{"title":"Evaluation of Scoring Reliability in Polysomnography at a Single Sleep Center in Thailand.","authors":"Nannaphat Saiborisut, Apiwat Pugongchai, Chatkarin Tepwimonpetkun, Kannaphob Ladthavorlaphatt","doi":"10.1080/21646821.2025.2536408","DOIUrl":"10.1080/21646821.2025.2536408","url":null,"abstract":"<p><p>The reliability of Thai certificate qualifications for Advanced Sleep Technicians (ASTs) and Sleep Disorders Specialists (SDSs) in manual polysomnography (PSG) scoring has not been previously evaluated. This study assessed the reliability of PSG scoring performed by ASTs, an SDS, and an automated scoring system (AUTO) at Thammasat University Hospital, Thailand. A retrospective analysis of 250 PSG recordings conducted between September 2022 and February 2023 classified patients into four groups based on the apnea-hypopnea index (AHI): No OSA (AHI <5), mild OSA (AHI 5-15), moderate OSA (AHI 15-30), and severe OSA (AHI >30), comprising 11, 77, 105, and 57 cases, respectively. Scoring reliability was compared among ASTs, SDSs, and AUTO. A single-blinded SDS independently scored the PSG data without knowing the AST's scoring to ensure an unbiased assessment. Across more than 630,000 epochs, the Kappa (κ) statistic demonstrated stronger agreement between AST and SDS (κ = 0.980, 95% CI 0.976-0.984) than between AST and AUTO (κ = 0.599, 95% CI 0.543-0.655), indicating significant differences (<i>p</i> < .0001). For mixed apneas (MAs), intraclass correlation coefficients (ICCs) showed the highest consistency between AST and SDS (ICC = 0.998, 95% CI 0.997-0.998) compared to AST and AUTO (ICC = 0.869, 95% CI 0.836-0.897). Significant differences were observed between AST and SDS compared to AST and AUTO across most metrics (P < .0487). While ASTs and SDSs demonstrated excellent scoring consistency, AUTO scoring was notably less accurate, suggesting that the AUTO system requires further refinement to ensure reliable clinical use.</p>","PeriodicalId":22816,"journal":{"name":"The Neurodiagnostic Journal","volume":" ","pages":"197-217"},"PeriodicalIF":0.0,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144970038","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Erik Padilla, Barbara Fleming, Sindy Navarro, Karen Richey
{"title":"More Than EEG Electrodes: Building Safer Neurodiagnostic Care Through Psychological Safety and Lean Six Sigma Methodology.","authors":"Erik Padilla, Barbara Fleming, Sindy Navarro, Karen Richey","doi":"10.1080/21646821.2025.2531579","DOIUrl":"10.1080/21646821.2025.2531579","url":null,"abstract":"<p><p>At Ann & Robert H. Lurie Children's Hospital of Chicago, the increasing volume of video EEGs, extended diagnostic recording times, higher patient acuity, and variability in EEG connection techniques among neurodiagnostic technologists (NDTs) contributed to a rise in device-related skin injuries. In response, the Epilepsy Monitoring Unit (EMU) adopted Lean Six Sigma, a structured improvement methodology that combines the principles of Lean (waste reduction) and Six Sigma (defect reduction). This approach was implemented alongside humble inquiry and a psychologically safe environment, empowering the NDT team to identify root causes and drive meaningful change.Through root cause analysis, the neurodiagnostic team developed and implemented six key interventions: Targeted retraining in skin education and terminologyIntegrated evidence-based products (Mepitel and Mepilex)Strengthened collaboration with bedside nursesImplemented standardized work for EEG electrode application and head-wrapping techniquesStandardized skin checks and documentationEstablished a skin compliance monitoring system using the electronic medical recordAs a result, over the past three fiscal years, the rate of video EEG electrode-related injuries has decreased by 70%, while NDT compliance with skin checks and documentation has improved from 26% to 85%.This quality improvement article examines the application of the Define, Measure, Analyze, Improve, and Control (DMAIC) framework in achieving these outcomes.</p>","PeriodicalId":22816,"journal":{"name":"The Neurodiagnostic Journal","volume":" ","pages":"218-241"},"PeriodicalIF":0.0,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144699621","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Katherine G Stark, Justin M Turpin, Laura Mittelman, Daniel G Lynch, Taylor N Winby, Justin W Silverstein, Randy S D'Amico
{"title":"Brainstem Auditory Evoked Potentials to Guide Minimally Invasive Decompression in Chiari 1.5: Technical Case Report.","authors":"Katherine G Stark, Justin M Turpin, Laura Mittelman, Daniel G Lynch, Taylor N Winby, Justin W Silverstein, Randy S D'Amico","doi":"10.1080/21646821.2025.2554521","DOIUrl":"https://doi.org/10.1080/21646821.2025.2554521","url":null,"abstract":"<p><p>Chiari malformation types 1 and 1.5 can be treated with posterior fossa decompression, though surgical techniques vary considerably, with more aggressive approaches often considered for type 1.5. Given this variability, an objective intraoperative marker of adequate decompression would support more tailored surgery. While brainstem auditory evoked potentials (BAEPs) have been explored in pediatric populations, their utility in adults remains unstudied. We present a 26-year-old female with Chiari 1.5 and symptoms including migraines, visual disturbances, balance issues, and right-hand clumsiness. She underwent a BAEP-guided, minimally invasive decompression involving a C1 laminectomy, linear dural opening, and tonsillar cauterization. Intraoperative BAEP monitoring allowed for a targeted, less extensive decompression, resulting in significant clinical improvement. This case highlights the potential utility of BAEPs in adult Chiari decompression, suggesting a role for further investigation of this technique in optimizing outcomes while minimizing invasiveness.</p>","PeriodicalId":22816,"journal":{"name":"The Neurodiagnostic Journal","volume":"65 3","pages":"242-250"},"PeriodicalIF":0.0,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145087382","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"A Systematic Review and Meta-Analysis Evaluating the Clinical Impact and Accuracy of Artificial Intelligence in EEG for the Early Detection of Nonconvulsive Seizures.","authors":"Patama Gomutbutra, Sarawut Krongsut, John Lott","doi":"10.1080/21646821.2025.2520094","DOIUrl":"10.1080/21646821.2025.2520094","url":null,"abstract":"<p><p>Artificial intelligence-integrated electroencephalography (AI-EEG) has demonstrated promise in the early detection of nonconvulsive status epilepticus (NCSE), particularly in emergency and intensive care settings with limited access to trained EEG technologists. This review includes 20 studies, of which 12 were incorporated into a meta-analysis assessing the diagnostic accuracy of AI-EEG. The pooled sensitivity reached 95%, with a specificity of 83%. However, when the pretest probability of NCSE is 40%, false positives may occur in approximately one in seven patients. Commercial AI-EEG platforms have shown a reduction in unnecessary antiepileptic drug (AED) administration compared to clinical judgment alone. Four prospective cohort studies reported a 26% relative risk reduction (RR -0.26; 95% CI -0.50 to -0.02; p = .03) in unnecessary AED use. Additionally, AI-EEG shortened the median time to EEG acquisition in resource-limited settings-from 4.5 hours (IQR 3.2-6.8) to 2.1 hours (IQR 1.5-3.4). A sub-analysis from an industry-sponsored trial suggested potential benefits of AI-EEG in reducing morbidity and ICU length of stay, though evidence remains insufficient for definitive conclusions. Despite these advantages, rapid-deployment AI-EEG systems face challenges: lack of video integration makes it difficult to distinguish seizures from artifacts or behavioral events, and limited electrode coverage may miss central brain activity. Moreover, AI algorithms tend to overread sharp and spike activities compared to human interpretation. Further investigator-initiated studies are needed to evaluate the diagnostic yield of AI-EEG beyond its simplified setup, assess its true impact on patient outcomes, and determine its feasibility for large-scale clinical implementation. .</p>","PeriodicalId":22816,"journal":{"name":"The Neurodiagnostic Journal","volume":" ","pages":"173-196"},"PeriodicalIF":0.0,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144660298","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}