scholarly journals A.06 Assessing inter-rater reliability in localizing sleep-related hypermotor seizures: a video-based survey

2019 ◽  
Vol 46 (s1) ◽  
pp. S9
Author(s):  
PM Lobbezoo ◽  
L Nobili ◽  
S Gibbs
Keyword(s):  
Focal Epilepsy ◽  
Small Difference ◽  
Training Session ◽  
Sleep Medicine ◽  
Kappa Statistics ◽  
Clinical Use ◽  
Rater Reliability ◽  
Intracerebral Eeg ◽  
Hypermotor Seizures ◽  
Eeg Recordings

Background: Sleep-related hypermotor epilepsy (SHE) is a focal epilepsy characterized by abrupt sleep-related hypermotor seizures (SRHS) with complex semiology. Although difficult to localize within the frontal lobe recent studies using intracerebral EEG recordings have suggested the existence of four distinct semiology patterns (SP) organized in a rostro-caudal manner. It remains unclear however if these SP are clinically useful. Methods: We aimed to estimate the inter-rater reliability (IR) of classifying SP in SHE amongst epilepsy and sleep medicine experts. Following a short training session, ten experts were asked to review and classify 40 videos of SRHS in patients with confirmed SHE. IR was calculated using Kappa statistics. Results: SP1 and SP4, who are at the opposite ends of the SHE semiology spectrum, had substantial IR (0.82 and 0.67, respectively). Meanwhile, SP2 and SP3 showed fair agreement (0.25 and 0.35, respectively) and represented the major source of variance, with a small difference favouring epilepsy experts. Conclusions: Amongst epilepsy and sleep medicine experts, IR of classifying SRHS into four SP was only mildly satisfactory. SP1 and SP4 were shown to be easily recognizable while SP2 and SP3 were frequently confounded. Improvements in SP recognition are needed before widespread clinical use.

Neurophysiological seizure-onset predictors of epilepsy surgery outcome: a multivariable analysis

2020 ◽  
Vol 133 (6) ◽  
pp. 1863-1872 ◽  
Author(s):  
Hideaki Tanaka ◽  
Jean Gotman ◽  
Hui Ming Khoo ◽  
André Olivier ◽  
Jeffery Hall ◽  
...  
Keyword(s):  
Surgical Outcome ◽  
Focal Epilepsy ◽  
Univariate Analysis ◽  
Multivariable Analysis ◽  
Postoperative Outcome ◽  
Seizure Onset ◽  
Resective Surgery ◽  
Scalp Eeg ◽  
Surgery Outcome ◽  
Intracerebral Eeg

OBJECTIVEThe authors sought to determine which neurophysiological seizure-onset features seen during scalp electroencephalography (EEG) and intracerebral EEG (iEEG) monitoring are predictors of postoperative outcome in a large series of patients with drug-resistant focal epilepsy who underwent resective surgery.METHODSThe authors retrospectively analyzed the records of 75 consecutive patients with focal epilepsy, who first underwent scalp EEG and then iEEG (stereo-EEG) for presurgical assessment and who went on to undergo resective surgery between 2004 and 2015. To determine the independent prognostic factors from the neurophysiological scalp EEG and iEEG seizure-onset information, univariate and standard multivariable logistic regression analyses were used. Since scalp EEG and iEEG data were recorded at different times, the authors matched scalp seizures with intracerebral seizures for each patient using strict criteria.RESULTSA total of 3057 seizures were assessed. Forty-eight percent (36/75) of patients had a favorable outcome (Engel class I–II) after a minimum follow-up of at least 1 year. According to univariate analysis, a localized scalp EEG seizure onset (p < 0.001), a multilobar intracerebral seizure-onset zone (SOZ) (p < 0.001), and an extended SOZ (p = 0.001) were significantly associated with surgical outcome. According to multivariable analysis, the following two independent factors were found: 1) the ability of scalp EEG to localize the seizure onset was a predictor of a favorable postoperative outcome (OR 6.073, 95% CI 2.011–18.339, p = 0.001), and 2) a multilobar SOZ was a predictor of an unfavorable outcome (OR 0.076, 95% CI 0.009–0.663, p = 0.020).CONCLUSIONSThe study findings show that localization at scalp seizure onset and a multilobar SOZ were strong predictors of surgical outcome. These predictors can help to select the better candidates for resective surgery.

Psychiatry Transcript Annotation: Process Study and Improvements

2021 ◽  
Vol 10 (1) ◽  
pp. 71-75
Author(s):  
Srinivasan Sridhar ◽  
Nazmul Kazi ◽  
Indika Kahanda ◽  
Bernadette McCrory
Keyword(s):  
Mental Health ◽  
Work Experience ◽  
Phase 1 ◽  
Kappa Statistics ◽  
Phase 2 ◽  
Rater Reliability ◽  
Standard Data ◽  
Annotation Process ◽  
Data Collection Process ◽  
Two Phases

Background: The demand for psychiatry is increasing each year. Limited research has been performed to improve psychiatrist work experience and reduce daily workload using computational methods. There is currently no validated tool or procedure for the mental health transcript annotation process for generating “gold-standard” data. The purpose of this paper was to determine the annotation process for mental health transcripts and how it can be improved to acquire more reliable results considering human factors elements. Method: Three expert clinicians were recruited in this study to evaluate the transcripts. The clinicians were asked to fully annotate two transcripts. An additional five subjects were recruited randomly (aged between 20-40) for this pilot study, which was divided into two phases, phase 1 (annotation without training) and phase 2 (annotation with training) of five transcripts. Kappa statistics were used to measure the inter-rater reliability and accuracy between subjects. Results: The inter-rater reliability between expert clinicians for two transcripts were 0.26 (CI 0.19 to 0.33) and 0.49 (CI 0.42 to 0.57), respectively. In the pilot testing phases, the mean inter-rater reliability between subjects was higher in phase 2 with training transcript (k= 0.35 (CI 0.052 to 0.625)) than in phase 1 without training transcript (k= 0.29 (CI 0.128 to 0.451)). After training, the accuracy percentage among subjects was significantly higher in transcript A (p=0.04) than transcript B (p=0.10). Conclusion: This study focused on understanding the annotation process for mental health transcripts, which will be applied in training machine learning models. Through this exploratory study, the research found appropriate categorical labels that should be included for transcripts annotation, and the importance of training the subjects. Contributions of this case study will help the psychiatric clinicians and researchers in implementing the recommended data collection process to develop a more accurate artificial intelligence model for fully- or semi-automated transcript annotation.

Abstract WP282: Protecting Stroke Patients from Aspiration and Mortality through a Bedside Aspiration Screen

Stroke ◽  
2013 ◽  
Vol 44 (suppl_1) ◽  
Author(s):  
Edith Matesic
Keyword(s):  
Organizational Learning ◽  
Aspiration Pneumonia ◽  
The Body ◽  
Kappa Statistics ◽  
Evidence Based ◽  
Stroke Patients ◽  
Rater Reliability ◽  
Stroke Treatment ◽  
Risk Of Death ◽  
The Impact

Background: Stroke patients initially experience dysphagia approximately 42-76% of the time, putting them at high risk for developing aspiration pneumonia and increasing the risk of death threefold in the first 30 days following onset of the condition. Interventions to identify risk for aspiration pneumonia are key to reducing mortality in hospitalized patients. However, no generally recognized bedside aspiration screen exists, and few have been rigorously tested. The Edith-Huhn-Matesic Bedside Aspiration Screen (EHMBAS) TM was developed as an evidence-based RN bedside aspiration screening protocol. Purpose: This study analyzed the sensitivity and inter-rater reliability of EHMBAS TM , assessed the efficacy of training methods, evaluated patient feedback, and looked at the impact of organizational learning. Methods: RNs were trained to apply the EHMBAS TM . An evaluation study assessed the sensitivity, specificity and predictability of the screen to detect aspiration in the stroke population study group. Cohen’s Kappa statistics was applied to test inter-rater reliability. Pre- and post-implementation Likert surveys examined patient and staff satisfaction on the education plan and screening process, respectively. Lastly, an analysis of organizational learning examined whether changes enhanced adherence to screening requirements. Results: Results showed that the EHMBAS TM demonstrated strong validity (94% sensitivity) and high inter-rater reliability (Kappa = .92, p<.001). Pre- and post- staff training survey results demonstrated a significant positive change in knowledge gained, feelings of preparedness, and satisfaction with teaching methods. Further, 92.3% of patients surveyed had positive screening experiences. The hospital received Silver recognition from The American Heart Association for following stroke treatment guidelines 85% of the time for at least 12 months, demonstrating the positive impact of the protocol on organizational change. Conclusions: This study contributes to the body of work aimed at establishing a reliable evidence-based, bedside aspiration screen. Patient safety is enhanced, because screen results help determine when patients can safely receive medication and nutrition by mouth.

scholarly journals Canard solutions in neural mass models: consequences on critical regimes

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Elif Köksal Ersöz ◽  
Fabrice Wendling
Keyword(s):  
Temporal Dynamics ◽  
Spatial Scales ◽  
Singular Perturbation Theory ◽  
Geometric Singular Perturbation Theory ◽  
Critical Transitions ◽  
Intracerebral Eeg ◽  
Neural Mass ◽  
Mesoscopic Level ◽  
Eeg Recordings ◽  
Physiological Background

AbstractMathematical models at multiple temporal and spatial scales can unveil the fundamental mechanisms of critical transitions in brain activities. Neural mass models (NMMs) consider the average temporal dynamics of interconnected neuronal subpopulations without explicitly representing the underlying cellular activity. The mesoscopic level offered by the neural mass formulation has been used to model electroencephalographic (EEG) recordings and to investigate various cerebral mechanisms, such as the generation of physiological and pathological brain activities. In this work, we consider a NMM widely accepted in the context of epilepsy, which includes four interacting neuronal subpopulations with different synaptic kinetics. Due to the resulting three-time-scale structure, the model yields complex oscillations of relaxation and bursting types. By applying the principles of geometric singular perturbation theory, we unveil the existence of the canard solutions and detail how they organize the complex oscillations and excitability properties of the model. In particular, we show that boundaries between pathological epileptic discharges and physiological background activity are determined by the canard solutions. Finally we report the existence of canard-mediated small-amplitude frequency-specific oscillations in simulated local field potentials for decreased inhibition conditions. Interestingly, such oscillations are actually observed in intracerebral EEG signals recorded in epileptic patients during pre-ictal periods, close to seizure onsets.

The Diagnostic Interview for Social and Communication Disorders: background, inter-rater reliability and clinical use

2002 ◽  
Vol 43 (3) ◽  
pp. 307-325 ◽  
Author(s):  
Lorna Wing ◽  
Susan R. Leekam ◽  
Sarah J. Libby ◽  
Judith Gould ◽  
Michael Larcombe
Keyword(s):  
Communication Disorders ◽  
Diagnostic Interview ◽  
Clinical Use ◽  
Rater Reliability

scholarly journals Pitfalls in EEG analysis in patients with non-convulsive status epilepticus

2020 ◽  
Author(s):  
Ying Wang ◽  
Ivan C Zibrandtsen ◽  
Richard HC Lazeron ◽  
Johannes P van Dijk ◽  
Xi Long ◽  
...  
Keyword(s):  
Status Epilepticus ◽  
Brain Activity ◽  
Automated Analysis ◽  
Kappa Statistics ◽  
Convulsive Status Epilepticus ◽  
Eeg Analysis ◽  
Gradual Onset ◽  
Movement Artifacts ◽  
Eeg Recordings ◽  
Interictal Discharges

AbstractObjectiveElectroencephalography (EEG) interpretations through visual (by human raters) and automated (by computer technology) analysis are still not reliable for the diagnosis of non-convulsive status epilepticus (NCSE). This study aimed to identify typical pitfalls in the EEG analysis and make suggestions as to how those pitfalls might be avoided.MethodsWe analyzed the EEG recordings of individuals who had clinically confirmed or suspected NCSE. Epileptiform EEG activity during seizures (ictal discharges) were visually analyzed by two independent raters. We investigated whether unreliable EEG visual interpretations quantified by low inter-rater agreement can be predicted by the characteristics of ictal discharges and individuals’ clinical data. In addition, the EEG recordings were automatically analyzed by in-house algorithms. To further explore the causes of unreliable EEG interpretations, two epileptologists analyzed EEG patterns most likely misinterpreted as ictal discharges based on the differences between the EEG interpretations through the visual and automated analysis.ResultsShort ictal discharges with a gradual onset (developing over 3 seconds in length) were liable to be misinterpreted. An extra 2 minutes of ictal discharges contributed to an increase in the kappa statistics of > 0.1. Other problems were the misinterpretation of abnormal background activity (slow wave activities, other abnormal brain activity, and the ictal-like movement artifacts), continuous interictal discharges, and continuous short ictal discharges.ConclusionA longer duration criterion for NCSE-EEGs than 10 seconds that commonly used in NCSE working criteria is needed. Using knowledge of historical EEGs, individualized algorithms, and context-dependent alarm thresholds may also avoid the pitfalls.

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