaired. The FSIQ–GAI discrepancy was equal in both patient groups and significantly larger than in the Healthy Controls. WMS-IV memory indices were of average level in all groups. Memory impairment in ACA was not statistically different from the Epilepsy Controls. 85.7% of ACA-patients could be correctly classified through factors DET_FSIQ and PSI. Conclusions Cognitive deterioration in ACA is characterized by an average drop of 19 IQ-points in FSIQ and PRI. Verbal abilities remain unimpaired. Impairments in fluid functions compromise cognitive abilities in epilepsy, but only partially contribute to cognitive deterioration in ACA. PSI proved to have some diagnostic value in differentiating epilepsy patients from healthy controls, but fails to differentiate between ACA and Epilepsy Controls. A comparison made between OPIE-IV equations and obtained IQs leads to a significant better detection of cognitive deterioration in epilepsy than the use of GAI–FSIQ discrepancies alone. Accelerated Cognitive Ageing, Cognitive deterioration, Epilepsy, IQ, Wechsler-Adult Intelligence Scale-Fourth Edition, General Ability Index Introduction Cognitive impairment is a common comorbidity in epilepsy. It is recently estimated that up to 65% of all patients show cognitive impairment, accounting for about half of the burden of disease (Helmstaedter et al., 2014). For a long time research has focused on impairments in specific cognitive domains, such as memory impairment in temporal lobe epilepsy or impairment of the executive functions in frontal lobe epilepsy. More recently, fMRI studies brought to light that these impairments are a consequence of aberrant neuronal networks covering wide brain areas, i.e. not just limited to the site of the epileptic area (Besseling et al., 2013; Braakman et al., 2012, 2013; Vaessen et al., 2013, 2014). In addition to these aforementioned specific cognitive impairments, also global cognitive decline has been a long-standing concern and an important topic of interest. In 1889, Gowers introduced the concept of “epileptic dementia” (in: Rose, 2010). Information merely based on case reports suggests that this type of cognitive deterioration almost exclusively occurs in the context of childhood-onset chronic and often refractory epilepsies. In these conditions, accumulation of medication effects and (tonic–clonic) seizures over decades leads to gradual decline of the higher cognitive functions. The final cognitive outcome of this “chronic accumulation model” of decline can be similar to the cognitive outcome in some forms of dementia. However, in daily clinical practice clinicians also encounter another form of cognitive decline that is less well described in the literature. In a subgroup of adult patients with epilepsy who complain about cognition and a quite sudden inability to meet the demands of daily (working) life, cognitive functioning appears to be globally deteriorated. These patients do not fulfill the neuropsychological or clinical diagnostic criteria of epileptic dementia or a progressive neurological disease such as Alzheimer’s. The majority of these patients have an adult-onset epilepsy, so that they do not fit into the aforementioned “chronic accumulation model” of decline either. In a recent review, we concluded that there may exist another pattern of cognitive deterioration (Breuer et al., 2016a). We hypothesize that in a subgroup of adult patients with epilepsy, cognitive deterioration may be “cascadic” rather than progressive, thus: deterioration takes place in a relatively short period of time, and not as a consequence of chronicity. Cognitive deterioration in this subgroup develops in a stepwise “second hit model” when epilepsy affects an already vulnerable brain. The model predicts loss of cognitive reserve capacity due to e.g. traumatic brain injury (TBI) or old age, leading to a cascade of events after a second hit, i.e. epilepsy. “Ageing” is a very important factor in this process since cognitive reserve capacity decreases with age and the ageing brain might be less able to functionally compensate for additional interference, i.e. the pathogenic effects of epilepsy or comorbid diseases. The ageing adult population with an adult- or geriatric-onset epilepsy is at particular risk for this type of deterioration, taking into account that many factors converge in these late-onset epilepsies: comorbidity (especially stroke and other (cardio)vascular diseases), metabolic disturbances, increased inflammatory response to seizures, and the use of polypharmacy (Baram, 2012; Brodie, Elder & Kwan, 2009; Leppik & Birnbaum, 2010; Palop & Mucke, 2009; Stefan et al., 2014; Trinka, 2003). All these conditions, in conjunction with ageing and the associated decrease of the brain’s neuronal plasticity, increase cerebral vulnerability and lead to irreversible loss of functional reserve capacity, eventually resulting in cascadic deterioration and acceleration of cognitive ageing. We use the term “Accelerated Cognitive Ageing” for this process. Fig. 1 graphically represents the second hit model and the process of cognitive deterioration. Fig. 1. View largeDownload slide Graphical representation of Accelerated Cognitive Ageing (ACA). The dashed blue line represents the cognitive ageing trajectory without pathology. With increasing age, cognitive functioning is declining until the minimal cognitive threshold is reached. Two alternative cognitive ageing trajectories are shown. The yellow line depicts the cognitive trajectory after one hit (e.g. TBI). There is decline in cognitive function which recovers. Recovery is, however, not complete and results in a loss of functional reserve. This is followed by a normal rate of subsequent ageing. The solid red line represents ACA in the second-hit model. After a second hit (e.g. epilepsy), cascadic deterioration takes place and does not recover due to the diminished cognitive reserve capacity. In combination and interaction with the expected changes of normal ageing, cognitive ageing is accelerated and the patient’s cognitive profile resembles that of an older individual. Published in: Breuer et al., 2016a. Fig. 1. View largeDownload slide Graphical representation of Accelerated Cognitive Ageing (ACA). The dashed blue line represents the cognitive ageing trajectory without pathology. With increasing age, cognitive functioning is declining until the minimal cognitive threshold is reached. Two alternative cognitive ageing trajectories are shown. The yellow line depicts the cognitive trajectory after one hit (e.g. TBI). There is decline in cognitive function which recovers. Recovery is, however, not complete and results in a loss of functional reserve. This is followed by a normal rate of subsequent ageing. The solid red line represents ACA in the second-hit model. After a second hit (e.g. epilepsy), cascadic deterioration takes place and does not recover due to the diminished cognitive reserve capacity. In combination and interaction with the expected changes of normal ageing, cognitive ageing is accelerated and the patient’s cognitive profile resembles that of an older individual. Published in: Breuer et al., 2016a. In a previous study, we described the clinical characteristics in a series of patients with a focal epilepsy and this hypothesized cascadic cognitive deterioration (Breuer et al., 2016b). The key neuropsychological characteristics are significant cognitive deterioration in Full Scale and Performance IQ but with preservation of the higher order cognitive functions (Verbal IQ and memory). The purpose of the current study is to shed light on this cognitive deterioration from a neuropsychological point of view by comparing the IQ-profile of ACA-patients with that of matched epilepsy patients without ACA and healthy controls, in order to elucidate the classification of this type of cognitive deterioration and improve clinical diagnostics. Methods Study Population Included in this study are outpatients with a confirmed diagnosis of epilepsy, referred to a leading Dutch tertiary care centre for epilepsy (Kempenhaeghe, Heeze). In total, 201 adult epilepsy patients with subjectively reported cognitive impairment underwent a neuropsychological assessment in the period Jan. 2016–July 2017. Patients aged 18–80 with intellectual deterioration were evaluated for inclusion in our study. Intellectual deterioration was defined as ≥1 SD discrepancy between the actual WAIS-IV FSIQ and the estimated premorbid FSIQ. Exclusion criteria were mental retardation (FSIQ < 70 before the age of 18), progressive epileptic syndromes, psychiatric disease at the time of the study (e.g. schizophrenia, psychotic episodes, major depression), and a history of epilepsy-related brain surgery. Patients with neurological or psychiatric diseases that could underlie this cognitive decline (≥1 SD discrepancy between the actual WAIS-IV FSIQ and the estimated premorbid FSIQ), or progressive neurological disorders (suspicion of) neurodegenerative diseases, or other causes of aforementioned cognitive decline were also excluded. A total of 21 patients met the inclusion criterion of significant intellectual deterioration without a known or suspected cause (ACA Group). They were consecutively matched with 21 other epilepsy patients without ACA with age, educational level, type of epilepsy and duration of epilepsy as matching factors (Epilepsy Controls). Our second control group consisted of 16 age- and education-matched healthy controls (Healthy Controls). A detailed medical history as well as demographic and clinical details were obtained. All subjects signed informed consent and gave permission to use the obtained clinical data for scientific purposes. Premorbid Intelligence, Intellectual Deterioration, General Ability Index and Other Cognitive Measures Intelligence was measured using the Dutch version of the WAIS-IV (Wechsler, 2008a). For an estimation of the premorbid intelligence, the Oklahoma Premorbid Intelligence Estimate (OPIE-IV) formula was applied. The OPIE-IV equations are derived from hierarchical regression models using raw scores of two WAIS-IV subtests (Vocabulary (V) and Matrix Reasoning (MR)), age, education, sex, and ethnicity (Holdnack, Schoenberg, Lange & Iverson, 2013). OPIE-IV predictions were derived for the FSIQ, verbal intelligence (Verbal Comprehension Index (VCI)) and performance abilities (Perceptual Reasoning Index (PRI)), resulting in OPIE IV_FSIQ, OPIE IV_VCI and OPIE IV_PRI scores, respectively. There was a significant (strong) correlation between the WAIS-IV FSIQ and the OPIE IV_FSIQ in norm group Healthy Controls (r = .81, p = < .001). Similar effects were found for VCI and OPIE IV_VCI (r = .89, p = < .001) and PRI and OPIE IV_PRI (r = .72, p = .002), comparable to findings of Holdnack et al. (2013) in the normal population. Deterioration scores were calculated by subtracting the estimated premorbid IQs (OPIE IV_scores) from the actual obtained IQs, resulting in three IQ-deterioration scores: DET_FSIQ, DET_VCI, and DET_PRI. Subsequently, the WAIS-IV General Ability Index (GAI), a composite score derived from the six core subtests of the VCI and PRI, was calculated for all subjects. The GAI provides a measure of general intellectual ability and is described to serve as more of a “hold measure” since it minimizes processing speed and working memory demands, and is therefore considered to be less susceptible to cognitive decline after neurological disease than the FSIQ (Tulsky, Saklofke, Wilkins, & Weiss, 2001). The discrepancy between the GAI and the obtained FSIQ was calculated by subtracting the GAI from the FSIQ (FSIQ–GAI). The discrepancy between the GAI and the estimated premorbid FSIQ was derived in a similar manner (OPIE IV_FSIQ–GAI). The Dutch translation of the Wechsler Memory Scale Fourth Edition (WMS-IV; Wechsler, 2009) was used for measurement of memory functions. Also the Dutch version of the WMS-IV Brief Cognitive Status Exam, a valid screening instrument for brief screening of cognitive impairment in dementia (similar to the widely used Mini Mental State Examination (MMSE)), was applied. The cut-off score for rough detection of dementia was set at 42, following Bouman, Hendriks, Aldenkamp, and Kessels (2015). Data Analysis Data was analyzed using statistical software (SPSS version 24.0). Results of exploratory analyses are reported in mean (M) and standard deviation (SD). One-way ANOVAs or unpaired t-tests were used to determine whether subject groups differed on demographic and clinical variables. A multivariate analysis of variance was performed on all IQ- and cognitive deterioration measures (MANOVA using Pillai’s trace including: obtained FSIQ/VCI/PRI/WMI/PSI, OPIE-IV_scores, DET_scores, and GAI-scores). Post-hoc univariate tests with Bonferroni correction were then performed to compare each subject group to the other two subject groups on all aforementioned dependent variables. The MANOVA was followed up with a stepwise discriminant analysis. Correct classification rates were obtained using a standard and a cross-validation procedure in which each case is classified successively by the functions derived from all other cases (leave-one out classification). This method leads to more conservative estimates of the correct classification rate. A comparable result in the standard and cross-validation procedure generally attests of the stability of the classification model (Rainville, Bechara, Naqvi, & Damasio, 2006). Results Main demographic and clinical data are shown in Table 1. Table 1. Demographic and clinical characteristics of all included subjects ACA Epilepsy Controls Healthy Controls Age in years M (SD) + range 57.5 (11.6) 57.5 (11.5) 61.4 (9.4) 30–78 y 29–77 y 47–79 y Gender 42.9% male 43.8% male 57.1% male Handedness 90.5% right-handed 100% right-handed 87.5% right-handed Highest educational level 14.3% < vocational training 14.3% < vocational training 12.5% < vocational training 42.9% vocational training 42.9% vocational training 50.0% vocational training 42.9% bachelor’s degree 42.9% bachelor’s degree 37.5% bachelor’s degree 0% master’s degree 0% master’s degree 0% master’s degree Age at epilepsy onset M (SD) + range 38.2 (16.3) 32.6 (19.2) — 12–71 y 1–74 y Duration of epilepsy M (SD) + range 17.2 (15.1) 22.7 (18.3) — 1–50 y 1–54 y Type of epilepsy 61.9% cryptogenic localization-related 61.9% cryptogenic localization-related — 28.6% symptomatic 38.1% symptomatic 9.5% idiopathic 0% idiopathic Dominant seizure typea 19.0% simple partial 4.8% simple partial — 33.3% complex partial 47.6% complex partial 9.5% absence 0% absence 0% tonic–clonic 28.6% tonic–clonic 38.1% seizure free 19.0% seizure free Status epilepticus 33.3% yes 4.8% yes Seizure frequency 38.1% seizure (sz) free 19.0% seizure (sz) free — 4.8% < 1 sz/y 9.5% < 1 sz/y 19.0% 1–5 sz/y 28.6% 1–5 sz/y 14.3% 1 sz per 2 months 4.8% 1 sz per 2 months 9.5% monthly sz 14.3% monthly sz 14.3% weekly sz 19.0% weekly sz 0% daily sz 4.8% daily sz Drug loadb 1.4 (0.5) 1.5 (0.9) — Comorbid disease 81.0% has at least one comorbid disease, of which; 47.6% has at least one comorbid disease, of which; 25.0% has at least one medical condition, of which; 58.8% cardiovascular 70.0% cardiovascular 25% cardiovascular 23.5% cerebrovascular 10% cerebrovascular 0% cerebrovascular 17.6% TBI 10% TBI 0% TBI 35.3% other (i.e. immunologic, inflammatory) 50.0% other (i.e. immunologic, inflammatory) 75% other (i.e. immunologic, inflammatory) ACA Epilepsy Controls Healthy Controls Age in years M (SD) + range 57.5 (11.6) 57.5 (11.5) 61.4 (9.4) 30–78 y 29–77 y 47–79 y Gender 42.9% male 43.8% male 57.1% male Handedness 90.5% right-handed 100% right-handed 87.5% right-handed Highest educational level 14.3% < vocational training 14.3% < vocational training 12.5% < vocational training 42.9% vocational training 42.9% vocational training 50.0% vocational training 42.9% bachelor’s degree 42.9% bachelor’s degree 37.5% bachelor’s degree 0% master’s degree 0% master’s degree 0% master’s degree Age at epilepsy onset M (SD) + range 38.2 (16.3) 32.6 (19.2) — 12–71 y 1–74 y Duration of epilepsy M (SD) + range 17.2 (15.1) 22.7 (18.3) — 1–50 y 1–54 y Type of epilepsy 61.9% cryptogenic localization-related 61.9% cryptogenic localization-related — 28.6% symptomatic 38.1% symptomatic 9.5% idiopathic 0% idiopathic Dominant seizure typea 19.0% simple partial 4.8% simple partial — 33.3% complex partial 47.6% complex partial 9.5% absence 0% absence 0% tonic–clonic 28.6% tonic–clonic 38.1% seizure free 19.0% seizure free Status epilepticus 33.3% yes 4.8% yes Seizure frequency 38.1% seizure (sz) free 19.0% seizure (sz) free — 4.8% < 1 sz/y 9.5% < 1 sz/y 19.0% 1–5 sz/y 28.6% 1–5 sz/y 14.3% 1 sz per 2 months 4.8% 1 sz per 2 months 9.5% monthly sz 14.3% monthly sz 14.3% weekly sz 19.0% weekly sz 0% daily sz 4.8% daily sz Drug loadb 1.4 (0.5) 1.5 (0.9) — Comorbid disease 81.0% has at least one comorbid disease, of which; 47.6% has at least one comorbid disease, of which; 25.0% has at least one medical condition, of which; 58.8% cardiovascular 70.0% cardiovascular 25% cardiovascular 23.5% cerebrovascular 10% cerebrovascular 0% cerebrovascular 17.6% TBI 10% TBI 0% TBI 35.3% other (i.e. immunologic, inflammatory) 50.0% other (i.e. immunologic, inflammatory) 75% other (i.e. immunologic, inflammatory) Note: * = p < 0.01. aDominant seizure type is determined for the two years preceding neuropsychological assessment. bThe prescribed daily dose of antiepileptic medication divided by the defined daily dose (Lammers et al., 1995). Table 1. Demographic and clinical characteristics of all included subjects ACA Epilepsy Controls Healthy Controls Age in years M (SD) + range 57.5 (11.6) 57.5 (11.5) 61.4 (9.4) 30–78 y 29–77 y 47–79 y Gender 42.9% male 43.8% male 57.1% male Handedness 90.5% right-handed 100% right-handed 87.5% right-handed Highest educational level 14.3% < vocational training 14.3% < vocational training 12.5% < vocational training 42.9% vocational training 42.9% vocational training 50.0% vocational training 42.9% bachelor’s degree 42.9% bachelor’s degree 37.5% bachelor’s degree 0% master’s degree 0% master’s degree 0% master’s degree Age at epilepsy onset M (SD) + range 38.2 (16.3) 32.6 (19.2) — 12–71 y 1–74 y Duration of epilepsy M (SD) + range 17.2 (15.1) 22.7 (18.3) — 1–50 y 1–54 y Type of epilepsy 61.9% cryptogenic localization-related 61.9% cryptogenic localization-related — 28.6% symptomatic 38.1% symptomatic 9.5% idiopathic 0% idiopathic Dominant seizure typea 19.0% simple partial 4.8% simple partial — 33.3% complex partial 47.6% complex partial 9.5% absence 0% absence 0% tonic–clonic 28.6% tonic–clonic 38.1% seizure free 19.0% seizure free Status epilepticus 33.3% yes 4.8% yes Seizure frequency 38.1% seizure (sz) free 19.0% seizure (sz) free — 4.8% < 1 sz/y 9.5% < 1 sz/y 19.0% 1–5 sz/y 28.6% 1–5 sz/y 14.3% 1 sz per 2 months 4.8% 1 sz per 2 months 9.5% monthly sz 14.3% monthly sz 14.3% weekly sz 19.0% weekly sz 0% daily sz 4.8% daily sz Drug loadb 1.4 (0.5) 1.5 (0.9) — Comorbid disease 81.0% has at least one comorbid disease, of which; 47.6% has at least one comorbid disease, of which; 25.0% has at least one medical condition, of which; 58.8% cardiovascular 70.0% cardiovascular 25% cardiovascular 23.5% cerebrovascular 10% cerebrovascular 0% cerebrovascular 17.6% TBI 10% TBI 0% TBI 35.3% other (i.e. immunologic, inflammatory) 50.0% other (i.e. immunologic, inflammatory) 75% other (i.e. immunologic, inflammatory) ACA Epilepsy Controls Healthy Controls Age in years M (SD) + range 57.5 (11.6) 57.5 (11.5) 61.4 (9.4) 30–78 y 29–77 y 47–79 y Gender 42.9% male 43.8% male 57.1% male Handedness 90.5% right-handed 100% right-handed 87.5% right-handed Highest educational level 14.3% < vocational training 14.3% < vocational training 12.5% < vocational training 42.9% vocational training 42.9% vocational training 50.0% vocational training 42.9% bachelor’s degree 42.9% bachelor’s degree 37.5% bachelor’s degree 0% master’s degree 0% master’s degree 0% master’s degree Age at epilepsy onset M (SD) + range 38.2 (16.3) 32.6 (19.2) — 12–71 y 1–74 y Duration of epilepsy M (SD) + range 17.2 (15.1) 22.7 (18.3) — 1–50 y 1–54 y Type of epilepsy 61.9% cryptogenic localization-related 61.9% cryptogenic localization-related — 28.6% symptomatic 38.1% symptomatic 9.5% idiopathic 0% idiopathic Dominant seizure typea 19.0% simple partial 4.8% simple partial — 33.3% complex partial 47.6% complex partial 9.5% absence 0% absence 0% tonic–clonic 28.6% tonic–clonic 38.1% seizure free 19.0% seizure free Status epilepticus 33.3% yes 4.8% yes Seizure frequency 38.1% seizure (sz) free 19.0% seizure (sz) free — 4.8% < 1 sz/y 9.5% < 1 sz/y 19.0% 1–5 sz/y 28.6% 1–5 sz/y 14.3% 1 sz per 2 months 4.8% 1 sz per 2 months 9.5% monthly sz 14.3% monthly sz 14.3% weekly sz 19.0% weekly sz 0% daily sz 4.8% daily sz Drug loadb 1.4 (0.5) 1.5 (0.9) — Comorbid disease 81.0% has at least one comorbid disease, of which; 47.6% has at least one comorbid disease, of which; 25.0% has at least one medical condition, of which; 58.8% cardiovascular 70.0% cardiovascular 25% cardiovascular 23.5% cerebrovascular 10% cerebrovascular 0% cerebrovascular 17.6% TBI 10% TBI 0% TBI 35.3% other (i.e. immunologic, inflammatory) 50.0% other (i.e. immunologic, inflammatory) 75% other (i.e. immunologic, inflammatory) Note: * = p < 0.01. aDominant seizure type is determined for the two years preceding neuropsychological assessment. bThe prescribed daily dose of antiepileptic medication divided by the defined daily dose (Lammers et al., 1995). Mean age was not statistically significant different in all subject groups. There was an almost equal gender distribution within and between groups. The mean age at epilepsy onset was equal in both patient groups, though with a larger range in the Epilepsy Controls. In the ACA-group, none of the patients had an age at onset in early childhood. In fact, more than 85% of ACA-patients had an age at onset over 18 years with almost 67% of patients having an age at onset over 30 years. There was no significant difference in duration of disease among the two groups. Most epilepsy patients suffer from a cryptogenic localization-related epilepsy. In line with this, partial seizures were the most common dominant seizure type in both patient groups. More than one-third of ACA-patients have had no seizures for the past 2 years compared to nearly one-fifth in the Epilepsy Controls. Almost 29% of patients in the latter group had tonic–clonic seizures as their current dominant seizure type whereas this was the case in none of the ACA-patients. Status epilepticus (SE) was a quite common phenomenon in ACA, but not in the Epilepsy Controls (more than 33% of ACA-patients had at least one SE versus less than 5% in the Epilepsy control group). Seizure frequency in general seemed to be somewhat higher in the Epilepsy Controls than in the ACA-group. Over 14% in the ACA-group had a high seizure frequency (weekly or daily seizures) versus 23.8% in the Epilepsy Control group. Drug load in both patient groups was equal. A noteworthy difference between all three subject groups lied in the fact that no less than 81.0% of ACA-patients had at least one comorbid disease versus 47.6% in Epilepsy Controls and only 25% in the Healthy Controls. The origin of these comorbid diseases in ACA was rather diverse, but mostly (58.8%) cardiovascular. IQ-, Deterioration-, and Other Cognitive Measures (Multivariate Tests and Discriminant Analysis) Means and SDs of WAIS-IV IQs, OPIE-IV_scores, DET_scores, and GAI-scores, as well as the results of the multivariate and post-hoc univariate tests are presented in Table 2. Using Pillai’s trace, there was a significant effect of “Group” on the aforementioned cognitive measures in multivariate analysis, V = 0.96, F (26, 88) = 3.14, p = < .001. Table 2. Multivariate and univariate comparisons on cognitive measures per subject group ACA M (SD) Epilepsy M (SD) Healthy M (SD) Fa p ACA vs. H ACA vs. E E vs. H WAIS-IV indexes  FSIQ 81.1 (13.7) 99.1 (11.9) 107.8 (13.8) 20.38 .000 .000 .000 NS  VCI 95.5 (15.2) 101.3 (12.5) 106.1 (11.7) 2.94 .061 NS NS NS  PRI 80.0 (11.5) 100.5 (12.7) 102.8 (14.3) 19.10 .000 .000 .000 NS  WMI 82.1 (13.3) 93.4 (24.4) 104.6 (13.4) 7.07 .002 .001 NS NS  PSI 75.5 (18.0) 96.3 (9.6) 113.5 (9.6) 30.99 .000 .000 .000 .003 OPIE-IV scores  OPIE IV_FSIQ 100.6 (13.2) 105.4 (10.9) 109.6 (12.1) 2.58 .085 NS NS NS  OPIE IV_VCI 96.1 (15.5) 101.0 (13.3) 105.1 (14.3) 1.77 .179 NS NS NS  OPIE IV_PRI 97.7 (11.5) 101.9 (11.0) 103.7 (12.2) 1.34 .271 NS NS NS Deterioration scores  DET_FSIQ –19.4 (5.5) –6.5 (6.9) –1.8 (8.2) 34.44 .000 .000 .000 NS  DET_VCI –0.7 (6.4) 0,1 (6.3) 0.8 (5.9) 0.24 .786 NS NS NS  DET_PRI –17.7 (6.7) –1.3 (8.4) –0.9 (10.0) 26.65 .000 .000 .000 NS GAI discrepancies  GAI 86.6 (14.2) 101.2 (11.2) 105.3 (13.7) 11.04 .000 .000 .002 NS  FSIQ–GAI –5.4 (3.8) –2.1 (6.0) 2.6 (3.0) 14.18 .000 .000 NS .008  OPIE IV_FSIQ–GAI 14.0 (4.6) 4.1 (5.4) 4.4 (7.1) 19.84 .000 .000 .000 NS ACA M (SD) Epilepsy M (SD) Healthy M (SD) Fa p ACA vs. H ACA vs. E E vs. H WAIS-IV indexes  FSIQ 81.1 (13.7) 99.1 (11.9) 107.8 (13.8) 20.38 .000 .000 .000 NS  VCI 95.5 (15.2) 101.3 (12.5) 106.1 (11.7) 2.94 .061 NS NS NS  PRI 80.0 (11.5) 100.5 (12.7) 102.8 (14.3) 19.10 .000 .000 .000 NS  WMI 82.1 (13.3) 93.4 (24.4) 104.6 (13.4) 7.07 .002 .001 NS NS  PSI 75.5 (18.0) 96.3 (9.6) 113.5 (9.6) 30.99 .000 .000 .000 .003 OPIE-IV scores  OPIE IV_FSIQ 100.6 (13.2) 105.4 (10.9) 109.6 (12.1) 2.58 .085 NS NS NS  OPIE IV_VCI 96.1 (15.5) 101.0 (13.3) 105.1 (14.3) 1.77 .179 NS NS NS  OPIE IV_PRI 97.7 (11.5) 101.9 (11.0) 103.7 (12.2) 1.34 .271 NS NS NS Deterioration scores  DET_FSIQ –19.4 (5.5) –6.5 (6.9) –1.8 (8.2) 34.44 .000 .000 .000 NS  DET_VCI –0.7 (6.4) 0,1 (6.3) 0.8 (5.9) 0.24 .786 NS NS NS  DET_PRI –17.7 (6.7) –1.3 (8.4) –0.9 (10.0) 26.65 .000 .000 .000 NS GAI discrepancies  GAI 86.6 (14.2) 101.2 (11.2) 105.3 (13.7) 11.04 .000 .000 .002 NS  FSIQ–GAI –5.4 (3.8) –2.1 (6.0) 2.6 (3.0) 14.18 .000 .000 NS .008  OPIE IV_FSIQ–GAI 14.0 (4.6) 4.1 (5.4) 4.4 (7.1) 19.84 .000 .000 .000 NS adf = 2, 55. ACA = ACA-group. Epilepsy/E = Epilepsy Controls. Healthy/H = Healthy Controls. In pairwise comparisons, p-values are given for significant contrasts based on Bonferroni-correction. NS = non-significant. Table 2. Multivariate and univariate comparisons on cognitive measures per subject group ACA M (SD) Epilepsy M (SD) Healthy M (SD) Fa p ACA vs. H ACA vs. E E vs. H WAIS-IV indexes  FSIQ 81.1 (13.7) 99.1 (11.9) 107.8 (13.8) 20.38 .000 .000 .000 NS  VCI 95.5 (15.2) 101.3 (12.5) 106.1 (11.7) 2.94 .061 NS NS NS  PRI 80.0 (11.5) 100.5 (12.7) 102.8 (14.3) 19.10 .000 .000 .000 NS  WMI 82.1 (13.3) 93.4 (24.4) 104.6 (13.4) 7.07 .002 .001 NS NS  PSI 75.5 (18.0) 96.3 (9.6) 113.5 (9.6) 30.99 .000 .000 .000 .003 OPIE-IV scores  OPIE IV_FSIQ 100.6 (13.2) 105.4 (10.9) 109.6 (12.1) 2.58 .085 NS NS NS  OPIE IV_VCI 96.1 (15.5) 101.0 (13.3) 105.1 (14.3) 1.77 .179 NS NS NS  OPIE IV_PRI 97.7 (11.5) 101.9 (11.0) 103.7 (12.2) 1.34 .271 NS NS NS Deterioration scores  DET_FSIQ –19.4 (5.5) –6.5 (6.9) –1.8 (8.2) 34.44 .000 .000 .000 NS  DET_VCI –0.7 (6.4) 0,1 (6.3) 0.8 (5.9) 0.24 .786 NS NS NS  DET_PRI –17.7 (6.7) –1.3 (8.4) –0.9 (10.0) 26.65 .000 .000 .000 NS GAI discrepancies  GAI 86.6 (14.2) 101.2 (11.2) 105.3 (13.7) 11.04 .000 .000 .002 NS  FSIQ–GAI –5.4 (3.8) –2.1 (6.0) 2.6 (3.0) 14.18 .000 .000 NS .008  OPIE IV_FSIQ–GAI 14.0 (4.6) 4.1 (5.4) 4.4 (7.1) 19.84 .000 .000 .000 NS ACA M (SD) Epilepsy M (SD) Healthy M (SD) Fa p ACA vs. H ACA vs. E E vs. H WAIS-IV indexes  FSIQ 81.1 (13.7) 99.1 (11.9) 107.8 (13.8) 20.38 .000 .000 .000 NS  VCI 95.5 (15.2) 101.3 (12.5) 106.1 (11.7) 2.94 .061 NS NS NS  PRI 80.0 (11.5) 100.5 (12.7) 102.8 (14.3) 19.10 .000 .000 .000 NS  WMI 82.1 (13.3) 93.4 (24.4) 104.6 (13.4) 7.07 .002 .001 NS NS  PSI 75.5 (18.0) 96.3 (9.6) 113.5 (9.6) 30.99 .000 .000 .000 .003 OPIE-IV scores  OPIE IV_FSIQ 100.6 (13.2) 105.4 (10.9) 109.6 (12.1) 2.58 .085 NS NS NS  OPIE IV_VCI 96.1 (15.5) 101.0 (13.3) 105.1 (14.3) 1.77 .179 NS NS NS  OPIE IV_PRI 97.7 (11.5) 101.9 (11.0) 103.7 (12.2) 1.34 .271 NS NS NS Deterioration scores  DET_FSIQ –19.4 (5.5) –6.5 (6.9) –1.8 (8.2) 34.44 .000 .000 .000 NS  DET_VCI –0.7 (6.4) 0,1 (6.3) 0.8 (5.9) 0.24 .786 NS NS NS  DET_PRI –17.7 (6.7) –1.3 (8.4) –0.9 (10.0) 26.65 .000 .000 .000 NS GAI discrepancies  GAI 86.6 (14.2) 101.2 (11.2) 105.3 (13.7) 11.04 .000 .000 .002 NS  FSIQ–GAI –5.4 (3.8) –2.1 (6.0) 2.6 (3.0) 14.18 .000 .000 NS .008  OPIE IV_FSIQ–GAI 14.0 (4.6) 4.1 (5.4) 4.4 (7.1) 19.84 .000 .000 .000 NS adf = 2, 55. ACA = ACA-group. Epilepsy/E = Epilepsy Controls. Healthy/H = Healthy Controls. In pairwise comparisons, p-values are given for significant contrasts based on Bonferroni-correction. NS = non-significant. As listed in Table 2, the premorbid IQ-indices (OPIE-IV scores) were estimated at an average level in all three subject groups, suggesting all subjects had a comparable level of intelligence before onset of disease, in line with the matched educational levels. When comparing the obtained WAIS-IV intelligence-indices however, the FSIQ, PRI, and PSI in the ACA-group were in a significantly lower range than in the Epilepsy and Healthy Controls, whereas the VCI remained unimpaired. Verbal working memory in ACA was impaired relative to the Healthy Controls, but at the same level as the Epilepsy Control group. Information processing speed was impaired in both epilepsy patient groups, though with significantly more impairment seen in the ACA-patients. This was confirmed when comparing deterioration scores among subject groups. In the ACA-group, significant deterioration was apparent in the FSIQ and PRI, whereas no deterioration took place in the two control groups. The mean GAI was, in accordance with the above, in a significantly lower range in the ACA-group than it was in the other two subject groups. The FSIQ–GAI discrepancy was equal in both patient groups and in both cases significantly larger than in the Healthy Controls. In the ACA-group, a total of 28.6% had a clinically significant GAI > FSIQ discrepancy as determined via the base rate for the overall normative sample, which only slightly differed from the total of 23.8% of clinically significant GAI > FSIQ discrepancies in the Epilepsy Controls. In the Epilepsy control-group, only two subjects had a clinically significant discrepancy in the other direction (GAI < FSIQ) versus none in the ACA-group. In the Healthy Controls, only one subject had a clinically significant GAI–FSIQ discrepancy (GAI < FSIQ). The discrepancy between the premorbid IQ (OPIE IV_FSIQ) and the GAI was comparable in both control groups, but significantly larger in ACA-patients. Analysis of memory scores (listed in Table 3) revealed all WMS-IV memory indices to be of average level in all three subject groups. Compared to the Healthy Controls, memory scores in ACA were significantly lower, though not statistically different from the Epilepsy Controls. Auditory Memory as well as Delayed Memory were both significantly impaired in all epilepsy patients compared to the Healthy Controls. Table 3. Univariate comparisons on WMS-IV memory indexes per subject group ACA M (SD) Epilepsy M (SD) Healthy M (SD) Fa p ACA vs. H ACA vs. E E vs. H WMS-IV indexes  Auditory M. 96.0 (12.5) 93.0 (16.6) 108.8 (12.5) 5.86 .005 .037 NS .006  Visual M. 91.6 (10.4) 98.8 (12.9) 102.8 (12.8) 3.64 .034 .033 NS NS  Visual Working M. 94.3 (12.2) 107.5 (14.1) 112.6 (13.9) 5.10 .012 .012 NS NS  Immediate M. 92.6 (12.1) 96.6 (15.6) 108.4 (15.0) 5.42 .008 .008 NS NS  Delayed M. 93.1 (12.0) 93.0 (13.2) 106.1 (12.3) 5.98 .005 .013 NS .011 ACA M (SD) Epilepsy M (SD) Healthy M (SD) Fa p ACA vs. H ACA vs. E E vs. H WMS-IV indexes  Auditory M. 96.0 (12.5) 93.0 (16.6) 108.8 (12.5) 5.86 .005 .037 NS .006  Visual M. 91.6 (10.4) 98.8 (12.9) 102.8 (12.8) 3.64 .034 .033 NS NS  Visual Working M. 94.3 (12.2) 107.5 (14.1) 112.6 (13.9) 5.10 .012 .012 NS NS  Immediate M. 92.6 (12.1) 96.6 (15.6) 108.4 (15.0) 5.42 .008 .008 NS NS  Delayed M. 93.1 (12.0) 93.0 (13.2) 106.1 (12.3) 5.98 .005 .013 NS .011 adf = 2, 48 for Auditory M(emory), Visual M(emory), Immediate M(emory) and Delayed M(emory). df = 2, 32 for Visual Working M(emory). ACA = ACA-group. Epilepsy/E = Epilepsy Controls. Healthy/H = Healthy Controls. In pairwise comparisons, p-values are given for significant contrasts based on Bonferroni-correction. NS = non-significant. Table 3. Univariate comparisons on WMS-IV memory indexes per subject group ACA M (SD) Epilepsy M (SD) Healthy M (SD) Fa p ACA vs. H ACA vs. E E vs. H WMS-IV indexes  Auditory M. 96.0 (12.5) 93.0 (16.6) 108.8 (12.5) 5.86 .005 .037 NS .006  Visual M. 91.6 (10.4) 98.8 (12.9) 102.8 (12.8) 3.64 .034 .033 NS NS  Visual Working M. 94.3 (12.2) 107.5 (14.1) 112.6 (13.9) 5.10 .012 .012 NS NS  Immediate M. 92.6 (12.1) 96.6 (15.6) 108.4 (15.0) 5.42 .008 .008 NS NS  Delayed M. 93.1 (12.0) 93.0 (13.2) 106.1 (12.3) 5.98 .005 .013 NS .011 ACA M (SD) Epilepsy M (SD) Healthy M (SD) Fa p ACA vs. H ACA vs. E E vs. H WMS-IV indexes  Auditory M. 96.0 (12.5) 93.0 (16.6) 108.8 (12.5) 5.86 .005 .037 NS .006  Visual M. 91.6 (10.4) 98.8 (12.9) 102.8 (12.8) 3.64 .034 .033 NS NS  Visual Working M. 94.3 (12.2) 107.5 (14.1) 112.6 (13.9) 5.10 .012 .012 NS NS  Immediate M. 92.6 (12.1) 96.6 (15.6) 108.4 (15.0) 5.42 .008 .008 NS NS  Delayed M. 93.1 (12.0) 93.0 (13.2) 106.1 (12.3) 5.98 .005 .013 NS .011 adf = 2, 48 for Auditory M(emory), Visual M(emory), Immediate M(emory) and Delayed M(emory). df = 2, 32 for Visual Working M(emory). ACA = ACA-group. Epilepsy/E = Epilepsy Controls. Healthy/H = Healthy Controls. In pairwise comparisons, p-values are given for significant contrasts based on Bonferroni-correction. NS = non-significant. The average score on the Dutch version of the WMS-IV Brief Cognitive Status Exam (not in table), a valid screening instrument for the detection of cognitive impairment in dementia, was well above the cut-off point of 42 in all three groups (Mean and SD 48.3 (6.3), 51.5 (5.7), and 51.7 (10.2) in the ACA-group, Epilepsy Controls, and Healthy Controls, respectively). The possibility to discriminate between the three subject groups based on all cognitive measures in Table 2 was further tested in a stepwise discriminant analysis. This analysis revealed two discriminant functions of which the first (DET_FSIQ) explained 96.7% of variance (canonical R2 = .61), whereas the second (PSI) explained 3.3% of variance (canonical R2 = .05). In combination, these discriminant functions significantly differentiated between the subject groups (Λ = 0.37, χ2 (4) = 54.29, p = < .0005), but removing the first function learned that the second function alone did not significantly differentiate between the three groups (Λ = 0.95, χ2 (1) = 2.85, p = .092). The discriminant function plot showed that the function DET_FSIQ discriminated the ACA-group from the two control groups, whereas the PSI differentiated between the epilepsy control-group and the Healthy Controls. The overall successful ACA-classification rate was 85.7% in both the original classification-method and the more conservative cross-validation procedure, whereas 52.4% and 62.5% of Epilepsy and Healthy Controls respectively could be successfully classified in the cross-validation procedure (Table 4). Table 4. Classification results and predicted group membership ACA Healthy Controls Epilepsy Controls Original % ACA 85.7 4.8 9.5 Healthy controls .0 68.8 31.3 Epilepsy controls 23.8 19.0 57.1 Cross-validated % ACA 85.7 4.8 9.5 Healthy controls .0 62.5 37.5 Epilepsy controls 28.6 19.0 52.4 ACA Healthy Controls Epilepsy Controls Original % ACA 85.7 4.8 9.5 Healthy controls .0 68.8 31.3 Epilepsy controls 23.8 19.0 57.1 Cross-validated % ACA 85.7 4.8 9.5 Healthy controls .0 62.5 37.5 Epilepsy controls 28.6 19.0 52.4 Table 4. Classification results and predicted group membership ACA Healthy Controls Epilepsy Controls Original % ACA 85.7 4.8 9.5 Healthy controls .0 68.8 31.3 Epilepsy controls 23.8 19.0 57.1 Cross-validated % ACA 85.7 4.8 9.5 Healthy controls .0 62.5 37.5 Epilepsy controls 28.6 19.0 52.4 ACA Healthy Controls Epilepsy Controls Original % ACA 85.7 4.8 9.5 Healthy controls .0 68.8 31.3 Epilepsy controls 23.8 19.0 57.1 Cross-validated % ACA 85.7 4.8 9.5 Healthy controls .0 62.5 37.5 Epilepsy controls 28.6 19.0 52.4 Discussion Results from an increasing number of studies have indicated that the cognitive ageing trajectory in patients with epilepsy differs from the pattern observed in healthy ageing (Helmstaedter & Elger, 2009; Hermann et al., 2006b, 2008). In our previous work, we described two models of aberrant cognitive ageing, with on the one hand “epileptic dementia” as proposed by Gowers in the past; i.e. slow and gradual cognitive deterioration due to accumulation of negative effects of seizures, treatment, and other epilepsy-related factors in early-onset, chronic and often drug-resistant epilepsy. On the other hand and in addition to this “chronic accumulation model”, cognitive deterioration may develop in a shorter period of time and in a stepwise “second hit model”, where cascadic deterioration takes places as a consequence of irreversible loss of cognitive reserve capacity due to first and second hits to the brain in combination and interaction with the normal ageing process and loss of brain plasticity inherent to ageing. The ageing adult population with an adult- or geriatric-onset epilepsy is at particular risk for this Accelerated Cognitive Ageing (ACA), taking into account that many factors converge in these late-onset epilepsies: comorbidity (especially stroke and other (cardio)vascular disease), metabolic disturbances, increased inflammatory response to seizures, and the use of polypharmacy (Baram, 2012; Brodie et al., 2009; Leppik & Birnbaum, 2010; Palop & Mucke, 2009; Stefan et al., 2014; Trinka, 2003). Especially in this group, however, underdetection may lurk as deteriorated cognition may be attributed to “normal ageing effects” or, in case of severe deterioration, to a form of dementia. The purpose of the current study was to shed light on this cognitive deterioration from a neuropsychological point of view by comparing the IQ-profile of 21 ACA-patients with that of matched healthy controls and epilepsy patients without ACA, in order to elucidate the classification of this type of cognitive deterioration and hopefully improve clinical diagnostics by reducing underdetection. Cognitive deterioration in our patient group is characterized by an average discrepancy score of more than 15 IQ-points (>1 SD) in FSIQ and PRI compared to the estimated premorbid intelligence levels as derived from the OPIE-IV equations. Verbal abilities remain virtually unimpaired. Working memory and in particular information processing speed were impaired in all patients with epilepsy, though with more impairment seen in the ACA-group. Since it is known that intellectual ability in epilepsy is often compromised by an impaired working memory and reduced processing speed, one might hypothesize that the reduction, as seen in the FSIQ and PRI, is in fact just a consequence of selective impairments in working memory and processing speed, rather than a loss of general cognitive ability. To assess the effects of impairments in aforementioned fluid functions on the expression of underlying intellectual abilities, the GAI was obtained and compared to the FSIQ. According to the WAIS-IV Technical and Interpretive Manual, the GAI is comparable to the FSIQ in the normal healthy population with a GAI–FSIQ discrepancy of eight points or more considered to be clinically significant with a rate of 5.2% in the general population (Baxendale, McGrath, & Thompson, 2014; Wechsler, 2008b). In our sample, the GAI–FSIQ discrepancy was significantly larger in all epilepsy patients compared to healthy controls with clinically significant GAI > FSIQ discrepancies in 23.8–28.6% of cases. This suggests that, in accordance with findings of Baxendale and colleagues (2014), the rates of discrepancies between GAI and FSIQ are substantially larger in epilepsy patients than in the general population. However, there was no significant difference in GAI > FSIQ discrepancy between both patient groups, suggesting impairments in fluid functions do compromise cognitive abilities in epilepsy, but only partially contribute to cognitive deterioration as seen in ACA. Reduced processing speed (but not working memory) accounted for 37% of variance in cognitive deterioration scores in the epilepsy control group, versus a relatively modest 22% in the ACA-group. In accordance with this, the WAIS-IV PSI proved to have some diagnostic value in differentiating epilepsy patients from healthy controls, but fails to differentiate between the neuropsychological profile of ACA-patients and the general epilepsy population. In our sample, more than 85% of ACA-patients could be correctly classified based on their (extended) IQ-profile and deterioration scores specifically (accounting for almost 97% of variance in a discriminant analysis). The discrepancy between predicted premorbid ability and current test performance appears to be highly reliable in differentiating between ACA- and non-ACA patients with an average discrepancy of more than 19 IQ-points between the obtained FSIQ and predicted OPIE IV-FSIQ in ACA, which is nearly three times as much as the OPIE IV FSIQ- obtained FSIQ discrepancy of 6.5 points observed in our general epilepsy population. The clinical value of this comparison between the estimated premorbid level of intellectual functioning and current neuropsychological performance has been shown in other neurological populations as well, such as in TBI (Langeluddecke & Lucas, 2004, OPIE-III) and mixed clinical samples with among others stroke, Alzheimer’s disease, Parkinson’s disease, and Huntington’s disease (Schoenberg, Duff, Scott, & Adams, 2003; Scott, Krull, Williamson, Adams, & Iverson, 1997, both OPIE-III). From a clinical perspective it is known that ACA might be mistaken for dementia. Decline in memory function in dementia is significantly correlated with decline in global cognition. In other words: more impaired global cognition is suggestive of greater discrepancies between premorbid and current memory functioning (Duff, Chelune, & Dennett, 2011). In our ACA-sample, despite the fact that severe global cognitive deterioration took place, memory functions were relatively preserved at an average functioning level (mean WMS-IV indexes varying from 91.6 to 96.0), compatible with the assumed premorbid intelligence level. Memory impairment can be present in ACA-patients, but is comparable to the level of memory functioning of the general epilepsy population. There was no significant correlation between cognitive deterioration and any of the memory scores. This seems to be in clear distinction with the most common types of dementia. Furthermore, results of a short cognitive screening with a clinically valid MMSE-like instrument for (rough) detection of cognitive impairment in dementia yielded no indications for such impairment in our ACA-group. In fact, scores in ACA-patients were equal to those observed in healthy controls. To our knowledge, no studies have been published applying OPIE-IV equations in dementia. Studies in which the neuropsychological profiles of ACA and dementia are being compared are therefore needed to further explore methods and instruments in order to make a reliable differentiation between both neurological conditions. Utilization of longitudinal data is required to monitor the process of cognitive deterioration, i.e. to confirm ACA is characterized by a cascadic drop in IQ-scores that stabilizes over time, how deterioration develops time-wise after a second hit, and whether (MRI-)biomarkers can be identified to confine or even prevent this significant and invalidating cognitive deterioration. In conclusion, a typical ACA-patient can be portrayed as a person somewhat older (50+), with an onset of epilepsy in adulthood, and a history of cardiovascular disease and/or status epilepticus. He or she complains about memory and a quite sudden inability to meet the demands of daily (working) life. The FSIQ and PRI appear to be deteriorated by an average drop of more than 15 IQ-points, which can be easily missed when only memory is evaluated in neuropsychological assessment. In contrast to most patients with dementia, memory and other higher order functions (such as verbal abilities) as well as social skills and decorum are rather preserved. A comparison made between OPIE-IV equations on the estimated premorbid intellectual functioning level and obtained IQs leads to a significant better detection of cognitive deterioration in epilepsy than the use of GAI–FSIQ discrepancies alone. Conflict of Interest Authors report no conflicts of interest. Acknowledgements None. References Baram , T. Z. ( 2012 ). The brain, seizures and epilepsy throughout life: Understanding a moving target . Epilepsy Currents , 12 , 7 – 12 . Google Scholar CrossRef Search ADS PubMed Baxendale , S. , McGrath , K. , & Thompson , P. J. ( 2014 ). 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Archives of Clinical NeuropsychologyOxford University Press

Published: Apr 27, 2018

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