Sleep functional connectivity, hyperexcitability, and cognition in Alzheimer's disease.

INTRODUCTION: Sleep disturbances are common in Alzheimer's disease (AD) and may reflect pathologic changes in brain networks. To date, no studies have examined changes in sleep functional connectivity (FC) in AD or their relationship with network hyperexcitability and cognition. METHODS: We assessed electroencephalogram (EEG) sleep FC in 33 healthy controls, 36 individuals with AD without epilepsy, and 14 individuals with AD and epilepsy. RESULTS: AD participants showed increased gamma connectivity in stage 2 sleep (N2), which was associated with longitudinal cognitive decline. Network hyperexcitability in AD was associated with a distinct sleep connectivity signature, characterized by decreased N2 delta connectivity and reversal of several connectivity changes associated with AD. Machine learning algorithms using sleep connectivity features accurately distinguished diagnostic groups and identified "fast cognitive decliners" among study participants who had AD. DISCUSSION: Our findings reveal changes in sleep functional networks associated with cognitive decline in AD and may have implications for disease monitoring and therapeutic development. HIGHLIGHTS: Brain functional connectivity (FC) in Alzheimer's disease is altered during sleep. Sleep FC measures correlate with cognitive decline in AD. Network hyperexcitability in AD has a distinct sleep connectivity signature.

Associations of Posttraumatic Stress Disorder Symptom Clusters and Pain Interference in Post-9/11 Veterans: Exploring Sleep Impairment and Physical Activity as Underlying Mechanisms.

BACKGROUND: Posttraumatic stress disorder (PTSD) symptoms and pain are highly prevalent and comorbid, particularly in veterans, but mechanisms explaining their linkage remain unclear. The aims of this study were to determine: (1) whether sleep impairment and physical activity (PA) mediate relations between PTSD symptoms and pain interference (assessed both longitudinally and as residual change) and (2) the unique roles of each PTSD symptom cluster in those relationships. METHODS: The present study is a secondary analysis of a longitudinal observational investigation of 673 post-9/11 veterans (45.8% women). Surveys were administered at baseline and 3-month and 6-month follow-ups. RESULTS: PTSD symptoms were significantly associated with pain interference longitudinally and worsening pain interference over time. Sleep impairment, but not PA, significantly mediated the relationship between PTSD symptoms and subsequent pain interference. Hyperarousal symptoms were found to be the primary driver of the relationship between PTSD symptoms and pain interference and re-experiencing symptoms were associated with change in pain interference via sleep impairment. Men and women did not differ on any of the study variables with the exception of PA. CONCLUSION: Findings underscore the importance of targeting sleep as a key modifiable health factor linking PTSD symptoms to pain interference in post-9/11 veterans.

Physical activity, posttraumatic stress, and gender: A longitudinal study of post-9/11 veterans.

Given the importance of physical activity (PA) for both physical and mental health, the present study characterizes post-9/11 veterans' leisure-time PA engagement over time. Further, this study examines the relationship between PA and posttraumatic stress symptoms (PTSS), as well as whether this relation differs by gender and time since military discharge. This study was a secondary analysis of a 12-month longitudinal observational investigation of 410 (39.5% female) post-9/11 veterans. Participants completed self-report questionnaires at baseline and 12 months. Over a third of post-9/11 veterans were not engaging in any weekly leisure-time PA at study baseline and PA engagement significantly decreased in the subsequent year. The longitudinal relationship between PA and PTSS depended on both gender and time since military discharge. These results underscore the importance of considering both gender and time since discharge when tailoring interventions to support leisure-time PA as a key health habit in post-9/11 veterans.

Altered Sleep Microarchitecture and Cognitive Impairment in Patients With Temporal Lobe Epilepsy.

BACKGROUND AND OBJECTIVES: To investigate the spatiotemporal characteristics of sleep waveforms in temporal lobe epilepsy (TLE) and examine their association with cognition. METHODS: In this retrospective, cross-sectional study, we examined overnight EEG data from adult patients with TLE and nonepilepsy comparisons (NECs) admitted to the epilepsy monitoring unit at Mass General Brigham hospitals. Automated algorithms were used to characterize sleep macroarchitecture (sleep stages) and microarchitecture (spindles, slow oscillations [SOs]) on scalp EEG and to detect hippocampal interictal epileptiform discharges (hIEDs) from foramen ovale electrodes simultaneously recorded in a subset of patients with TLE. We examined the association of sleep features and hIEDs with memory and executive function from clinical neuropsychological evaluations. RESULTS: A total of 81 adult patients with TLE and 28 NEC adult patients were included with similar mean ages. There were no significant differences in sleep macroarchitecture between groups, including relative time spent in each sleep stage, sleep efficiency, and sleep fragmentation. By contrast, the spatiotemporal characteristics of sleep microarchitecture were altered in TLE compared with NEC and were associated with cognitive impairments. Specifically, we observed a ∼30% reduction in spindle density in patients with TLE compared with NEC, which was significantly associated with worse memory performance. Spindle-SO coupling strength was also reduced in TLE and, in contrast to spindles, was associated with diminished executive function. We found no significant association between sleep macroarchitectural and microarchitectural parameters and hIEDs. DISCUSSION: There is a fundamental alteration of sleep microarchitecture in TLE, characterized by a reduction in spindle density and spindle-SO coupling, and these changes may contribute to neurocognitive comorbidity in this disorder.

Interictal epileptiform discharges in Alzheimer's disease: prevalence, relevance, and controversies.

Alzheimer's disease (AD) is the most common type of dementia and remains an incurable, progressive disease with limited disease-modifying interventions available. In patients with AD, interictal epileptiform discharges (IEDs) have been identified in up to 54% of combined cohorts of mild cognitive impairment (MCI) or mild dementia and are a marker of a more aggressive disease course. Studies assessing the role of IEDs in AD are limited by the lack of standardization in the definition of IEDs or the different neurophysiologic techniques used to capture them. IEDs are an appealing treatment target given the availability of EEG and anti-seizure medications. There remains uncertainty regarding when to treat IEDs, the optimal drug and dose for treatment, and the impact of treatment on disease course. This review covers the state of knowledge of the field of IEDs in AD, and the steps needed to move the field forward.

Initial case series of a novel sensing deep brain stimulation device in drug-resistant epilepsy and consistent identification of alpha/beta oscillatory activity: A feasibility study.

OBJECTIVE: Here, we report a retrospective, single-center experience with a novel deep brain stimulation (DBS) device capable of chronic local field potential (LFP) recording in drug-resistant epilepsy (DRE) and explore potential electrophysiological biomarkers that may aid DBS programming and outcome tracking. METHODS: Five patients with DRE underwent thalamic DBS, targeting either the bilateral anterior (n = 3) or centromedian (n = 2) nuclei. Postoperative electrode lead localizations were visualized in Lead-DBS software. Local field potentials recorded over 12-18 months were tracked, and changes in power were associated with patient events, medication changes, and stimulation. We utilized a combination of lead localization, in-clinic broadband LFP recordings, real-time LFP response to stimulation, and chronic recordings to guide DBS programming. RESULTS: Four patients (80%) experienced a >50% reduction in seizure frequency, whereas one patient had no significant reduction. Peaks in the alpha and/or beta frequency range were observed in the thalamic LFPs of each patient. Stimulation suppressed these LFP peaks in a dose-dependent manner. Chronic timeline data identified changes in LFP amplitude associated with stimulation, seizure occurrences, and medication changes. We also noticed a circadian pattern of LFP amplitudes in all patients. Button-presses during seizure events via a mobile application served as a digital seizure diary and were associated with elevations in LFP power. SIGNIFICANCE: We describe an initial cohort of patients with DRE utilizing a novel sensing DBS device to characterize potential LFP biomarkers of epilepsy that may be associated with seizure control after DBS in DRE. We also present a new workflow utilizing the Percept device that may optimize DBS programming using real-time and chronic LFP recording.

Epilepsy and sleep characteristics are associated with diminished 24-h memory retention in older adults with epilepsy.

OBJECTIVE: Individuals with epilepsy often have memory difficulties, and older adults with epilepsy are especially vulnerable, due to the additive effect of aging. The goal of this study was to assess factors that are associated with 24-h memory retention in older adults with epilepsy. METHODS: Fifty-five adults with epilepsy, all aged >50 years, performed a declarative memory task involving the recall of the positions of 15 card pairs on a computer screen prior to a 24-h ambulatory electroencephalogram (EEG). We assessed the percentage of encoded card pairs that were correctly recalled after 24 h (24-h retention rate). EEGs were evaluated for the presence and frequency of scalp interictal epileptiform activity (IEA) and scored for total sleep. Global slow wave activity (SWA) power during non-rapid eye movement sleep was also calculated. RESULTS: Forty-four participants successfully completed the memory task. Two were subsequently excluded due to seizures on EEG. The final cohort (n = 42) had a mean age of 64.3 ± 7.5 years, was 52% female, and had an average 24-h retention rate of 70.9% ± 30.2%. Predictors of 24-h retention based on multivariate regression analysis when controlling for age, sex, and education included number of antiseizure medications (ß = -.20, p = .013), IEA frequency (ß = -.08, p = .0094), and SWA power (ß = +.002, p = .02). SIGNIFICANCE: In older adults with epilepsy, greater frequency of IEA, reduced SWA power, and higher burden of antiseizure medications correlated with worse 24-h memory retention. These factors represent potential treatment targets to improve memory in older adults with epilepsy.

Thyroid Cancer Knowledge and Awareness Among Women in Makkah Region, Saudi Arabia.

INTRODUCTION: Thyroid cancer (TC) is the most prevalent endocrine cancer, and it has shown a rapid rise in incidence across the globe in recent decades. This study aimed to evaluate the level of knowledge about TC among women in the Makkah Region, Saudi Arabia. METHODS: A cross-sectional study was conducted between 28 December 2022 and 20 January 2023 among women in the Makkah Region via a self-administrated online questionnaire using Google Forms. Our inclusion criteria were women aged 18 years and older from the Makkah Region, and we excluded healthcare professionals and women who declined to participate in the study. The collected data were analyzed using the SPSS program. RESULTS: The sample included 1219 participants. The majority (64%, n = 784) were 18 to 35. Of the participants, 362 (29.7%) had poor knowledge of TC, and only 94 (7.7%) possessed good knowledge. Forty-four percent of the participants (n = 541) believed that TC was incurable, and 86% (n = 1050) did not watch or participate in TC campaigns. Age, marital status, and family members or friends working in the medical field all significantly impacted the participants' knowledge scores. CONCLUSION: According to our study, women in the Makkah Region in Saudi Arabia do not fully comprehend the risk factors and symptoms of TC or the diagnostic methods and treatment for it. The results emphasize the value of health campaigns focused on women-in public places and on social media platforms to increase awareness of TC.

Outcomes for treatment of depression in the Veterans Health Administration: Rates of response and remission calculated from clinical and survey data.

Healthcare Effectiveness Data and Information Set (HEDIS) quality measures for depression treatment aggregate Patient Health Questionnaire (PHQ)-9 data from routine clinical assessments recorded in electronic health records (EHR). To determine whether aggregated PHQ-9 data in US Veterans Health Administration (VHA) EHRs should be used to characterize the organization's performance, we compared rates for depression response and remission calculated from EHRs with rates calculated with data representing the underlying Veteran patient population estimated using Veterans Outcome Assessment (VOA) survey data. We analyzed data from initial assessments and 3-month follow-up for Veterans beginning treatment for depression. EHR data were available for only a minority of Veteran patients, and the group of Veterans with EHR data differed from the underlying Veteran patient population with respect to demographic and clinical characteristics. Aggregated rates of response and remission from EHR data were significantly different from estimates based on representative VOA data. The findings suggest that until patient-reported outcome from EHRs are available for a substantial majority of patients receiving care, aggregated measures of patient outcomes derived from these data cannot be assumed to be representative of the outcomes for the overall population, and they should not be used as outcome-based measures of quality or performance.

Mesenteric Cyst: A Case Report.

Mesenteric cysts are rare benign abdominal lesions that possess the risk of malignant transformation in 3% of reported cases. Most cysts are asymptomatic and diagnosed incidentally or during the management of their complications. In the majority of cases, they arise from the mesentery of the small bowel, followed by the mesocolon. We present a case report of a 20-year-old female with an abdominal mesenteric cyst.

Development of Expert-Level Classification of Seizures and Rhythmic and Periodic Patterns During EEG Interpretation.

BACKGROUND AND OBJECTIVES: Seizures (SZs) and other SZ-like patterns of brain activity can harm the brain and contribute to in-hospital death, particularly when prolonged. However, experts qualified to interpret EEG data are scarce. Prior attempts to automate this task have been limited by small or inadequately labeled samples and have not convincingly demonstrated generalizable expert-level performance. There exists a critical unmet need for an automated method to classify SZs and other SZ-like events with expert-level reliability. This study was conducted to develop and validate a computer algorithm that matches the reliability and accuracy of experts in identifying SZs and SZ-like events, known as "ictal-interictal-injury continuum" (IIIC) patterns on EEG, including SZs, lateralized and generalized periodic discharges (LPD, GPD), and lateralized and generalized rhythmic delta activity (LRDA, GRDA), and in differentiating these patterns from non-IIIC patterns. METHODS: We used 6,095 scalp EEGs from 2,711 patients with and without IIIC events to train a deep neural network, SPaRCNet, to perform IIIC event classification. Independent training and test data sets were generated from 50,697 EEG segments, independently annotated by 20 fellowship-trained neurophysiologists. We assessed whether SPaRCNet performs at or above the sensitivity, specificity, precision, and calibration of fellowship-trained neurophysiologists for identifying IIIC events. Statistical performance was assessed by the calibration index and by the percentage of experts whose operating points were below the model's receiver operating characteristic curves (ROCs) and precision recall curves (PRCs) for the 6 pattern classes. RESULTS: SPaRCNet matches or exceeds most experts in classifying IIIC events based on both calibration and discrimination metrics. For SZ, LPD, GPD, LRDA, GRDA, and "other" classes, SPaRCNet exceeds the following percentages of 20 experts-ROC: 45%, 20%, 50%, 75%, 55%, and 40%; PRC: 50%, 35%, 50%, 90%, 70%, and 45%; and calibration: 95%, 100%, 95%, 100%, 100%, and 80%, respectively. DISCUSSION: SPaRCNet is the first algorithm to match expert performance in detecting SZs and other SZ-like events in a representative sample of EEGs. With further development, SPaRCNet may thus be a valuable tool for an expedited review of EEGs. CLASSIFICATION OF EVIDENCE: This study provides Class II evidence that among patients with epilepsy or critical illness undergoing EEG monitoring, SPaRCNet can differentiate (IIIC) patterns from non-IIIC events and expert neurophysiologists.

Utility of Amyloid Positron Emission Tomography Imaging in Older Adults With Epilepsy and Cognitive Decline.

In older adults with cognitive decline and epilepsy, diagnosing the etiology of cognitive decline is challenging. We identified 6 subjects enrolled in the Imaging Dementia-Evidence of Amyloid Imaging Scanning (IDEAS) study and nonlesional epilepsy. Three cognitive neurologists reviewed each case to determine the likelihood of underlying Alzheimer's disease (AD) pathology. Their impressions were compared to amyloid PET findings. In 3 cases the impression was concordant with PET findings. In 2 cases "possibly suggestive," the PET reduced diagnostic uncertainty, with 1 having a PET without elevated amyloid and the other PET with intermediate amyloid. In the remaining case with lack of reviewer concordance, the significance of PET with elevated amyloid remains uncertain. This case series highlights that in individuals with a history of epilepsy and cognitive decline, amyloid PET can be a useful tool in evaluating the etiology of cognitive decline when used in an appropriate context.

EEG Entropy in REM Sleep as a Physiologic Biomarker in Early Clinical Stages of Alzheimer's Disease.

BACKGROUND: Alzheimer's disease (AD) is associated with EEG changes across the sleep-wake cycle. As the brain is a non-linear system, non-linear EEG features across behavioral states may provide an informative physiologic biomarker of AD. Multiscale fluctuation dispersion entropy (MFDE) provides a sensitive non-linear measure of EEG information content across a range of biologically relevant time-scales. OBJECTIVE: To evaluate MFDE in awake and sleep EEGs as a potential biomarker for AD. METHODS: We analyzed overnight scalp EEGs from 35 cognitively normal healthy controls, 23 participants with mild cognitive impairment (MCI), and 19 participants with mild dementia due to AD. We examined measures of entropy in wake and sleep states, including a slow-to-fast-activity ratio of entropy (SFAR-entropy). We compared SFAR-entropy to linear EEG measures including a slow-to-fast-activity ratio of power spectral density (SFAR-PSD) and relative alpha power, as well as to cognitive function. RESULTS: SFAR-entropy differentiated dementia from MCI and controls. This effect was greatest in REM sleep, a state associated with high cholinergic activity. Differentiation was evident in the whole brain EEG and was most prominent in temporal and occipital regions. Five minutes of REM sleep was sufficient to distinguish dementia from MCI and controls. Higher SFAR-entropy during REM sleep was associated with worse performance on the Montreal Cognitive Assessment. Classifiers based on REM sleep SFAR-entropy distinguished dementia from MCI and controls with high accuracy, and outperformed classifiers based on SFAR-PSD and relative alpha power. CONCLUSION: SFAR-entropy measured in REM sleep robustly discriminates dementia in AD from MCI and healthy controls.

Life meaning and mental health in post-9/11 veterans: the mediating role of perceived stress.

BACKGROUND AND OBJECTIVES: Post-9/11 veterans frequently experience diminished mental health following military service. Life meaning is related to better mental health in veterans, yet its mechanism of action is unknown. A meaning-making model suggests that life meaning can reduce perceived stress, thus enhancing mental health. The present study tested this meaning-making model by predicting multiple dimensions of mental health (i.e., symptoms of posttraumatic stress disorder, anxiety, insomnia, and depression, and mental health quality of life) from life meaning as mediated by perceived stress. DESIGN AND METHODS: The present study was a secondary analysis of a 12-month observational study of 367 post-9/11 veterans. Participants completed demographic and health surveys at baseline, 6-month, and 12-month follow-ups. A multivariate mediation model was created predicting changes in dimensions of mental health from 6 months to 12 months. RESULTS: Higher life meaning at baseline predicted changes in all dimensions of mental health between 6 and 12 months, an effect mediated by changes in perceived stress between baseline and 6 months. CONCLUSIONS: Across dimensions of mental health, the meaning-making model was supported. Understanding post-9/11 veteran mental health from this theoretical perspective may help better tailor healthcare efforts and enhance veteran health overall.

Interrater Reliability of Expert Electroencephalographers Identifying Seizures and Rhythmic and Periodic Patterns in EEGs.

BACKGROUND AND OBJECTIVES: The validity of brain monitoring using electroencephalography (EEG), particularly to guide care in patients with acute or critical illness, requires that experts can reliably identify seizures and other potentially harmful rhythmic and periodic brain activity, collectively referred to as "ictal-interictal-injury continuum" (IIIC). Previous interrater reliability (IRR) studies are limited by small samples and selection bias. This study was conducted to assess the reliability of experts in identifying IIIC. METHODS: This prospective analysis included 30 experts with subspecialty clinical neurophysiology training from 18 institutions. Experts independently scored varying numbers of ten-second EEG segments as "seizure (SZ)," "lateralized periodic discharges (LPDs)," "generalized periodic discharges (GPDs)," "lateralized rhythmic delta activity (LRDA)," "generalized rhythmic delta activity (GRDA)," or "other." EEGs were performed for clinical indications at Massachusetts General Hospital between 2006 and 2020. Primary outcome measures were pairwise IRR (average percent agreement [PA] between pairs of experts) and majority IRR (average PA with group consensus) for each class and beyond chance agreement (κ). Secondary outcomes were calibration of expert scoring to group consensus, and latent trait analysis to investigate contributions of bias and noise to scoring variability. RESULTS: Among 2,711 EEGs, 49% were from women, and the median (IQR) age was 55 (41) years. In total, experts scored 50,697 EEG segments; the median [range] number scored by each expert was 6,287.5 [1,002, 45,267]. Overall pairwise IRR was moderate (PA 52%, κ 42%), and majority IRR was substantial (PA 65%, κ 61%). Noise-bias analysis demonstrated that a single underlying receiver operating curve can account for most variation in experts' false-positive vs true-positive characteristics (median [range] of variance explained ([Formula: see text]): 95 [93, 98]%) and for most variation in experts' precision vs sensitivity characteristics ([Formula: see text]: 75 [59, 89]%). Thus, variation between experts is mostly attributable not to differences in expertise but rather to variation in decision thresholds. DISCUSSION: Our results provide precise estimates of expert reliability from a large and diverse sample and a parsimonious theory to explain the origin of disagreements between experts. The results also establish a standard for how well an automated IIIC classifier must perform to match experts. CLASSIFICATION OF EVIDENCE: This study provides Class II evidence that an independent expert review reliably identifies ictal-interictal injury continuum patterns on EEG compared with expert consensus.