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  1. Book ; Online ; E-Book: The acute neurology survival guide

    Albin, Catherine S. W. / Zafar, Sahar F.

    a practical resource for inpatient and ICU neurology

    2022  

    Author's details Catherine S.W. Albin, Sahar F. Zafar editors
    Keywords Neurology ; Nervous system—Surgery ; Surgery
    Language English
    Size 1 Online-Ressource (xvi, 364 Seiten), Illustrationen, Diagramme
    Publisher Springer
    Publishing place Cham
    Publishing country Switzerland
    Document type Book ; Online ; E-Book
    Remark Zugriff für angemeldete ZB MED-Nutzerinnen und -Nutzer
    HBZ-ID HT021389327
    ISBN 978-3-030-75732-8 ; 9783030757311 ; 3-030-75732-3 ; 3030757315
    DOI 10.1007/978-3-030-75732-8
    Database ZB MED Catalogue: Medicine, Health, Nutrition, Environment, Agriculture

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  2. Article: Automated Extraction of Stroke Severity from Unstructured Electronic Health Records using Natural Language Processing.

    Fernandes, Marta / Westover, M Brandon / Singhal, Aneesh B / Zafar, Sahar F

    medRxiv : the preprint server for health sciences

    2024  

    Abstract: Background: Multi-center electronic health records (EHR) can support quality improvement initiatives and comparative effectiveness research in stroke care. However, limitations of EHR-based research include challenges in abstracting key clinical ... ...

    Abstract Background: Multi-center electronic health records (EHR) can support quality improvement initiatives and comparative effectiveness research in stroke care. However, limitations of EHR-based research include challenges in abstracting key clinical variables from non-structured data at scale. This is further compounded by missing data. Here we develop a natural language processing (NLP) model that automatically reads EHR notes to determine the NIH stroke scale (NIHSS) score of patients with acute stroke.
    Methods: The study included notes from acute stroke patients (>= 18 years) admitted to the Massachusetts General Hospital (MGH) (2015-2022). The MGH data were divided into training (70%) and hold-out test (30%) sets. A two-stage model was developed to predict the admission NIHSS. A linear model with the least absolute shrinkage and selection operator (LASSO) was trained within the training set. For notes in the test set where the NIHSS was documented, the scores were extracted using regular expressions (stage 1), for notes where NIHSS was not documented, LASSO was used for prediction (stage 2). The reference standard for NIHSS was obtained from Get With The Guidelines Stroke Registry. The two-stage model was tested on the hold-out test set and validated in the MIMIC-III dataset (Medical Information Mart for Intensive Care-MIMIC III 2001-2012) v1.4, using root mean squared error (RMSE) and Spearman correlation (SC).
    Results: We included 4,163 patients (MGH = 3,876; MIMIC = 287); average age of 69 [SD 15] years; 53% male, and 72% white. 90% patients had ischemic stroke and 10% hemorrhagic stroke. The two-stage model achieved a RMSE [95% CI] of 3.13 [2.86-3.41] (SC = 0.90 [0.88-0. 91]) in the MGH hold-out test set and 2.01 [1.58-2.38] (SC = 0.96 [0.94-0.97]) in the MIMIC validation set.
    Conclusions: The automatic NLP-based model can enable large-scale stroke severity phenotyping from EHR and therefore support real-world quality improvement and comparative effectiveness studies in stroke.
    Language English
    Publishing date 2024-03-11
    Publishing country United States
    Document type Preprint
    DOI 10.1101/2024.03.08.24304011
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  3. Article ; Online: Identifying inpatient hospitalizations with continuous electroencephalogram monitoring from administrative data.

    Fernandes, Marta / Westover, M Brandon / Zafar, Sahar F

    BMC health services research

    2023  Volume 23, Issue 1, Page(s) 1234

    Abstract: Background: Continuous electroencephalography (cEEG) is increasingly utilized in hospitalized patients to detect and treat seizures. Epidemiologic and observational studies using administrative datasets can provide insights into the comparative and cost ...

    Abstract Background: Continuous electroencephalography (cEEG) is increasingly utilized in hospitalized patients to detect and treat seizures. Epidemiologic and observational studies using administrative datasets can provide insights into the comparative and cost effectiveness of cEEG utilization. Defining patient cohorts that underwent acute inpatient cEEG from administrative datasets is limited by the lack of validated codes differentiating elective epilepsy monitoring unit (EMU) admissions from acute inpatient hospitalization with cEEG utilization. Our aim was to develop hospital administrative data-based models to identify acute inpatient admissions with cEEG monitoring and distinguish them from EMU admissions.
    Methods: This was a single center retrospective cohort study of adult (≥ 18 years old) inpatient admissions with a cEEG procedure (EMU or acute inpatient) between January 2016-April 2022. The gold standard for acute inpatient cEEG vs. EMU was obtained from the local EEG recording platform. An extreme gradient boosting model was trained to classify admissions as acute inpatient cEEG vs. EMU using administrative data including demographics, diagnostic and procedure codes, and medications.
    Results: There were 9,523 patients in our cohort with 10,783 hospital admissions (8.5% EMU, 91.5% acute inpatient cEEG); with average age of 59 (SD 18.2) years; 46.2% were female. The model achieved an area under the receiver operating curve of 0.92 (95% CI [0.91-0.94]) and area under the precision-recall curve of 0.99 [0.98-0.99] for classification of acute inpatient cEEG.
    Conclusions: Our model has the potential to identify cEEG monitoring admissions in larger cohorts and can serve as a tool to enable large-scale, administrative data-based studies of EEG utilization.
    MeSH term(s) Adult ; Humans ; Female ; Middle Aged ; Adolescent ; Male ; Retrospective Studies ; Inpatients ; Seizures/diagnosis ; Hospitalization ; Monitoring, Physiologic/methods ; Electroencephalography/methods
    Language English
    Publishing date 2023-11-10
    Publishing country England
    Document type Journal Article
    ZDB-ID 2050434-2
    ISSN 1472-6963 ; 1472-6963
    ISSN (online) 1472-6963
    ISSN 1472-6963
    DOI 10.1186/s12913-023-10262-8
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  4. Article: Identifying inpatient hospitalizations with continuous electroencephalogram monitoring from administrative data.

    Fernandes, Marta / Westover, M Brandon / Zafar, Sahar F

    Research square

    2023  

    Abstract: Background: Continuous electroencephalography (cEEG) is increasingly utilized in hospitalized patients to detect and treat seizures. Epidemiologic and observational studies using administrative datasets can provide insights into the comparative and cost ...

    Abstract Background: Continuous electroencephalography (cEEG) is increasingly utilized in hospitalized patients to detect and treat seizures. Epidemiologic and observational studies using administrative datasets can provide insights into the comparative and cost effectiveness of cEEG utilization. Defining patient cohorts that underwent acute inpatient cEEG from administrative datasets is limited by the lack of validated codes differentiating elective epilepsy monitoring unit (EMU) admissions from acute inpatient hospitalization with cEEG utilization. Our aim was to develop hospital administrative data-based models to identify acute inpatient admissions with cEEG monitoring and distinguish them from EMU admissions.
    Methods: This was a single center retrospective cohort study of adult (≥ 18 years old) inpatient admissions with a cEEG procedure (EMU or acute inpatient) between January 2016-April 2022. The gold standard for acute inpatient cEEG vs. EMU was obtained from the local EEG recording platform. An extreme gradient boosting model was trained to classify admissions as acute inpatient cEEG vs. EMU using administrative data including demographics, diagnostic and procedure codes, and medications.
    Results: There were 9,523 patients in our cohort with 10,783 hospital admissions (8.5% EMU, 91.5% acute inpatient cEEG); with average age of 59 (SD 18.2) years; 46.2% were female. The model achieved an area under the receiver operating curve of 0.92 (95% CI [0.91-0.94]) and area under the precision-recall curve of 0.99 [0.98-0.99] for classification of acute inpatient cEEG.
    Conclusions: Our model has the potential to identify cEEG monitoring admissions in larger cohorts and can serve as a tool to enable large-scale, administrative data-based studies of EEG utilization.
    Language English
    Publishing date 2023-05-08
    Publishing country United States
    Document type Preprint
    DOI 10.21203/rs.3.rs-2882806/v1
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  5. Article ; Online: Predictors of follow-up care for critically-ill patients with seizures and epileptiform abnormalities on EEG monitoring.

    Rice, Hunter J / Fernandes, Marta Bento / Punia, Vineet / Rubinos, Clio / Sivaraju, Adithya / Zafar, Sahar F

    Clinical neurology and neurosurgery

    2024  Volume 241, Page(s) 108275

    Abstract: Objective: Post-hospitalization follow-up visits are crucial for preventing long-term complications. Patients with electrographic epileptiform abnormalities (EA) including seizures and periodic and rhythmic patterns are especially in need of follow-up ... ...

    Abstract Objective: Post-hospitalization follow-up visits are crucial for preventing long-term complications. Patients with electrographic epileptiform abnormalities (EA) including seizures and periodic and rhythmic patterns are especially in need of follow-up for long-term seizure risk stratification and medication management. We sought to identify predictors of follow-up.
    Methods: This is a retrospective cohort study of all patients (age ≥ 18 years) admitted to intensive care units that underwent continuous EEG (cEEG) monitoring at a single center between 01/2016-12/2019. Patients with EAs were included. Clinical and demographic variables were recorded. Follow-up status was determined using visit records 6-month post discharge, and visits were stratified as outpatient follow-up, neurology follow-up, and inpatient readmission. Lasso feature selection analysis was performed.
    Results: 723 patients (53 % female, mean (std) age of 62.3 (16.4) years) were identified from cEEG records with 575 (79 %) surviving to discharge. Of those discharged, 450 (78 %) had outpatient follow-up, 316 (55 %) had a neurology follow-up, and 288 (50 %) were readmitted during the 6-month period. Discharge on antiseizure medications (ASM), younger age, admission to neurosurgery, and proximity to the hospital were predictors of neurology follow-up visits. Discharge on ASMs, along with longer length of stay, younger age, emergency admissions, and higher illness severity were predictors of readmission.
    Significance: ASMs at discharge, demographics (age, address), hospital care teams, and illness severity determine probability of follow-up. Parameters identified in this study may help healthcare systems develop interventions to improve care transitions for critically-ill patients with seizures and other EA.
    Language English
    Publishing date 2024-04-06
    Publishing country Netherlands
    Document type Journal Article
    ZDB-ID 193107-6
    ISSN 1872-6968 ; 0303-8467
    ISSN (online) 1872-6968
    ISSN 0303-8467
    DOI 10.1016/j.clineuro.2024.108275
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  6. Article: Implications of stimulus-induced, rhythmic, periodic, or ictal discharges (SIRPIDs) in hospitalized patients.

    Martinez, Paola / Sheikh, Irfan / Westover, M Brandon / Zafar, Sahar F

    Frontiers in neurology

    2023  Volume 13, Page(s) 1062330

    Abstract: Background: Stimulus-induced electroencephalographic (EEG) patterns are commonly seen in acutely ill patients undergoing continuous EEG monitoring. Despite ongoing investigations, the pathophysiology, therapeutic and prognostic significance of stimulus- ... ...

    Abstract Background: Stimulus-induced electroencephalographic (EEG) patterns are commonly seen in acutely ill patients undergoing continuous EEG monitoring. Despite ongoing investigations, the pathophysiology, therapeutic and prognostic significance of stimulus-induced rhythmic, periodic or ictal discharges (SIRPIDs) and how it applies to specific pathologies remain unclear. We aimed to investigate the clinical implications of SIRPIDs in hospitalized patients.
    Methods: This is a retrospective single-center study of hospitalized patients from May 2016 to August 2017. We included patients above the age of 18 years who underwent >16 h of EEG monitoring during a single admission. We excluded patients with cardiac arrest and anoxic brain injury. Demographic data were obtained as well as admission GCS, and discharge modified Rankin Score (mRS). EEGs were reviewed for background activity in addition to epileptiform, periodic, and rhythmic patterns. The presence or absence of SIRPIDs was recorded. Our outcome was discharge mRS defined as good outcome, mRS 0-4, and poor outcome mRS, 5-6.
    Results: A total of 351 patients were included in the final analysis. The median age was 63 years and 175 (50%) were women. SIRPIDs were identified in 82 patients (23.4%). Patients with SIRPIDs had a median initial GCS of 12 (IQR, 6-15) and a length of stay of 12 days (IQR, 6-15). They were more likely to have absent posterior dominant rhythm, decreased reactivity, and more likely to have spontaneous periodic and rhythmic patterns and higher frequency of burst suppression. After adjusting for baseline clinical variables, underlying disease type and severity, and EEG background features, the presence of SIRPIDs was also associated with poor outcomes classified as MRS 5 or 6 (OR 4.75 [2.74-8.24]
    Conclusion: In our cohort of hospitalized patients excluding anoxic brain injury, SIRPIDs were identified in 23.4% and were seen most commonly in patients with primary systemic illness. We found SIRPIDs were independently associated with poor neurologic outcomes. Several studies are indicated to validate these findings and determine the risks vs. benefits of anti-seizure treatment.
    Language English
    Publishing date 2023-01-23
    Publishing country Switzerland
    Document type Journal Article
    ZDB-ID 2564214-5
    ISSN 1664-2295
    ISSN 1664-2295
    DOI 10.3389/fneur.2022.1062330
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  7. Article ; Online: Immediate and long-term management practices of acute symptomatic seizures and epileptiform abnormalities: A cross-sectional international survey.

    Punia, Vineet / Daruvala, Sanaya / Dhakar, Monica B / Zafar, Sahar F / Rubinos, Clio / Ayub, Neishay / Hirsch, Lawrence J / Sivaraju, Adithya

    Epilepsia

    2024  Volume 65, Issue 4, Page(s) 909–919

    Abstract: Objectives: Acute symptomatic seizures (ASyS) and epileptiform abnormalities (EAs) on electroencephalography (EEG) are commonly encountered following acute brain injury. Their immediate and long-term management remains poorly investigated. We conducted ... ...

    Abstract Objectives: Acute symptomatic seizures (ASyS) and epileptiform abnormalities (EAs) on electroencephalography (EEG) are commonly encountered following acute brain injury. Their immediate and long-term management remains poorly investigated. We conducted an international survey to understand their current management.
    Methods: The cross-sectional web-based survey of 21 fixed-response questions was based on a common clinical encounter: convulsive or suspected ASyS following an acute brain injury. Respondents selected the option that best matched their real-world practice. Respondents completing the survey were compared with those who accessed but did not complete it.
    Results: A total of 783 individuals (44 countries) accessed the survey; 502 completed it. Almost everyone used anti-seizure medications (ASMs) for secondary prophylaxis after convulsive or electrographic ASyS (95.4% and 97.2%, respectively). ASM dose escalation after convulsive ASyS depends on continuous EEG (cEEG) findings: most often increased after electrographic seizures (78% of respondents), followed by lateralized periodic discharges (LPDs; 41%) and sporadic epileptiform discharges (sEDs; 17.5%). If cEEG is unrevealing, one in five respondents discontinue ASMs after a week. In the absence of convulsive and electrographic ASyS, a large proportion of respondents start ASMs due to LPD (66.7%) and sED (44%) on cEEG. At hospital discharge, most respondents (85%) continue ASM without dose change. The recommended duration of outpatient ASM use is as follows: 1-3 months (36%), 3-6 months (30%), 6-12 months (13%), >12 months (11%). Nearly one-third of respondents utilized ancillary testing before outpatient ASM taper, most commonly (79%) a <2 h EEG. Approximately half of respondents had driving restrictions recommended for 6 months after discharge.
    Significance: ASM use for secondary prophylaxis after convulsive and electrographic ASyS is a universal practice and is continued upon discharge. Outpatient care, particularly the ASM duration, varies significantly. Wide practice heterogeneity in managing acute EAs reflects uncertainty about their significance and management. These results highlight the need for a structured outpatient follow-up and optimized care pathway for patients with ASyS.
    MeSH term(s) Humans ; Cross-Sectional Studies ; Seizures/diagnosis ; Seizures/therapy ; Status Epilepticus ; Electroencephalography ; Brain Injuries ; Retrospective Studies
    Language English
    Publishing date 2024-02-15
    Publishing country United States
    Document type Journal Article
    ZDB-ID 216382-2
    ISSN 1528-1167 ; 0013-9580
    ISSN (online) 1528-1167
    ISSN 0013-9580
    DOI 10.1111/epi.17915
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  8. Article ; Online: Teaching NeuroImage: Sturge-Weber Syndrome in an Adult.

    Nascimento, Fábio A / McLaren, John R / Westover, M Brandon / Zafar, Sahar F / Stufflebeam, Steven M

    Neurology

    2022  Volume 98, Issue 19, Page(s) 814–815

    MeSH term(s) Adult ; Humans ; Sturge-Weber Syndrome/complications ; Sturge-Weber Syndrome/diagnostic imaging
    Language English
    Publishing date 2022-04-11
    Publishing country United States
    Document type Journal Article
    ZDB-ID 207147-2
    ISSN 1526-632X ; 0028-3878
    ISSN (online) 1526-632X
    ISSN 0028-3878
    DOI 10.1212/WNL.0000000000200512
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  9. Article ; Online: Association of Epileptiform Activity With Outcomes in Toxic-Metabolic Encephalopathy.

    Chen, Patrick M / Stekhoven, Sophie Schuurmans / Haider, Adnan / Jing, Jin / Ge, Wendong / Rosenthal, Eric S / Westover, M Brandon / Zafar, Sahar F

    Critical care explorations

    2023  Volume 5, Issue 5, Page(s) e0913

    Abstract: The clinical significance of epileptiform abnormalities (EAs) specific to toxic-metabolic encephalopathy (TME) is unknown.: Objectives: To quantify EA burden in patients with TME and its association with neurologic outcomes.: Design setting and ... ...

    Abstract The clinical significance of epileptiform abnormalities (EAs) specific to toxic-metabolic encephalopathy (TME) is unknown.
    Objectives: To quantify EA burden in patients with TME and its association with neurologic outcomes.
    Design setting and participant: This is a retrospective study. A cohort of patients with TME and EA (positive) were age, Sequential Organ Failure Assessment Score, Acute Physiology and Chronic Health Evaluation II (APACHE-II) score matched to a cohort of TME patients without EA (control). Univariate analysis compared EA-positive patients against controls. Multivariable logistical regression adjusting for underlying disease etiology was performed to examine the relationship between EA burden and probability of poor neurologic outcome (modified Rankin Score [mRS] 4-6) at discharge. Consecutive admissions to inpatient floors or ICUs that underwent continuous electroencephalography (cEEG) monitoring at a single center between 2012 and 2019. Inclusion criteria were 1) patients with TME diagnosis, 2) age greater than 18 years, and 3) greater than or equal to 16 hours of cEEG. Patients with acute brain injury and cardiac arrest were excluded.
    Main outcomes and measures: Poor neurologic outcome defined by mRS (mRS 4-6).
    Results: One hundred sixteen patients were included, 58 with EA and 58 controls without EA, where matching was performed on age and APACHE-II score. The median age was 66 (Q1-Q3, 57-75) and median APACHE II score was 18 (Q1-Q3, 13-22). Overall cohort discharge mortality was 22% and 70% had a poor neurologic outcome. Peak EA burden was defined as the 12-hour window of recording with the highest prevalence of EAs. In multivariable analysis adjusted for Charlson Comorbidity Index and primary diagnosis, presence of EAs was associated with poor outcome (odds ratio 3.89; CI [1.05-14.2],
    Conclusions and relevance: Increasing burden of EA is associated with worse discharge outcomes in patients with TME. Future studies are needed to determine whether short-term treatment with anti-seizure medications while medically treating the underlying metabolic derangement improves outcomes.
    Language English
    Publishing date 2023-05-05
    Publishing country United States
    Document type Journal Article
    ISSN 2639-8028
    ISSN (online) 2639-8028
    DOI 10.1097/CCE.0000000000000913
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  10. Article: Association of Early Seizure Prophylaxis With Posttraumatic Seizures and Mortality: A Meta-analysis With Evidence Quality Assessment.

    Coelho, Lilian Maria Godeiro / Blacker, Deborah / Hsu, John / Newhouse, Joseph P / Westover, M Brandon / Zafar, Sahar F / Moura, Lidia M V R

    Neurology. Clinical practice

    2023  Volume 13, Issue 3, Page(s) e200145

    Abstract: Purpose of the review: To evaluate the quality of evidence about the association of primary seizure prophylaxis with antiseizure medication (ASM) within 7 days postinjury and the 18- or 24-month epilepsy/late seizure risk or all-cause mortality in ... ...

    Abstract Purpose of the review: To evaluate the quality of evidence about the association of primary seizure prophylaxis with antiseizure medication (ASM) within 7 days postinjury and the 18- or 24-month epilepsy/late seizure risk or all-cause mortality in adults with new-onset traumatic brain injury (TBI), in addition to early seizure risk.
    Results: Twenty-three studies met the inclusion criteria (7 randomized and 16 nonrandomized studies). We analyzed 9,202 patients, including 4,390 in the exposed group and 4,812 in the unexposed group (894 in placebo and 3,918 in no ASM groups). There was a moderate to serious bias risk based on our assessment. Within the limitations of existing studies, our data revealed a lower risk for early seizures in the ASM prophylaxis group compared with placebo or no ASM prophylaxis (risk ratio [RR] 0.43, 95% confidence interval [CI] 0.33-0.57,
    Summary: Our data suggest that the evidence showing no association between early ASM use and 18- or 24-month epilepsy risk in adults with new-onset TBI was of low quality. The analysis indicated a moderate quality for the evidence showing no effect on all-cause mortality. Therefore, higher-quality evidence is needed as a supplement for stronger recommendations.
    Language English
    Publishing date 2023-03-30
    Publishing country United States
    Document type Journal Article ; Review
    ZDB-ID 2645818-4
    ISSN 2163-0933 ; 2163-0402
    ISSN (online) 2163-0933
    ISSN 2163-0402
    DOI 10.1212/CPJ.0000000000200145
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