Source-sink connectivity: A novel interictal EEG marker of the epileptic brain network

Epilepsy affects over 60 million people worldwide. Epilepsy diagnosis depends on abnormalities in scalp electroencephalography (EEG) signals but their presence varies from 29-55%, resulting in a delayed diagnosis. Additionally, artifacts mimicking abnormalities and conditions imitating epileptic seizures contribute to a misdiagnosis rate of 30%. Antiepileptic drugs (AEDs) are the mainstay of epilepsy treatment, but around 30% of patients do not respond to AEDs. Surgical treatment is a hopeful alternative but outcomes depend on precise identification of the epileptogenic zone (EZ), the brain region(s) where seizures originate, and success rates range from 20-80%. Localization of the EZ requires visual inspection of intracranial EEG (iEEG) recordings during seizures which is costly and time-consuming and, in the end, clinicians ignore most of the data captured. Diagnosis and management of epilepsy rely on detecting sporadic EEG signatures. Thus, there is a great need to more quickly and accurately identify the underlying cause and location of seizures in the brain. We developed and tested the source-sink index (SSI) as an interictal (between seizures) EEG marker of epileptogenic activity. We hypothesized that seizures are suppressed when the EZ is inhibited by neighboring regions. We developed an algorithm that identifies two groups of nodes from the EEG network: those inhibiting their neighboring nodes ("sources") and the inhibited nodes themselves ("sinks"). Specifically, dynamical network models were estimated from EEG data and their connectivity properties revealed top sources and sinks in the network. We tested and validated a twofold application of SSI, as: i) an iEEG marker of the EZ, and ii) a scalp EEG marker of epilepsy. We found that SSI highly agreed with the annotated EZ in successful outcome patients but identified untreated regions in failure patients. Further, SSI outperformed high frequency oscillations, a frequently proposed interictal EZ marker, in predicting surgical outcomes. When used to predict diagnostic outcomes, SSI showed significant improvement over the gold standard's reported sensitivity and specificity. Our results suggest that SSI captures the characteristics of regions responsible for seizure initiation. As such, it is a promising marker of epileptogenicity that could significantly improve the speed and outcomes of epilepsy management and diagnosis

Towards Automating Sleep Stage Scoring to Diagnose Sleep Disorders

Overnight polysomnography (PSG) is an important tool used to characterize sleep and the gold standard procedure for diagnosing many sleep disorders. PSG is a non-invasive procedure that collects various physiological data, such as EEG, EMG, EOG and ECG signals. The data is then scored in a subjective, laborious and time-consuming process by sleep specialists who assign a sleep stage to every 30-second window of the data according to predefined scoring rules by the American Academy of Sleep Medicine (AASM). Finally, clinicians make a diagnosis based on this annotated data. Consequently, the current process is heavily dependent upon human factors, which can result in poor agreement between expert scorers, but inter-scorer reliability has been found to be only around 82%. In this study we developed an automatic sleep stage scoring method, using a likelihood ratio decision tree classifier, with the goal of improving the speed, reliability, accuracy and cost efficiency of the current PSG scoring process. The algorithm was developed using the AASM Manual for Scoring Sleep. We extracted features from various physiological recordings of the PSG, based on the predefined rules of the AASM Manual. The features were computed for each 30-second epoch, in either the time or the frequency domain. The most useful features were selected by looking at probability distributions for each metric conditioned on the sleep stage, and identifying the features giving the greatest separation between stages. Examples of meaningful features include the power in different frequency bands of EEG signals, EMG energy per epoch, and number of spindles per epoch, to mention a few. These features were then used as inputs to the classifier which assigned each epoch one of five possible stages:; N3, N2, N1, REM or Wake. The automatic scoring was trained and tested on PSG data from 39 healthy individuals (age range: 24.2±3.1 years) with no sleep disturbances. The overall scoring accuracy was 76.97% on the test set. Some of the stages, such as stage N2, have more distinctive characteristics and thus yielded a higher per-stage scoring accuracy, whereas the other stages, for example stages N1 and REM, got confused more easily, resulting in lower per-stage accuracies. As expected, most misclassifications occurred between adjacent sleep stages. Although this accuracy may at first seem low, it is likely that the stages that the tool classified inaccurately may be sleep stages that contribute to inter-scorer reliability. Therefore, we see this tool as assisting sleep scorers to enhance efficiency with the further goal of eventually improving inter-scorer reliability. Sleep stage scoring provides an important basis for diagnosis of sleep disorders in general. However, the detection of sleep disturbances is very costly and time-consuming, and relies on subjective measures. Automating the scoring process improves the efficiency and consistency of scoring procedures and offers a way to diagnose sleeping disorders in a more robust, quantitative manner

A Patients' Perspective Towards the Injection Devices for Humira® and Imraldi® in a Nationwide Switching Program.

To access publisher's full text version of this article, please click on the hyperlink in Additional Links field or click on the hyperlink at the top of the page marked DownloadObjective: Due to a tender process in Iceland, all patients on Humira® were switched nationwide to its biosimilar Imraldi® in March 2019. The study aimed to explore the patient's perspective of the Humira® and Imraldi® injection devices. Methods: A standard telephone interview was carried out among patients with inflammatory arthritis, inflammatory bowel disease and psoriasis, who underwent this nationwide switching program a few months earlier. Results: The response rate was 84.5% (n = 198). The average age was 50.8 years, and 53.5% were female. The patients self-administered the drugs in 96% of the cases. The majority (90.5%) stated that they received individualized instruction on using the Humira® pen, compared to 18.2% who accepted instruction in the case of the Imraldi® pen. Almost half (46.6%) of the patients found it more difficult to use the Imraldi® pen than the Humira® pen, while only 12.5% found the Imraldi® pen easier to use. Firstly, these differences were due to more painful insertion of the needle (62.2%) and secondly, due to the experience, the injection process was different (63.0%). Conclusion: Patients with inflammatory disorders who have been treated regularly with adalimumab preferred the Humira® injection device over the Imraldi® device, according to our results. After all, these injection devices' structure and content are not the same, although both contain the same active ingredient, i.e. adalimumab. Our results highlight the importance of thorough information, not only with an information letter but also with the possibilities for individualized introduction in planning switching to biosimilars. Keywords: Humira; Imraldi; adalimumab; injection devices; medicine administration at home

Vitamin D status and association with gestational diabetes mellitus in a pregnant cohort in Iceland.

To access publisher's full text version of this article, please click on the hyperlink in Additional Links field or click on the hyperlink at the top of the page marked DownloadBackground: Vitamin D deficiency has been associated with an increased risk of gestational diabetes mellitus (GDM), one of the most common pregnancy complications. The vitamin D status has never previously been studied in pregnant women in Iceland. Objective: The aim of this research study was to evaluate the vitamin D status of an Icelandic cohort of pregnant women and the association between the vitamin D status and the GDM incidence. Design: Subjects included pregnant women (n = 938) who attended their first ultrasound appointment, during gestational weeks 11-14, between October 2017 and March 2018. The use of supplements containing vitamin D over the previous 3 months, height, pre-pregnancy weight, and social status were assessed using a questionnaire, and blood samples were drawn for analyzing the serum 25‑hydroxyvitamin D (25OHD) concentration. Information regarding the incidence of GDM later in pregnancy was collected from medical records. Results: The mean ± standard deviation of the serum 25OHD (S-25OHD) concentration in this cohort was 63±24 nmol/L. The proportion of women with an S-25OHD concentration of ≥ 50 nmol/L (which is considered adequate) was 70%, whereas 25% had concentrations between 30 and 49.9 nmol/L (insufficient) and 5% had concentrations < 30 nmol/L (deficient). The majority of women (n = 766, 82%) used supplements containing vitamin D on a daily basis. A gradual decrease in the proportion of women diagnosed with GDM was reported with increasing S-25OHD concentrations, going from 17.8% in the group with S-25OHD concentrations < 30 nmol/L to 12.8% in the group with S-25OHD concentrations ≥75 nmol/L; however, the association was not significant (P for trend = 0.11). Conclusion: Approximately one-third of this cohort had S-25OHD concentrations below adequate levels (< 50 nmol/L) during the first trimester of pregnancy, which may suggest that necessary action must be taken to increase their vitamin D levels. No clear association was observed between the vitamin D status and GDM in this study. Keywords: cod liver oil; gestational diabetes mellitus; nutritional status; pregnancy; supplements; vitamin D.University of Iceland Research Fund Science Fund of Landspitali National University Hospita

Physical and cognitive impact following SARS-CoV-2 infection in a large population-based case-control study

© 2023. The Author(s).BACKGROUND: Persistent symptoms are common after SARS-CoV-2 infection but correlation with objective measures is unclear. METHODS: We invited all 3098 adults who tested SARS-CoV-2 positive in Iceland before October 2020 to the deCODE Health Study. We compared multiple symptoms and physical measures between 1706 Icelanders with confirmed prior infection (cases) who participated, and 619 contemporary and 13,779 historical controls. Cases participated in the study 5-18 months after infection. RESULTS: Here we report that 41 of 88 symptoms are associated with prior infection, most significantly disturbed smell and taste, memory disturbance, and dyspnea. Measured objectively, cases had poorer smell and taste results, less grip strength, and poorer memory recall. Differences in grip strength and memory recall were small. No other objective measure associated with prior infection including heart rate, blood pressure, postural orthostatic tachycardia, oxygen saturation, exercise tolerance, hearing, and traditional inflammatory, cardiac, liver, and kidney blood biomarkers. There was no evidence of more anxiety or depression among cases. We estimate the prevalence of long Covid to be 7% at a median of 8 months after infection. CONCLUSIONS: We confirm that diverse symptoms are common months after SARS-CoV-2 infection but find few differences between cases and controls in objective parameters measured. These discrepancies between symptoms and physical measures suggest a more complicated contribution to symptoms related to prior infection than is captured with conventional tests. Traditional clinical assessment is not expected to be particularly informative in relating symptoms to a past SARS-CoV-2 infection.Peer reviewe

Molecular benchmarks of a SARS-CoV-2 epidemic.

To access publisher's full text version of this article, please click on the hyperlink in Additional Links field or click on the hyperlink at the top of the page marked DownloadA pressing concern in the SARS-CoV-2 epidemic and other viral outbreaks, is the extent to which the containment measures are halting the viral spread. A straightforward way to assess this is to tally the active cases and the recovered ones throughout the epidemic. Here, we show how epidemic control can be assessed with molecular information during a well characterized epidemic in Iceland. We demonstrate how the viral concentration decreased in those newly diagnosed as the epidemic transitioned from exponential growth phase to containment phase. The viral concentration in the cases identified in population screening decreased faster than in those symptomatic and considered at high risk and that were targeted by the healthcare system. The viral concentration persists in recovering individuals as we found that half of the cases are still positive after two weeks. We demonstrate that accumulation of mutations in SARS-CoV-2 genome can be exploited to track the rate of new viral generations throughout the different phases of the epidemic, where the accumulation of mutations decreases as the transmission rate decreases in the containment phase. Overall, the molecular signatures of SARS-CoV-2 infections contain valuable epidemiological information that can be used to assess the effectiveness of containment measures

Invasive infections of Bacillus species in Iceland, 2006-2018

Publisher Copyright: © 2022 Laeknafelag Islands. All rights reserved.INNGANGUR Bakteríur af ættkvíslinni Bacillus finnast víða í umhverfinu og eru almennt taldar hafa litla meinvirkni, að miltisbrandsbakteríunni B. anthracis undanskilinni. Oft er álitið að um mengun sé að ræða ef Bacillus-tegundir finnast með ræktun. Tegundin B. cereus getur valdið ífarandi sýkingum í mönnum en hún getur framleitt vefjaskemmandi eitur. Faraldsfræði þessara sýkinga hefur lítið verið rannsökuð. EFNIVIÐUR OG AÐFERÐIR Allar mögulegar ífarandi sýkingar af völdum Bacillus á Landspítala árabilið 2006-2018 voru fundnar með leit í ræktunarniðurstöðum. Farið var yfir klínískar upplýsingar þeirra sem taldir voru með mögulegar eða staðfestar sýkingar. Mat á því hvort bakterían taldist vera mengunarvaldur, mögulegur sýkingarvaldur eða staðfestur sýkingarvaldur byggðist á skilmerkjum sem höfundar settu saman. Nýgengi mögulegra eða staðfestra ífarandi sýkinga var reiknað. NIÐURSTÖÐUR Á tímabilinu 2006-2018 ræktaðist Bacillus frá 126 einstaklingum; í blóði (116), liðvökva (8) eða heila- og mænuvökva (2). Alls voru 26 tilvik talin staðfest sýking (20,6%), 10 möguleg sýking (7,9%) og 90 mengun (71,4%). Nýgengi mögulegra eða staðfestra sýkinga var 1,4/100.000 íbúa/ár. Notkun vímuefna í æð var áhættuþáttur meðal 11/26 með staðfesta sýkingu. Algengasta birtingarmynd sýkingar var blóðsýking/sýklasótt. Bakterían var ónæm fyrir beta-laktam sýklalyfjum í 92% staðfestra sýkingartilvika en í 66% mengunartilvika (p=0,02). ÁLYKTANIR Mikilvægt er að taka jákvæðar ræktanir af Bacillus alvarlega, sérstaklega þegar um ræðir sjúklinga sem nota vímuefni í æð, hafa illkynja sjúkdóm eða eru ónæmisbældir. Mikilvægt er að taka ávallt tvö sett af blóðræktu INTRODUCTION: The bacterial genus Bacillus is widely distributed environmentally and is usually considered a low-virulence organism, except for B. anthracis. A blood culture positive for Bacillus is often looked at as contamination. Nevertheless, B. cereus can cause invasive infections in humans and produces harmful toxins. The epidemiology of these infections remains poorly studied. MATERIAL AND METHODS: All possible invasive infections caused by Bacillus during 2006-2018 at Landspitali University Hospital were identified from culture results. Clinical information was used to evaluate if there was a possible infection or confirmed infection. Here, the authors propose and use clinical criteria to categorize each case as contamination, possible infection or confirmed infection. The incidence of possible or confirmed infections was calculated using hospital catchment population data. RESULTS: Positive cultures of Bacillus sp. from sterile sites during 2006-2018 were identified from 126 patients; blood (116), synovial fluid (8) and cerebrospinal fluid (2). In total, 26 cases were confirmed infection (20.6%), 10 possible infection (7.9%) and 90 contamination (71.4%). The incidence was 1.4 cases/100.000 inhabitants/year. Injection drug use was a risk factor among 11/26 patients with confirmed infection. The most common clinical presentation was sepsis. In this study, Bacillus was resistant to beta-lactam antibiotics in 92% of confirmed infections and 66% of the cases considered contamination (p=0.02). CONCLUSION: Positive blood cultures of Bacillus sp. should be taken seriously, especially among patients with injection drug use, malignancy or immunocompromised state. It is important to draw two sets of blood cultures if there is a real suspicion of an infection to establish diagnosis and avoid unnecessary antibiotic therapy.Peer reviewe

Family members of cancer patients: Needs, quality of life and symptoms of anxiety and depression

To access publisher full text version of this article. Please click on the hyperlink in Additional Links fieldBACKGROUND: Family members of cancer patient's have multiple needs, many of which are not adequately met. Unmet needs may affect psychological distress and quality of life (QOL). The purpose of this study was to assess needs and unmet needs, QOL, symptoms of anxiety and depression, and the relationship between those variables in a large sample of family members of cancer patients in different phases of illness. MATERIAL AND METHODS: Of 332 family members invited to participate, 330 accepted and 223 (67%) completed a cross-sectional, descriptive study. Data was collected with the Family Inventory of Needs (FIN), Quality of Life Scale (QOLS) and the Hospital Anxiety and Depression Scale (HADS). RESULTS: Of 20 needs assessed the mean (SD) number of important needs and unmet needs was 16.4 ± 4.3 and 6.2 ± 5.6, respectively. Twelve important needs were unmet in 40-56% of the sample. The mean number of unmet needs was significantly higher among women than men, other relatives than spouses, younger family members, those currently working and those of patients with metastatic cancer. QOL was similar to what has been reported for healthy populations and cancer caregivers in advanced stages. The prevalence of symptoms of anxiety and depression was high (20-40%). Anxiety scores were higher among women than men and both anxiety and depression scores were highest during years 1-5 compared to the first year and more than five years post diagnosis. There was a positive relationship between number of important needs and QOL, and between needs met and QOL. Additionally, there was a significant relationship between anxiety and unmet needs. Finally, there was a significant relationship between QOL and symptoms of anxiety and depression. CONCLUSION: The results support the importance of screening needs and psychological distress among family members of cancer patients in all phases of illness

Emerging roles of network analysis for epilepsy

In recent years there has been increasing interest in applying network science tools to EEG data. At the 2018 American Epilepsy Society conference in New Orleans, LA, the yearly session of the Engineering and Neurostimulation Special Interest Group focused on emerging, translational technologies to analyze seizure networks. Each speaker demonstrated practical examples of how network tools can be utilized in clinical care and provide additional data to help care for patients with intractable epilepsy. The groups presented advances using tools from functional connectivity, control theory, and graph theory to analyze human EEG data. These tools have great potential to augment clinical interpretation of EEG signals

Source-sink connectivity: a novel interictal EEG marker for seizure localization

Over 15 million epilepsy patients worldwide have drug-resistant epilepsy. Successful surgery is a standard of care treatment but can only be achieved through complete resection or disconnection of the epileptogenic zone, the brain region(s) where seizures originate. Surgical success rates vary between 20% and 80%, because no clinically validated biological markers of the epileptogenic zone exist. Localizing the epileptogenic zone is a costly and time-consuming process, which often requires days to weeks of intracranial EEG (iEEG) monitoring. Clinicians visually inspect iEEG data to identify abnormal activity on individual channels occurring immediately before seizures or spikes that occur interictally (i.e. between seizures). In the end, the clinical standard mainly relies on a small proportion of the iEEG data captured to assist in epileptogenic zone localization (minutes of seizure data versus days of recordings), missing opportunities to leverage these largely ignored interictal data to better diagnose and treat patients.IEEG offers a unique opportunity to observe epileptic cortical network dynamics but waiting for seizures increases patient risks associated with invasive monitoring. In this study, we aimed to leverage interictal iEEG data by developing a new network-based interictal iEEG marker of the epileptogenic zone. We hypothesized that when a patient is not clinically seizing, it is because the epileptogenic zone is inhibited by other regions. We developed an algorithm that identifies two groups of nodes from the interictal iEEG network: those that are continuously inhibiting a set of neighbouring nodes ('sources') and the inhibited nodes themselves ('sinks'). Specifically, patient-specific dynamical network models were estimated from minutes of iEEG and their connectivity properties revealed top sources and sinks in the network, with each node being quantified by source-sink metrics. We validated the algorithm in a retrospective analysis of 65 patients. The source-sink metrics identified epileptogenic regions with 73% accuracy and clinicians agreed with the algorithm in 93% of seizure-free patients. The algorithm was further validated by using the metrics of the annotated epileptogenic zone to predict surgical outcomes. The source-sink metrics predicted outcomes with an accuracy of 79% compared to an accuracy of 43% for clinicians' predictions (surgical success rate of this dataset). In failed outcomes, we identified brain regions with high metrics that were untreated. When compared with high frequency oscillations, the most commonly proposed interictal iEEG feature for epileptogenic zone localization, source-sink metrics outperformed in predictive power (by a factor of 1.2), suggesting they may be an interictal iEEG fingerprint of the epileptogenic zone