Giacino, Joseph T.

Abstract Objective An accurate evaluation of behavioral responsiveness during and after seizures in people with epilepsy is critical for diagnosis and management. Current methods for assessing behavioral responsiveness are characterized by substantial variation, subjectivity, and limited reliability and reproducibility in ambulatory and epilepsy monitoring unit settings. In this study, we aimed to develop and implement a novel mobile platform for deployment of automated responsiveness testing in epilepsy—the ARTiE Watch—to facilitate standardized, objective assessments of behavioral responsiveness during and after seizures. Methods We prospectively recruited patients admitted to the epilepsy monitoring units for diagnostic evaluation and long‐term video‐electroencephalographic monitoring at Mayo Clinic and Yale New Haven Hospital. Participants wore the ARTiE Watch, a smartwatch paired with custom smartphone software integrated with cloud infrastructure allowing for remote activation of standardized assessment on the participants' smartwatches. The assessment consisted of 18 command prompts that test behavioral responsiveness across motor, language, and memory domains. Upon visually identifying an electrographic seizure during EMU monitoring, the BrainRISE platform was used to deploy the ARTiE Watch behavioral testing sequence. Responsiveness scoring was conducted on smartwatch files. Results Eighteen of 56 participants had a total of 39 electrographic seizures assessed with the ARTiE Watch. The 18 subjects with ARTiE Watch‐tested seizures had a total of 67 baseline (interictal) ARTiE Watch tests collected for analysis. The analysis showed distinct ARTiE Watch behavioral responsiveness phenotypes: (1) decreased responsiveness across all ARTiE Watch commands during seizure (ictal–postictal) periods compared (to baseline ( p < .0001), (2) decreased responsiveness in bilateral tonic–clonic seizures compared to baseline ( p < .0001) and compared to focal seizures ( p < .0001), and (3) decreased responsiveness during focal impaired awareness seizures compared to baseline ( p < .0001) and compared to focal aware seizures ( p < .001). Significance ARTiE Watch behavioral testing deployed utilizing a mobile cloud‐based platform is feasible and can provide standardized, objective behavioral responsiveness assessments during seizures.

Abstract Objective To conduct a scoping review of models of care for chronic disease management to identify potentially effective components for management of chronic traumatic brain injury (TBI). Methods Information sources : Systematic searches of three databases (Ovid MEDLINE, Embase, and Cochrane Database of Systematic Reviews) from January 2010 to May 2021. Eligibility criteria : Systematic reviews and meta‐analyses reporting on the effectiveness of the Chronic Care Model (CCM), collaborative/integrated care, and other chronic disease management models. Data : Target diseases, model components used ( n = 11), and six outcomes (disease‐specific, generic health‐related quality of life and functioning, adherence, health knowledge, patient satisfaction, and cost/health care use). Synthesis : Narrative synthesis, including proportion of reviews documenting outcome benefits. Results More than half (55%) of the 186 eligible reviews focused on collaborative/integrated care models, with 25% focusing on CCM and 20% focusing on other chronic disease management models. The most common health conditions were diabetes ( n = 22), depression ( n = 16), heart disease ( n = 12), aging ( n = 11), and kidney disease ( n = 8). Other single medical conditions were the focus of 22 reviews, multiple medical conditions of 59 reviews, and other or mixed mental health/behavioral conditions of 20 reviews. Some type of quality rating for individual studies was conducted in 126 (68%) of the reviews. Of reviews that assessed particular outcomes, 80% reported disease‐specific benefits, and 57% to 72% reported benefits for the other five types of outcomes. Outcomes did not differ by the model category, number or type of components, or target disease. Conclusions Although there is a paucity of evidence for TBI per se, care model components proven effective for other chronic diseases may be adaptable for chronic TBI care.

AbstractObjectiveTo identify group‐based patterns in suicidal ideation (SI) over the first 10 years after traumatic brain injury (TBI).MethodsParticipants included 9539 individuals in the TBI Model Systems National Database who responded to Patient Health Questionnaire‐9 Item 9 assessing SI at 1, 2, 5, and/or 10 years post‐injury. Ak‐means cluster analysis was conducted to determine group‐based patterns of SI, and pre‐injury variables were compared with ANOVAs and chi‐square tests.ResultsSI and attempts decreased over time. Four group‐based patterns emerged: Low, increasing, moderate, and decreasing SI. The low SI group comprised 89% of the sample, had the highest pre‐injury employment, fewer mental health vulnerabilities, least severe injuries, and were oldest. The increasing SI group had the most severe TBIs, were youngest, and disproportionately Black or Asian/Pacific Islander.ConclusionThese findings reinforce the importance of mental health and suicide risk assessment during chronic recovery from TBI.

Glial fibrillary acidic protein (GFAP) is cleared by the Food and Drug Administration (FDA) to determine need for head computed tomography (CT) within 12 h after mild traumatic brain injury (TBI) (Glasgow Coma Score [GCS] 13–15); S100 calcium-binding protein B (S100B) serves this function in Europe. This phase 1 biomarker cohort analysis of the multi-center, observational Transforming Research and Clinical Knowledge in Traumatic Brain Injury (TRACK-TBI) study compares GFAP's diagnostic performance, measured on a rapid point-of-care platform, against protein S100B to predict intracranial abnormalities on CT within 24 h post-injury across the spectrum of TBI (GCS 3–15). Head CT scan performed in TBI subjects and blood was collected for all consenting subjects presenting to 18 United States level 1 trauma centers. Plasma was analyzed on a point-of-care device prototype assay for GFAP and serum was analyzed for S100B. In 1359 patients with TBI (GCS 3–15), mean (standard deviation [SD]) age = 40.1 (17.0) years; 68% were male. Plasma GFAP levels were significantly higher in CT+ TBI subjects (median = 1358 pg/mL, interquartile range [IQR]: 472–3803) than in CT- TBI subjects (median = 116 pg/mL, IQR: 26–397) or orthopedic trauma controls ( n = 122; median = 13 pg/mL, IQR: 7–20), p < 0.001. Serum S100B levels were likewise higher in CT+ TBI subjects (median = 0.17 μg/L, IQR: 0.09–0.38) than in CT- TBI subjects (median = 0.10 μg/L, IQR: 0.06–0.18), p < 0.001. Receiver operating characteristic curves were generated for prediction of intracranial injury on admission CT scan; area under the curve (AUC) for GFAP was significantly higher than for S100B in the same cohort (GFAP AUC – 0.85, 95% confidence interval [CI] 0.83–0.87; S100B AUC – 0.67, 95% CI 0.64-0.70; p < 0.001). GFAP, measured on a point-of-care platform prototype assay, has high discriminative ability to predict intracranial abnormalities on CT scan in patients with TBI across the full injury spectrum of GCS 3–15 through 24 h post-injury. GFAP substantially outperforms S100B.