Plain Language Summary of the KarMMa-3 study of ide-cel or standard of care regimens in people with relapsed or refractory multiple myeloma.

WHAT IS THIS SUMMARY ABOUT?: This plain language summary describes the results of a Phase 3 study called KarMMa-3. In this ongoing study, researchers looked at a relatively new treatment for people with multiple myeloma, a type of blood cancer, whose cancer got worse despite treatment (refractory) or had cancer that at first improved with treatment, but eventually stopped responding (relapsed). HOW WAS THIS STUDY CONDUCTED?: In the KarMMa-3 study, people with relapsed or refractory multiple myeloma received either a one-time infusion of a new treatment, named ide-cel, or one of the standard of care regimens currently available for patients with this cancer. People were treated with the standard of care regimens in weekly or monthly cycles until the cancer got worse, there were unacceptable side effects, or the person withdrew from the study. WHAT WERE THE RESULTS?: The results of this study showed that people receiving the one-time infusion of ide-cel lived longer without the cancer getting worse and had a greater reduction in cancer cells than patients receiving the standard of care regimen. A higher percentage of patients receiving ide-cel responded to treatment than patients receiving the standard of care regimen, and the response to treatment was better with idecel. These results show that ide-cel is a promising treatment for this challenging disease. Clinical Trial Registration: NCT03651128 (KarMMa-3 study).

Potential smoke-free dividend across local areas in England: a cross-sectional analysis.

BACKGROUND: The value that might be added to local economies each year through the money that people who smoke tobacco would save if everyone quit smoking is called the 'smoke-free dividend'. This study aimed to estimate the value of the smoke-free dividend across local areas in England, and how it relates to the average income in those areas. METHODS: The study was a cross-sectional descriptive analysis of tobacco expenditure from the Smoking Toolkit Study (STS) matched to income and smoking prevalence data for English local authorities. The STS sample was from 2014 to 2020 and comprised 18 721 adults who smoke cigarettes. Self-reported expenditure estimates from the STS were adjusted for under-reporting. This adjustment aimed to align the total expenditure estimate with figures derived from government tax receipts and national estimates of illicit tobacco use. The smoke-free dividend is calculated as 93% of spending on legal tobacco, which is the percentage estimated to leave the local economy, plus 100% of spending on illicit tobacco. RESULTS: The total dividend in England is estimated to be £10.9 billion each year, which equates to £1776 per person who smokes or £246 per adult regardless of smoking status. The estimated dividend is greater in areas with lower average income, with a correlation coefficient of -0.521 (95% CI -0.629, -0.392) between the average income of local areas and the dividend per adult. CONCLUSIONS: This study has estimated that local economies could gain a substantial dividend if everybody stopped smoking, which is larger in lower income areas, meaning that geographical economic inequalities could be reduced.

Over- and underreporting of seizures: How big is the problem?

OBJECTIVE: Clinical decisions on managing epilepsy patients rely on patient accuracy regarding seizure reporting. Studies have noted disparities between patient-reported seizures and electroencephalographic (EEG) findings during video-EEG monitoring periods, chiefly highlighting underreporting of seizures, a well-recognized phenomenon. However, seizure overreporting is a significant problem discussed within the literature, although not in such a large cohort. Our aim is to quantify the over- and underreporting of seizures in a large cohort of ambulatory EEG patients. METHODS: We performed a retrospective data analysis on 3407 patients referred to a diagnostic service for ambulatory video-EEG between 2020 and 2022. Both patient-reported events and events discovered on review of the video-EEG were analyzed and classified as epileptic, psychogenic (typically clinical motor events, without accompanying EEG change), or noncorrelated events (NCEs; without perceivable clinical or EEG change). Events were analyzed by state of arousal and indication for referral. Subgroup analysis was performed in patients with focal and generalized epilepsies. RESULTS: A total of 21 024 events were recorded by 3407 patients. Fifty-eight percent of reported events were NCEs, whereas 27% of all events were epileptic. Sixty-four percent of epileptic seizures were not reported by the patient but discovered by the clinical service on review of the recording. NCEs were in the highest proportion in the awake and drowsy arousal states and were the most common event type for the majority of referral indications. Subgroup analysis found a significantly higher proportion of NCEs in the patients with focal epilepsy (23%) compared to generalized epilepsy (10%; p < .001, chi-squared proportion test). SIGNIFICANCE: Our results reaffirm the phenomenon of underreporting and highlight the prevalence of overreporting. Overreporting likely represents irrelevant symptoms or electrographic discharges not represented on scalp electrodes, identification of which has important clinical relevance. Future studies should analyze events by risk factors to elucidate relationships clinicians can use and investigate the etiology of NCEs.

Diagnostic utility of prolonged ambulatory video-electroencephalography monitoring.

OBJECTIVES: Ambulatory video-electroencephalography (video-EEG) represents a low-cost, convenient and accessible alternative to inpatient video-EEG monitoring, however few studies have examined their diagnostic yield. In this large-scale retrospective study conducted in Australia, we evaluated the efficacy of prolonged ambulatory video-EEG recordings in capturing diagnostic events and resolving the referring question. METHODS: Sequential adult and paediatric ambulatory video-EEG reports from April 2020 to June 2021 were reviewed retrospectively. Data collection included patient demographics, clinical information, and details of events and EEG abnormalities. Clinical utility was assessed by examining i) time to first diagnostic event, and ii) ability to resolve the referring questions - seizure localisation, quantification, classification, and differentiation (differentiating seizures from non-epileptic events). RESULTS: Of the 600 reports analysed, 49 % captured at least one event, and 45 % captured interictal abnormalities (epileptiform or non-epileptiform). Seizures, probable psychogenic events (mostly non-convulsive), and other non-epileptic events occurred in 13 %, 23 % and 21 % of recordings respectively, with overlap. Unreported events were captured in 53 (9 %) recordings, and unreported seizures represented more than half of all seizures captured (51 %, 392/773). Nine percent of events were missing clinical, video or electrographic data. A diagnostic event occurred in 244 (41 %) recordings, of which 14 % were captured between the fifth and eighth day of recording. Reported event frequency ≥ 1/week was the only significant predictor of diagnostic event capture. In recordings with both seizures and psychogenic events, unrecognized seizures were frequent, and seizures may be missed if recording is terminated early. The referring question was resolved in 85 % of reports with at least one event, and 53 % of all reports. Specifically, this represented 46 % of reports (235/512) for differentiation of events, and 75 % of reports (27/36) for classification of seizures. CONCLUSION: Ambulatory video-EEG recordings are of high diagnostic value in capturing clinically relevant events and resolving the referring clinical questions.

Health-related quality of life in patients with triple-class exposed relapsed and refractory multiple myeloma treated with idecabtagene vicleucel or standard regimens: patient-reported outcomes from the phase 3, randomised, open-label KarMMa-3 clinical trial.

BACKGROUND: Chimeric antigen receptor T-cell therapy idecabtagene vicleucel (ide-cel) showed significantly improved progression-free survival compared with standard regimens in adults with relapsed and refractory multiple myeloma who had received two to four previous regimens in the ongoing phase 3 KarMMa-3 trial (NCT03651128). This study analysed patient-reported outcomes (PROs), a KarMMa-3 secondary endpoint. METHODS: In the randomised, open-label, phase 3 KarMMa-3 trial, 386 patients in hospitals (≥18 years of age, with measurable disease and an Eastern Cooperative Oncology Group performance status score of 0 or 1, who had received two to four previous regimens-including an immunomodulatory agent, a proteasome inhibitor, and daratumumab-and had documented disease progression after receiving their last dose of the last therapy) were randomly assigned to ide-cel (n=254) or standard regimens (daratumumab, pomalidomide, and dexamethasone; daratumumab, bortezomib, and dexamethasone; ixazomib, lenalidomide, and dexamethasone; carfilzomib and dexamethasone; or elotuzumab, pomalidomide, and dexamethasone; n=132). Patients were expected to complete the European Organisation for Research and Treatment of Cancer (EORTC) Quality of Life C30 Questionnaire (QLQ-C30), Multiple Myeloma Module (QLQ-MY20), EQ 5 dimensions (EQ-5D), and EQ-5D visual analogue scale (VAS) at baseline and follow-up timepoints (data cutoff April 18, 2022). PROs included nine prespecified primary domains: EORTC QLQ-C30 GHS-quality of life (QoL), physical functioning, cognitive functioning, fatigue, and pain; QLQ-MY20 disease symptoms and side effects of treatment; and five-level EQ-5D (EQ-5D-5L) index score and EQ-5D visual VAS. Differences in overall least-squares mean changes from baseline to month 20 were analysed using post-hoc constrained longitudinal data analysis. Time to confirmed improvement or deterioration from baseline was analysed using Cox proportional hazard models. FINDINGS: Patients were randomly assigned between May 6, 2019, and April 8, 2022. Overall, the median age was 63 years (IQR 55-68); 151 (39%) patients were female; and 250 (65%) patients were White, 36 (9%) Black or African American, 19 (5%) Hispanic or Latino, 12 (3%) Asian, and seven (2%) of other race. The median follow-up was 18·6 months (IQR 14·0-26·4). PRO compliance was higher than 75% throughout. Overall least-squares mean changes from baseline favoured ide-cel with Hedges' g effect sizes from 0·3 to 0·7 for most domains. Patients in the ide-cel group showed statistically significant and clinically meaningful improvements across the primary PRO domains of interest, with the exception of QLQ-MY20 disease symptoms, side effects of treatment, and EQ-5D-5L index score, which showed improvement across assessment visits but did not exceed the within-group minimally important difference thresholds. The ide-cel group had shorter times to clinically meaningful improvement than the standard regimens group in QLQ-C30 domains except in role functioning, diarrhoea, and financial difficulties; in QLQ-MY20 domains except body image; and in EQ-5D-VAS. INTERPRETATION: Ide-cel offers improved health-related quality of life compared with standard regimens for patients with relapsed and refractory multiple myeloma after previous lines of therapy. The PRO data highlight the extended QoL benefits of a one-time infusion with ide-cel compared with continuous treatment with standard regimens in the treatment of triple-class exposed patients with relapsed and refractory multiple myeloma. FUNDING: 2seventy bio and Celgene, a Bristol Myers Squibb Company.

Early discontinuation of ambulatory vEEG among individuals with intellectual disabilities: A retrospective chart review.

OBJECTIVE: This retrospective chart review aims to quantify the rate of patients with intellectual disability (ID) accessing an Australian ambulatory EEG service, and understand the clinical implications of discontinuing studies prematurely. METHODS: Electronic records of referrals, patient monitoring notes, and EEG reports were accessed retrospectively. Each referral was assessed to determine whether the patient had an ID. For each study where patients were discharged prematurely, the outcomes of their EEG report were assessed and compared between the ID and non-ID groups. Exploratory analysis was performed assessing the effects of age, the percentage of the requested monitoring undertaken, and outcome rates as a function of monitoring duration. RESULTS: There were significantly more patients in the ID group with early disconnection than the non-ID group (Chi squared test, p = 0.000). There was no significant difference in the rates of clinical outcomes between the ID and non-ID groups amongst patients who disconnected early. CONCLUSIONS: Although rates of early disconnection are higher in those with ID, study outcomes are largely similar between patients with and without ID in this retrospective analysis of an ambulatory EEG service. SIGNIFICANCE: Ambulatory EEG is a viable modality of EEG monitoring for patients with ID.

Clinical outcomes of deep brain stimulation for obsessive-compulsive disorder: Insight as a predictor of symptom changes.

AIM: Deep brain stimulation (DBS) is a safe and effective treatment option for people with refractory obsessive-compulsive disorder (OCD). Yet our understanding of predictors of response and prognostic factors remains rudimentary, and long-term comprehensive follow-ups are lacking. We aim to investigate the efficacy of DBS therapy for OCD patients, and predictors of clinical response. METHODS: Eight OCD participants underwent DBS stimulation of the nucleus accumbens (NAc) in an open-label longitudinal trial, duration of follow-up varied between 9 months and 7 years. Post-operative care involved comprehensive fine tuning of stimulation parameters and adjunct multidisciplinary therapy. RESULTS: Six participants achieved clinical response (35% improvement in obsessions and compulsions on the Yale Brown Obsessive Compulsive Scale (YBOCS)) within 6-9 weeks, response was maintained at last follow up. On average, the YBOCS improved by 45% at last follow up. Mixed linear modeling elucidated directionality of symptom changes: insight into symptoms strongly predicted (P = 0.008) changes in symptom severity during DBS therapy, likely driven by initial changes in depression and anxiety. Precise localization of DBS leads demonstrated that responders most often had their leads (and active contacts) placed dorsal compared to non-responders, relative to the Nac. CONCLUSION: The clinical efficacy of DBS for OCD is demonstrated, and mediators of changes in symptoms are proposed. The symptom improvements within this cohort should be seen within the context of the adjunct psychological and biopsychosocial care that implemented a shared decision-making approach, with flexible iterative DBS programming. Further research should explore the utility of insight as a clinical correlate of response. The trial was prospectively registered with the ANZCTR (ACTRN12612001142820).

Model Parameter Estimation As Features to Predict the Duration of Epileptic Seizures From Onset.

The durations of epileptic seizures are linked to severity and risk for patients. It is unclear if the spatiotemporal evolution of a seizure has any relationship with its duration. Understanding such mechanisms may help reveal treatments for reducing the duration of a seizure. Here, we present a novel method to predict whether a seizure is going to be short or long at its onset using features that can be interpreted in the parameter space of a brain model. The parameters of a Jansen-Rit neural mass model were tracked given intracranial electroencephalography (iEEG) signals, and were processed as time series features using MINIROCKET. By analysing 2954 seizures from 10 patients, patient-specific classifiers were built to predict if a seizure would be short or long given 7 s of iEEG at seizure onset. The method achieved an area under the receiver operating characteristic curve (AUC) greater than 0.6 for five of 10 patients. The behaviour in the parameter space has shown different mechanisms are associated with short/long seizures.Clinical relevance-This shows that it is possible to classify whether a seizure will be short or long based on its early characteristics. Timely interventions and treatments can be applied if the duration of the seizures can be predicted.

Long latency reflexes of the median nerves in healthy adults.

INTRODUCTION/AIMS: Long latency reflexes (LLRs) are late responses in nerve conduction studies seen after peripheral nerve stimulation during submaximal muscle contraction. They follow a short latency reflex, also known as the H reflex, and are thought to involve transcortical pathways, providing a measure of proximal nerve and central conduction. For this reason, they have been evaluated in several central nervous system diseases, but reference values are not widely published and are mostly based on old studies with very small numbers of participants. Therefore, in this work we aim to provide comprehensive reference values for LLR testing. METHODS: LLRs were tested in a cohort of 100 healthy participants, testing the median nerve bilaterally. RESULTS: Mean latencies for short latency reflex (SLR), LLR1, LLR2, and LLR3 were 27.00, 38.50, 47.60, and 67.34 milliseconds, respectively. The allowable side-to-side difference was approximately 3 to 4 milliseconds. No significant sex-related differences were seen. Height correlated moderately with the SLR latency, but only weakly with LLR1, LLR2, and LLR3. DISCUSSION: This work provides normal LLR values for comparison with future studies in disease. The technique used may allow for improved evaluation of central nervous system or proximal peripheral nerve disorders.

Circadian distribution of epileptiform discharges in epilepsy: Candidate mechanisms of variability.

Epilepsy is a serious neurological disorder characterised by a tendency to have recurrent, spontaneous, seizures. Classically, seizures are assumed to occur at random. However, recent research has uncovered underlying rhythms both in seizures and in key signatures of epilepsy-so-called interictal epileptiform activity-with timescales that vary from hours and days through to months. Understanding the physiological mechanisms that determine these rhythmic patterns of epileptiform discharges remains an open question. Many people with epilepsy identify precipitants of their seizures, the most common of which include stress, sleep deprivation and fatigue. To quantify the impact of these physiological factors, we analysed 24-hour EEG recordings from a cohort of 107 people with idiopathic generalized epilepsy. We found two subgroups with distinct distributions of epileptiform discharges: one with highest incidence during sleep and the other during day-time. We interrogated these data using a mathematical model that describes the transitions between background and epileptiform activity in large-scale brain networks. This model was extended to include a time-dependent forcing term, where the excitability of nodes within the network could be modulated by other factors. We calibrated this forcing term using independently-collected human cortisol (the primary stress-responsive hormone characterised by circadian and ultradian patterns of secretion) data and sleep-staged EEG from healthy human participants. We found that either the dynamics of cortisol or sleep stage transition, or a combination of both, could explain most of the observed distributions of epileptiform discharges. Our findings provide conceptual evidence for the existence of underlying physiological drivers of rhythms of epileptiform discharges. These findings should motivate future research to explore these mechanisms in carefully designed experiments using animal models or people with epilepsy.

Chronic intracranial EEG recordings and interictal spike rate reveal multiscale temporal modulations in seizure states.

Many biological processes are modulated by rhythms on circadian and multidien timescales. In focal epilepsy, various seizure features, such as spread and duration, can change from one seizure to the next within the same patient. However, the specific timescales of this variability, as well as the specific seizure characteristics that change over time, are unclear. Here, in a cross-sectional observational study, we analysed within-patient seizure variability in 10 patients with chronic intracranial EEG recordings (185-767 days of recording time, 57-452 analysed seizures/patient). We characterized the seizure evolutions as sequences of a finite number of patient-specific functional seizure network states. We then compared seizure network state occurrence and duration to (1) time since implantation and (2) patient-specific circadian and multidien cycles in interictal spike rate. In most patients, the occurrence or duration of at least one seizure network state was associated with the time since implantation. Some patients had one or more seizure network states that were associated with phases of circadian and/or multidien spike rate cycles. A given seizure network state's occurrence and duration were usually not associated with the same timescale. Our results suggest that different time-varying factors modulate within-patient seizure evolutions over multiple timescales, with separate processes modulating a seizure network state's occurrence and duration. These findings imply that the development of time-adaptive treatments in epilepsy must account for several separate properties of epileptic seizures and similar principles likely apply to other neurological conditions.

Neuropsychological function in psychosis of epilepsy.

OBJECTIVE: The neuropsychological profile of patients with psychosis of epilepsy (POE) has received limited research attention. Recent neuroimaging work in POE has identified structural network pathology in the default mode network and the cognitive control network. This study examined the neuropsychological profile of POE focusing on cognitive domains subserved by these networks. METHODS: Twelve consecutive patients with a diagnosis of POE were prospectively recruited from the Comprehensive Epilepsy Programmes at The Royal Melbourne, Austin and St Vincent's Hospitals, Melbourne, Australia between January 2015 and February 2017. They were compared to 12 matched patients with epilepsy but no psychosis and 42 healthy controls on standardised neuropsychological tests of memory and executive functioning in a case-control design. RESULTS: Mean scores across all cognitive tasks showed a graded pattern of impairment, with the POE group showing the poorest performance, followed by the epilepsy without psychosis and the healthy control groups. This was associated with significant group-level differences on measures of working memory (p = < 0.01); immediate (p = < 0.01) and delayed verbal recall (p = < 0.01); visual memory (p < 0.001); and verbal fluency (p = 0.02). In particular, patients with POE performed significantly worse than the healthy control group on measures of both cognitive control (p = .005) and memory (p < .001), whereas the epilepsy without psychosis group showed only memory difficulties (delayed verbal recall) compared to healthy controls (p = .001). CONCLUSION: People with POE show reduced performance in neuropsychological functions supported by the default mode and cognitive control networks, when compared to both healthy participants and people with epilepsy without psychosis.

Deep learning for automated detection of generalized paroxysmal fast activity in Lennox-Gastaut syndrome.

OBJECTIVES: Generalized paroxysmal fast activity (GPFA) is a key electroencephalographic (EEG) feature of Lennox-Gastaut Syndrome (LGS). Automated analysis of scalp EEG has been successful in detecting more typical abnormalities. Automatic detection of GPFA has been more challenging, due to its variability from patient to patient and similarity to normal brain rhythms. In this work, a deep learning model is investigated for detection of GPFA events and estimating their overall burden from scalp EEG. METHODS: Data from 10 patients recorded during four ambulatory EEG monitoring sessions are used to generate and validate the model. All patients had confirmed LGS and were recruited into a trial for thalamic deep-brain stimulation therapy (ESTEL Trial). RESULTS: The correlation coefficient between manual and model estimates of event counts was r2 = 0.87, and for total burden was r2 = 0.91. The average GPFA detection sensitivity was 0.876, with an average false-positive rate of 3.35 per minute. There was no significant difference found between patients with early or delayed deep brain stimulation (DBS) treatment, or those with active vagal nerve stimulation (VNS). CONCLUSIONS: Overall, the deep learning model was able to accurately detect GPFA and provide accurate estimates of the overall GPFA burden and electrographic event counts, albeit with a high false-positive rate. SIGNIFICANCE: Automated GPFA detection may enable automated calculation of EEG biomarkers of burden of disease in LGS.

Inhibitory stabilized network behaviour in a balanced neural mass model of a cortical column.

Strong inhibitory recurrent connections can reduce the tendency for a neural network to become unstable. This is known as inhibitory stabilization; networks that are unstable in the absence of strong inhibitory feedback because of their unstable excitatory recurrent connections are known as Inhibition Stabilized Networks (ISNs). One of the characteristics of ISNs is their "paradoxical response", where perturbing the inhibitory neurons with additional excitatory input results in a decrease in their activity after a temporal delay instead of increasing their activity. Here, we develop a model of populations of neurons across different layers of cortex. Within each layer, there is one population of inhibitory neurons and one population of excitatory neurons. The connectivity weights across different populations in the model are derived from a synaptic physiology database provided by the Allen Institute. The model shows a gradient of excitation-inhibition balance across different layers in the cortex, where superficial layers are more inhibitory dominated compared to deeper layers. To investigate the presence of ISNs across different layers, we measured the membrane potentials of neural populations in the model after perturbing inhibitory populations. The results show that layer 2/3 in the model does not operate in the ISN regime but layers 4 and 5 do operate in the ISN regime. These results accord with neurophysiological findings that explored the presence of ISNs across different layers in the cortex. The results show that there may be a systematic macroscopic gradient of inhibitory stabilization across different layers in the cortex that depends on the level of excitation-inhibition balance, and that the strength of the paradoxical response increases as the model moves closer to bifurcation points.

Proregenerative extracellular matrix hydrogel mitigates pathological alterations of pelvic skeletal muscles after birth injury.

Pelvic floor disorders, including pelvic organ prolapse and urinary and fecal incontinence, affect millions of women globally and represent a major public health concern. Pelvic floor muscle (PFM) dysfunction has been identified as one of the leading risk factors for the development of these morbid conditions. Childbirth, specifically vaginal delivery, has been recognized as the most important potentially modifiable risk factor for PFM injury; however, the precise mechanisms of PFM dysfunction after parturition remain elusive. In this study, we demonstrated that PFMs exhibit atrophy and fibrosis in parous women with symptomatic pelvic organ prolapse. These pathological alterations were recapitulated in a preclinical rat model of simulated birth injury (SBI). The transcriptional signature of PFMs after injury demonstrated an impairment in muscle anabolism, persistent expression of genes that promote extracellular matrix (ECM) deposition, and a sustained inflammatory response. We also evaluated the administration of acellular injectable skeletal muscle ECM hydrogel for the prevention of these pathological alterations. Treatment of PFMs with the ECM hydrogel either at the time of birth injury or 4 weeks after injury mitigated PFM atrophy and fibrosis. By evaluating gene expression, we demonstrated that these changes are mainly driven by the hydrogel-induced enhancement of endogenous myogenesis, ECM remodeling, and modulation of the immune response. This work furthers our understanding of PFM birth injury and demonstrates proof of concept for future investigations of proregenerative biomaterial approaches for the treatment of injured pelvic soft tissues.

The prevalence and clustering of alcohol consumption, gambling, smoking, and excess weight in an English adult population.

BACKGROUND: The aim of this study was to examine the prevalence and clustering of four health risks (increasing-/higher-risk drinking, current smoking, overweight/obesity, and at-risk gambling), and to examine variation across sociodemographic groups in the English adult population. METHODS: We analysed data from the 2012, 2015, 2016, and 2018 Health Survey for England (n = 20,698). Prevalence odds ratios (POR) were calculated to examine the clustering of risks. We undertook a multinomial multilevel regression model to examine sociodemographic variation in the clustering of health risks. RESULTS: Overall, 23.8% of the adult English population had two or more co-occurring health risks. The most prevalent was increasing-/higher-risk drinking and overweight/obesity (17.2%). Alcohol consumption and smoking were strongly clustered, particularly higher-risk drinking and smoking (POR = 2.68; 95% CI = 2.31, 3.11; prevalence = 1.7%). Higher-risk drinking and at-risk gambling were also clustered (POR = 2.66; 95% CI = 1.76, 4.01), albeit with a very low prevalence (0.2%). Prevalence of multiple risks was higher among men for all risk combinations except smoking and obesity. The odds of multiple risks were highest for men and women aged 35-64 years. Unemployed men and women with lower educational qualifications had a higher odds of multiple risks. The relationship between deprivation and multiple risks depended on the definition of multiple risks, with the clearest socioeconomic gradients seen for the highest risk health behaviours. CONCLUSION: An understanding of the prevalence, clustering, and risk factors for multiple health risks can help inform effective prevention and treatment approaches and may support the design and use of multiple behaviour change interventions.

Ambulatory video EEG extended to 10 days: A retrospective review of a large database of ictal events.

OBJECTIVE: This work aims to determine the ambulatory video electroencephalography monitoring (AVEM) duration and number of captured seizures required to resolve different clinical questions, using a retrospective review of ictal recordings. METHODS: Patients who underwent home-based AVEM had event data analyzed retrospectively. Studies were grouped by clinical indication: differential diagnosis, seizure type classification, or treatment assessment. The proportion of studies where the conclusion was changed after the first seizure was determined, as was the AVEM duration needed for at least 99% of studies to reach a diagnostic conclusion. RESULTS: The referring clinical question was not answered entirely by the first event in 29.6% (n = 227) of studies. Diagnostic and classification indications required a minimum of 7 days for at least 99% of studies to be answered, whilst treatment-assessment required at least 6 days. CONCLUSIONS: At least 7 days of monitoring, and potentially multiple events, are required to adequately answer these clinical questions in at least 99% of patients. The widely applied 72 h or single event recording cut-offs may be inadequate to adequately answer these three indications in a substantial proportion of patients. SIGNIFICANCE: Extended duration of monitoring and capturing multiple events should be considered when attempting to capture seizures on video-EEG.

Continuous synthesis of artificial speech sounds from human cortical surface recordings during silent speech production.

Objective. Brain-computer interfaces can restore various forms of communication in paralyzed patients who have lost their ability to articulate intelligible speech. This study aimed to demonstrate the feasibility of closed-loop synthesis of artificial speech sounds from human cortical surface recordings during silent speech production.Approach. Ten participants with intractable epilepsy were temporarily implanted with intracranial electrode arrays over cortical surfaces. A decoding model that predicted audible outputs directly from patient-specific neural feature inputs was trained during overt word reading and immediately tested with overt, mimed and imagined word reading. Predicted outputs were later assessed objectively against corresponding voice recordings and subjectively through human perceptual judgments.Main results. Artificial speech sounds were successfully synthesized during overt and mimed utterances by two participants with some coverage of the precentral gyrus. About a third of these sounds were correctly identified by naïve listeners in two-alternative forced-choice tasks. A similar outcome could not be achieved during imagined utterances by any of the participants. However, neural feature contribution analyses suggested the presence of exploitable activation patterns during imagined speech in the postcentral gyrus and the superior temporal gyrus. In future work, a more comprehensive coverage of cortical surfaces, including posterior parts of the middle frontal gyrus and the inferior frontal gyrus, could improve synthesis performance during imagined speech.Significance.As the field of speech neuroprostheses is rapidly moving toward clinical trials, this study addressed important considerations about task instructions and brain coverage when conducting research on silent speech with non-target participants.

Forecasting seizure likelihood from cycles of self-reported events and heart rate: a prospective pilot study.

BACKGROUND: Seizure risk forecasting could reduce injuries and even deaths in people with epilepsy. There is great interest in using non-invasive wearable devices to generate forecasts of seizure risk. Forecasts based on cycles of epileptic activity, seizure times or heart rate have provided promising forecasting results. This study validates a forecasting method using multimodal cycles recorded from wearable devices. METHOD: Seizure and heart rate cycles were extracted from 13 participants. The mean period of heart rate data from a smartwatch was 562 days, with a mean of 125 self-reported seizures from a smartphone app. The relationship between seizure onset time and phases of seizure and heart rate cycles was investigated. An additive regression model was used to project heart rate cycles. The results of forecasts using seizure cycles, heart rate cycles, and a combination of both were compared. Forecasting performance was evaluated in 6 of 13 participants in a prospective setting, using long-term data collected after algorithms were developed. FINDINGS: The results showed that the best forecasts achieved a mean area under the receiver-operating characteristic curve (AUC) of 0.73 for 9/13 participants showing performance above chance during retrospective validation. Subject-specific forecasts evaluated with prospective data showed a mean AUC of 0.77 with 4/6 participants showing performance above chance. INTERPRETATION: The results of this study demonstrate that cycles detected from multimodal data can be combined within a single, scalable seizure risk forecasting algorithm to provide robust performance. The presented forecasting method enabled seizure risk to be estimated for an arbitrary future period and could be generalised across a range of data types. In contrast to earlier work, the current study evaluated forecasts prospectively, in subjects blinded to their seizure risk outputs, representing a critical step towards clinical applications. FUNDING: This study was funded by an Australian Government National Health & Medical Research Council and BioMedTech Horizons grant. The study also received support from the Epilepsy Foundation of America's 'My Seizure Gauge' grant.