Neuropsychiatric complications of coronavirus disease 2019: Mount Sinai Health System cohort study.

OBJECTIVE: To describe the frequency of neuropsychiatric complications among hospitalized patients with coronavirus disease 2019 (COVID-19) and their association with pre-existing comorbidities and clinical outcomes. METHODS: We retrospectively identified all patients hospitalized with COVID-19 within a large multicenter New York City health system between March 15, 2020 and May 17, 2021 and randomly selected a representative cohort for detailed chart review. Clinical data, including the occurrence of neuropsychiatric complications (categorized as either altered mental status [AMS] or other neuropsychiatric complications) and in-hospital mortality, were extracted using an electronic medical record database and individual chart review. Associations between neuropsychiatric complications, comorbidities, laboratory findings, and in-hospital mortality were assessed using multivariate logistic regression. RESULTS: Our study cohort consisted of 974 patients, the majority were admitted during the first wave of the pandemic. Patients were treated with anticoagulation (88.4%), glucocorticoids (24.8%), and remdesivir (10.5%); 18.6% experienced severe COVID-19 pneumonia (evidenced by ventilator requirement). Neuropsychiatric complications occurred in 58.8% of patients; 39.8% experienced AMS; and 19.0% experienced at least one other complication (seizures in 1.4%, ischemic stroke in 1.6%, hemorrhagic stroke in 1.0%) or symptom (headache in 11.4%, anxiety in 6.8%, ataxia in 6.3%). Higher odds of mortality, which occurred in 22.0%, were associated with AMS, ventilator support, increasing age, and higher serum inflammatory marker levels. Anticoagulant therapy was associated with lower odds of mortality and AMS. CONCLUSION: Neuropsychiatric complications of COVID-19, especially AMS, were common, varied, and associated with in-hospital mortality in a diverse multicenter cohort at an epicenter of the COVID-19 pandemic.

Older adults with epilepsy and COVID-19: Outcomes in a multi-hospital health system.

BACKGROUND: Coronavirus disease 2019 (COVID-19) is associated with high rates of mortality and morbidity in older adults, especially those with pre-existing conditions. There is little work investigating how neurological conditions affect older adults with COVID-19. We aimed to compare in-hospital outcomes, including mortality, in older adults with and without epilepsy. METHODS: This retrospective study in a large multicenter New York health system included consecutive older patients (age ≥65 years) either with or without epilepsy who were admitted with COVID-19 between 3/2020-5/2021. Epilepsy was identified using a validated International Classification of Disease (ICD) and antiseizure medicationbased case definition. Univariate comparisons were calculated using Chi-square, Fisher's exact, Mann-Whitney U, or Student's t-tests. Multivariable logistic regression models were generated to examine factors associated with mortality, discharge disposition and length of stay (LOS). RESULTS: We identified 5384 older adults admitted with COVID-19 of whom 173 (3.21 %) had epilepsy. Mean age was significantly lower in those with (75.44, standard deviation (SD): 7.23) compared to those without epilepsy (77.98, SD: 8.68, p = 0.007). Older adults with epilepsy were more likely to be ventilated (35.84 % vs. 16.18 %, p < 0.001), less likely to be discharged home (21.39 % vs. 43.12 %, p < 0.001), had longer median LOS (13 days vs. 8 days, p < 0.001), and had higher in-hospital death (35.84 % vs. 28.29 %, p = 0.030) compared to those without epilepsy. Epilepsy in older adults was associated with increased odds of in-hospital death (adjusted odds ratio (aOR), 1.55; 95 % CI 1.12-2.14, p = 0.032), non-routine discharge disposition (aOR, 3.34; 95 % CI 2.21-5.03, p < 0.001), and longer LOS (46.46 % 95 % CI 34 %-59 %, p < 0.001). CONCLUSIONS: In models that adjusted for multiple confounders including comorbidity and age, our study found that epilepsy was still associated with higher in-hospital mortality, longer LOS and worse discharge dispositions in older adults with COVID-19 higher in-hospital mortality, longer LOS and worse discharge dispositions in older adults with COVID-19. This work reinforces that epilepsy is a risk factor for worse outcomes in older adults admitted with COVID-19. Timely identification and treatment of COVID-19 in epilepsy may improve outcomes in older people with epilepsy.

Common Pathways of Epileptogenesis in Patients With Epilepsy Post-Brain Injury: Findings From a Systematic Review and Meta-analysis.

BACKGROUND AND OBJECTIVES: Epilepsy may result from various brain injuries, including stroke (ischemic and hemorrhagic), traumatic brain injury, and infections. Identifying shared common biological pathways and biomarkers of the epileptogenic process initiated by the different injuries may lead to novel targets for preventing the development of epilepsy. We systematically reviewed biofluid biomarkers to test their association with the risk of post-brain injury epilepsy. METHODS: We searched articles until January 25, 2022, in MEDLINE, Embase, PsycInfo, Web of Science, and Cochrane. The primary outcome was the difference in mean biomarker levels in patients with and without post-brain injury epilepsy. We used the modified quality score on prognostic studies for risk of bias assessment. We calculated each biomarker's pooled standardized mean difference (SMD) and 95% CI. Molecular interaction network and enrichment analyses were conducted in Cytoscape (PROSPERO CRD42021297110). RESULTS: We included 22 studies with 1,499 cases with post-brain injury epilepsy and 7,929 controls without post-brain injury epilepsy. Forty-five biomarkers in the blood or CSF were investigated with samples collected at disparate time points. Of 22 studies, 21 had a moderate-to-high risk of bias. Most of the biomarkers (28/45) were investigated in single studies; only 9 provided validation data, and studies used variable definitions for early-onset and late-onset seizures. A meta-analysis was possible for 19 biomarkers. Blood glucose levels in 4 studies were significantly higher in patients with poststroke epilepsy (PSE) than those without PSE (SMD 0.44; CI 0.19-0.69). From individual studies, 15 biomarkers in the blood and 7 in the CSF were significantly associated with post-brain injury epilepsy. Enrichment analysis identified that the significant biomarkers (interleukin [IL]-6, IL-1ß]) were predominantly inflammation related. DISCUSSION: We cannot yet recommend using the reported biomarkers for designing antiepileptogenesis trials or use in the clinical setting because of methodological heterogeneity, bias in the included studies, and insufficient validation studies. Although our analyses indicate the plausible role of inflammation in epileptogenesis, this is likely not the only mechanism. For example, an individual's genetic susceptibilities might contribute to his/her risk of epileptogenesis after brain injury. Rigorously designed biomarker studies with methods acceptable to the regulatory bodies should be conducted.

In-hospital outcomes in patients with and without epilepsy diagnosed with COVID-19-A cohort study.

OBJECTIVES: Coronavirus disease 2019 (COVID-19) is associated with mortality in persons with comorbidities. The aim of this study was to evaluate in-hospital outcomes in patients with COVID-19 with and without epilepsy. METHODS: We conducted a retrospective study of patients with COVID-19 admitted to a multicenter health system between March 15, 2020, and May 17, 2021. Patients with epilepsy were identified using a validated International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM)/ICD-10-CM case definition. Logistic regression models and Kaplan-Meier analyses were conducted for mortality and non-routine discharges (i.e., not discharged home). An ordinary least-squares regression model was fitted for length of stay (LOS). RESULTS: We identified 9833 people with COVID-19 including 334 with epilepsy. On univariate analysis, people with epilepsy had significantly higher ventilator use (37.70% vs 14.30%, p < .001), intensive care unit (ICU) admissions (39.20% vs 17.70%, p < .001) mortality rate (29.60% vs 19.90%, p < .001), and longer LOS (12 days vs 7 days, p < .001). and fewer were discharged home (29.64% vs 57.37%, p < .001). On multivariate analysis, only non-routine discharge (adjusted odds ratio [aOR] 2.70, 95% confidence interval [CI] 2.00-3.70; p < .001) and LOS (32.50% longer, 95% CI 22.20%-43.60%; p < .001) were significantly different. Factors associated with higher odds of mortality in epilepsy were older age (aOR 1.05, 95% CI 1.03-1.08; p < .001), ventilator support (aOR 7.18, 95% CI 3.12-16.48; p < .001), and higher Charlson comorbidity index (CCI) (aOR 1.18, 95% CI 1.04-1.34; p = .010). In epilepsy, admissions between August and December 2020 or January and May 2021 were associated with a lower odds of non-routine discharge and decreased LOS compared to admissions between March and July 2020, but this difference was not statistically significant. SIGNIFICANCE: People with COVID-19 who had epilepsy had a higher odds of non-routine discharge and longer LOS but not higher mortality. Older age (≥65), ventilator use, and higher CCI were associated with COVID-19 mortality in epilepsy. This suggests that older adults with epilepsy and multimorbidity are more vulnerable than those without and should be monitored closely in the setting of COVID-19.

Point-of-care electroencephalography enables rapid evaluation and management of non-convulsive seizures and status epilepticus in the emergency department.

Objectives: To describe our institutional experience with point-of-care electroencephalography (pocEEG) and its impact on the evaluation/management of suspected non-convulsive seizures in the emergency department (ED). Methods: We retrospectively identified 157 adults who underwent pocEEG monitoring in our community hospital ED in 1 year. We calculated the time to obtain pocEEG in the ED (door-to-EEG time) and examined the impact of pocEEG findings (categorized as seizure, highly epileptiform patterns, slowing, or normal activity) on antiseizure medication treatment. Results: PocEEG revealed seizures (14%, n = 22), highly epileptiform patterns (22%, n = 34), slowing (44%, n = 69), and normal activity (20%, n = 32). The median door-to-EEG time (from initial ED evaluation to pocEEG monitoring) was only 1.2 hours (interquartile range 0.1-2.1) even though 55% of studies were performed after-hours (5 pm-9 am). Most patients were admitted (54% to the intensive care unit, 41% to floor). Antiseizure medication treatment occurred pre-pocEEG in 93 patients (59%) and post-pocEEG in 88 patients (56%). By reviewing the relationship between pocEEG monitoring and antiseizure medication management, we found a significant association between pocEEG findings and changes in management (P < 0.001). Treatment escalation occurred more frequently in patients with epileptiform activity (seizures or highly epileptiform patterns, 52%) than patients with non-epileptiform activity (normal or slow, 25%, P < 0.001), and avoidance of treatment escalation occurred more frequently in patients with normal or slow activity (27%) than patients with seizures or highly epileptiform patterns (2%, P < 0.001). Conclusion: Our study, the largest to date describing the real-world use of pocEEG in emergency medicine, found that rapid EEG acquisition in the ED was feasible in a community hospital and significantly affected the management of suspected non-convulsive seizures.

Neuroimaging findings and neurological manifestations in hospitalized COVID-19 patients: Impact of cancer and ventilatory support status.

INTRODUCTION: Coronavirus 2019 (COVID-19) is known to affect the central nervous system. Neurologic morbidity associated with COVID-19 is commonly attributed to sequelae of some combination of thrombotic and inflammatory processes. The aim of this retrospective observational study was to evaluate neuroimaging findings in hospitalized COVID-19 patients with neurological manifestations in cancer versus non-cancer patients, and in patients with versus without ventilatory support (with ventilatory support defined as including patients with intubation and noninvasive ventilation). Cancer patients are frequently in an immunocompromised or prothrombotic state with side effects from chemotherapy and radiation that may cause neurological issues and increase vulnerability to systemic illness. We wanted to determine whether neurological and/or neuroimaging findings differed between patients with and without cancer. METHODS: Eighty adults (44 male, 36 female, 64.5 ±14 years) hospitalized in the Mount Sinai Health System in New York City between March 2020 and April 2021 with reverse-transcriptase polymerase chain reaction-confirmed COVID-19 underwent magnetic resonance imaging (MRI) during their admissions. The cohort consisted of four equal subgroups based on cancer and ventilatory support status. Clinical and imaging data were acquired and analyzed. RESULTS: Neuroimaging findings included non-ischemic parenchymal T2/FLAIR signal hyperintensities (36.3%), acute/subacute infarcts (26.3%), chronic infarcts (25.0%), microhemorrhages (23.8%), chronic macrohemorrhages (10.0%), acute macrohemorrhages (7.5%), and encephalitis-like findings (7.5%). There were no significant differences in neuroimaging findings between cancer and non-cancer subgroups. Clinical neurological manifestations varied. The most common was encephalopathy (77.5%), followed by impaired responsiveness/coma (38.8%) and stroke (26.3%). There were significant differences between patients with versus without ventilatory support. Encephalopathy and impaired responsiveness/coma were more prevalent in patients with ventilatory support (p = 0.02). Focal weakness was more frequently seen in patients without ventilatory support (p = 0.01). DISCUSSION: This study suggests COVID-19 is associated with neurological manifestations that may be visible with brain imaging techniques such as MRI. In our COVID-19 cohort, there was no association between cancer status and neuroimaging findings. Future studies might include more prospectively enrolled systematically characterized patients, allowing for more rigorous statistical analysis.

Analysis of Electrocorticography in Epileptic Patients With Responsive Neurostimulation Undergoing Scalp Electroencephalography Monitoring.

PURPOSE: To describe the relationship of electrocorticography events detected by a brain-responsive neurostimulation system (RNS) and their association with ictal and interictal activity detected on simultaneous scalp EEG. METHODS: We retrospectively identified patients with drug-resistant epilepsy implanted with RNS who subsequently underwent long-term scalp EEG monitoring. RNS detections were correlated to simultaneous activity recorded on scalp EEG to determine the characteristics of electrocorticography-stored long episodes associated with seizures or other findings on scalp EEG. RESULTS: Eleven patients were included with an average of 3.6 days of monitoring. Most RNS detections were of very brief duration (<10 seconds, 92.9%) and received one stimulation therapy (80.8%). A high proportion of long episodes (67.1%) were not identified as electrographic seizures on scalp EEG. Of those ictal-appearing (71.2%) long episodes, 68.2% had seizure correlates. Long episodes associated with seizures on scalp EEG had a longer median duration compared with those without (39.7 vs. 16.8 seconds, P < 0.002) and had broader spread pattern and were of higher amplitude on electrocorticography. Brief potentially ictal rhythmic discharges were the most common EEG findings associated with long episodes that did not have scalp EEG seizure correlates (100% for ictal- and 50% for non-ictal-appearing long episodes). CONCLUSIONS: Longer, broader spread and higher amplitude intracranial RNS detections are more likely to manifest as electrographic seizures on scalp EEG. Brief potentially ictal rhythmic discharges may serve as a scalp EEG biomarker of ictal intracranial episodes that are detected as long episodes by the RNS but not identified as electrographic seizures on scalp EEG.

Comparing Seizures Captured by Rapid Response EEG and Conventional EEG Recordings in a Multicenter Clinical Study.

Objective: A recent multicenter prospective study (DECIDE trial) examined the use of Ceribell Rapid Response EEG (Rapid-EEG) in the emergent evaluation and management of critically ill patients suspected to have non-convulsive seizures. We present a detailed, patient-level examination of seizures detected either on initial Rapid-EEG or subsequent conventional EEG within 24 h to investigate whether seizures were missed on Rapid-EEG due to the exclusion of midline/parasagittal coverage. Methods: We identified from 164 patients studied in the DECIDE trial those who had seizures detected on Rapid-EEG but not conventional EEG (n = 6), conventional EEG but not Rapid-EEG (n = 4), or both Rapid-EEG and conventional EEG (n = 9). We examined the electrographic characteristics of ictal and interictal findings on both devices, especially their detection in lateral or midline/parasagittal chains, and patient clinical histories to identify contributors toward discordant seizure detection. Results: Seizures detected on both EEG systems had similar electrographic appearance and laterality. Seizures detected only on conventional EEG (within 24 h following Rapid-EEG) were visible in the temporal chains, and external clinical factors (e.g., treatment with anti-seizure medications, sedation, and duration of recordings) explained the delayed presentation of seizures. Patients with seizures detected only by Rapid-EEG were treated with anti-seizure medications, and subsequent conventional EEG detected interictal highly epileptiform patterns with similar laterality. Conclusions: Our case series demonstrates that electrographic data obtained from initial Rapid-EEG and subsequent conventional EEG monitoring are largely concordant relative to morphology and laterality. These findings are valuable to inform future investigation of abbreviated EEG systems to optimize management of suspected non-convulsive seizures and status epilepticus. Future, larger studies could further investigate the value of Rapid-EEG findings for forecasting and predicting seizures in long-term EEG recordings.

Improved access to rapid electroencephalography at a community hospital reduces inter-hospital transfers for suspected non-convulsive seizures.

OBJECTIVE: Patients with suspected non-convulsive seizures are optimally evaluated with EEG. However, limited EEG infrastructure at community hospitals often necessitates transfer for long-term EEG monitoring (LTM). Novel point-of-care EEG systems could expedite management of nonconvulsive seizures and reduce unnecessary transfers. We aimed to describe the impact of rapid access to EEG using a novel EEG device with remote expert interpretation (tele-EEG) on rates of transfer for LTM. METHODS: We retrospectively identified a cohort of patients who underwent Rapid-EEG (Ceribell Inc., Mountain View, CA) monitoring as part of a new standard-of-care at a community hospital. Rapid-EEGs were initially reviewed on-site by a community hospital neurologist before transitioning to tele-EEG review by epileptologists at an affiliated academic hospital. We compared the rate of transfer for LTM after Rapid-EEG/tele-EEG implementation to the expected rate if rapid access to EEG was unavailable. RESULTS: Seventy-four patients underwent a total of 118 Rapid-EEG studies (10 with seizure, 18 with highly epileptiform patterns, 90 with slow/normal activity). Eighty-one studies (69%), including 9 of 10 studies that detected seizures, occurred after-hours when EEG was previously unavailable. Based on historical practice patterns, we estimated that Rapid-EEG potentially obviated transfer for LTM in 31 of 33 patients (94%); both completed transfers occurred before the transition to tele-EEG review. SIGNIFICANCE: Rapid access to EEG led to the detection of seizures that would otherwise have been missed and reduced inter-hospital transfers for LTM. We estimate that the reduction in inter-hospital transportation costs alone would be in excess of $39,000 ($1,274 per patient). Point-of-care EEG systems may support a hub-and-spoke model for managing non-convulsive seizures (similar to that utilized in this study and analogous to existing acute stroke infrastructures), with increased EEG capacity at community hospitals and tele-EEG interpretation by specialists at academic hospitals that can accept transfers for LTM.

Electroencephalography at the height of a pandemic: EEG findings in patients with COVID-19.

OBJECTIVE: To characterize continuous video electroencephalogram (VEEG) findings of hospitalized COVID-19 patients. METHODS: We performed a retrospective chart review of patients admitted at three New York City hospitals who underwent VEEG at the peak of the COVID-19 pandemic. Demographics, comorbidities, neuroimaging, VEEG indications and findings, treatment, and outcomes were collected. RESULTS: Of 93 patients monitored, 77% had severe COVID-19 and 40% died. Acute ischemic or hemorrhagic stroke was present in 26% and 15%, respectively. Most common VEEG indications were encephalopathy/coma (60%) and seizure-like movements (38%). Most common VEEG findings were generalized slowing (97%), generalized attenuation (31%), generalized periodic discharges (17%) and generalized sharp waves (15%). Epileptiform abnormalities were present in 43% and seizures in 8% of patients, all of whom had seizure risk factors. Factors associated with an epileptiform VEEG included increasing age (OR 1.07, p = 0.001) and hepatic/renal failure (OR 2.99, p = 0.03). CONCLUSIONS: Most COVID-19 patients who underwent VEEG monitoring had severe COVID-19 and over one-third had acute cerebral injury (e.g., stroke, anoxia). Seizures were uncommon. VEEG findings were nonspecific. SIGNIFICANCE: VEEG findings in this cohort of hospitalized COVID-19 patients were those often seen in critical illness. Seizures were uncommon and occurred in the setting of common seizure risk factors.

Evaluating the utility of Rapid Response EEG in emergency care.

BACKGROUND: Timely management of non-convulsive status epilepticus (NCSE) is critical to improving patient outcomes. However, NCSE can only be confirmed using electroencephalography (EEG), which is either significantly delayed or entirely unavailable in emergency departments (EDs). We piloted the use of a new bedside EEG device, Rapid Response EEG (Rapid-EEG, Ceribell), in the ED and evaluated its impact on seizure management when used by emergency physicians. METHODS: Patients who underwent Rapid-EEG to rule out NCSE were prospectively enrolled in a pilot project conducted at two ED sites (an academic hospital and a community hospital). Physicians were surveyed on the perceived impact of the device on seizure treatment and patient disposition, and we calculated physicians' sensitivity and specificity (with 95% CI) for diagnosing NCSE using Rapid-EEG's Brain Stethoscope function. RESULTS: Of the 38 patients enrolled, the one patient with NCSE was successfully diagnosed and treated within minutes of evaluation. Physicians reported that Rapid-EEG changed clinical management for 20 patients (53%, 95% CI 37% to 68%), primarily by ruling out seizures and avoiding antiseizure treatment escalation, and expedited disposition for 8 patients (21%, 95% CI 11% to 36%). At the community site, physicians diagnosed seizures by their sound using Brain Stethoscope with 100% sensitivity (95% CI 5% to 100%) and 92% specificity (95% CI 62% to 100%). CONCLUSION: Rapid-EEG was successfully deployed by emergency physicians at academic and community hospitals, and the device changed management in a majority of cases. Widespread adoption of Rapid-EEG may lead to earlier diagnosis of NCSE, reduced unnecessary treatment and expedited disposition of seizure mimics.

Modeling the economic value of Ceribell Rapid Response EEG in the inpatient hospital setting.

AIMS: Potentially life-threatening diagnosis of non-convulsive status epilepticus (NCSE) can only be confirmed with electroencephalography (EEG). When access to EEG is limited, physicians may empirically treat, risking unnecessary sedation and intubation, or not treat, increasing risk of refractory seizures. Either may prolong hospital length of stay (LOS). The current study aimed to examine the effect of a new EEG system (Ceribell Rapid Response EEG, Rapid-EEG) on hospital costs by enabling easy access to EEG and expedited seizure diagnosis and treatment. MATERIALS AND METHODS: We built a two-armed decision-analytic cost-benefit model comparing Rapid-EEG with clinical suspicion alone for NCSE. Diagnostic parameters were informed by a multicenter clinical trial (DECIDE, NCT03534258), while LOS and cost parameters were from public US inpatient data, published literature, and Center for Medicare and Medicaid Services fee schedules. We calculated reference case estimates from mean values, while uncertainty was assessed using 95% prediction intervals (PI) generated by probabilistic sensitivity analysis (PSA) and ANCOVA sum of squares. All costs were indexed to 2019 US$. RESULTS: Each use case of Rapid-EEG saved $3,971 to $17,290 as it led to reduction in the hospital LOS by 1.2 days (6.1 vs. 7.4 days) and ICU LOS by 0.4 days (1.5 vs. 1.9 days). Using PSA, Rapid-EEG saving was $5,633 per use case (95% PI: $($4,649 to $6,617), as it led to diminished hospital LOS by 1.1 days (95% PI: 0.9-1.4 days) and reduced ICU LOS by 0.5 days (95% PI: 0.4-0.6 days). Cost-savings were demonstrated in 75% of replications. Sixty-four percent of variance in total costs was attributable to LOS for persons incorrectly diagnosed with seizures. LIMITATIONS: Results were obtained from the analysis of existing data and not a prospective outcome trial. CONCLUSIONS: Rapid-EEG alters the treatment course for patients with suspected seizures and will result in cost savings per patient.

Monitoring the Burden of Seizures and Highly Epileptiform Patterns in Critical Care with a Novel Machine Learning Method.

INTRODUCTION: Current electroencephalography (EEG) practice relies on interpretation by expert neurologists, which introduces diagnostic and therapeutic delays that can impact patients' clinical outcomes. As EEG practice expands, these experts are becoming increasingly limited resources. A highly sensitive and specific automated seizure detection system would streamline practice and expedite appropriate management for patients with possible nonconvulsive seizures. We aimed to test the performance of a recently FDA-cleared machine learning method (Claritγ, Ceribell Inc.) that measures the burden of seizure activity in real time and generates bedside alerts for possible status epilepticus (SE). METHODS: We retrospectively identified adult patients (n = 353) who underwent evaluation of possible seizures with Rapid Response EEG system (Rapid-EEG, Ceribell Inc.). Automated detection of seizure activity and seizure burden throughout a recording (calculated as the percentage of ten-second epochs with seizure activity in any 5-min EEG segment) was performed with Claritγ, and various thresholds of seizure burden were tested (≥ 10% indicating ≥ 30 s of seizure activity in the last 5 min, ≥ 50% indicating ≥ 2.5 min of seizure activity, and ≥ 90% indicating ≥ 4.5 min of seizure activity and triggering a SE alert). The sensitivity and specificity of Claritγ's real-time seizure burden measurements and SE alerts were compared to the majority consensus of at least two expert neurologists. RESULTS: Majority consensus of neurologists labeled the 353 EEGs as normal or slow activity (n = 249), highly epileptiform patterns (HEP, n = 87), or seizures [n = 17, nine longer than 5 min (e.g., SE), and eight shorter than 5 min]. The algorithm generated a SE alert (≥ 90% seizure burden) with 100% sensitivity and 93% specificity. The sensitivity and specificity of various thresholds for seizure burden during EEG recordings for detecting patients with seizures were 100% and 82% for ≥ 50% seizure burden and 88% and 60% for ≥ 10% seizure burden. Of the 179 EEG recordings in which the algorithm detected no seizures, seizures were identified by the expert reviewers in only two cases, indicating a negative predictive value of 99%. DISCUSSION: Claritγ detected SE events with high sensitivity and specificity, and it demonstrated a high negative predictive value for distinguishing nonepileptiform activity from seizure and highly epileptiform activity. CONCLUSIONS: Ruling out seizures accurately in a large proportion of cases can help prevent unnecessary or aggressive over-treatment in critical care settings, where empiric treatment with antiseizure medications is currently prevalent. Claritγ's high sensitivity for SE and high negative predictive value for cases without epileptiform activity make it a useful tool for triaging treatment and the need for urgent neurological consultation.

Acute Cerebrovascular Events With COVID-19 Infection.

BACKGROUND AND PURPOSE: Coronavirus disease 2019 (COVID-19) has been associated with an increased incidence of thrombotic events, including stroke. However, characteristics and outcomes of COVID-19 patients with stroke are not well known. METHODS: We conducted a retrospective observational study of risk factors, stroke characteristics, and short-term outcomes in a large health system in New York City. We included consecutively admitted patients with acute cerebrovascular events from March 1, 2020 through April 30, 2020. Data were stratified by COVID-19 status, and demographic variables, medical comorbidities, stroke characteristics, imaging results, and in-hospital outcomes were examined. Among COVID-19-positive patients, we also summarized laboratory test results. RESULTS: Of 277 patients with stroke, 105 (38.0%) were COVID-19-positive. Compared with COVID-19-negative patients, COVID-19-positive patients were more likely to have a cryptogenic (51.8% versus 22.3%, P<0.0001) stroke cause and were more likely to suffer ischemic stroke in the temporal (P=0.02), parietal (P=0.002), occipital (P=0.002), and cerebellar (P=0.028) regions. In COVID-19-positive patients, mean coagulation markers were slightly elevated (prothrombin time 15.4±3.6 seconds, partial thromboplastin time 38.6±24.5 seconds, and international normalized ratio 1.4±1.3). Outcomes were worse among COVID-19-positive patients, including longer length of stay (P<0.0001), greater percentage requiring intensive care unit care (P=0.017), and greater rate of neurological worsening during admission (P<0.0001); additionally, more COVID-19-positive patients suffered in-hospital death (33% versus 12.9%, P<0.0001). CONCLUSIONS: Baseline characteristics in patients with stroke were similar comparing those with and without COVID-19. However, COVID-19-positive patients were more likely to experience stroke in a lobar location, more commonly had a cryptogenic cause, and had worse outcomes.

A Case of Postoperative Methicillin-Resistant Staphylococcus aureus Enterocolitis in an 81-Year-Old Man and Review of the Literature.

BACKGROUND Nosocomial diarrhea affects 12% to 32% of hospitalized patients. Before the development of the Clostridium difficile cytotoxin assay in the 1970s, Staphylococcus aureus was frequently implicated as a cause of hospital-acquired infectious colitis, particularly in association with recent antibiotic therapy or abdominal surgery. Decreased utilization of stool culture has reduced the recognition of S. aureus as a rare, but historically important, cause of enterocolitis. CASE REPORT An 81-year-old man with no recent history of travel, exposure to potential infectious sources (e.g., sick contacts, animals, undercooked foods), or antibiotic or proton-pump inhibitor use was admitted for a Whipple procedure (expanded intraoperatively with total pancreatectomy, splenectomy, and portal vein resection) for stage III pancreatic adenocarcinoma. On postoperative day (POD) 5, the patient developed large-volume watery diarrhea that did not improve with tube feeding cessation and oral pancreatic enzyme replacement. He subsequently became clinically septic on POD10, and workup revealed severe radiographic sigmoid and rectal colitis and methicillin-resistant S. aureus (MRSA) bacteremia. Polymerase chain reaction testing for C. difficile was negative twice (POD5 and POD12). He was diagnosed with MRSA proctocolitis and improved with initiation of oral and intravenous vancomycin. CONCLUSIONS We describe a case of staphylococcal enterocolitis, a previously common cause of nosocomial diarrhea that has become increasingly underappreciated since the advent of culture-independent stool testing for C. difficile. Increased awareness of this entity, especially when Clostridium assays are negative, may guide more effective treatment of hospital-acquired infection.

Evaluating the Clinical Impact of Rapid Response Electroencephalography: The DECIDE Multicenter Prospective Observational Clinical Study.

OBJECTIVES: To measure the diagnostic accuracy, timeliness, and ease of use of Ceribell rapid response electroencephalography. We assessed physicians' diagnostic assessments and treatment plans before and after rapid response electroencephalography assessment. Primary outcomes were changes in physicians' diagnostic and therapeutic decision making and their confidence in these decisions based on the use of the rapid response electroencephalography system. Secondary outcomes were time to electroencephalography, setup time, ease of use, and quality of electroencephalography data. DESIGN: Prospective multicenter nonrandomized observational study. SETTING: ICUs in five academic hospitals in the United States. SUBJECTS: Patients with encephalopathy suspected of having nonconvulsive seizures and physicians evaluating these patients. INTERVENTIONS: Physician bedside assessment of sonified electroencephalography (30 s from each hemisphere) and visual electroencephalography (60 s) using rapid response electroencephalography. MEASUREMENTS AND MAIN RESULTS: Physicians (29 fellows or residents, eight attending neurologists) evaluated 181 ICU patients; complete clinical and electroencephalography data were available in 164 patients (average 58.6 ± 18.7 yr old, 45% females). Relying on rapid response electroencephalography information at the bedside improved the sensitivity (95% CI) of physicians' seizure diagnosis from 77.8% (40.0%, 97.2%) to 100% (66.4%, 100%) and the specificity (95% CI) of their diagnosis from 63.9% (55.8%, 71.4%) to 89% (83.0%, 93.5%). Physicians' confidence in their own diagnosis and treatment plan were also improved. Time to electroencephalography (median [interquartile range]) was 5 minutes (4-10 min) with rapid response electroencephalography while the conventional electroencephalography was delayed by several hours (median [interquartile range] delay = 239 minutes [134-471 min] [p < 0.0001 using Wilcoxon signed rank test]). The device was rated as easy to use (mean ± SD: 4.7 ± 0.6 [1 = difficult, 5 = easy]) and was without serious adverse effects. CONCLUSIONS: Rapid response electroencephalography enabled timely and more accurate assessment of patients in the critical care setting. The use of rapid response electroencephalography may be clinically beneficial in the assessment of patients with high suspicion for nonconvulsive seizures and status epilepticus.

Diagnostic Value of Electroencephalography with Ten Electrodes in Critically Ill Patients.

BACKGROUND: In critical care settings, electroencephalography (EEG) with reduced number of electrodes (reduced montage EEG, rm-EEG) might be a timely alternative to the conventional full montage EEG (fm-EEG). However, past studies have reported variable accuracies for detecting seizures using rm-EEG. We hypothesized that the past studies did not distinguish between differences in sensitivity from differences in classification of EEG patterns by different readers. The goal of the present study was to revisit the diagnostic value of rm-EEG when confounding issues are accounted for. METHODS: We retrospectively collected 212 adult EEGs recorded at Massachusetts General Hospital and reviewed by two epileptologists with access to clinical, trending, and video information. In Phase I of the study, we re-configured the first 4 h of the EEGs in lateral circumferential montage with ten electrodes and asked new readers to interpret the EEGs without access to any other ancillary information. We compared their rating to the reading of hospital clinicians with access to ancillary information. In Phase II, we measured the accuracy of the same raters reading representative samples of the discordant EEGs in full and reduced configurations presented randomly by comparing their performance to majority consensus as the gold standard. RESULTS: Of the 95 EEGs without seizures in the selected fm-EEG, readers of rm-EEG identified 92 cases (97%) as having no seizure activity. Of 117 EEGs with "seizures" identified in the selected fm-EEG, none of the cases was labeled as normal on rm-EEG. Readers of rm-EEG reported pathological activity in 100% of cases, but labeled them as seizures (N = 77), rhythmic or periodic patterns (N = 24), epileptiform spikes (N = 7), or burst suppression (N = 6). When the same raters read representative epochs of the discordant EEG cases (N = 43) in both fm-EEG and rm-EEG configurations, we found high concordance (95%) and intra-rater agreement (93%) between fm-EEG and rm-EEG diagnoses. CONCLUSIONS: Reduced EEG with ten electrodes in circumferential configuration preserves key features of the traditional EEG system. Discrepancies between rm-EEG and fm-EEG as reported in some of the past studies can be in part due to methodological factors such as choice of gold standard diagnosis, asymmetric access to ancillary clinical information, and inter-rater variability rather than detection failure of rm-EEG as a result of electrode reduction per se.

Midline and Parasagittal Seizures are Rare in Adult Patients.

BACKGROUND: For decades, half of the electrodes used in traditional electroencephalography (EEG) have been dedicated to midline and parasagittal coverage. Recently, newer EEG devices have used fewer electrodes without direct coverage over the midline or parasagittal regions. However, no systematic study to date has explored the prevalence of midline parasagittal seizures, and as such the risk of missing such seizures with only ten electrodes remains unknown. METHODS: We reviewed retrospective EEG data from a cohort of 300 patients at Stanford University Medical Center and determined the frequency of seizures localized to the midline parasagittal regions. We then compiled previously reported EEG cohorts that reported the prevalence of midline parasagittal seizures to validate our findings. RESULTS: In our cohort, only two EEGs (0.66%) were identified with a midline or parasagittal seizure focus. In a subsequent study, we compiled literature evidence from 169510 EEGs and found that the prevalence of midline or parasagittal epileptic spikes/seizures was similarly less than 1%. CONCLUSIONS: Our study serves as the first to systematically explore the scope of EEG abnormalities captured exclusively by midline or parasagittal electrodes and document their very low prevalence.

Diagnostic utility of eight-channel EEG for detecting generalized or hemispheric seizures and rhythmic periodic patterns.

OBJECTIVES: To compare the diagnostic utility of electroencephalography (EEG) using reduced, 8-channel montage (rm-EEG) to full, 18-channel montage (fm-EEG) for detection of generalized or hemispheric seizures and rhythmic periodic patterns (RPPs) by neurologists with extensive EEG training, neurology residents with minimal EEG exposure, and medical students without EEG experience. METHODS: We presented EEG samples in both fm-EEG (bipolar montage) and rm-EEG (lateral leads of bipolar montage) to 20 neurologists, 20 residents, and 42 medical students. Unanimous agreement of three senior epileptologists defined samples as seizures (n = 7), RPPs (n = 10), and normal or slowing (n = 20). Differences in median accuracy, sensitivity, and specificity were assessed using Wilcoxon signed-rank tests. RESULTS: Full and reduced EEG demonstrated similar accuracy when read by neurologists (fm-EEG: 95%, rm-EEG: 95%, p = 0.29), residents (fm-EEG: 80%, rm-EEG: 80%, p = 0.05), and students (fm-EEG: 60%, rm-EEG: 51%, p = 0.68). Moreover, neurologists' sensitivity for detecting seizure activity was comparable between fm-EEG (100%) and rm-EEG (98%) (p = 0.17). Furthermore, the specificity of rm-EEG for seizures and RPP (neurologists: 100%, residents: 90%, students: 86%) was significantly greater than that of fm-EEG (neurologists: 93%, p = 0.03; residents: 80%, p = 0.01; students: 69%, p < 0.001). CONCLUSIONS: The reduction of the number of EEG channels from 18 to 8 does not compromise neurologists' sensitivity for detecting seizures that are often a core reason for performing urgent EEG. It may also increase their specificity for detecting rhythmic and periodic patterns, and thereby providing important diagnostic information to guide patient's management. SIGNIFICANCE: Our study is the first to document the utility of a reduced channel EEG above the hairline compared to full montage EEG in aiding medical staff with varying degrees of EEG training to detect generalized or hemispheric seizures.