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Background Idiopathic generalized epilepsy (IGE) affects young individuals and is typically successfully managed with anti-seizure medications (ASMs). Discontinuing therapy in IGE patients is a critical decision due to the risk of seizure recurrence. This study aims to identify factors influencing seizure freedom (SF) or relapse after ASM discontinuation. Methods We retrospectively reviewed the medical records of patients seen at our clinic between 2002 and 2024. Collected data included demographics, disease history, seizure types, ASMs used, EEG findings, outcomes related to SF and ASM withdrawal. Results We identified 322 records, with a mean age of 30 ± 12.4 years and an age at onset of 16 ± 5.9 years. On average, patients tried 1.9 ASMs, 23% on polytherapy. The main seizure types were generalized tonic–clonic seizures (GTCS) in 53.1%, myoclonic seizures in 31.7%, absences in 15.2%. SF was achieved by 76.6%. Patients with GTCS as main seizure type or presenting with GTCS in the first year of disease experienced a delayed achievement of SF. ASM discontinuation was attempted in 64 patients. Predictors of relapse after discontinuation were myoclonic and generalized seizures as principal seizure type and higher seizure frequency. Early SF and lower seizure frequency were associated with successful discontinuation. EEG predictors of discontinuation failure included worsening during treatment tapering and specific abnormalities, such as spike waves, photosensitivity, and hyperpnoea sensitivity. Conclusions This study provides long-term follow-up data on IGE patients, highlighting key predictors of seizure control, including GTCS or myoclonic seizures and a rapid initial ASM response. EEG emerges as a valuable tool for the longitudinal monitoring of patients undergoing ASM discontinuation.

Background and Purpose Precise and timely diagnosis is crucial for the optimal use of emerging disease‐modifying treatments for Alzheimer disease (AD). Electroencephalography (EEG), which is noninvasive and cost‐effective, can capture neural abnormalities linked to various dementias. This study explores the use of individual alpha frequency (IAF) derived from EEG as a diagnostic and prognostic tool in cognitively impaired patients. Methods This retrospective study included 375 patients from the tertiary Memory Clinic of IRCCS San Raffaele Hospital, Milan, Italy. Participants underwent clinical and neuropsychological assessments, brain imaging, cerebrospinal fluid biomarker analysis, and resting‐state EEG. Patients were categorized by amyloid status, the AT(N) classification system, clinical diagnosis, and mild cognitive impairment (MCI) progression to AD dementia. IAF was calculated and compared among study groups. Receiver operating characteristic (ROC) analysis was used to calculate its discriminative performance. Results IAF was higher in amyloid‐negative subjects and varied significantly across AT(N) groups. ROC analysis confirmed IAF's ability to distinguish A–T–N– from the A+T+N+ and A+T–N+ groups. IAF was lower in AD and Lewy body dementia patients compared to MCI and other dementia types, with moderate discriminatory capability. Among A+ MCI patients, IAF was significantly lower in those who converted to AD within 2 years compared to stable MCI patients and predicted time to conversion (p < 0.001, R = 0.38). Conclusions IAF is a valuable tool for dementia diagnosis and prognosis, correlating with amyloid status and neurodegeneration. It effectively predicts MCI progression to AD, supporting its use in early, targeted interventions in the context of disease‐modifying treatments.

Background Alzheimer's disease (AD) is a neurodegenerative disorder characterized by cognitive decline and cortical dysfunction. Resting‐state EEG provides insights into AD‐related neurophysiological changes. This study investigates the associations between 32‐channel resting‐state EEG and AD plasma biomarkers in patients from a Memory Clinic population. Method This cross‐sectional study consecutively included 193 patients with cognitive disturbances due to heterogeneous conditions from the tertiary Memory Clinic at San Raffaele Hospital, Milan, Italy. Resting‐state 32‐channel EEG and Lumipulse plasma biomarkers (pTau217, pTau181, NfL, Ab42/40 ratio) were collected. Patients were stratified into three groups based on dual pTau217 cutoffs, calculated on a sample of 184 individuals to achieve 97% sensitivity and specificity for identifying pathological CSF pTau181/Aβ42 ratios. Linear regression models, adjusted for age, sex, and disease duration, assessed associations between plasma biomarkers and EEG parameters, including alpha amplitude, alpha frequency, and relative power in delta, theta, alpha, beta, and gamma bands. ANCOVA compared EEG parameters across the three pTau217‐defined groups. Result In the full sample, pTau217, pTau181, and the pTau217/Ab42 ratio were positively associated with theta power (+0.34 to +0.45) and delta power (+0.24), and negatively with alpha amplitude, alpha power (‐0.20 to ‐0.32), and beta power (‐0.20). In group 1 (low pTau217), the pTau217/Abeta42 ratio was negatively associated with beta, gamma, and alpha power (‐0.27 to ‐0.32). In group 2 (intermediate pTau217), NfL was positively associated with theta power (+0.47) and negatively with beta power (‐0.35). In group 3 (high pTau217), pTau217, pTau181, and the pTau217/Abeta42 ratio were positively associated with theta (+0.39) and delta power (+0.30), and negatively with alpha amplitude and alpha power. ANCOVA showed reduced alpha amplitude and alpha power together with higher theta in groups 2 and 3 versus group 1. Conclusion This study demonstrates that resting‐state EEG parameters, particularly theta and alpha power, are closely linked to AD plasma biomarkers. Stratification based on pTau217 revealed distinct EEG patterns across biomarker‐defined groups, emphasizing EEG's utility as a non‐invasive tool for capturing disease‐specific neurophysiological alterations. These findings underline the potential of EEG as an accessible, non‐invasive, and scalable method to support the diagnosis and monitoring of AD. Funding: Fujirebio Italia

Alzheimer's disease (AD) is a neurodegenerative disorder characterized by cognitive decline and cortical dysfunction. Resting-state EEG provides insights into AD-related neurophysiological changes. This study investigates the associations between 32-channel resting-state EEG and AD plasma biomarkers in patients from a Memory Clinic population. This cross-sectional study consecutively included 193 patients with cognitive disturbances due to heterogeneous conditions from the tertiary Memory Clinic at San Raffaele Hospital, Milan, Italy. Resting-state 32-channel EEG and Lumipulse plasma biomarkers (pTau217, pTau181, NfL, Ab42/40 ratio) were collected. Patients were stratified into three groups based on dual pTau217 cutoffs, calculated on a sample of 184 individuals to achieve 97% sensitivity and specificity for identifying pathological CSF pTau181/Aβ42 ratios. Linear regression models, adjusted for age, sex, and disease duration, assessed associations between plasma biomarkers and EEG parameters, including alpha amplitude, alpha frequency, and relative power in delta, theta, alpha, beta, and gamma bands. ANCOVA compared EEG parameters across the three pTau217-defined groups. In the full sample, pTau217, pTau181, and the pTau217/Ab42 ratio were positively associated with theta power (+0.34 to +0.45) and delta power (+0.24), and negatively with alpha amplitude, alpha power (-0.20 to -0.32), and beta power (-0.20). In group 1 (low pTau217), the pTau217/Abeta42 ratio was negatively associated with beta, gamma, and alpha power (-0.27 to -0.32). In group 2 (intermediate pTau217), NfL was positively associated with theta power (+0.47) and negatively with beta power (-0.35). In group 3 (high pTau217), pTau217, pTau181, and the pTau217/Abeta42 ratio were positively associated with theta (+0.39) and delta power (+0.30), and negatively with alpha amplitude and alpha power. ANCOVA showed reduced alpha amplitude and alpha power together with higher theta in groups 2 and 3 versus group 1. This study demonstrates that resting-state EEG parameters, particularly theta and alpha power, are closely linked to AD plasma biomarkers. Stratification based on pTau217 revealed distinct EEG patterns across biomarker-defined groups, emphasizing EEG's utility as a non-invasive tool for capturing disease-specific neurophysiological alterations. These findings underline the potential of EEG as an accessible, non-invasive, and scalable method to support the diagnosis and monitoring of AD. Fujirebio Italia.

Background Previous EEG studies highlighted the potential of analyzing neural oscillatory activity for differentially diagnosing Alzheimer’s disease (AD) and frontotemporal dementia (FTD). We recently studied primary progressive aphasia (PPA) variants associated with AD and FTD, revealing distinctive patterns of alterations in linear lagged connectivity (LLC) values within the default mode network (DMN) and the salience network (SN). This study utilizes the same functional MRI‐driven model for source reconstruction to investigate LLC values across typical amnestic AD and the behavioral variant of FTD (bvFTD). Method In this cross‐sectional, single‐center study, we consecutively recruited AD, bvFTD, and healthy subjects from the Neurology Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy. Resting‐state 19‐channel EEG data were acquired, and LLC values estimated across 6239 voxels at the whole‐brain level using standardized low‐resolution brain electromagnetic tomography (sLORETA). Subsequently, LLC values were averaged within SN and DMN maps derived from functional MRI data of healthy controls using seed‐based analysis. Network‐based statistics (5000 permutations‐based adjustment) were employed to compare LLC values among study groups. Result 39 bvFTD patients, 39 AD subjects, and 21 healthy controls were enrolled. AD patients exhibited elevated connectivity at delta frequency band in both DMN and SN (p<0.01), and decreased values at alpha2 band in both DMN (p = 0.04) and SN (p = 0.03) compared to controls. Furthermore, AD patients displayed higher LLC values at theta band than both bvFTD and healthy subjects within both DMN and SN (p = 0.01). BvFTD patients exhibited a significant increase in EEG connectivity at delta band compared to healthy individuals, specifically within SN (p = 0.05). No other significant differences were observed. Conclusion LLC findings in AD patients align with our previous studies, indicating a comprehensive disruption of neural oscillatory activity, with theta frequency band emerging as a potential biomarker of AD. Consistent with our study in PPA patients, FTD patients exhibited a connectivity alterations at delta band limited to anterior cerebral regions. EEG holds promise in the differential diagnosis between AD and bvFTD, suggesting a link with underlying pathology. Funding: Foundation Research on Alzheimer Disease. Next Generation EU/National Recovery and Resilience Plan, Investment PE8‐Project Age‐It.

BACKGROUND:People with myopia (near sightedness) are at increased risk for retinal detachment. We explored other factors that may be associated with retinal detachment within this high-risk group. METHODS:We conducted a case-control study comprising 61 cases with retinal detachment and myopia and 99 hospital controls who also had myopia. Cases were recruited from a general hospital, and controls from ophthalmologic clinics. Participants compiled a questionnaire including details of past and current occupational lifting tasks to explore Valsalva maneuver as a possible risk factor. We devised a cumulative lifting index to distinguish light and heavy lifting. RESULTS:After adjusting for potential confounders, we found strong associations of retinal detachment with eye surgery, eye or head trauma, severe myopia (all known risk factors), and heavy lifting (vs. no lifting, odds ratio = 4.4 [95% confidence interval = 1.5–13]) and high body mass index (≥25.5 kg/m, 6.8 [1.6–29]). CONCLUSIONS:Heavy occupational lifting and being overweight may be important risk factors for retinal detachment among people with myopia. The role of these risk factors in the etiology of retinal detachment deserves to be explored in more general populations.