Grading system for assessing the confidence in the epileptogenic zone reported in published studies: A Delphi consensus study.

OBJECTIVE: This study was undertaken to develop a standardized grading system based on expert consensus for evaluating the level of confidence in the localization of the epileptogenic zone (EZ) as reported in published studies, to harmonize and facilitate systematic reviews in the field of epilepsy surgery. METHODS: We conducted a Delphi study involving 22 experts from 18 countries, who were asked to rate their level of confidence in the localization of the EZ for various theoretical clinical scenarios, using different scales. Information provided in these scenarios included one or several of the following data: magnetic resonance imaging (MRI) findings, invasive electroencephalography summary, and postoperative seizure outcome. RESULTS: The first explorative phase showed an overall interrater agreement of .347, pointing to large heterogeneity among experts' assessments, with only 17% of the 42 proposed scenarios associated with a substantial level of agreement. A majority showed preferences for the simpler scale and single-item scenarios. The successive Delphi voting phases resulted in a majority consensus across experts, with more than two thirds of respondents agreeing on the rating of each of the tested single-item scenarios. High or very high levels of confidence were ascribed to patients with either an Engel class I or class IA postoperative seizure outcome, a well-delineated EZ according to all available invasive EEG (iEEG) data, or a well-delineated focal epileptogenic lesion on MRI. MRI signs of hippocampal sclerosis or atrophy were associated with a moderate level of confidence, whereas a low level was ascribed to other MRI findings, a poorly delineated EZ according to iEEG data, or an Engel class II-IV postoperative seizure outcome. SIGNIFICANCE: The proposed grading system, based on an expert consensus, provides a simple framework to rate the level of confidence in the EZ reported in published studies in a structured and harmonized way, offering an opportunity to facilitate and increase the quality of systematic reviews and guidelines in the field of epilepsy surgery.

Visual outcomes after anterior temporal lobectomy and transsylvian selective amygdalohippocampectomy: A quantitative comparison of clinical and diffusion data.

OBJECTIVE: Anterior temporal lobectomy (ATL) and transsylvian selective amygdalohippocampectomy (tsSAHE) are effective treatment strategies for intractable temporal lobe epilepsy but may cause visual field deficits (VFDs) by damaging the optic radiation (OpR). Due to the OpR's considerable variability and because it is indistinguishable from surrounding tissue without further technical guidance, it is highly vulnerable to iatrogenic injury. This imaging study uses a multimodal approach to assess visual outcomes after epilepsy surgery. METHODS: We studied 62 patients who underwent ATL (n = 32) or tsSAHE (n = 30). Analysis of visual outcomes was conducted in four steps, including the assessment of (1) perimetry outcome (VFD incidence/extent, n = 44/40), (2) volumetric OpR tractography damage (n = 55), and the (3) relation of volumetric OpR tractography damage and perimetry outcome (n = 35). Furthermore, (4) fixel-based analysis (FBA) was performed to assess micro- and macrostructural changes within the OpR following surgery (n = 36). RESULTS: Altogether, 56% of all patients had postoperative VFDs (78.9% after ATL, 36.36% after tsSAHE, p = .011). VFDs and OpR tractography damage tended to be more severe within the ATL group (ATL vs. tsSAHE, integrity of contralateral upper quadrant: 65% vs. 97%, p = .002; OpR tractography damage: 69.2 mm3 vs. 3.8 mm3 , p = .002). Volumetric OpR tractography damage could reliably predict VFD incidence (86% sensitivity, 78% specificity) and could significantly explain VFD extent (R2  = .47, p = .0001). FBA revealed a more widespread decline of fibre cross-section within the ATL group. SIGNIFICANCE: In the context of controversial visual outcomes following epilepsy surgery, this study provides clinical as well as neuroimaging evidence for a higher risk and greater severity of postoperative VFDs after ATL compared to tsSAHE. Volumetric OpR tractography damage is a feasible parameter to reliably predict this morbidity in both treatment groups and may ultimately support personalized planning of surgical candidates. Advanced diffusion analysis tools such as FBA offer a structural explanation of surgically induced visual pathway damage, allowing noninvasive quantification and visualization of micro- and macrostructural tract affection.

Seizure detection with deep neural networks for review of two-channel electroencephalogram.

Ultra-long-term electroencephalographic (EEG) registration using minimally invasive low-channel devices is an emerging technology to assess sporadic seizure events. Highly sensitive automatic seizure detection algorithms are needed for semiautomatic evaluation of these prolonged recordings. We describe the design and validation of a deep neural network for two-channel seizure detection. The model is trained using EEG recordings from 590 patients in a publicly available seizure database. These recordings are based on the full 10-20 electrode system and include seizure annotations created by reviews of the full set of EEG channels. Validation was performed using 48 scalp EEG recordings from an independent epilepsy center and consensus seizure annotations from three neurologists. For each patient, a three-electrode subgroup (two channels with a common reference) of the full montage was selected for validation of the two-channel model. Mean sensitivity across patients of 88.8% and false positive rate across patients of 12.9/day were achieved. The proposed training approach is of great practical relevance, because true recordings from low-channel devices are currently available only in small numbers, and the generation of gold standard seizure annotations in two EEG channels is often difficult. The study demonstrates that automatic seizure detection based on two-channel EEG data is feasible and review of ultra-long-term recordings can be made efficient and effective.

Systematic analysis and comparison of commercial seizure-detection software.

OBJECTIVE: To determine if three different commercially available seizure-detection software packages (Besa 2.0, Encevis 1.7, and Persyst 13) accurately detect seizures with high sensitivity, high specificity, and short detection delay in epilepsy patients undergoing long-term video-electroencephalography (EEG) monitoring (VEM). METHODS: Comparison of sensitivity (detection rate), specificity (false alarm rate), and detection delay of three commercially available seizure-detection software packages in 81 randomly selected patients with epilepsy undergoing long-term VEM. RESULTS: Detection rates on a per-patient basis were not significantly different between Besa (mean 67.6%, range 0-100%), Encevis (77.8%, 0-100%) and Persyst (81%, 0-100%; P = .059). False alarm rate (per hour) was significantly different between Besa (mean 0.7/h, range 0.01-6.2/h), Encevis (0.2/h, 0.01-0.5/h), and Persyst (0.9/h, 0.04-6.5/h; P < .001). Detection delay was significantly different between Besa (mean 30 s, range 0-431 s), Encevis (25 s, 2-163 s), and Persyst (20 s, 0-167 s; P = .007). Kappa statistics showed moderate to substantial agreement between the reference standard and each seizure-detection software (Besa: 0.47, 95% confidence interval [CI] 0.36-0.59; Encevis: 0.59, 95% CI 0.47-0.7; Persyst: 0.63, 95% CI 0.51-0.74). SIGNIFICANCE: Three commercially available seizure-detection software packages showed similar, reasonable sensitivities on the same data set, but differed in false alarm rates and detection delay. Persyst 13 showed the highest detection rate and false alarm rate with the shortest detection delay, whereas Encevis 1.7 had a slightly lower sensitivity, the lowest false alarm rate, and longer detection delay.

Hyposmia Is Associated with Reduced Cognitive Function in COVID-19: First Preliminary Results.

BACKGROUND: Hyposmia is frequently reported as an initial symptom in coronavirus disease 2019 (COVID-19). OBJECTIVE: As hyposmia accompanies cognitive impairment in several neurological disorders, we aimed to study whether hyposmia represents a clinical biomarker for both neurological involvement and cognitive impairment in mild CO-VID-19. We aimed to study whether olfactory dysfunction (OD) represents a clinical biomarker for both neurological involvement and cognitive impairment in mild COVID-19. METHODS: Formal olfactory testing using the Sniffin'Sticks® Screening test, neuropsychological assessment using the Montreal Cognitive Assessment (MoCA), and detailed neurological examination were performed in 7 COVID-19 patients with mild disease course and no history of olfactory or cognitive impairment, and 7 controls matched for age, sex, and education. Controls were initially admitted to a dedicated COVID-19 screening ward but tested negative by real-time PCR. RESULTS: The number of correctly identified odors was significantly lower in COVID-19 than in controls (6 ± 3, vs. 10 ± 1 p = 0.028, r = 0.58). Total MoCA score was significantly lower in COVID-19 patients than in controls (20 ± 5 vs. 26 ± 3, p = 0.042, r = 0.54). Cognitive performance indicated by MoCA was associated with number of correctly identified odors in COVID-19 patients and controls (COVID-19: p = 0.018, 95% CI = 9-19; controls: p = 0.18, r = 0.63, 95% CI = 13-18.5 r = 0.64). DISCUSSION/CONCLUSION: OD is associated with cognitive impairment in controls and mild COVID-19. OD may represent a potentially useful clinical biomarker for subtle and even subclinical neurological involvement in severe acute respiratory distress syndrome coronavirus-2 infection.

[Automatic detection of epileptiform potentials and seizures in the EEG]. / Automatische Erkennung von epilepsietypischen Potenzialen und Anfällen im EEG.

Automatic computer-based algorithms for the detection of epileptiform potentials and seizure patterns on EEG facilitate a time-saving, objective method of quantitative EEG interpretation which is available 7/24. For the automatic detection of interictal epileptiform potentials sensitivities range from 65 to 99% with false positive detections of 0,09 to 13,4 per minute. Recent studies documented equal or even better performance of automatic spike detection programs compared with experienced human EEG readers. The seizure detection problem-one of the major problems in clinical epileptology-consists of the fact that the majority of focal onset seizures with impaired awareness and of seizures arising out of sleep occur unnoticed by patients and their caregivers. Automatic seizure detection systems could facilitate objective seizure documentation and thus help to solve the seizure detection problem. Furthermore, seizure detection systems may help to prevent seizure-related injuries and sudden unexpected death in epilepsy (SUDEP), and could be an integral part of novel, seizure-triggered on-demand therapies in epilepsy. During long-term video-EEG monitoring seizure detection systems could improve patient safety, provide a time-saving objective and reproducible analysis of seizure patterns and facilitate automatic computer-based patient testing during seizures. Sensitivities of seizure detection systems range from 75 to 90% with extratemporal seizures being more difficult to detect than temporal seizures. The false positive alarm rate ranges from 0,1 to 5 per 24 hours. Finally, machine learning algorithms, especially deep learning approaches, open a new highly promising era in automatic spike and seizure detection.

Critical Care EEG.

Neuromonitoring by means of continuous EEG (cEEG) has been increasingly used in intensive care patients. Standardized EEG criteria can be used to reliably detect and distinguish nonconvulsive seizures or status epileptici as well as rhythmic and periodic ictal-interictal continuum EEG patterns. Likewise, cerebral ischemia can be detected early by means of cEEG, and sedation and therapy management can be monitored and controlled.

Critique of the 2017 epileptic seizure and epilepsy classifications.

This article critiques the International League Against Epilepsy (ILAE) 2015-2017 classifications of epilepsy, epileptic seizures, and status epilepticus. It points out the following shortcomings of the ILAE classifications: (1) they mix semiological terms with epileptogenic zone terminology; (2) simple and widely accepted terminology has been replaced by complex terminology containing less information; (3) seizure evolution cannot be described in any detail; (4) in the four-level epilepsy classification, level two (epilepsy category) overlaps almost 100% with diagnostic level one (seizure type); and (5) the design of different classifications with distinct frameworks for newborns, adults, and patients in status epilepticus is confusing. The authors stress the importance of validating the new ILAE classifications and feel that the decision of Epilepsia to accept only manuscripts that use the ILAE classifications is premature and regrettable.

Epidemiology and pathophysiology of autonomic seizures: a systematic review.

PURPOSE: To review the epidemiology and pathophysiology of autonomic symptoms and signs during epileptic seizures. METHODS: We performed a systematic literature search on the following autonomic symptoms and signs during epileptic seizures: cardiovascular changes, respiratory manifestations, gastrointestinal symptoms, cutaneous manifestations, sexual and genital manifestations, and urinary symptoms. RESULTS: Autonomic symptoms and signs can represent the predominant symptom at the onset of a focal seizure, which would then lead to the seizure being classified as a focal onset autonomic seizure. Conversely, clinically relevant autonomic symptoms and signs frequently accompany seizures of focal, generalized, and/or unknown onset, but the seizure is regardless classified according to other, more relevant features. Autonomic symptoms and signs do not represent mere reactions to motor activity or other behavioral seizure manifestations, but rather they are generated by epileptic discharges affecting the central autonomic network. We have reviewed the localizing and lateralizing information currently available on the seizure onset zone and on seizure propagation pathways as provided by systematic analysis of specific autonomic seizure symptoms and signs. We present data on how autonomic seizure symptoms and signs are useful for gaining a better understanding of the anatomical and functional organization of the central autonomic network. Finally, we discuss the differential diagnosis of focal autonomic seizures with autonomic symptoms and signs representing the sole seizure manifestation versus various non-epileptic conditions. CONCLUSIONS: Autonomic seizure symptoms and signs are relevant in clinical epileptology and open a unique window on the functional organization and pathophysiology of the central autonomic network.

Seizure detection using scalp-EEG.

Scalp electroencephalography (EEG)-based seizure-detection algorithms applied in a clinical setting should detect a broad range of different seizures with high sensitivity and selectivity and should be easy to use with identical parameter settings for all patients. Available algorithms provide sensitivities between 75% and 90%. EEG seizure patterns with short duration, low amplitude, circumscribed focal activity, high frequency, and unusual morphology as well as EEG seizure patterns obscured by artifacts are generally difficult to detect. Therefore, detection algorithms generally perform worse on seizures of extratemporal origin as compared to those of temporal lobe origin. Specificity (false-positive alarms) varies between 0.1 and 5 per hour. Low false-positive alarm rates are of critical importance for acceptance of algorithms in a clinical setting. Reasons for false-positive alarms include physiological and pathological interictal EEG activities as well as various artifacts. To achieve a stable, reproducible performance (especially concerning specificity), algorithms need to be tested and validated on a large amount of EEG data comprising a complete temporal assessment of all interictal EEG. Patient-specific algorithms can further improve sensitivity and specificity but need parameter adjustments and training for individual patients. Seizure alarm systems need to provide on-line calculation with short detection delays in the order of few seconds. Scalp-EEG-based seizure detection systems can be helpful in an everyday clinical setting in the epilepsy monitoring unit, but at the current stage cannot replace continuous supervision of patients and complete visual review of the acquired data by specially trained personnel. In an outpatient setting, application of scalp-EEG-based seizure-detection systems is limited because patients won't tolerate wearing widespread EEG electrode arrays for long periods in everyday life. Recently developed subcutaneous EEG electrodes may offer a solution in this respect.

Early Epileptiform Discharges and Clinical Signs Predict Nonconvulsive Status Epilepticus on Continuous EEG.

BACKGROUND: Critical care continuous electroencephalography (CCEEG) represents the gold standard for detection of nonconvulsive status epilepticus (NCSE) in neurological critical care patients. It is unclear which findings on short-term routine EEG and which clinical parameters predict NCSE during subsequent CCEEG reliably. The aim of the present study was to assess the prognostic significance of changes within the first 30 min of EEG as well as of clinical parameters for the occurrence of NCSE during subsequent CCEEG. METHODS: Systematic analysis of the first 30 min and the remaining segments of prospective CCEEG recordings according to the ACNS Standardized Critical Care EEG Terminology and according to recently proposed NCSE criteria as well as review of clinical parameters of 85 consecutive neurological critical care patients. Logistic regression and binary classification tests were used to determine the most useful parameters within the first 30 min of EEG predicting subsequent NCSE. RESULTS: The presence of early sporadic epileptiform discharges (SED) and early rhythmic or periodic EEG patterns of "ictal-interictal uncertainty" (RPPIIIU) (OR 15.51, 95% CI 2.83-84.84, p = 0.002) and clinical signs of NCS (OR 18.43, 95% CI 2.06-164.62, p = 0.009) predicted NCSE on subsequent CCEEG. Various combinations of early SED, early RPPIIIU, and clinical signs of NCS showed sensitivities of 79-100%, specificities of 49-89%, and negative predictive values of 95-100% regarding the incidence of subsequent NCSE (p < 0.001). CONCLUSIONS: Early SED and early RPPIIIU within the first 30 min of EEG as well as clinical signs of NCS predict the occurrence of NCSE during subsequent CCEEG with high sensitivity and high negative predictive value and may be useful to select patients who should undergo CCEEG.

Predictors of and attitudes toward counseling about SUDEP and other epilepsy risk factors among Austrian, German, and Swiss neurologists and neuropediatricians.

OBJECTIVE: To examine the attitudes toward counseling about sudden unexpected death in epilepsy (SUDEP) and other epilepsy risk factors among Austrian, German, and Swiss neurologists and neuropediatricians, and to determine factors associated with not discussing SUDEP. METHODS: Questionnaires were sent to approximately 5,000 neurologists and neuropediatricians in 2014 regarding respondents' demographics, their working environments, and how often they discussed SUDEP, suicidal ideations on anticonvulsive medication, driving restrictions, and risks in daily life activities. RESULTS: In total, 519 surveys were completed (respondents' mean age: 45.5 years, 41.6% female, 66.9% adult neurologists, 31.0% neuropediatricians). A minority of 2.7% reported that they counseled all of their patients on SUDEP, 8.7% counseled most of the time (50-90%), 20.8% sometimes (10-49%), 44.5% rarely (1-9%), and 23.3% reported not counseling about SUDEP at all. In contrast, 92.9% reported that they counseled all patients about driving restrictions and 81.5% about risks in daily life activities. Suicidal ideations were discussed in 59.0% for some and in 3.3% for all patients, whereas 35.1% of respondents reported never discussing suicidal ideations. Independent predictors of not discussing SUDEP were no additional epilepsy training, no or uncertain SUDEP cases in the past, <10 years in practice, <25 epilepsy patients seen per quarter, and the opinion of a lack of consequences in SUDEP prevention. The opinion that SUDEP is a risk factor in particular patient groups and the attitude that all risks should be discussed predicted counseling on SUDEP. SIGNIFICANCE: Our findings show a discrepancy between guidelines and practice regarding the discussion of premature mortality due to SUDEP or suicidality. Both are not discussed at all by a substantial proportion of neurologists and neuropediatricians. This is in contrast to ubiquitous education about driving restrictions. Dissemination of knowledge among physicians about potential preventive strategies might increase the likelihood of discussion. Clinical practice guidelines are welcomed by the majority of physicians in this process.

Psychoses in epilepsy: A comparison of postictal and interictal psychoses.

We retrospectively analyzed data of patients with epilepsy (n=1434) evaluated with prolonged EEG monitoring in order to estimate the prevalence of postictal psychosis (PP) and interictal psychosis (IP), to investigate a potential association of psychosis subtype with epilepsy type, and to assess differences between PP and IP. The overall prevalence of psychosis was 5.9% (N=85); prevalence of PP (N=53) and IP (N=32) was 3.7% and 2.2%, respectively. Of patients with psychosis, 97.6% had localization-related epilepsy (LRE). Prevalence of psychosis was highest (9.3%) in patients with temporal lobe epilepsy (TLE). When comparing PP with IP groups on demographic, clinical, and psychopathological variables, patients with IP were younger at occurrence of first psychosis (P=0.048), had a shorter interval between epilepsy onset and first psychosis (P=0.002), and more frequently exhibited schizophreniform traits (conceptual disorganization: P=0.008; negative symptoms: P=0.017) than those with PP. Postictal psychosis was significantly associated with a temporal seizure onset on ictal EEG (P=0.000) and a higher incidence of violent behavior during psychosis (P=0.047). To conclude, our results support the presumption of a preponderance of LRE in patients with psychosis and that of a specific association of TLE with psychosis, in particular with PP. Given the significant differences between groups, PP and IP may represent distinct clinical entities potentially with a different neurobiological background.

Proposal: different types of alteration and loss of consciousness in epilepsy.

There are at least five types of alterations of consciousness that occur during epileptic seizures: auras with illusions or hallucinations, dyscognitive seizures, epileptic delirium, dialeptic seizures, and epileptic coma. Each of these types of alterations of consciousness has a specific semiology and a distinct pathophysiologic mechanism. In this proposal we emphasize the need to clearly define each of these alterations/loss of consciousness and to apply this terminology in semiologic descriptions and classifications of epileptic seizures. The proposal is a consensus opinion of experienced epileptologists, and it is hoped that it will lead to systematic studies that will allow a scientific characterization of the different types of alterations/loss of consciousness described in this article.

Feasibility of an Integrated Telemonitoring System for Home-Recorded EEG with Automated AI-Based EEG Analysis.

BACKGROUND: Self-recorded EEG by patients at home might present a viable alternative to inpatient epilepsy evaluations. OBJECTIVES AND METHODS: We developed a novel telemonitoring system comprising seamlessly integrated hard- and software with automated AI-based EEG analysis. RESULTS: The first complete study participation results demonstrate feasibility and clinical utility. CONCLUSION: Our telemonitoring solution potentially improves treatment of patients with epilepsy and moreover might help to better distribute resources in the healthcare system.

Idiopathic generalized epilepsies in the epilepsy monitoring unit: Systematic quantification of focal EEG and semiological signs.

OBJECTIVE: Focal seizure symptoms (FSS) and focal interictal epileptiform discharges (IEDs) are common in patients with idiopathic generalized epilepsies (IGEs), but dedicated studies systematically quantifying them both are lacking. We used automatic IED detection and localization algorithms and correlated these EEG findings with clinical FSS for the first time in IGE patients. METHODS: 32 patients with IGEs undergoing long-term video EEG monitoring were systematically analyzed regarding focal vs. generalized IEDs using automatic IED detection and localization algorithms. Quantitative EEG findings were correlated with FSS. RESULTS: We observed FSS in 75% of patients, without significant differences between IGE subgroups. Mostly varying/shifting lateralizations of FSS across successive recorded seizures were seen. We detected a total of 81,949 IEDs, whereof 19,513 IEDs were focal (23.8%). Focal IEDs occurred in all patients (median 13% focal IEDs per patient, range 1.1 - 51.1%). Focal IED lateralization and localization predominance had no significant effect on FSS. CONCLUSIONS: All included patients with IGE showed focal IEDs and three-quarter had focal seizure symptoms irrespective of the specific IGE subgroup. Focal IED localization had no significant effect on lateralization and localization of FSS. SIGNIFICANCE: Our findings may facilitate diagnostic and treatment decisions in patients with suspected IGE and focal signs.

Signatures of migraine aura in high-density-EEG.

OBJECTIVE: Cortical spreading depolarization is highly conserved among the species. It is easily detectable in direct cortical surface recordings and has been recorded in the cortex of humans with severe neurological disease. It is considered the pathophysiological correlate of human migraine aura, but direct electrophysiological evidence is still missing. As signatures of cortical spreading depolarization have been recognized in scalp EEG, we investigated typical spontaneous migraine aura, using full band high-density EEG (HD-EEG). METHODS: In this prospective study, patients with migraine with aura were investigated during spontaneous migraine aura and interictally. Time compressed HD-EEG were analyzed for the presence of cortical spreading depolarization characterized by (a) slow potential changes below 0.05 Hz, (b) suppression of faster activity from 0.5 Hz - 45 Hz (c) spreading of these changes to neighboring regions during the aura phase. Further, topographical changes in alpha-power spectral density (8-14 Hz) during aura were analyzed. RESULTS: In total, 26 HD-EEGs were recorded in patients with migraine with aura, thereof 10 HD-EEGs during aura. Eight HD-EEGs were recorded in the same subject. During aura, no slow potentials were recorded, but alpha-power was significantly decreased in parieto-occipito-temporal location on the hemisphere contralateral to visual aura, lasting into the headache phase. Interictal alpha-power in patients with migraine with aura did not differ significantly from age- and sex-matched healthy controls. CONCLUSIONS: Unequivocal signatures of spreading depolarization were not recorded with EEG on the intact scalp in migraine. The decrease in alpha-power contralateral to predominant visual symptoms is consistent with focal depression of spontaneous brain activity as a consequence of cortical spreading depolarization but is not specific thereof. SIGNIFICANCE: Cortical spreading depolarization is relevant in migraine, other paroxysmal neurological disorders and neurointensive care.

Which parameters influence cognitive, psychiatric and long-term seizure outcome in mesial temporal lobe epilepsy after selective amygdalohippocampectomy?

BACKGROUND: We aimed to analyze potentially prognostic factors which could have influence on postoperative seizure, neuropsychological and psychiatric outcome in a cohort of patients with mesial temporal lobe epilepsy (MTLE) due to hippocampal sclerosis (HS) after selective amygdalohippocampectomy (SAHE) via transsylvian approach. METHODS: Clinical variables of 171 patients with drug-resistant MTLE with HS (88 females) who underwent SAHE between 1994 and 2019 were evaluated using univariable and multivariable logistic regression models, to investigate which of the explanatory parameters can best predict the outcome. RESULTS: At the last available follow-up visit 12.3 ± 6.3 years after surgery 114 patients (67.9%) were seizure-free. Left hemispheric MTLE was associated with worse postoperative seizure outcome at first year after surgery (OR = 0.54, p = 0.01), female sex-with seizure recurrence at years 2 (OR = 0.52, p = 0.01) and 5 (OR = 0.53, p = 0.025) and higher number of preoperative antiseizure medication trials-with seizure recurrence at year 2 (OR = 0.77, p = 0.0064), whereas patients without history of traumatic brain injury had better postoperative seizure outcome at first year (OR = 2.08, p = 0.0091). All predictors lost their predictive value in long-term course. HS types had no prognostic influence on outcome. Patients operated on right side performed better in verbal memory compared to left (VLMT 1-5 p < 0.001, VLMT 7 p = 0.001). Depression occurred less frequently in seizure-free patients compared to non-seizure-free patients (BDI-II Z = - 2.341, p = 0.019). CONCLUSIONS: SAHE gives an improved chance of achieving good postoperative seizure, psychiatric and neuropsychological outcome in patients with in MTLE due to HS. Predictors of short-term outcome don't predict long-term outcome.