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Beekman R, Gilmore EJ. Cerebral edema following cardiac arrest: Are all shades of gray equal? Resuscitation 2024:110213. [PMID: 38636600 DOI: 10.1016/j.resuscitation.2024.110213] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/02/2024] [Accepted: 04/05/2024] [Indexed: 04/20/2024]
Affiliation(s)
- Rachel Beekman
- Department of Neurology, Yale School of Medicine, New Haven, CT, United States.
| | - Emily J Gilmore
- Department of Neurology, Yale School of Medicine, New Haven, CT, United States
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Monti MM, Beekman R, Spivak NM, Thibaut A, Schnakers C, Whyte J, Molteni E. Common Data Element for Disorders of Consciousness: Recommendations from the Working Group on Therapeutic Interventions. Neurocrit Care 2024; 40:51-57. [PMID: 38030874 DOI: 10.1007/s12028-023-01873-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/28/2023] [Accepted: 09/29/2023] [Indexed: 12/01/2023]
Abstract
BACKGROUND Over the past 30 years, there have been significant advances in the understanding of the mechanisms associated with loss and recovery of consciousness following severe brain injury. This work has provided a strong grounding for the development of novel restorative therapeutic interventions. Although all interventions are aimed at modulating and thereby restoring brain function, the landscape of existing interventions encompasses a very wide scope of techniques and protocols. Despite vigorous research efforts, few approaches have been assessed with rigorous, high-quality randomized controlled trials. As a growing number of exploratory interventions emerge, it is paramount to develop standardized approaches to reporting results. The successful evaluation of novel interventions depends on implementation of shared nomenclature and infrastructure. To address this gap, the Neurocritical Care Society's Curing Coma Campaign convened nine working groups and charged them with developing common data elements (CDEs). Here, we report the work of the Therapeutic Interventions Working Group. METHODS The working group reviewed existing CDEs relevant to therapeutic interventions within the National Institutes of Health National Institute of Neurological Disorders and Stroke database and reviewed the literature for assessing key areas of research in the intervention space. CDEs were then proposed, iteratively discussed and reviewed, classified, and organized in a case report form (CRF). RESULTS We developed a unified CRF, including CDEs and key design elements (i.e., methodological or protocol parameters), divided into five sections: (1) patient information, (2) general study information, (3) behavioral interventions, (4) pharmacological interventions, and (5) device interventions. CONCLUSIONS The newly created CRF enhances systematization of future work by proposing a portfolio of measures that should be collected in the development and implementation of studies assessing novel interventions intended to increase the level of consciousness or rate of recovery of consciousness in patients with disorders of consciousness.
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Affiliation(s)
- Martin M Monti
- Department of Psychology, University of California Los Angeles, 6522 Pritzker Hall, Los Angeles, CA, USA.
| | - Rachel Beekman
- Department of Neurology, Yale University School of Medicine, New Haven, CT, USA
| | - Norman M Spivak
- David Geffen School of Medicine, University of California, Los Angeles, CA, USA
| | - Aurore Thibaut
- Coma Science Group, GIGA-Consciousness, University of Liège, Liège, Belgium
| | | | - John Whyte
- Moss Rehabilitation Research Institute, Elkins Park, PA, USA
| | - Erika Molteni
- School of Biomedical Engineering and Imaging Sciences, Faculty of Life Sciences and Medicine, School of Life Course Sciences, King's College London, London, UK
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Prasad A, Gilmore EJ, Kim JA, Begunova L, Olexa M, Beekman R, Falcone GJ, Matouk C, Ortega-Gutierrez S, Temkin NR, Barber J, Diaz-Arrastia R, de Havenon A, Petersen NH. Impact of Therapeutic Interventions on Cerebral Autoregulatory Function Following Severe Traumatic Brain Injury: A Secondary Analysis of the BOOST-II Study. Neurocrit Care 2023:10.1007/s12028-023-01896-x. [PMID: 38158481 DOI: 10.1007/s12028-023-01896-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/01/2023] [Accepted: 11/17/2023] [Indexed: 01/03/2024]
Abstract
BACKGROUND The Brain Oxygen Optimization in Severe Traumatic Brain Injury Phase II randomized controlled trial used a tier-based management protocol based on brain tissue oxygen (PbtO2) and intracranial pressure (ICP) monitoring to reduce brain tissue hypoxia after severe traumatic brain injury. We performed a secondary analysis to explore the relationship between brain tissue hypoxia, blood pressure (BP), and interventions to improve cerebral perfusion pressure (CPP). We hypothesized that BP management below the lower limit of autoregulation would lead to cerebral hypoperfusion and brain tissue hypoxia that could be improved with hemodynamic augmentation. METHODS Of the 119 patients enrolled in the Brain Oxygen Optimization in Severe Traumatic Brain Injury Phase II trial, 55 patients had simultaneous recordings of arterial BP, ICP, and PbtO2. Autoregulatory function was measured by interrogating changes in ICP and PbtO2 in response to fluctuations in CPP using time-correlation analysis. The resulting autoregulatory indices (pressure reactivity index and oxygen reactivity index) were used to identify the "optimal" CPP and limits of autoregulation for each patient. Autoregulatory function and percent time with CPP outside personalized limits of autoregulation were calculated before, during, and after all interventions directed to optimize CPP. RESULTS Individualized limits of autoregulation were computed in 55 patients (mean age 38 years, mean monitoring time 92 h). We identified 35 episodes of brain tissue hypoxia (PbtO2 < 20 mm Hg) treated with CPP augmentation. Following each intervention, mean CPP increased from 73 ± 14 mm Hg to 79 ± 17 mm Hg (p = 0.15), and mean PbtO2 improved from 18.4 ± 5.6 mm Hg to 21.9 ± 5.6 mm Hg (p = 0.01), whereas autoregulatory function trended toward improvement (oxygen reactivity index 0.42 vs. 0.37, p = 0.14; pressure reactivity index 0.25 vs. 0.21, p = 0.2). Although optimal CPP and limits remained relatively unchanged, there was a significant decrease in the percent time with CPP below the lower limit of autoregulation in the 60 min after compared with before an intervention (11% vs. 23%, p = 0.05). CONCLUSIONS Our analysis suggests that brain tissue hypoxia is associated with cerebral hypoperfusion characterized by increased time with CPP below the lower limit of autoregulation. Interventions to increase CPP appear to improve autoregulation. Further studies are needed to validate the importance of autoregulation as a modifiable variable with the potential to improve outcomes.
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Affiliation(s)
- Ayush Prasad
- Division of Neurocritical Care and Emergency, Department of Neurology, Yale University School of Medicine, 15 York St, LCI 1003, New Haven, CT, CT 06510, USA
| | - Emily J Gilmore
- Division of Neurocritical Care and Emergency, Department of Neurology, Yale University School of Medicine, 15 York St, LCI 1003, New Haven, CT, CT 06510, USA
| | - Jennifer A Kim
- Division of Neurocritical Care and Emergency, Department of Neurology, Yale University School of Medicine, 15 York St, LCI 1003, New Haven, CT, CT 06510, USA
| | - Liza Begunova
- Division of Neurocritical Care and Emergency, Department of Neurology, Yale University School of Medicine, 15 York St, LCI 1003, New Haven, CT, CT 06510, USA
| | - Madelynne Olexa
- Division of Neurocritical Care and Emergency, Department of Neurology, Yale University School of Medicine, 15 York St, LCI 1003, New Haven, CT, CT 06510, USA
| | - Rachel Beekman
- Division of Neurocritical Care and Emergency, Department of Neurology, Yale University School of Medicine, 15 York St, LCI 1003, New Haven, CT, CT 06510, USA
| | - Guido J Falcone
- Division of Neurocritical Care and Emergency, Department of Neurology, Yale University School of Medicine, 15 York St, LCI 1003, New Haven, CT, CT 06510, USA
| | - Charles Matouk
- Department of Neurosurgery, Yale University School of Medicine, New Haven, CT, USA
| | | | - Nancy R Temkin
- Department of Neurological Surgery, University of Washington, Seattle, WA, USA
- Department of Biostatistics, University of Washington, Seattle, WA, USA
| | - Jason Barber
- Department of Biostatistics, University of Washington, Seattle, WA, USA
| | - Ramon Diaz-Arrastia
- Department of Neurology, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Adam de Havenon
- Division of Neurocritical Care and Emergency, Department of Neurology, Yale University School of Medicine, 15 York St, LCI 1003, New Haven, CT, CT 06510, USA
| | - Nils H Petersen
- Division of Neurocritical Care and Emergency, Department of Neurology, Yale University School of Medicine, 15 York St, LCI 1003, New Haven, CT, CT 06510, USA.
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Mazurek MH, Parasuram NR, Peng TJ, Beekman R, Yadlapalli V, Sorby-Adams AJ, Lalwani D, Zabinska J, Gilmore EJ, Petersen NH, Falcone GJ, Sujijantarat N, Matouk C, Payabvash S, Sze G, Schiff SJ, Iglesias JE, Rosen MS, de Havenon A, Kimberly WT, Sheth KN. Detection of Intracerebral Hemorrhage Using Low-Field, Portable Magnetic Resonance Imaging in Patients With Stroke. Stroke 2023; 54:2832-2841. [PMID: 37795593 DOI: 10.1161/strokeaha.123.043146] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/20/2023] [Accepted: 09/13/2023] [Indexed: 10/06/2023]
Abstract
BACKGROUND Neuroimaging is essential for detecting spontaneous, nontraumatic intracerebral hemorrhage (ICH). Recent data suggest ICH can be characterized using low-field magnetic resonance imaging (MRI). Our primary objective was to investigate the sensitivity and specificity of ICH on a 0.064T portable MRI (pMRI) scanner using a methodology that provided clinical information to inform rater interpretations. As a secondary aim, we investigated whether the incorporation of a deep learning (DL) reconstruction algorithm affected ICH detection. METHODS The pMRI device was deployed at Yale New Haven Hospital to examine patients presenting with stroke symptoms from October 26, 2020 to February 21, 2022. Three raters independently evaluated pMRI examinations. Raters were provided the images alongside the patient's clinical information to simulate real-world context of use. Ground truth was the closest conventional computed tomography or 1.5/3T MRI. Sensitivity and specificity results were grouped by DL and non-DL software to investigate the effects of software advances. RESULTS A total of 189 exams (38 ICH, 89 acute ischemic stroke, 8 subarachnoid hemorrhage, 3 primary intraventricular hemorrhage, 51 no intracranial abnormality) were evaluated. Exams were correctly classified as positive or negative for ICH in 185 of 189 cases (97.9% overall accuracy). ICH was correctly detected in 35 of 38 cases (92.1% sensitivity). Ischemic stroke and no intracranial abnormality cases were correctly identified as blood-negative in 139 of 140 cases (99.3% specificity). Non-DL scans had a sensitivity and specificity for ICH of 77.8% and 97.1%, respectively. DL scans had a sensitivity and specificity for ICH of 96.6% and 99.3%, respectively. CONCLUSIONS These results demonstrate improvements in ICH detection accuracy on pMRI that may be attributed to the integration of clinical information in rater review and the incorporation of a DL-based algorithm. The use of pMRI holds promise in providing diagnostic neuroimaging for patients with ICH.
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Affiliation(s)
- Mercy H Mazurek
- Department of Neurology (M.H.M., N.R.P., T.J.P., R.B., V.Y., D.L., J.Z., E.J.G., N.H.P., G.J.F., A.d.H., K.N.S.), Yale School of Medicine, New Haven, CT
| | - Nethra R Parasuram
- Department of Neurology (M.H.M., N.R.P., T.J.P., R.B., V.Y., D.L., J.Z., E.J.G., N.H.P., G.J.F., A.d.H., K.N.S.), Yale School of Medicine, New Haven, CT
| | - Teng J Peng
- Department of Neurology (M.H.M., N.R.P., T.J.P., R.B., V.Y., D.L., J.Z., E.J.G., N.H.P., G.J.F., A.d.H., K.N.S.), Yale School of Medicine, New Haven, CT
| | - Rachel Beekman
- Department of Neurology (M.H.M., N.R.P., T.J.P., R.B., V.Y., D.L., J.Z., E.J.G., N.H.P., G.J.F., A.d.H., K.N.S.), Yale School of Medicine, New Haven, CT
| | - Vineetha Yadlapalli
- Department of Neurology (M.H.M., N.R.P., T.J.P., R.B., V.Y., D.L., J.Z., E.J.G., N.H.P., G.J.F., A.d.H., K.N.S.), Yale School of Medicine, New Haven, CT
| | - Annabel J Sorby-Adams
- Division of Neurocritical Care, Department of Neurology, Massachusetts General Hospital, Boston (A.J.S.-A., W.T.K.)
| | - Dheeraj Lalwani
- Department of Neurology (M.H.M., N.R.P., T.J.P., R.B., V.Y., D.L., J.Z., E.J.G., N.H.P., G.J.F., A.d.H., K.N.S.), Yale School of Medicine, New Haven, CT
| | - Julia Zabinska
- Department of Neurology (M.H.M., N.R.P., T.J.P., R.B., V.Y., D.L., J.Z., E.J.G., N.H.P., G.J.F., A.d.H., K.N.S.), Yale School of Medicine, New Haven, CT
| | - Emily J Gilmore
- Department of Neurology (M.H.M., N.R.P., T.J.P., R.B., V.Y., D.L., J.Z., E.J.G., N.H.P., G.J.F., A.d.H., K.N.S.), Yale School of Medicine, New Haven, CT
| | - Nils H Petersen
- Department of Neurology (M.H.M., N.R.P., T.J.P., R.B., V.Y., D.L., J.Z., E.J.G., N.H.P., G.J.F., A.d.H., K.N.S.), Yale School of Medicine, New Haven, CT
| | - Guido J Falcone
- Department of Neurology (M.H.M., N.R.P., T.J.P., R.B., V.Y., D.L., J.Z., E.J.G., N.H.P., G.J.F., A.d.H., K.N.S.), Yale School of Medicine, New Haven, CT
| | - Nanthiya Sujijantarat
- Department of Neurosurgery (N.S., C.M., S.J.S.), Yale School of Medicine, New Haven, CT
| | - Charles Matouk
- Department of Neurosurgery (N.S., C.M., S.J.S.), Yale School of Medicine, New Haven, CT
| | - Sam Payabvash
- Department of Radiology, Yale University School of Medicine, New Haven, CT (S.P., G.S.)
| | - Gordon Sze
- Department of Radiology, Yale University School of Medicine, New Haven, CT (S.P., G.S.)
| | - Steven J Schiff
- Yale Center for Brain & Mind Health (S.J.S., K.N.S.), Yale School of Medicine, New Haven, CT
| | - Juan Eugenio Iglesias
- Centre for Medical Image Computing, University College London, United Kingdom (J.E.I.)
- Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, Cambridge (J.E.I.)
| | | | - Adam de Havenon
- Department of Neurology (M.H.M., N.R.P., T.J.P., R.B., V.Y., D.L., J.Z., E.J.G., N.H.P., G.J.F., A.d.H., K.N.S.), Yale School of Medicine, New Haven, CT
| | - W Taylor Kimberly
- Division of Neurocritical Care, Department of Neurology, Massachusetts General Hospital, Boston (A.J.S.-A., W.T.K.)
| | - Kevin N Sheth
- Department of Neurology (M.H.M., N.R.P., T.J.P., R.B., V.Y., D.L., J.Z., E.J.G., N.H.P., G.J.F., A.d.H., K.N.S.), Yale School of Medicine, New Haven, CT
- Yale Center for Brain & Mind Health (S.J.S., K.N.S.), Yale School of Medicine, New Haven, CT
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Kitlen E, Kim N, Rubenstein A, Keenan C, Garcia G, Khosla A, Johnson J, Miller PE, Wira C, Greer D, Gilmore EJ, Beekman R. Development and validation of a novel score to predict brain death after out-of-hospital cardiac arrest. Resuscitation 2023; 192:109955. [PMID: 37661012 DOI: 10.1016/j.resuscitation.2023.109955] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/18/2023] [Revised: 08/21/2023] [Accepted: 08/27/2023] [Indexed: 09/05/2023]
Abstract
BACKGROUND AND OBJECTIVES Brain death (BD) occurs in 9-24% of successfully resuscitated out-of-hospital cardiac arrests (OHCA). To predict BD after OHCA, we developed a novel brain death risk (BDR) score. METHODS We identified independent predictors of BD after OHCA in a retrospective, single academic center cohort between 2011 and 2021. The BDR score ranges from 0 to 7 points and includes: non-shockable rhythm (1 point), drug overdose as etiology of arrest (1 point), evidence of grey-white differentiation loss or sulcal effacement on head computed tomography (CT) radiology report within 24 hours of arrest (2 points), Full-Outline-Of-UnResponsiveness (FOUR) score of 0 (2 points), FOUR score 1-5 (1 point), and age <45 years (1 point). We internally validated the BDR score using k-fold cross validation (k = 8) and externally validated the score at an independent academic center. The main outcome was BD. RESULTS The development cohort included 362OHCA patients, of whom 18% (N = 58) experienced BD. Internal validation provided an area under the receiving operator characteristic curve (AUC) (95% CI) of 0.931 (0.905-0.957). In the validation cohort, 19.8% (N = 17) experienced BD. The AUC (95% CI) was 0.849 (0.765-0.933). In both cohorts, a BDR score >4 was the optimal cut off (sensitivity 0.903 and 0.882, specificity 0.830 and 0.652, in the development and validation cohorts respectively). DISCUSSION The BDR score identifies those at highest risk for BD after OHCA. Our data suggest that a BDR score >4 is the optimal cut off.
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Affiliation(s)
- Eva Kitlen
- Department of Neurology, Yale School of Medicine, New Haven, CT, United States
| | - Noah Kim
- Department of Neurology, Yale School of Medicine, New Haven, CT, United States
| | - Alexandra Rubenstein
- Department of Neurology, Boston University Medical Center, Boston, MA, United States
| | - Caitlyn Keenan
- Department of Neurology, Boston University Medical Center, Boston, MA, United States
| | - Gabriella Garcia
- Department of Neurology, University of Pennsylvania, PA, United States
| | - Akhil Khosla
- Department of Pulmonary Critical Care, Yale School of Medicine, New Haven, CT, United States
| | | | - P Elliott Miller
- Section of Cardiovascular Medicine, Department of Internal Medicine, Yale School of Medicine, New Haven, CT, United States
| | - Charles Wira
- Department of Emergency Medicine, Yale School of Medicine, New Haven, CT, United States
| | - David Greer
- Department of Neurology, Boston University Medical Center, Boston, MA, United States
| | - Emily J Gilmore
- Department of Neurology, Yale School of Medicine, New Haven, CT, United States
| | - Rachel Beekman
- Department of Neurology, Yale School of Medicine, New Haven, CT, United States.
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Beekman R, Khosla A, Buckley R, Honiden S, Gilmore EJ. Temperature Control in the Era of Personalized Medicine: Knowledge Gaps, Research Priorities, and Future Directions. J Intensive Care Med 2023:8850666231203596. [PMID: 37787185 DOI: 10.1177/08850666231203596] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/04/2023]
Abstract
Hypoxic-ischemic brain injury (HIBI) is the leading cause of death and disability after cardiac arrest. To date, temperature control is the only intervention shown to improve neurologic outcomes in patients with HIBI. Despite robust preclinical evidence supporting hypothermia as neuroprotective therapy after cardiac arrest, there remains clinical equipoise regarding optimal core temperature, therapeutic window, and duration of therapy. Current guidelines recommend continuous temperature monitoring and active fever prevention for at least 72 h and additionally note insufficient evidence regarding temperature control targeting 32 °C-36 °C. However, population-based thresholds may be inadequate to support the metabolic demands of ischemic, reperfused, and dysregulated tissue. Promoting a more personalized approach with individualized targets has the potential to further improve outcomes. This review will analyze current knowledge and evidence, address research priorities, explore the components of high-quality temperature control, and define critical future steps that are needed to advance patient-centered care for cardiac arrest survivors.
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Affiliation(s)
- Rachel Beekman
- Department of Neurology, Yale University School of Medicine, New Haven, CT, USA
| | - Akhil Khosla
- Department of Medicine, Yale University School of Medicine, New Haven, CT, USA
| | - Ryan Buckley
- Department of Medicine, Yale University School of Medicine, New Haven, CT, USA
| | - Shyoko Honiden
- Department of Medicine, Yale University School of Medicine, New Haven, CT, USA
| | - Emily J Gilmore
- Department of Neurology, Yale University School of Medicine, New Haven, CT, USA
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Kimberly WT, Sorby-Adams AJ, Webb AG, Wu EX, Beekman R, Bowry R, Schiff SJ, de Havenon A, Shen FX, Sze G, Schaefer P, Iglesias JE, Rosen MS, Sheth KN. Brain imaging with portable low-field MRI. Nat Rev Bioeng 2023; 1:617-630. [PMID: 37705717 PMCID: PMC10497072 DOI: 10.1038/s44222-023-00086-w] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Accepted: 06/06/2023] [Indexed: 09/15/2023]
Abstract
The advent of portable, low-field MRI (LF-MRI) heralds new opportunities in neuroimaging. Low power requirements and transportability have enabled scanning outside the controlled environment of a conventional MRI suite, enhancing access to neuroimaging for indications that are not well suited to existing technologies. Maximizing the information extracted from the reduced signal-to-noise ratio of LF-MRI is crucial to developing clinically useful diagnostic images. Progress in electromagnetic noise cancellation and machine learning reconstruction algorithms from sparse k-space data as well as new approaches to image enhancement have now enabled these advancements. Coupling technological innovation with bedside imaging creates new prospects in visualizing the healthy brain and detecting acute and chronic pathological changes. Ongoing development of hardware, improvements in pulse sequences and image reconstruction, and validation of clinical utility will continue to accelerate this field. As further innovation occurs, portable LF-MRI will facilitate the democratization of MRI and create new applications not previously feasible with conventional systems.
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Affiliation(s)
- W Taylor Kimberly
- Department of Neurology and the Center for Genomic Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | - Annabel J Sorby-Adams
- Department of Neurology and the Center for Genomic Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | - Andrew G Webb
- Department of Radiology, Leiden University Medical Center, Leiden, The Netherlands
| | - Ed X Wu
- Laboratory of Biomedical Imaging and Signal Processing, Department of Electrical and Electronic Engineering, The University of Hong Kong, Hong Kong SAR, China
| | - Rachel Beekman
- Division of Neurocritical Care and Emergency Neurology, Department of Neurology, Yale New Haven Hospital and Yale School of Medicine, Yale Center for Brain & Mind Health, New Haven, CT, USA
| | - Ritvij Bowry
- Departments of Neurosurgery and Neurology, McGovern Medical School, University of Texas Health Neurosciences, Houston, TX, USA
| | - Steven J Schiff
- Department of Neurosurgery, Yale School of Medicine, New Haven, CT, USA
| | - Adam de Havenon
- Division of Vascular Neurology, Department of Neurology, Yale New Haven Hospital and Yale School of Medicine, New Haven, CT, USA
| | - Francis X Shen
- Harvard Medical School Center for Bioethics, Harvard law School, Boston, MA, USA
- Department of Psychiatry, Massachusetts General Hospital, Boston, MA, USA
| | - Gordon Sze
- Department of Radiology, Yale New Haven Hospital and Yale School of Medicine, New Haven, CT, USA
| | - Pamela Schaefer
- Division of Neuroradiology, Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | - Juan Eugenio Iglesias
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
- Centre for Medical Image Computing, University College London, London, UK
- Computer Science and AI Laboratory, Massachusetts Institute of Technology, Boston, MA, USA
| | - Matthew S Rosen
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | - Kevin N Sheth
- Division of Neurocritical Care and Emergency Neurology, Department of Neurology, Yale New Haven Hospital and Yale School of Medicine, Yale Center for Brain & Mind Health, New Haven, CT, USA
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8
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Perman SM, Beekman R. Dissecting the Complex Association Between Age and Sex in Cardiac Arrest Outcomes-Age Disparity, Sex Disparity, or All of the Above? JAMA Netw Open 2023; 6:e2321751. [PMID: 37405778 DOI: 10.1001/jamanetworkopen.2023.21751] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 07/06/2023] Open
Affiliation(s)
- Sarah M Perman
- Department of Emergency Medicine, Yale School of Medicine, New Haven, Connecticut
| | - Rachel Beekman
- Department of Neurology, Yale School of Medicine, New Haven, Connecticut
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Parasuram NR, Crawford AL, Mazurek MH, Chavva IR, Beekman R, Gilmore EJ, Petersen NH, Payabvash S, Sze G, Eugenio Iglesias J, Omay SB, Matouk C, Longbrake EE, de Havenon A, Schiff SJ, Rosen MS, Kimberly WT, Sheth KN. Future of Neurology & Technology: Neuroimaging Made Accessible Using Low-Field, Portable MRI. Neurology 2023; 100:1067-1071. [PMID: 36720639 PMCID: PMC10259275 DOI: 10.1212/wnl.0000000000207074] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/02/2022] [Accepted: 01/04/2023] [Indexed: 02/02/2023] Open
Abstract
In the 20th century, the advent of neuroimaging dramatically altered the field of neurologic care. However, despite iterative advances since the invention of CT and MRI, little progress has been made to bring MR neuroimaging to the point of care. Recently, the emergence of a low-field (<1 T) portable MRI (pMRI) is setting the stage to revolutionize the landscape of accessible neuroimaging. Users can transport the pMRI into a variety of locations, using a standard 110-220 V wall outlet. In this article, we discuss current applications for pMRI, including in the acute and critical care settings, the barriers to broad implementation, and future opportunities.
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Affiliation(s)
- Nethra R Parasuram
- From the Department of Neurology (N.R.P., A.L.C., M.H.M., I.R.C., R.B., E.J.G., N.H.P., E.E.L., A.d.H., K.N.S.), and Department of Radiology (S.P., G.S.), Yale University School of Medicine, New Haven, CT; Computer Science and Artificial Intelligence Laboratory (CSAIL) (J.E.I.), Massachusetts Institute of Technology, Cambridge; Athinoula A. Martinos Center for Biomedical Imaging (J.E.I., M.S.R.), Massachusetts General Hospital, Charlestown; Department of Neurosurgery (S.B.O., C.M.), Yale University School of Medicine, New Haven, CT; Department of Neurosurgery (S.J.S.), Engineering Science and Mechanics, and Physics, The Pennsylvania State University, University Park; and Division of Neurocritical Care (W.T.K.), Department of Neurology, Massachusetts General Hospital, Boston
| | - Anna L Crawford
- From the Department of Neurology (N.R.P., A.L.C., M.H.M., I.R.C., R.B., E.J.G., N.H.P., E.E.L., A.d.H., K.N.S.), and Department of Radiology (S.P., G.S.), Yale University School of Medicine, New Haven, CT; Computer Science and Artificial Intelligence Laboratory (CSAIL) (J.E.I.), Massachusetts Institute of Technology, Cambridge; Athinoula A. Martinos Center for Biomedical Imaging (J.E.I., M.S.R.), Massachusetts General Hospital, Charlestown; Department of Neurosurgery (S.B.O., C.M.), Yale University School of Medicine, New Haven, CT; Department of Neurosurgery (S.J.S.), Engineering Science and Mechanics, and Physics, The Pennsylvania State University, University Park; and Division of Neurocritical Care (W.T.K.), Department of Neurology, Massachusetts General Hospital, Boston
| | - Mercy H Mazurek
- From the Department of Neurology (N.R.P., A.L.C., M.H.M., I.R.C., R.B., E.J.G., N.H.P., E.E.L., A.d.H., K.N.S.), and Department of Radiology (S.P., G.S.), Yale University School of Medicine, New Haven, CT; Computer Science and Artificial Intelligence Laboratory (CSAIL) (J.E.I.), Massachusetts Institute of Technology, Cambridge; Athinoula A. Martinos Center for Biomedical Imaging (J.E.I., M.S.R.), Massachusetts General Hospital, Charlestown; Department of Neurosurgery (S.B.O., C.M.), Yale University School of Medicine, New Haven, CT; Department of Neurosurgery (S.J.S.), Engineering Science and Mechanics, and Physics, The Pennsylvania State University, University Park; and Division of Neurocritical Care (W.T.K.), Department of Neurology, Massachusetts General Hospital, Boston
| | - Isha R Chavva
- From the Department of Neurology (N.R.P., A.L.C., M.H.M., I.R.C., R.B., E.J.G., N.H.P., E.E.L., A.d.H., K.N.S.), and Department of Radiology (S.P., G.S.), Yale University School of Medicine, New Haven, CT; Computer Science and Artificial Intelligence Laboratory (CSAIL) (J.E.I.), Massachusetts Institute of Technology, Cambridge; Athinoula A. Martinos Center for Biomedical Imaging (J.E.I., M.S.R.), Massachusetts General Hospital, Charlestown; Department of Neurosurgery (S.B.O., C.M.), Yale University School of Medicine, New Haven, CT; Department of Neurosurgery (S.J.S.), Engineering Science and Mechanics, and Physics, The Pennsylvania State University, University Park; and Division of Neurocritical Care (W.T.K.), Department of Neurology, Massachusetts General Hospital, Boston
| | - Rachel Beekman
- From the Department of Neurology (N.R.P., A.L.C., M.H.M., I.R.C., R.B., E.J.G., N.H.P., E.E.L., A.d.H., K.N.S.), and Department of Radiology (S.P., G.S.), Yale University School of Medicine, New Haven, CT; Computer Science and Artificial Intelligence Laboratory (CSAIL) (J.E.I.), Massachusetts Institute of Technology, Cambridge; Athinoula A. Martinos Center for Biomedical Imaging (J.E.I., M.S.R.), Massachusetts General Hospital, Charlestown; Department of Neurosurgery (S.B.O., C.M.), Yale University School of Medicine, New Haven, CT; Department of Neurosurgery (S.J.S.), Engineering Science and Mechanics, and Physics, The Pennsylvania State University, University Park; and Division of Neurocritical Care (W.T.K.), Department of Neurology, Massachusetts General Hospital, Boston
| | - Emily J Gilmore
- From the Department of Neurology (N.R.P., A.L.C., M.H.M., I.R.C., R.B., E.J.G., N.H.P., E.E.L., A.d.H., K.N.S.), and Department of Radiology (S.P., G.S.), Yale University School of Medicine, New Haven, CT; Computer Science and Artificial Intelligence Laboratory (CSAIL) (J.E.I.), Massachusetts Institute of Technology, Cambridge; Athinoula A. Martinos Center for Biomedical Imaging (J.E.I., M.S.R.), Massachusetts General Hospital, Charlestown; Department of Neurosurgery (S.B.O., C.M.), Yale University School of Medicine, New Haven, CT; Department of Neurosurgery (S.J.S.), Engineering Science and Mechanics, and Physics, The Pennsylvania State University, University Park; and Division of Neurocritical Care (W.T.K.), Department of Neurology, Massachusetts General Hospital, Boston
| | - Nils H Petersen
- From the Department of Neurology (N.R.P., A.L.C., M.H.M., I.R.C., R.B., E.J.G., N.H.P., E.E.L., A.d.H., K.N.S.), and Department of Radiology (S.P., G.S.), Yale University School of Medicine, New Haven, CT; Computer Science and Artificial Intelligence Laboratory (CSAIL) (J.E.I.), Massachusetts Institute of Technology, Cambridge; Athinoula A. Martinos Center for Biomedical Imaging (J.E.I., M.S.R.), Massachusetts General Hospital, Charlestown; Department of Neurosurgery (S.B.O., C.M.), Yale University School of Medicine, New Haven, CT; Department of Neurosurgery (S.J.S.), Engineering Science and Mechanics, and Physics, The Pennsylvania State University, University Park; and Division of Neurocritical Care (W.T.K.), Department of Neurology, Massachusetts General Hospital, Boston
| | - Seyedmehdi Payabvash
- From the Department of Neurology (N.R.P., A.L.C., M.H.M., I.R.C., R.B., E.J.G., N.H.P., E.E.L., A.d.H., K.N.S.), and Department of Radiology (S.P., G.S.), Yale University School of Medicine, New Haven, CT; Computer Science and Artificial Intelligence Laboratory (CSAIL) (J.E.I.), Massachusetts Institute of Technology, Cambridge; Athinoula A. Martinos Center for Biomedical Imaging (J.E.I., M.S.R.), Massachusetts General Hospital, Charlestown; Department of Neurosurgery (S.B.O., C.M.), Yale University School of Medicine, New Haven, CT; Department of Neurosurgery (S.J.S.), Engineering Science and Mechanics, and Physics, The Pennsylvania State University, University Park; and Division of Neurocritical Care (W.T.K.), Department of Neurology, Massachusetts General Hospital, Boston
| | - Gordon Sze
- From the Department of Neurology (N.R.P., A.L.C., M.H.M., I.R.C., R.B., E.J.G., N.H.P., E.E.L., A.d.H., K.N.S.), and Department of Radiology (S.P., G.S.), Yale University School of Medicine, New Haven, CT; Computer Science and Artificial Intelligence Laboratory (CSAIL) (J.E.I.), Massachusetts Institute of Technology, Cambridge; Athinoula A. Martinos Center for Biomedical Imaging (J.E.I., M.S.R.), Massachusetts General Hospital, Charlestown; Department of Neurosurgery (S.B.O., C.M.), Yale University School of Medicine, New Haven, CT; Department of Neurosurgery (S.J.S.), Engineering Science and Mechanics, and Physics, The Pennsylvania State University, University Park; and Division of Neurocritical Care (W.T.K.), Department of Neurology, Massachusetts General Hospital, Boston
| | - Juan Eugenio Iglesias
- From the Department of Neurology (N.R.P., A.L.C., M.H.M., I.R.C., R.B., E.J.G., N.H.P., E.E.L., A.d.H., K.N.S.), and Department of Radiology (S.P., G.S.), Yale University School of Medicine, New Haven, CT; Computer Science and Artificial Intelligence Laboratory (CSAIL) (J.E.I.), Massachusetts Institute of Technology, Cambridge; Athinoula A. Martinos Center for Biomedical Imaging (J.E.I., M.S.R.), Massachusetts General Hospital, Charlestown; Department of Neurosurgery (S.B.O., C.M.), Yale University School of Medicine, New Haven, CT; Department of Neurosurgery (S.J.S.), Engineering Science and Mechanics, and Physics, The Pennsylvania State University, University Park; and Division of Neurocritical Care (W.T.K.), Department of Neurology, Massachusetts General Hospital, Boston
| | - Sacit B Omay
- From the Department of Neurology (N.R.P., A.L.C., M.H.M., I.R.C., R.B., E.J.G., N.H.P., E.E.L., A.d.H., K.N.S.), and Department of Radiology (S.P., G.S.), Yale University School of Medicine, New Haven, CT; Computer Science and Artificial Intelligence Laboratory (CSAIL) (J.E.I.), Massachusetts Institute of Technology, Cambridge; Athinoula A. Martinos Center for Biomedical Imaging (J.E.I., M.S.R.), Massachusetts General Hospital, Charlestown; Department of Neurosurgery (S.B.O., C.M.), Yale University School of Medicine, New Haven, CT; Department of Neurosurgery (S.J.S.), Engineering Science and Mechanics, and Physics, The Pennsylvania State University, University Park; and Division of Neurocritical Care (W.T.K.), Department of Neurology, Massachusetts General Hospital, Boston
| | - Charles Matouk
- From the Department of Neurology (N.R.P., A.L.C., M.H.M., I.R.C., R.B., E.J.G., N.H.P., E.E.L., A.d.H., K.N.S.), and Department of Radiology (S.P., G.S.), Yale University School of Medicine, New Haven, CT; Computer Science and Artificial Intelligence Laboratory (CSAIL) (J.E.I.), Massachusetts Institute of Technology, Cambridge; Athinoula A. Martinos Center for Biomedical Imaging (J.E.I., M.S.R.), Massachusetts General Hospital, Charlestown; Department of Neurosurgery (S.B.O., C.M.), Yale University School of Medicine, New Haven, CT; Department of Neurosurgery (S.J.S.), Engineering Science and Mechanics, and Physics, The Pennsylvania State University, University Park; and Division of Neurocritical Care (W.T.K.), Department of Neurology, Massachusetts General Hospital, Boston
| | - Erin E Longbrake
- From the Department of Neurology (N.R.P., A.L.C., M.H.M., I.R.C., R.B., E.J.G., N.H.P., E.E.L., A.d.H., K.N.S.), and Department of Radiology (S.P., G.S.), Yale University School of Medicine, New Haven, CT; Computer Science and Artificial Intelligence Laboratory (CSAIL) (J.E.I.), Massachusetts Institute of Technology, Cambridge; Athinoula A. Martinos Center for Biomedical Imaging (J.E.I., M.S.R.), Massachusetts General Hospital, Charlestown; Department of Neurosurgery (S.B.O., C.M.), Yale University School of Medicine, New Haven, CT; Department of Neurosurgery (S.J.S.), Engineering Science and Mechanics, and Physics, The Pennsylvania State University, University Park; and Division of Neurocritical Care (W.T.K.), Department of Neurology, Massachusetts General Hospital, Boston
| | - Adam de Havenon
- From the Department of Neurology (N.R.P., A.L.C., M.H.M., I.R.C., R.B., E.J.G., N.H.P., E.E.L., A.d.H., K.N.S.), and Department of Radiology (S.P., G.S.), Yale University School of Medicine, New Haven, CT; Computer Science and Artificial Intelligence Laboratory (CSAIL) (J.E.I.), Massachusetts Institute of Technology, Cambridge; Athinoula A. Martinos Center for Biomedical Imaging (J.E.I., M.S.R.), Massachusetts General Hospital, Charlestown; Department of Neurosurgery (S.B.O., C.M.), Yale University School of Medicine, New Haven, CT; Department of Neurosurgery (S.J.S.), Engineering Science and Mechanics, and Physics, The Pennsylvania State University, University Park; and Division of Neurocritical Care (W.T.K.), Department of Neurology, Massachusetts General Hospital, Boston
| | - Steven J Schiff
- From the Department of Neurology (N.R.P., A.L.C., M.H.M., I.R.C., R.B., E.J.G., N.H.P., E.E.L., A.d.H., K.N.S.), and Department of Radiology (S.P., G.S.), Yale University School of Medicine, New Haven, CT; Computer Science and Artificial Intelligence Laboratory (CSAIL) (J.E.I.), Massachusetts Institute of Technology, Cambridge; Athinoula A. Martinos Center for Biomedical Imaging (J.E.I., M.S.R.), Massachusetts General Hospital, Charlestown; Department of Neurosurgery (S.B.O., C.M.), Yale University School of Medicine, New Haven, CT; Department of Neurosurgery (S.J.S.), Engineering Science and Mechanics, and Physics, The Pennsylvania State University, University Park; and Division of Neurocritical Care (W.T.K.), Department of Neurology, Massachusetts General Hospital, Boston
| | - Matthew S Rosen
- From the Department of Neurology (N.R.P., A.L.C., M.H.M., I.R.C., R.B., E.J.G., N.H.P., E.E.L., A.d.H., K.N.S.), and Department of Radiology (S.P., G.S.), Yale University School of Medicine, New Haven, CT; Computer Science and Artificial Intelligence Laboratory (CSAIL) (J.E.I.), Massachusetts Institute of Technology, Cambridge; Athinoula A. Martinos Center for Biomedical Imaging (J.E.I., M.S.R.), Massachusetts General Hospital, Charlestown; Department of Neurosurgery (S.B.O., C.M.), Yale University School of Medicine, New Haven, CT; Department of Neurosurgery (S.J.S.), Engineering Science and Mechanics, and Physics, The Pennsylvania State University, University Park; and Division of Neurocritical Care (W.T.K.), Department of Neurology, Massachusetts General Hospital, Boston
| | - W Taylor Kimberly
- From the Department of Neurology (N.R.P., A.L.C., M.H.M., I.R.C., R.B., E.J.G., N.H.P., E.E.L., A.d.H., K.N.S.), and Department of Radiology (S.P., G.S.), Yale University School of Medicine, New Haven, CT; Computer Science and Artificial Intelligence Laboratory (CSAIL) (J.E.I.), Massachusetts Institute of Technology, Cambridge; Athinoula A. Martinos Center for Biomedical Imaging (J.E.I., M.S.R.), Massachusetts General Hospital, Charlestown; Department of Neurosurgery (S.B.O., C.M.), Yale University School of Medicine, New Haven, CT; Department of Neurosurgery (S.J.S.), Engineering Science and Mechanics, and Physics, The Pennsylvania State University, University Park; and Division of Neurocritical Care (W.T.K.), Department of Neurology, Massachusetts General Hospital, Boston
| | - Kevin N Sheth
- From the Department of Neurology (N.R.P., A.L.C., M.H.M., I.R.C., R.B., E.J.G., N.H.P., E.E.L., A.d.H., K.N.S.), and Department of Radiology (S.P., G.S.), Yale University School of Medicine, New Haven, CT; Computer Science and Artificial Intelligence Laboratory (CSAIL) (J.E.I.), Massachusetts Institute of Technology, Cambridge; Athinoula A. Martinos Center for Biomedical Imaging (J.E.I., M.S.R.), Massachusetts General Hospital, Charlestown; Department of Neurosurgery (S.B.O., C.M.), Yale University School of Medicine, New Haven, CT; Department of Neurosurgery (S.J.S.), Engineering Science and Mechanics, and Physics, The Pennsylvania State University, University Park; and Division of Neurocritical Care (W.T.K.), Department of Neurology, Massachusetts General Hospital, Boston.
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Kim N, Kitlen E, Garcia G, Khosla A, Elliott Miller P, Johnson J, Wira C, Greer DM, Gilmore EJ, Beekman R. Validation of the rCAST Score and Comparison to the PCAC and FOUR Scores for Prognostication after Out-of-Hospital Cardiac Arrest. Resuscitation 2023; 188:109832. [PMID: 37178901 DOI: 10.1016/j.resuscitation.2023.109832] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/14/2023] [Revised: 05/02/2023] [Accepted: 05/07/2023] [Indexed: 05/15/2023]
Abstract
AIM Early, accurate outcome prediction after out-of-hospital cardiac arrest (OHCA) is critical for clinical decision-making and resource allocation. We sought to validate the revised post-Cardiac Arrest Syndrome for Therapeutic hypothermia (rCAST) score in a United States cohort and compare its prognostic performance to the Pittsburgh Cardiac Arrest Category (PCAC) and Full Outline of UnResponsiveness (FOUR) scores. METHODS This is a single-center, retrospective study of OHCA patients admitted between January 2014-August 2022. Area under the receiver operating curve (AUC) was computed for each score for predicting poor neurologic outcome at discharge and in-hospital mortality. We compared the scores' predictive abilities via Delong's test. RESULTS Of 505 OHCA patients with all scores available, the medians [IQR] for rCAST, PCAC, and FOUR scores were 9.5 [6.0, 11.5], 4 [3,4], and 2 [0, 5], respectively. The AUC [95% confidence interval] of the rCAST, PCAC, and FOUR scores for predicting poor neurologic outcome were 0.815 [0.763 - 0.867], 0.753 [0.697 - 0.809], and 0.841 [0.796 - 0.886], respectively. The AUC [95% confidence interval] of the rCAST, PCAC, and FOUR scores for predicting mortality were 0.799 [0.751 - 0.847], 0.723 [0.673 - 0.773], and 0.813 [0.770 - 0.855], respectively. The rCAST score was superior to the PCAC score for predicting mortality (p=0.017). The FOUR score was superior to the PCAC score for predicting poor neurological outcome (p<0.001) and mortality (p<0.001). CONCLUSION The rCAST score can reliably predict poor outcome in a United States cohort of OHCA patients regardless of TTM status and outperforms the PCAC score.
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Affiliation(s)
- Noah Kim
- Department of Neurology, Yale School of Medicine, New Haven, CT, United States
| | - Eva Kitlen
- Department of Neurology, Yale School of Medicine, New Haven, CT, United States
| | - Gabriella Garcia
- Department of Neurology, Yale School of Medicine, New Haven, CT, United States
| | - Akhil Khosla
- Department of Pulmonary Critical Care, Yale School of Medicine, New Haven, CT, United States
| | - P Elliott Miller
- Section of Cardiovascular Medicine, Department of Internal Medicine, Yale School of Medicine, New Haven, CT, United States
| | | | - Charles Wira
- Department of Emergency Medicine, Yale School of Medicine, New Haven, CT, United States
| | - David M Greer
- Department of Neurology, Boston University Medical Center, Boston, MA, United States
| | - Emily J Gilmore
- Department of Neurology, Yale School of Medicine, New Haven, CT, United States
| | - Rachel Beekman
- Department of Neurology, Yale School of Medicine, New Haven, CT, United States.
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11
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Beekman R, Hirsch KG. Expanding beyond ischemic stroke: a qualitative MRI score that facilitates outcome prediction in patients with hypoxic ischemic brain injury. Resuscitation 2023; 187:109800. [PMID: 37080336 DOI: 10.1016/j.resuscitation.2023.109800] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/03/2023] [Accepted: 04/05/2023] [Indexed: 04/22/2023]
Affiliation(s)
| | - Karen G Hirsch
- Department of Neurology, Stanford University School of Medicine; 453 Quarry Road, Palo Alto, CA 94304.
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Beekman R, Hirsch KG. Brain imaging after cardiac arrest. Curr Opin Crit Care 2023; 29:192-198. [PMID: 37078612 DOI: 10.1097/mcc.0000000000001032] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/21/2023]
Abstract
PURPOSE OF REVIEW Many patients who survive a cardiac arrest have a disorder of consciousness in the period after resuscitation, and prediction of long-term neurologic outcome requires multimodal assessments. Brain imaging with computed tomography (CT) and MRI is a key component. We aim to provide an overview of the types of neuroimaging available and their uses and limitations. RECENT FINDINGS Recent studies have evaluated qualitative and quantitative techniques to analyze and interpret CT and MRI to predict both good and poor outcomes. Qualitative interpretation of CT and MRI is widely available but is limited by low inter-rater reliability and lack of specificity around which findings have the highest correlation with outcome. Quantitative analysis of CT (gray-white ratio) and MRI (amount of brain tissue with an apparent diffusion coefficient below certain thresholds) hold promise, though additional research is needed to standardize the approach. SUMMARY Brain imaging is important for evaluating the extent of neurologic injury after cardiac arrest. Future work should focus on addressing previous methodological limitations and standardizing approaches to qualitative and quantitative imaging analysis. Novel imaging techniques are being developed and new analytical methods are being applied to advance the field.
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Affiliation(s)
- Rachel Beekman
- Yale School of Medicine, Department of Neurology, New Haven, CT
| | - Karen G Hirsch
- Stanford School of Medicine, Department of Neurology, Stanford, CA, USA
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13
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Ammar AA, Elsamadicy AA, Ammar MA, Reeves BC, Koo AB, Falcone GJ, Hwang DY, Petersen N, Kim JA, Beekman R, Prust M, Magid-Bernstein J, Acosta JN, Herbert R, Sheth KN, Matouk CC, Gilmore EJ. Emergent external ventricular drain placement in patients with factor Xa inhibitor-associated intracerebral hemorrhage after reversal with andexanet alfa. Clin Neurol Neurosurg 2023; 226:107621. [PMID: 36791588 DOI: 10.1016/j.clineuro.2023.107621] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2022] [Revised: 02/04/2023] [Accepted: 02/06/2023] [Indexed: 02/11/2023]
Abstract
BACKGROUND Andexanet alfa (AA), a factor Xa-inhibitor (FXi) reversal agent, is given as a bolus followed by a 2-hour infusion. This long administration time can delay EVD placement in intracerebral hemorrhage (ICH) patients. We sought to evaluate the safety of EVD placement immediately post-AA bolus compared to post-AA infusion. METHODS We conducted a retrospective study that included adult patients admitted with FXi-associated ICH who received AA and underwent EVD placement The primary outcome was the occurrence of a new hemorrhage (tract, extra-axial, or intraventricular hemorrhage). Secondary outcomes included mortality, intensive care unit and hospital length of stay, and discharge modified Rankin Score. The primary safety outcome was documented thrombotic events. RESULTS Twelve patients with FXi related ICH were included (EVD placement post-AA bolus, N = 8; EVD placement post-AA infusion, N = 4). Each arm included one patient with bilateral EVD placed. There was no difference in the incidence of new hemorrhages, with one post-AA bolus patient had small, focal, nonoperative extra-axial hemorrhage. Morbidity and mortality were higher in post-AA infusion patients (mRS, post-AA bolus, 4 [4-6] vs. post-AA infusion 6 [5,6], p = 0.24 and post-AA bolus, 3 (37.5 %) vs. post-AA infusion, 3 (75 %), p = 0.54, respectively). One patient in the post-AA bolus group had thrombotic event. There was no difference in hospital LOS (post-AA bolus, 19 days [12-26] vs. post-AA infusion, 14 days [9-22], p = 0.55) and ICU LOS (post-AA bolus, 10 days [6-13] vs. post-AA infusion, 11 days [5-21], p = 0.86). CONCLUSION We report no differences in the incidence of tract hemorrhage, extra-axial hemorrhage, or intraventricular hemorrhage post-AA bolus versus post-AA infusion. Larger prospective studies to validate these results are warranted.
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Affiliation(s)
- Abdalla A Ammar
- Department of Pharmacy, Yale New Haven Hospital, 20 York Street, New Haven, CT 06510, USA; Department of Pharmacy, New York Presbyterian/Weill Cornell, 525 East 68th Street, New York, NY 10065, USA.
| | - Aladine A Elsamadicy
- Departments of Neurosurgery, Yale School of Medicine, 20 York Street, New Haven, CT 06510, USA
| | - Mahmoud A Ammar
- Department of Pharmacy, Yale New Haven Hospital, 20 York Street, New Haven, CT 06510, USA
| | - Benjamin C Reeves
- Departments of Neurosurgery, Yale School of Medicine, 20 York Street, New Haven, CT 06510, USA
| | - Andrew B Koo
- Departments of Neurosurgery, Yale School of Medicine, 20 York Street, New Haven, CT 06510, USA
| | - Guido J Falcone
- Division of Neurocritical Care and Emergency Neurology, Department of Neurology, Yale School of Medicine, 20 York Street, New Haven, CT 06510, USA
| | - David Y Hwang
- Department of Neurology, University of North Carolina School of Medicine, 170 Manning Drive, Chapel Hill, NC 27599, USA
| | - Nils Petersen
- Division of Neurocritical Care and Emergency Neurology, Department of Neurology, Yale School of Medicine, 20 York Street, New Haven, CT 06510, USA
| | - Jennifer A Kim
- Division of Neurocritical Care and Emergency Neurology, Department of Neurology, Yale School of Medicine, 20 York Street, New Haven, CT 06510, USA
| | - Rachel Beekman
- Division of Neurocritical Care and Emergency Neurology, Department of Neurology, Yale School of Medicine, 20 York Street, New Haven, CT 06510, USA
| | - Morgan Prust
- Division of Neurocritical Care and Emergency Neurology, Department of Neurology, Yale School of Medicine, 20 York Street, New Haven, CT 06510, USA
| | - Jessica Magid-Bernstein
- Division of Neurocritical Care and Emergency Neurology, Department of Neurology, Yale School of Medicine, 20 York Street, New Haven, CT 06510, USA
| | - Julián N Acosta
- Division of Neurocritical Care and Emergency Neurology, Department of Neurology, Yale School of Medicine, 20 York Street, New Haven, CT 06510, USA
| | - Ryan Herbert
- Departments of Neurosurgery, Yale School of Medicine, 20 York Street, New Haven, CT 06510, USA
| | - Kevin N Sheth
- Division of Neurocritical Care and Emergency Neurology, Department of Neurology, Yale School of Medicine, 20 York Street, New Haven, CT 06510, USA
| | - Charles C Matouk
- Departments of Neurosurgery, Yale School of Medicine, 20 York Street, New Haven, CT 06510, USA
| | - Emily J Gilmore
- Division of Neurocritical Care and Emergency Neurology, Department of Neurology, Yale School of Medicine, 20 York Street, New Haven, CT 06510, USA
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Daley J, Buckley R, Kisken KC, Barber D, Ayyagari R, Wira C, Aydin A, Latich I, Lozada JCP, Joseph D, Marino A, Mojibian H, Pollak J, Chaar CO, Bonz J, Belsky J, Coughlin R, Liu R, Sather J, Van Tonder R, Beekman R, Fults E, Johnson A, Moore C. Emergency department initiated resuscitative endovascular balloon occlusion of the aorta (REBOA) for out-of-hospital cardiac arrest is feasible and associated with improvements in end-tidal carbon dioxide. J Am Coll Emerg Physicians Open 2022; 3:e12791. [PMID: 36176506 PMCID: PMC9463569 DOI: 10.1002/emp2.12791] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/03/2022] [Revised: 06/20/2022] [Accepted: 07/07/2022] [Indexed: 11/28/2022] Open
Abstract
Objectives Out-of-hospital cardiac arrest (OHCA) claims the lives of approximately 350,000 people in the United States each year. Resuscitative endovascular balloon occlusion of the aorta (REBOA) when used as an adjunct to advanced cardiac life support may improve cardio-cerebral perfusion. Our primary research objective was to determine the feasibility of emergency department (ED)-initiated REBOA for OHCA patients in an academic urban ED. Methods This was a single-center, single-arm, early feasibility trial that used REBOA as an adjunct to advanced cardiac life support (ACLS) in OHCA. Subjects under 80 years with witnessed OHCA and who received cardiopulmonary rescuitation (CPR) within 6 minutes were eligible. Results Five patients were enrolled between February 2020 and April 2021. The procedure was successful in all patients and 4 of 5 (80%) patients had transient return of spontaneous circulation (ROSC) after aortic occlusion. Unfortunately, all patients re-arrested soon after intra-aortic balloon deflation and none survived to hospital admission. At 30 seconds post-aortic occlusion, investigators noted a statistically significant increase in end tidal carbon dioxide of 26% (95% confidence interval, 10%, 44%). Conclusion Initiating REBOA for OHCA patients in an academic urban ED setting is feasible. Aortic occlusion during chest compressions is temporally associated with improvements in end tidal carbon dioxide 30 seconds after aortic occlusion. Four of 5 patients achieved ROSC after aortic occlusion; however, deflation of the intra-aortic balloon quickly led to re-arrest and death in all patients. Future research should focus on the utilization of partial-REBOA to prevent re-arrest after ROSC, as well as the optimal way to incorporate this technique with other endovascular reperfusion strategies.
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15
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Thomas A, van Diepen S, Beekman R, Sinha SS, Brusca SB, Alviar CL, Jentzer J, Bohula EA, Katz JN, Shahu A, Barnett C, Morrow DA, Gilmore EJ, Solomon MA, Miller PE. Oxygen Supplementation and Hyperoxia in Critically Ill Cardiac Patients: From Pathophysiology to Clinical Practice. JACC Adv 2022; 1:100065. [PMID: 36238193 PMCID: PMC9555075 DOI: 10.1016/j.jacadv.2022.100065] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Abstract
Oxygen supplementation has been a mainstay in the management of patients with acute cardiac disease. While hypoxia is known to be detrimental, the adverse effects of artificially high oxygen levels (hyperoxia) have only recently been recognized. Hyperoxia may induce harmful hemodynamic effects, including peripheral and coronary vasoconstriction, and direct cellular toxicity through the production of reactive oxygen species. In addition, emerging evidence has shown that hyperoxia is associated with adverse clinical outcomes. Thus, it is essential for the cardiac intensive care unit (CICU) clinician to understand the available evidence and titrate oxygen therapies to specific goals. This review summarizes the pathophysiology of oxygen within the cardiovascular system and the association between supplemental oxygen and hyperoxia in patients with common CICU diagnoses, including acute myocardial infarction, heart failure, shock, cardiac arrest, pulmonary hypertension, and respiratory failure. Finally, we highlight lessons learned from available trials, gaps in knowledge, and future directions.
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Affiliation(s)
- Alexander Thomas
- Section of Cardiovascular Medicine, Yale School of Medicine, New Haven, CT
| | - Sean van Diepen
- Department of Critical Care and Division of Cardiology, Department of Medicine, University of Alberta, Edmonton, Canada
| | - Rachel Beekman
- Department of Neurology, Yale University School of Medicine, New Haven, CT
| | - Shashank S. Sinha
- Inova Heart and Vascular Institute, Inova Fairfax Medical Center, Falls Church, VA
| | - Samuel B. Brusca
- Division of Cardiology, University of California San Francisco, San Francisco, CA
| | - Carlos L. Alviar
- Leon H. Charney Division of Cardiology, New York University School of Medicine, New York, New York
| | - Jacob Jentzer
- Department of Cardiovascular Medicine, Mayo Clinic, Rochester, MN
| | - Erin A. Bohula
- TIMI Study Group, Cardiovascular Division, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA
| | - Jason N. Katz
- Division of Cardiology, Duke University Medical Center, Durham, NC
| | - Andi Shahu
- Section of Cardiovascular Medicine, Yale School of Medicine, New Haven, CT
| | - Christopher Barnett
- Division of Cardiology, University of California San Francisco, San Francisco, CA
| | - David A. Morrow
- TIMI Study Group, Cardiovascular Division, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA
| | - Emily J. Gilmore
- Department of Neurology, Yale University School of Medicine, New Haven, CT
| | - Michael A. Solomon
- Critical Care Medicine Department, National Institutes of Health Clinical Center and Cardiovascular Branch, National Heart, Lung, and Blood Institute, of the National Institutes of Health, Bethesda, MD
| | - P. Elliott Miller
- Section of Cardiovascular Medicine, Yale School of Medicine, New Haven, CT
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16
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Beekman R, Crawford A, Mazurek MH, Prabhat AM, Chavva IR, Parasuram N, Kim N, Kim JA, Petersen N, de Havenon A, Khosla A, Honiden S, Miller PE, Wira C, Daley J, Payabvash S, Greer DM, Gilmore EJ, Taylor Kimberly W, Sheth KN. Bedside monitoring of hypoxic ischemic brain injury using low-field, portable brain magnetic resonance imaging after cardiac arrest. Resuscitation 2022; 176:150-158. [PMID: 35562094 PMCID: PMC9746653 DOI: 10.1016/j.resuscitation.2022.05.002] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2022] [Revised: 04/25/2022] [Accepted: 05/03/2022] [Indexed: 12/15/2022]
Abstract
BACKGROUND Assessment of brain injury severity is critically important after survival from cardiac arrest (CA). Recent advances in low-field MRI technology have permitted the acquisition of clinically useful bedside brain imaging. Our objective was to deploy a novel approach for evaluating brain injury after CA in critically ill patients at high risk for adverse neurological outcome. METHODS This retrospective, single center study involved review of all consecutive portable MRIs performed as part of clinical care for CA patients between September 2020 and January 2022. Portable MR images were retrospectively reviewed by a blinded board-certified neuroradiologist (S.P.). Fluid-inversion recovery (FLAIR) signal intensities were measured in select regions of interest. RESULTS We performed 22 low-field MRI examinations in 19 patients resuscitated from CA (68.4% male, mean [standard deviation] age, 51.8 [13.1] years). Twelve patients (63.2%) had findings consistent with HIBI on conventional neuroimaging radiology report. Low-field MRI detected findings consistent with HIBI in all of these patients. Low-field MRI was acquired at a median (interquartile range) of 78 (40-136) hours post-arrest. Quantitatively, we measured FLAIR signal intensity in three regions of interest, which were higher amongst patients with confirmed HIBI. Low-field MRI was completed in all patients without disruption of intensive care unit equipment monitoring and no safety events occurred. CONCLUSION In a critically ill CA population in whom MR imaging is often not feasible, low-field MRI can be deployed at the bedside to identify HIBI. Low-field MRI provides an opportunity to evaluate the time-dependent nature of MRI findings in CA survivors.
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Affiliation(s)
- Rachel Beekman
- Department of Neurology, Yale School of Medicine, New Haven, CT, USA.
| | - Anna Crawford
- Department of Neurology, Yale School of Medicine, New Haven, CT, USA
| | - Mercy H Mazurek
- Department of Neurology, Yale School of Medicine, New Haven, CT, USA
| | - Anjali M Prabhat
- Department of Neurology, Yale School of Medicine, New Haven, CT, USA
| | - Isha R Chavva
- Department of Neurology, Yale School of Medicine, New Haven, CT, USA
| | - Nethra Parasuram
- Department of Neurology, Yale School of Medicine, New Haven, CT, USA
| | - Noah Kim
- Department of Neurology, Yale School of Medicine, New Haven, CT, USA
| | - Jennifer A Kim
- Department of Neurology, Yale School of Medicine, New Haven, CT, USA
| | - Nils Petersen
- Department of Neurology, Yale School of Medicine, New Haven, CT, USA
| | - Adam de Havenon
- Department of Neurology, Yale School of Medicine, New Haven, CT, USA
| | - Akhil Khosla
- Department of Pulmonary Critical Care, Yale School of Medicine, New Haven, CT, USA
| | - Shyoko Honiden
- Department of Pulmonary Critical Care, Yale School of Medicine, New Haven, CT, USA
| | - P Elliott Miller
- Section of Cardiology, Yale School of Medicine, New Haven, CT, USA
| | - Charles Wira
- Department of Emergency Medicine, Yale School of Medicine, New Haven, CT, USA
| | - James Daley
- Department of Emergency Medicine, Yale School of Medicine, New Haven, CT, USA
| | | | - David M Greer
- Department of Neurology, Boston University Medical Center, Boston, MA, USA
| | - Emily J Gilmore
- Department of Neurology, Yale School of Medicine, New Haven, CT, USA
| | - W Taylor Kimberly
- Department of Neurology, Massachusetts General Hospital, Boston, MA, USA
| | - Kevin N Sheth
- Department of Neurology, Yale School of Medicine, New Haven, CT, USA
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17
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Yuen MM, Prabhat AM, Mazurek MH, Chavva IR, Crawford A, Cahn BA, Beekman R, Kim JA, Gobeske KT, Petersen NH, Falcone GJ, Gilmore EJ, Hwang DY, Jasne AS, Amin H, Sharma R, Matouk C, Ward A, Schindler J, Sansing L, de Havenon A, Aydin A, Wira C, Sze G, Rosen MS, Kimberly WT, Sheth KN. Portable, low-field magnetic resonance imaging enables highly accessible and dynamic bedside evaluation of ischemic stroke. Sci Adv 2022; 8:eabm3952. [PMID: 35442729 PMCID: PMC9020661 DOI: 10.1126/sciadv.abm3952] [Citation(s) in RCA: 28] [Impact Index Per Article: 14.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/14/2021] [Accepted: 02/08/2022] [Indexed: 05/26/2023]
Abstract
Brain imaging is essential to the clinical management of patients with ischemic stroke. Timely and accessible neuroimaging, however, can be limited in clinical stroke pathways. Here, portable magnetic resonance imaging (pMRI) acquired at very low magnetic field strength (0.064 T) is used to obtain actionable bedside neuroimaging for 50 confirmed patients with ischemic stroke. Low-field pMRI detected infarcts in 45 (90%) patients across cortical, subcortical, and cerebellar structures. Lesions as small as 4 mm were captured. Infarcts appeared as hyperintense regions on T2-weighted, fluid-attenuated inversion recovery and diffusion-weighted imaging sequences. Stroke volume measurements were consistent across pMRI sequences and between low-field pMRI and conventional high-field MRI studies. Low-field pMRI stroke volumes significantly correlated with stroke severity and functional outcome at discharge. These results validate the use of low-field pMRI to obtain clinically useful imaging of stroke, setting the stage for use in resource-limited environments.
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Affiliation(s)
- Matthew M. Yuen
- Department of Neurology, Yale School of Medicine, New Haven, CT, USA
| | - Anjali M. Prabhat
- Department of Neurology, Yale School of Medicine, New Haven, CT, USA
| | - Mercy H. Mazurek
- Department of Neurology, Yale School of Medicine, New Haven, CT, USA
| | - Isha R. Chavva
- Department of Neurology, Yale School of Medicine, New Haven, CT, USA
| | - Anna Crawford
- Department of Neurology, Yale School of Medicine, New Haven, CT, USA
| | - Bradley A. Cahn
- Department of Neurology, Yale School of Medicine, New Haven, CT, USA
| | - Rachel Beekman
- Department of Neurology, Yale School of Medicine, New Haven, CT, USA
| | - Jennifer A. Kim
- Department of Neurology, Yale School of Medicine, New Haven, CT, USA
| | - Kevin T. Gobeske
- Department of Neurology, Yale School of Medicine, New Haven, CT, USA
| | - Nils H. Petersen
- Department of Neurology, Yale School of Medicine, New Haven, CT, USA
| | - Guido J. Falcone
- Department of Neurology, Yale School of Medicine, New Haven, CT, USA
| | - Emily J. Gilmore
- Department of Neurology, Yale School of Medicine, New Haven, CT, USA
| | - David Y. Hwang
- Department of Neurology, Yale School of Medicine, New Haven, CT, USA
| | - Adam S. Jasne
- Department of Neurology, Yale School of Medicine, New Haven, CT, USA
| | - Hardik Amin
- Department of Neurology, Yale School of Medicine, New Haven, CT, USA
| | - Richa Sharma
- Department of Neurology, Yale School of Medicine, New Haven, CT, USA
| | - Charles Matouk
- Department of Neurosurgery, Yale School of Medicine, New Haven, CT, USA
| | - Adrienne Ward
- Neuroscience Intensive Care Unit, Yale New Haven Hospital, New Haven, CT, USA
| | - Joseph Schindler
- Department of Neurology, Yale School of Medicine, New Haven, CT, USA
| | - Lauren Sansing
- Department of Neurology, Yale School of Medicine, New Haven, CT, USA
| | - Adam de Havenon
- Department of Neurology, Yale School of Medicine, New Haven, CT, USA
| | - Ani Aydin
- Department of Emergency Medicine, Yale School of Medicine, New Haven, CT, USA
| | - Charles Wira
- Department of Emergency Medicine, Yale School of Medicine, New Haven, CT, USA
| | - Gordon Sze
- Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, CT, USA
| | - Matthew S. Rosen
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, USA
| | - W. Taylor Kimberly
- Department of Neurology, Massachusetts General Hospital, Boston, MA, USA
| | - Kevin N. Sheth
- Department of Neurology, Yale School of Medicine, New Haven, CT, USA
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18
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Bartolome D, Begunova Y, Prasad A, Soto A, Kobsa J, Top I, Quispe-Orozco D, Farooqui M, Zevallos C, Kim J, Gilmore EJ, Beekman R, de Havenon A, Matouk C, Sheth KN, Ortega-Gutierrez S, Petersen NH. Abstract 89: Nimodipine-induced Blood Pressure Reductions Below Personalized Limits Of Autoregulation Are Associated With Worse Outcomes After Subarachnoid Hemorrhage. Stroke 2022. [DOI: 10.1161/str.53.suppl_1.89] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Background:
Impairment of cerebral autoregulation after subarachnoid hemorrhage (SAH) makes patients vulnerable to changes in blood pressure (BP). While oral nimodipine is recommended for improving neurological outcomes, its administration is frequently associated with reductions in BP. In this observational study, we examined the effect of nimodipine-induced BP reductions below personalized limits of autoregulation on outcome after aneurysmal SAH.
Methods:
Autoregulatory function was continuously measured by interrogating changes in near-infrared spectroscopy-derived tissue oxygenation (a cerebral blood flow surrogate) in response to changes in mean arterial pressure (MAP). The resulting autoregulatory index was used for trending the BP range at which autoregulation was most preserved. Cerebral hypoperfusion was defined as episodes with at least 30 minutes of MAP reductions below the lower limit of autoregulation (LLA) following nimodipine administration (Fig. 1). Functional outcome was measured with the modified Rankin Scale at 90 days.
Results:
We identified 593 occurrences of nimodipine administration with simultaneous recording of continuous physiologic data for 60 minutes before and after the intervention among 26 SAH patients (mean age 57
+
14, 21 F). Following nimodipine administration, the mean MAP decreased from 103 to 98 mmHg (p<0.001), and the time with MAP below the LLA increased from 9.5 to 21.7% (p<0.001). Moreover, the proportion of episodes with cerebral hypoperfusion was associated with worse 90-day outcomes after adjusting for age and SAH severity (OR for 10% increase 1.5, 95% CI 1.2-2.2, P=0.038).
Conclusions:
Nimodipine-induced BP reductions below the LLA may increase the risk of secondary brain injury and poor functional outcomes. A more personalized treatment approach accounting for cerebral autoregulation status could help identify vulnerable patients and maximize the benefit from current clinical interventions.
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19
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Beekman R, Sun JL, Alhanti B, Schwamm LH, Smith EE, Bhatt DL, Xian Y, Shah S, Lytle BL, Fonarow GC, Sheth KN. Outcomes of Endovascular Therapy in Patients With Prestroke Mobility Impairment. Stroke 2021; 52:e725-e728. [PMID: 34517771 DOI: 10.1161/strokeaha.121.034464] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
[Figure: see text].
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Affiliation(s)
- Rachel Beekman
- Department of Neurology, Yale School of Medicine, New Haven, CT (R.B., K.N.S.)
| | - Jie-Lena Sun
- Department of Biostatistics, Duke Clinical Research Institute, Duke University School of Medicine, Durham, NC (J.-L.S., B.A., Y.X., S.S., B.L.L.)
| | - Brooke Alhanti
- Department of Biostatistics, Duke Clinical Research Institute, Duke University School of Medicine, Durham, NC (J.-L.S., B.A., Y.X., S.S., B.L.L.)
| | - Lee H Schwamm
- Department of Neurology, Massachusetts General Hospital, Boston (L.H.S.)
| | - Eric E Smith
- Department of Clinical Neurosciences, Hotchkiss Brain Institute, University of Calgary, Alberta, Canada (E.E.S.)
| | - Deepak L Bhatt
- Department of Cardiovascular Medicine, Brigham and Women's Hospital Heart and Vascular Center, Harvard Medical School, Boston, MA (D.L.B.)
| | - Ying Xian
- Department of Biostatistics, Duke Clinical Research Institute, Duke University School of Medicine, Durham, NC (J.-L.S., B.A., Y.X., S.S., B.L.L.)
| | - Shreyansh Shah
- Department of Biostatistics, Duke Clinical Research Institute, Duke University School of Medicine, Durham, NC (J.-L.S., B.A., Y.X., S.S., B.L.L.)
| | - Barbara L Lytle
- Department of Biostatistics, Duke Clinical Research Institute, Duke University School of Medicine, Durham, NC (J.-L.S., B.A., Y.X., S.S., B.L.L.)
| | - Gregg C Fonarow
- Division of Cardiology/Department of Medicine, Ronald-Regan UCLA Medical Center, Los Angeles, CA (G.C.F.)
| | - Kevin N Sheth
- Department of Neurology, Yale School of Medicine, New Haven, CT (R.B., K.N.S.)
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20
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Beekman R, Maciel CB, Ormseth CH, Zhou SE, Galluzzo D, Miyares LC, Torres-Lopez VM, Payabvash S, Mak A, Greer DM, Gilmore EJ. Early head CT in post-cardiac arrest patients: A helpful tool or contributor to self-fulfilling prophecy? Resuscitation 2021; 165:68-76. [PMID: 34147572 DOI: 10.1016/j.resuscitation.2021.06.004] [Citation(s) in RCA: 22] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/29/2021] [Revised: 05/21/2021] [Accepted: 06/10/2021] [Indexed: 02/06/2023]
Abstract
OBJECTIVE Neuroprognostication guidelines suggest that early head computed tomography (HCT) might be useful in the evaluation of cardiac arrest (CA) patients following return of spontaneous circulation. We aimed to determine the impact of early HCT, performed within the first 6 h following CA, on decision-making following resuscitation. METHODS We identified a cohort of initially unconscious post-CA patients at a tertiary care academic medical center from 2012 to 2017. Variables pertaining to demographics, CA details, post-CA care, including neuroimaging and neurophysiologic testing, were abstracted retrospectively from the electronic medical records. Changes in management resulting from HCT findings were recorded. Blinded board-certified neurointensivists adjudicated HCT findings related to hypoxic-ischemic brain injury (HIBI) burden. The gray-white matter ratio (GWR) was also calculated. RESULTS Of 302 patients, 182 (60.2%) underwent HCT within six hours of CA (early HCT group). Approximately 1 in 4 early HCTs were abnormal (most commonly HIBI changes; 78.7%, n = 37), which resulted in a change in management in nearly half of cases (46.8%, n = 22). The most common changes in management were de-escalation in care [including transition to do not resuscitate status), withholding targeted temperature management, and withdrawal of life sustaining therapy (WLST)]. In cases with radiographic HIBI, mean [standard deviation] GWR was lower (1.20 [0.10] vs 1.30 [0.09], P < 0.001) and progression to brain death was higher (44.4% vs 2.9%; P < 0.001). The inter-rater reliability (IRR) of early HCT to determine presence of HIBI between radiology and three neurointensivists had a wide range (κ 0.13-0.66). CONCLUSION Early HCT identified abnormalities in 25% of cases and frequently influenced therapeutic decisions. Neuroimaging interpretation discrepancies between radiology and neurointensivists are common and agreement on severity of HIBI on early HCT is poor (k 0.11).
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Affiliation(s)
- Rachel Beekman
- Department of Neurology, Yale School of Medicine, New Haven, CT, 06510, United States.
| | - Carolina B Maciel
- Department of Neurology, Yale School of Medicine, New Haven, CT, 06510, United States; Department of Neurology, UF Health Shands Hospital, University of Florida College of Medicine, Gainesville, FL, 32611, United States
| | - Cora H Ormseth
- Department of Neurology, Yale School of Medicine, New Haven, CT, 06510, United States
| | - Sonya E Zhou
- Department of Neurology, Yale School of Medicine, New Haven, CT, 06510, United States
| | - Daniela Galluzzo
- Department of Neurology, Yale School of Medicine, New Haven, CT, 06510, United States
| | - Laura C Miyares
- Department of Neurology, Yale School of Medicine, New Haven, CT, 06510, United States
| | - Victor M Torres-Lopez
- Department of Neurology, Yale School of Medicine, New Haven, CT, 06510, United States
| | - Seyedmehdi Payabvash
- Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, CT, 06510, United States
| | - Adrian Mak
- Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, CT, 06510, United States
| | - David M Greer
- Department of Neurology, Yale School of Medicine, New Haven, CT, 06510, United States; Department of Neurology, Boston University School of Medicine, Boston, MA, 02118, United States
| | - Emily J Gilmore
- Department of Neurology, Yale School of Medicine, New Haven, CT, 06510, United States
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21
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Katz JB, Owusu K, Nussbaum I, Beekman R, DeFilippo NA, Gilmore EJ, Hirsch LJ, Cervenka MC, Maciel CB. Pearls and Pitfalls of Introducing Ketogenic Diet in Adult Status Epilepticus: A Practical Guide for the Intensivist. J Clin Med 2021; 10:881. [PMID: 33671485 PMCID: PMC7926931 DOI: 10.3390/jcm10040881] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/07/2021] [Revised: 02/04/2021] [Accepted: 02/13/2021] [Indexed: 12/13/2022] Open
Abstract
Background: Status epilepticus (SE) carries an exceedingly high mortality and morbidity, often warranting an aggressive therapeutic approach. Recently, the implementation of a ketogenic diet (KD) in adults with refractory and super-refractory SE has been shown to be feasible and effective. Methods: We describe our experience, including the challenges of achieving and maintaining ketosis, in an adult with new onset refractory status epilepticus (NORSE). Case Vignette: A previously healthy 29-year-old woman was admitted with cryptogenic NORSE following a febrile illness; course was complicated by prolonged super-refractory SE. A comprehensive work-up was notable only for mild cerebral spinal fluid (CSF) pleocytosis, elevated nonspecific serum inflammatory markers, and edematous hippocampi with associated diffusion restriction on magnetic resonance imaging (MRI). Repeat CSF testing was normal and serial MRIs demonstrated resolution of edema and diffusion restriction with progressive hippocampal and diffuse atrophy. She required prolonged therapeutic coma with high anesthetic infusion rates, 16 antiseizure drug (ASD) trials, empiric immunosuppression and partial bilateral oophorectomy. Enteral ketogenic formula was started on hospital day 28. However, sustained beta-hydroxybutyrate levels >2 mmol/L were only achieved 37 days later following a comprehensive adjustment of the care plan. KD was challenging to maintain in the intensive care unit (ICU) and was discontinued due to poor nutritional state and pressure ulcers. KD was restarted again in a non-ICU unit facilitating ASD tapering without re-emergence of SE. Discussion: There are inconspicuous carbohydrates in commonly administered medications for SE including antibiotics, electrolyte repletion formulations, different preparations of the same drug (i.e., parenteral, tablet, or suspension) and even solutions used for oral care-all challenging the use of KD in the hospitalized patient. Tailoring comprehensive care and awareness of possible complications of KD are important for the successful implementation and maintenance of ketosis.
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Affiliation(s)
- Jason B. Katz
- Department of Neurology, Neurocritical Care Division, UF Health-Shands Hospital, University of Florida, Gainesville, FL 32611, USA;
| | - Kent Owusu
- Department of Neurology, Yale New Haven Hospital, Yale School of Medicine, New Haven, CT 06520, USA; (K.O.); (I.N.); (R.B.); (E.J.G.); (L.J.H.)
- Care Signature, Yale New Haven Health, New Haven, CT 06510, USA
| | - Ilisa Nussbaum
- Department of Neurology, Yale New Haven Hospital, Yale School of Medicine, New Haven, CT 06520, USA; (K.O.); (I.N.); (R.B.); (E.J.G.); (L.J.H.)
| | - Rachel Beekman
- Department of Neurology, Yale New Haven Hospital, Yale School of Medicine, New Haven, CT 06520, USA; (K.O.); (I.N.); (R.B.); (E.J.G.); (L.J.H.)
| | - Nicholas A. DeFilippo
- Department of Pharmacy Services, Yale New Haven Hospital, New Haven, CT 06510, USA;
- School of Pharmacy, University of Connecticut, Storrs, CT 06269, USA
| | - Emily J. Gilmore
- Department of Neurology, Yale New Haven Hospital, Yale School of Medicine, New Haven, CT 06520, USA; (K.O.); (I.N.); (R.B.); (E.J.G.); (L.J.H.)
| | - Lawrence J. Hirsch
- Department of Neurology, Yale New Haven Hospital, Yale School of Medicine, New Haven, CT 06520, USA; (K.O.); (I.N.); (R.B.); (E.J.G.); (L.J.H.)
| | - Mackenzie C. Cervenka
- Department of Neurology, Epilepsy Division, Johns Hopkins Hospital, Johns Hopkins University School of Medicine, Baltimore, MD 21287, USA;
| | - Carolina B. Maciel
- Department of Neurology, Neurocritical Care Division, UF Health-Shands Hospital, University of Florida, Gainesville, FL 32611, USA;
- Department of Neurology, Yale New Haven Hospital, Yale School of Medicine, New Haven, CT 06520, USA; (K.O.); (I.N.); (R.B.); (E.J.G.); (L.J.H.)
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22
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Cahn BA, Shah JT, By S, Welch EB, Sacolick L, Yuen MM, Mazurek MH, Wira C, Leasure AC, Matouk C, Ward A, Payabvash S, Beekman R, Brown SC, Falcone G, Gobeske K, Petersen N, Jasne A, Sharma R, Schindler J, Sansing L, Gilmore E, Sze G, Rosen M, Kimberly WT, Sheth KN. Abstract WP413: Portable, Bedside, Point of Care Magnetic Resonance Imaging in an Intensive Care Setting for Intracranial Hemorrhage. Stroke 2020. [DOI: 10.1161/str.51.suppl_1.wp413] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Background:
Radiographic diagnosis of intracranial hemorrhage (ICH) is a critical determinant of stroke care pathways requiring patient transport to a neuroimaging suite. Advances in low-field MRI have made it possible to obtain clinically useful imaging at the point of care (POC).
Aim:
The aim of this study was to obtain preliminary data regarding the ability of a bedside POC MRI scanner to detect ICH.
Methods:
We studied 36 patients with a diagnosis of ICH (n=18) or ischemic stroke (n=18). Five blinded readers independently evaluated T2W and FLAIR exams acquired prospectively on a 64 mT, portable bedside MRI system (Hyperfine Research, Inc). Kappa coefficients (κ) were calculated to determine inter-rater agreement. Ground truth was obtained from the clinical report of the closest conventional imaging study (17.9 ± 10.4 hours) and verified by a core reader. For each exam, majority consensus among raters was used to determine sensitivity.
Results:
ICH volume ranged from 4 to 101 cc (median of 13 cc). Exams were acquired within 7 days of symptom onset (51.1 ± 28.8 hours). A pathologic lesion was identified on every exam with 100% sensitivity. Sensitivity for distinguishing any hemorrhage was 89% and specificity was 83%. The mean sensitivity and specificity for individual raters was 79% and 69%, respectively. When limited to supratentorial hemorrhage, consensus sensitivity was 94%. For ICH cases detected by all raters (n=9), there was 100% accuracy for localizing the bleed (lobar vs. non-lobar) with perfect agreement among raters (κ = 1, p <0.0001). There was substantial agreement for identifying intraventricular hemorrhage (IVH) (κ = 0.72, p < 0.0001). Sensitivity for IVH was 100% based on rater consensus. Figure 1 shows a POC exam with an ICH and IVH.
Conclusions:
These data suggest that low-field, POC MRI may be used to detect hemorrhagic stroke at the bedside. Further work is needed to evaluate this approach in the hyperacute setting and across a wide range of ICH characteristics.
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Affiliation(s)
| | - Jill T Shah
- Dept of Neurology, Yale Sch of Medicine, New Haven, CT
| | | | | | | | | | | | - Charles Wira
- Dept of Emergency Medicine, Yale Sch of Medicine, New Haven, CT
| | | | - Charles Matouk
- Dept of Neurosurgery, Yale Sch of Medicine, New Haven, CT
| | - Adrienne Ward
- Dept of Neurology, Yale Sch of Medicine, New Haven, CT
| | - Sam Payabvash
- Dept of Radiology, Yale Sch of Medicine, New Haven, CT
| | | | - Stacy C Brown
- Dept of Neurology, Yale Sch of Medicine, New Haven, CT
| | - Guido Falcone
- Dept of Neurology, Yale Sch of Medicine, New Haven, CT
| | - Kevin Gobeske
- Dept of Neurology, Yale Sch of Medicine, New Haven, CT
| | - Nils Petersen
- Dept of Neurology, Yale Sch of Medicine, New Haven, CT
| | - Adam Jasne
- Dept of Neurology, Yale Sch of Medicine, New Haven, CT
| | - Richa Sharma
- Dept of Neurology, Yale Sch of Medicine, New Haven, CT
| | | | | | - Emily Gilmore
- Dept of Neurology, Yale Sch of Medicine, New Haven, CT
| | - Gordon Sze
- Dept of Radiology, Yale Sch of Medicine, New Haven, CT
| | | | | | - Kevin N Sheth
- Dept of Neurology, Yale Sch of Medicine, New Haven, CT
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Cahn BA, Shah JT, Dyvorne H, O'Halloran R, Poole M, Yuen MM, Mazurek MH, Ward A, Payabvash S, Beekman R, Brown SC, Falcone G, Gobeske K, Petersen N, Jasne A, Sharma R, Schindler J, Sansing L, Gilmore E, Wira C, Matouk C, Sze G, Rosen M, Kimberly WT, Sheth KN. Abstract 57: Deployment of Portable, Bedside, Low-Field Magnetic Resonance Imaging for Evaluation of Stroke Patients. Stroke 2020. [DOI: 10.1161/str.51.suppl_1.57] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Background:
Magnetic resonance imaging (MRI) is a powerful modality for diagnosing stroke. Conventionally, patients must travel to the location of a high-field MRI device. Advances in low-field MRI have enabled acquisition of clinically useful images using a portable device at the bedside. The feasibility of using point of care (POC) MRI in a clinical stroke setting is unknown.
Objective:
To determine the safety and feasibility of portable, bedside, low-field MRI in a clinical setting.
Design/Methods:
POC MRI exams were performed in Yale’s Neuroscience Intensive Care Unit (NICU) from July 2018 to August 2019. Images were acquired at the bedside using a standard 110V, 15A power outlet. The environment included the bedside vitals monitor, ventilators and intravenous infusion pumps. Exams were performed by research staff trained to operate the POC scanner in the absence of a trained MRI technician. No special precautions were necessary to remove ferrous metals from the room. Scan parameters were controlled using a tablet computer interface, and images were available immediately after acquisition.
Results:
POC MRI was obtained in 85 stroke cases (46% female, ages 18-96 years, 46% ischemic stroke, 34% intracerebral hemorrhage, 20% subarachnoid hemorrhage). Scans were obtained within 7 days of symptom onset. NIHSS scores ranged from 1 to 29 (median of 7). Of the 85 patients analyzed, 68 underwent T2-weighted imaging, 72 underwent FLAIR imaging, and 39 underwent diffusion weighted imaging (DWI). DWI was only tested in ischemic stroke cases. Patients’ BMI ranged from 20.0 to 46.5 with a median of 26.7. The majority 74 (87%) of patients completed the entire exam. Five patients (6%) were unable to fit in the scanner’s 30 cm opening, while 6 patients (7%) experienced claustrophobia resulting in early termination of the exam. Mean exam time was 28.9 ± 8.4 minutes. The 64 mT static magnetic field, gradient and RF pulses of the POC MRI scanner did not interfere with NICU equipment, and no significant adverse events occurred.
Conclusions:
We report the first use of a portable, low-field MRI system to image stroke patients at the bedside. This early work suggests our approach is safe and viable in a complex clinical care environment.
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Affiliation(s)
| | - Jill T Shah
- Dept of Neurology, Yale Sch of Medicine, New Haven, CT
| | | | | | | | | | | | - Adrienne Ward
- Dept of Neurology, Yale Sch of Medicine, New Haven, CT
| | - Sam Payabvash
- Dept of Radiology, Yale Sch of Medicine, New Haven, CT
| | | | - Stacy C Brown
- Dept of Neurology, Yale Sch of Medicine, New Haven, CT
| | - Guido Falcone
- Dept of Neurology, Yale Sch of Medicine, New Haven, CT
| | - Kevin Gobeske
- Dept of Neurology, Yale Sch of Medicine, New Haven, CT
| | - Nils Petersen
- Dept of Neurology, Yale Sch of Medicine, New Haven, CT
| | - Adam Jasne
- Dept of Neurology, Yale Sch of Medicine, New Haven, CT
| | - Richa Sharma
- Dept of Neurology, Yale Sch of Medicine, New Haven, CT
| | | | | | - Emily Gilmore
- Dept of Neurology, Yale Sch of Medicine, New Haven, CT
| | - Charles Wira
- Dept of Emergency Medicine, Yale Sch of Medicine, New Haven, CT
| | - Charles Matouk
- Dept of Neurosurgery, Yale Sch of Medicine, New Haven, CT
| | - Gordon Sze
- Dept of Radiology, Yale Sch of Medicine, New Haven, CT
| | | | | | - Kevin N Sheth
- Dept of Neurology, Yale Sch of Medicine, New Haven, CT
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Clifford KM, Hobson-Webb LD, Benatar M, Burns TM, Barnett C, Silvestri NJ, Howard JF, Visser A, Crum BA, Nowak R, Beekman R, Kumar A, Ruzhansky K, Chen IHA, Pulley MT, Laboy SM, Fellman MA, Howard DB, Kolb NA, Greene SM, Pasnoor M, Dimachkie MM, Barohn RJ, Hehir MK. Thymectomy may not be associated with clinical improvement in MuSK myasthenia gravis. Muscle Nerve 2019; 59:404-410. [PMID: 30575980 DOI: 10.1002/mus.26404] [Citation(s) in RCA: 41] [Impact Index Per Article: 8.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/09/2018] [Revised: 11/24/2018] [Accepted: 12/16/2018] [Indexed: 12/20/2022]
Abstract
INTRODUCTION A randomized trial demonstrated benefit from thymectomy in nonthymomatous acetylcholine receptor (AChR)-antibody positive myasthenia gravis (MG). Uncontrolled observational and histologic studies suggest thymectomy may not be efficacious in anti-muscle-specific kinase (MuSK)-MG. METHODS The therapeutic impact of thymectomy was evaluated from data collected for a multicenter, retrospective blinded review of rituximab in MuSK-MG. RESULTS Baseline characteristics were similar between thymectomy (n = 26) and nonthymectomy (n = 29) groups, including treatment with rituximab (42% vs. 45%). At last visit, 35% of thymectomy subjects reached the primary endpoint, a Myasthenia Gravis Foundation of America (MGFA) post-intervention status (PIS) score of minimal manifestations (MM) or better, compared with 55% of controls (P = 0.17). After controlling for age at onset of MG, rituximab, prednisone, and intravenous immunoglobulin/plasma exchange treatment, thymectomy was not associated with greater likelihood of favorable clinical outcome (odds ratio = 0.43, 95% confidence interval 0.12-1.53, P = 0.19). DISCUSSION Thymectomy was not associated with additional clinical improvement in this multicenter cohort of MuSK-MG patients. Muscle Nerve 59:404-410, 2019.
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Affiliation(s)
- Katherine M Clifford
- Larner College of Medicine, University of Vermont, 1 South Prospect Street, Burlington, Vermont 05401, USA
| | - Lisa D Hobson-Webb
- Department of Neurology, Duke University School of Medicine, Durham, North Carolina, USA
| | - Michael Benatar
- Department of Neurology, University of Miami Health System, Miami, Florida, USA
| | - Ted M Burns
- Department of Neurology, University of Virginia School of Medicine, Charlottesville, Virginia, USA
| | - Carolina Barnett
- Department of Neurology, University of Toronto School of Medicine, Toronto, Ontario, Canada
| | - Nicholas J Silvestri
- Department of Neurology, University at Buffalo Jacobs School of Medicine & Biomedical Sciences, Buffalo, New York, USA
| | - James F Howard
- Department of Neurology, University of North Carolina School of Medicine, Chapel Hill, North Carolina, USA
| | - Amy Visser
- Department of Neurology, Oregon Health & Science University, Portland, Oregon, USA
| | - Brian A Crum
- Department of Neurology, Mayo Clinic, Rochester, Minnesota, USA
| | - Richard Nowak
- Department of Neurology, Yale School of Medicine, New Haven, Connecticut, USA
| | - Rachel Beekman
- Department of Neurology, Yale School of Medicine, New Haven, Connecticut, USA
| | - Aditya Kumar
- Department of Neurology, Yale School of Medicine, New Haven, Connecticut, USA
| | - Katherine Ruzhansky
- Department of Neurology, Medical University of South Carolina, Charleston, South Carolina, USA
| | - I-Hweii Amy Chen
- Department of Neurology, Medical University of South Carolina, Charleston, South Carolina, USA
| | - Michael T Pulley
- Department of Neurology, University of Florida, Jacksonville, Florida, USA
| | - Shannon M Laboy
- Department of Neurology, University of Florida, Jacksonville, Florida, USA
| | - Melissa A Fellman
- Department of Neurology, University of Miami Health System, Miami, Florida, USA
| | - Diantha B Howard
- Larner College of Medicine, University of Vermont, 1 South Prospect Street, Burlington, Vermont 05401, USA
| | - Noah A Kolb
- Larner College of Medicine, University of Vermont, 1 South Prospect Street, Burlington, Vermont 05401, USA
| | - Shane M Greene
- Larner College of Medicine, University of Vermont, 1 South Prospect Street, Burlington, Vermont 05401, USA
| | - Mamatha Pasnoor
- Department of Neurology, University of Kansas Medical Center, Kansas City, Kansas, USA
| | - Mazen M Dimachkie
- Department of Neurology, University of Kansas Medical Center, Kansas City, Kansas, USA
| | - Richard J Barohn
- Department of Neurology, University of Kansas Medical Center, Kansas City, Kansas, USA
| | - Michael K Hehir
- Larner College of Medicine, University of Vermont, 1 South Prospect Street, Burlington, Vermont 05401, USA
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Beekman R, Greer DM, Brooks DC, Maciel CB. Author response: Clinical Reasoning: Prognostication after cardiac arrest: What do we really know? Neurology 2018; 91:103. [DOI: 10.1212/wnl.0000000000005770] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022] Open
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Burns A, Alsolami R, Becq J, Stamatopoulos B, Timbs A, Bruce D, Robbe P, Vavoulis D, Clifford R, Cabes M, Dreau H, Taylor J, Knight SJL, Mansson R, Bentley D, Beekman R, Martín-Subero JI, Campo E, Houlston RS, Ridout KE, Schuh A. Whole-genome sequencing of chronic lymphocytic leukaemia reveals distinct differences in the mutational landscape between IgHV mut and IgHV unmut subgroups. Leukemia 2017; 32:573. [PMID: 29160863 PMCID: PMC5808063 DOI: 10.1038/leu.2017.311] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022]
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Beekman R, Greer DM, Maciel CB. Poor neurologic outcomes after cardiac arrest; a spectrum with individual implications. Epilepsy Behav Case Rep 2017; 8:85-86. [PMID: 29159067 PMCID: PMC5678751 DOI: 10.1016/j.ebcr.2017.08.002] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Key Words] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Received: 06/21/2017] [Revised: 08/17/2017] [Accepted: 08/24/2017] [Indexed: 12/28/2022]
Affiliation(s)
- Rachel Beekman
- Department of Neurology, Yale School of Medicine, New Haven, CT 06510, United States
| | - David M Greer
- Department of Neurology, Boston University School of Medicine, Boston, MA 02118, United States
| | - Carolina B Maciel
- Department of Neurology, UF-Health Shands Hospital, University of Florida College of Medicine, Gainesville, FL 32611, United States
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Hehir MK, Hobson-Webb LD, Benatar M, Barnett C, Silvestri NJ, Howard JF, Howard D, Visser A, Crum BA, Nowak R, Beekman R, Kumar A, Ruzhansky K, Chen IHA, Pulley MT, LaBoy SM, Fellman MA, Greene SM, Pasnoor M, Burns TM. Rituximab as treatment for anti-MuSK myasthenia gravis: Multicenter blinded prospective review. Neurology 2017; 89:1069-1077. [PMID: 28801338 DOI: 10.1212/wnl.0000000000004341] [Citation(s) in RCA: 149] [Impact Index Per Article: 21.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/07/2017] [Accepted: 05/22/2017] [Indexed: 11/15/2022] Open
Abstract
OBJECTIVE To evaluate the efficacy of rituximab in treatment of anti-muscle-specific kinase (MuSK) myasthenia gravis (MG). METHODS This was a multicenter, blinded, prospective review, comparing anti-MuSK-positive patients with MG treated with rituximab to those not treated with rituximab. The primary clinical endpoint was the Myasthenia Gravis Status and Treatment Intensity (MGSTI), a novel outcome that combines the Myasthenia Gravis Foundation of America (MGFA) postintervention status (PIS) and the number and dosages of other immunosuppressant therapies used. A priori, an MGSTI of level ≤2 was used to define a favorable outcome. Secondary outcomes included modified MGFA PIS of minimal manifestations or better, mean/median prednisone dose, and mean/median doses of other immunosuppressant drugs. RESULTS Seventy-seven of 119 patients with anti-MuSK MG evaluated between January 1, 2005, and January 1, 2015, at 10 neuromuscular centers were selected for analysis after review of limited clinical data by a blinded expert panel. An additional 22 patients were excluded due to insufficient follow-up. Baseline characteristics were similar between the rituximab-treated patients (n = 24) and the controls (n = 31). Median follow-up duration was >3.5 years. At last visit, 58% (14/24) of rituximab-treated patients reached the primary outcome compared to 16% (5/31) of controls (p = 0.002). Number needed to treat for the primary outcome is 2.4. At last visit, 29% of rituximab-treated patients were taking prednisone (mean dose 4.5 mg/day) compared to 74% of controls (mean dose 13 mg/day) (p = 0.001 and p = 0.005). CLASSIFICATION OF EVIDENCE This study provides Class IV evidence that for patients with anti-MuSK MG, rituximab increased the probability of a favorable outcome.
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Affiliation(s)
- Michael K Hehir
- From the Larner College of Medicine at the University of Vermont (M.K.H., D.H., S.M.G.), Burlington; Duke University School of Medicine (L.D.H.-W.), Durham, NC; University of Miami Health System (M.B., M.A.F.), FL; University of Toronto School of Medicine (C.B.), Canada; SUNY Buffalo Jacobs School of Medicine (N.J.S.), NY; UNC School of Medicine (J.F.H.), Chapel Hill, NC; Mayo Clinic (A.V., B.A.C.), Rochester, MN; Yale School of Medicine (R.N., R.B., A.K.), New Haven, CT; Medical University of South Carolina (K.R., I.-H.A.C.), Columbia; University of Florida (M.T.P., S.M.L., Gainesville; University of Kansas Medical Center (M.P.), Kansas City; and University of Virginia School of Medicine (T.M.B.), Charlottesville.
| | - Lisa D Hobson-Webb
- From the Larner College of Medicine at the University of Vermont (M.K.H., D.H., S.M.G.), Burlington; Duke University School of Medicine (L.D.H.-W.), Durham, NC; University of Miami Health System (M.B., M.A.F.), FL; University of Toronto School of Medicine (C.B.), Canada; SUNY Buffalo Jacobs School of Medicine (N.J.S.), NY; UNC School of Medicine (J.F.H.), Chapel Hill, NC; Mayo Clinic (A.V., B.A.C.), Rochester, MN; Yale School of Medicine (R.N., R.B., A.K.), New Haven, CT; Medical University of South Carolina (K.R., I.-H.A.C.), Columbia; University of Florida (M.T.P., S.M.L., Gainesville; University of Kansas Medical Center (M.P.), Kansas City; and University of Virginia School of Medicine (T.M.B.), Charlottesville
| | - Michael Benatar
- From the Larner College of Medicine at the University of Vermont (M.K.H., D.H., S.M.G.), Burlington; Duke University School of Medicine (L.D.H.-W.), Durham, NC; University of Miami Health System (M.B., M.A.F.), FL; University of Toronto School of Medicine (C.B.), Canada; SUNY Buffalo Jacobs School of Medicine (N.J.S.), NY; UNC School of Medicine (J.F.H.), Chapel Hill, NC; Mayo Clinic (A.V., B.A.C.), Rochester, MN; Yale School of Medicine (R.N., R.B., A.K.), New Haven, CT; Medical University of South Carolina (K.R., I.-H.A.C.), Columbia; University of Florida (M.T.P., S.M.L., Gainesville; University of Kansas Medical Center (M.P.), Kansas City; and University of Virginia School of Medicine (T.M.B.), Charlottesville
| | - Carolina Barnett
- From the Larner College of Medicine at the University of Vermont (M.K.H., D.H., S.M.G.), Burlington; Duke University School of Medicine (L.D.H.-W.), Durham, NC; University of Miami Health System (M.B., M.A.F.), FL; University of Toronto School of Medicine (C.B.), Canada; SUNY Buffalo Jacobs School of Medicine (N.J.S.), NY; UNC School of Medicine (J.F.H.), Chapel Hill, NC; Mayo Clinic (A.V., B.A.C.), Rochester, MN; Yale School of Medicine (R.N., R.B., A.K.), New Haven, CT; Medical University of South Carolina (K.R., I.-H.A.C.), Columbia; University of Florida (M.T.P., S.M.L., Gainesville; University of Kansas Medical Center (M.P.), Kansas City; and University of Virginia School of Medicine (T.M.B.), Charlottesville
| | - Nicholas J Silvestri
- From the Larner College of Medicine at the University of Vermont (M.K.H., D.H., S.M.G.), Burlington; Duke University School of Medicine (L.D.H.-W.), Durham, NC; University of Miami Health System (M.B., M.A.F.), FL; University of Toronto School of Medicine (C.B.), Canada; SUNY Buffalo Jacobs School of Medicine (N.J.S.), NY; UNC School of Medicine (J.F.H.), Chapel Hill, NC; Mayo Clinic (A.V., B.A.C.), Rochester, MN; Yale School of Medicine (R.N., R.B., A.K.), New Haven, CT; Medical University of South Carolina (K.R., I.-H.A.C.), Columbia; University of Florida (M.T.P., S.M.L., Gainesville; University of Kansas Medical Center (M.P.), Kansas City; and University of Virginia School of Medicine (T.M.B.), Charlottesville
| | - James F Howard
- From the Larner College of Medicine at the University of Vermont (M.K.H., D.H., S.M.G.), Burlington; Duke University School of Medicine (L.D.H.-W.), Durham, NC; University of Miami Health System (M.B., M.A.F.), FL; University of Toronto School of Medicine (C.B.), Canada; SUNY Buffalo Jacobs School of Medicine (N.J.S.), NY; UNC School of Medicine (J.F.H.), Chapel Hill, NC; Mayo Clinic (A.V., B.A.C.), Rochester, MN; Yale School of Medicine (R.N., R.B., A.K.), New Haven, CT; Medical University of South Carolina (K.R., I.-H.A.C.), Columbia; University of Florida (M.T.P., S.M.L., Gainesville; University of Kansas Medical Center (M.P.), Kansas City; and University of Virginia School of Medicine (T.M.B.), Charlottesville
| | - Diantha Howard
- From the Larner College of Medicine at the University of Vermont (M.K.H., D.H., S.M.G.), Burlington; Duke University School of Medicine (L.D.H.-W.), Durham, NC; University of Miami Health System (M.B., M.A.F.), FL; University of Toronto School of Medicine (C.B.), Canada; SUNY Buffalo Jacobs School of Medicine (N.J.S.), NY; UNC School of Medicine (J.F.H.), Chapel Hill, NC; Mayo Clinic (A.V., B.A.C.), Rochester, MN; Yale School of Medicine (R.N., R.B., A.K.), New Haven, CT; Medical University of South Carolina (K.R., I.-H.A.C.), Columbia; University of Florida (M.T.P., S.M.L., Gainesville; University of Kansas Medical Center (M.P.), Kansas City; and University of Virginia School of Medicine (T.M.B.), Charlottesville
| | - Amy Visser
- From the Larner College of Medicine at the University of Vermont (M.K.H., D.H., S.M.G.), Burlington; Duke University School of Medicine (L.D.H.-W.), Durham, NC; University of Miami Health System (M.B., M.A.F.), FL; University of Toronto School of Medicine (C.B.), Canada; SUNY Buffalo Jacobs School of Medicine (N.J.S.), NY; UNC School of Medicine (J.F.H.), Chapel Hill, NC; Mayo Clinic (A.V., B.A.C.), Rochester, MN; Yale School of Medicine (R.N., R.B., A.K.), New Haven, CT; Medical University of South Carolina (K.R., I.-H.A.C.), Columbia; University of Florida (M.T.P., S.M.L., Gainesville; University of Kansas Medical Center (M.P.), Kansas City; and University of Virginia School of Medicine (T.M.B.), Charlottesville
| | - Brian A Crum
- From the Larner College of Medicine at the University of Vermont (M.K.H., D.H., S.M.G.), Burlington; Duke University School of Medicine (L.D.H.-W.), Durham, NC; University of Miami Health System (M.B., M.A.F.), FL; University of Toronto School of Medicine (C.B.), Canada; SUNY Buffalo Jacobs School of Medicine (N.J.S.), NY; UNC School of Medicine (J.F.H.), Chapel Hill, NC; Mayo Clinic (A.V., B.A.C.), Rochester, MN; Yale School of Medicine (R.N., R.B., A.K.), New Haven, CT; Medical University of South Carolina (K.R., I.-H.A.C.), Columbia; University of Florida (M.T.P., S.M.L., Gainesville; University of Kansas Medical Center (M.P.), Kansas City; and University of Virginia School of Medicine (T.M.B.), Charlottesville
| | - Richard Nowak
- From the Larner College of Medicine at the University of Vermont (M.K.H., D.H., S.M.G.), Burlington; Duke University School of Medicine (L.D.H.-W.), Durham, NC; University of Miami Health System (M.B., M.A.F.), FL; University of Toronto School of Medicine (C.B.), Canada; SUNY Buffalo Jacobs School of Medicine (N.J.S.), NY; UNC School of Medicine (J.F.H.), Chapel Hill, NC; Mayo Clinic (A.V., B.A.C.), Rochester, MN; Yale School of Medicine (R.N., R.B., A.K.), New Haven, CT; Medical University of South Carolina (K.R., I.-H.A.C.), Columbia; University of Florida (M.T.P., S.M.L., Gainesville; University of Kansas Medical Center (M.P.), Kansas City; and University of Virginia School of Medicine (T.M.B.), Charlottesville
| | - Rachel Beekman
- From the Larner College of Medicine at the University of Vermont (M.K.H., D.H., S.M.G.), Burlington; Duke University School of Medicine (L.D.H.-W.), Durham, NC; University of Miami Health System (M.B., M.A.F.), FL; University of Toronto School of Medicine (C.B.), Canada; SUNY Buffalo Jacobs School of Medicine (N.J.S.), NY; UNC School of Medicine (J.F.H.), Chapel Hill, NC; Mayo Clinic (A.V., B.A.C.), Rochester, MN; Yale School of Medicine (R.N., R.B., A.K.), New Haven, CT; Medical University of South Carolina (K.R., I.-H.A.C.), Columbia; University of Florida (M.T.P., S.M.L., Gainesville; University of Kansas Medical Center (M.P.), Kansas City; and University of Virginia School of Medicine (T.M.B.), Charlottesville
| | - Aditya Kumar
- From the Larner College of Medicine at the University of Vermont (M.K.H., D.H., S.M.G.), Burlington; Duke University School of Medicine (L.D.H.-W.), Durham, NC; University of Miami Health System (M.B., M.A.F.), FL; University of Toronto School of Medicine (C.B.), Canada; SUNY Buffalo Jacobs School of Medicine (N.J.S.), NY; UNC School of Medicine (J.F.H.), Chapel Hill, NC; Mayo Clinic (A.V., B.A.C.), Rochester, MN; Yale School of Medicine (R.N., R.B., A.K.), New Haven, CT; Medical University of South Carolina (K.R., I.-H.A.C.), Columbia; University of Florida (M.T.P., S.M.L., Gainesville; University of Kansas Medical Center (M.P.), Kansas City; and University of Virginia School of Medicine (T.M.B.), Charlottesville
| | - Katherine Ruzhansky
- From the Larner College of Medicine at the University of Vermont (M.K.H., D.H., S.M.G.), Burlington; Duke University School of Medicine (L.D.H.-W.), Durham, NC; University of Miami Health System (M.B., M.A.F.), FL; University of Toronto School of Medicine (C.B.), Canada; SUNY Buffalo Jacobs School of Medicine (N.J.S.), NY; UNC School of Medicine (J.F.H.), Chapel Hill, NC; Mayo Clinic (A.V., B.A.C.), Rochester, MN; Yale School of Medicine (R.N., R.B., A.K.), New Haven, CT; Medical University of South Carolina (K.R., I.-H.A.C.), Columbia; University of Florida (M.T.P., S.M.L., Gainesville; University of Kansas Medical Center (M.P.), Kansas City; and University of Virginia School of Medicine (T.M.B.), Charlottesville
| | - I-Hweii Amy Chen
- From the Larner College of Medicine at the University of Vermont (M.K.H., D.H., S.M.G.), Burlington; Duke University School of Medicine (L.D.H.-W.), Durham, NC; University of Miami Health System (M.B., M.A.F.), FL; University of Toronto School of Medicine (C.B.), Canada; SUNY Buffalo Jacobs School of Medicine (N.J.S.), NY; UNC School of Medicine (J.F.H.), Chapel Hill, NC; Mayo Clinic (A.V., B.A.C.), Rochester, MN; Yale School of Medicine (R.N., R.B., A.K.), New Haven, CT; Medical University of South Carolina (K.R., I.-H.A.C.), Columbia; University of Florida (M.T.P., S.M.L., Gainesville; University of Kansas Medical Center (M.P.), Kansas City; and University of Virginia School of Medicine (T.M.B.), Charlottesville
| | - Michael T Pulley
- From the Larner College of Medicine at the University of Vermont (M.K.H., D.H., S.M.G.), Burlington; Duke University School of Medicine (L.D.H.-W.), Durham, NC; University of Miami Health System (M.B., M.A.F.), FL; University of Toronto School of Medicine (C.B.), Canada; SUNY Buffalo Jacobs School of Medicine (N.J.S.), NY; UNC School of Medicine (J.F.H.), Chapel Hill, NC; Mayo Clinic (A.V., B.A.C.), Rochester, MN; Yale School of Medicine (R.N., R.B., A.K.), New Haven, CT; Medical University of South Carolina (K.R., I.-H.A.C.), Columbia; University of Florida (M.T.P., S.M.L., Gainesville; University of Kansas Medical Center (M.P.), Kansas City; and University of Virginia School of Medicine (T.M.B.), Charlottesville
| | - Shannon M LaBoy
- From the Larner College of Medicine at the University of Vermont (M.K.H., D.H., S.M.G.), Burlington; Duke University School of Medicine (L.D.H.-W.), Durham, NC; University of Miami Health System (M.B., M.A.F.), FL; University of Toronto School of Medicine (C.B.), Canada; SUNY Buffalo Jacobs School of Medicine (N.J.S.), NY; UNC School of Medicine (J.F.H.), Chapel Hill, NC; Mayo Clinic (A.V., B.A.C.), Rochester, MN; Yale School of Medicine (R.N., R.B., A.K.), New Haven, CT; Medical University of South Carolina (K.R., I.-H.A.C.), Columbia; University of Florida (M.T.P., S.M.L., Gainesville; University of Kansas Medical Center (M.P.), Kansas City; and University of Virginia School of Medicine (T.M.B.), Charlottesville
| | - Melissa A Fellman
- From the Larner College of Medicine at the University of Vermont (M.K.H., D.H., S.M.G.), Burlington; Duke University School of Medicine (L.D.H.-W.), Durham, NC; University of Miami Health System (M.B., M.A.F.), FL; University of Toronto School of Medicine (C.B.), Canada; SUNY Buffalo Jacobs School of Medicine (N.J.S.), NY; UNC School of Medicine (J.F.H.), Chapel Hill, NC; Mayo Clinic (A.V., B.A.C.), Rochester, MN; Yale School of Medicine (R.N., R.B., A.K.), New Haven, CT; Medical University of South Carolina (K.R., I.-H.A.C.), Columbia; University of Florida (M.T.P., S.M.L., Gainesville; University of Kansas Medical Center (M.P.), Kansas City; and University of Virginia School of Medicine (T.M.B.), Charlottesville
| | - Shane M Greene
- From the Larner College of Medicine at the University of Vermont (M.K.H., D.H., S.M.G.), Burlington; Duke University School of Medicine (L.D.H.-W.), Durham, NC; University of Miami Health System (M.B., M.A.F.), FL; University of Toronto School of Medicine (C.B.), Canada; SUNY Buffalo Jacobs School of Medicine (N.J.S.), NY; UNC School of Medicine (J.F.H.), Chapel Hill, NC; Mayo Clinic (A.V., B.A.C.), Rochester, MN; Yale School of Medicine (R.N., R.B., A.K.), New Haven, CT; Medical University of South Carolina (K.R., I.-H.A.C.), Columbia; University of Florida (M.T.P., S.M.L., Gainesville; University of Kansas Medical Center (M.P.), Kansas City; and University of Virginia School of Medicine (T.M.B.), Charlottesville
| | - Mamatha Pasnoor
- From the Larner College of Medicine at the University of Vermont (M.K.H., D.H., S.M.G.), Burlington; Duke University School of Medicine (L.D.H.-W.), Durham, NC; University of Miami Health System (M.B., M.A.F.), FL; University of Toronto School of Medicine (C.B.), Canada; SUNY Buffalo Jacobs School of Medicine (N.J.S.), NY; UNC School of Medicine (J.F.H.), Chapel Hill, NC; Mayo Clinic (A.V., B.A.C.), Rochester, MN; Yale School of Medicine (R.N., R.B., A.K.), New Haven, CT; Medical University of South Carolina (K.R., I.-H.A.C.), Columbia; University of Florida (M.T.P., S.M.L., Gainesville; University of Kansas Medical Center (M.P.), Kansas City; and University of Virginia School of Medicine (T.M.B.), Charlottesville
| | - Ted M Burns
- From the Larner College of Medicine at the University of Vermont (M.K.H., D.H., S.M.G.), Burlington; Duke University School of Medicine (L.D.H.-W.), Durham, NC; University of Miami Health System (M.B., M.A.F.), FL; University of Toronto School of Medicine (C.B.), Canada; SUNY Buffalo Jacobs School of Medicine (N.J.S.), NY; UNC School of Medicine (J.F.H.), Chapel Hill, NC; Mayo Clinic (A.V., B.A.C.), Rochester, MN; Yale School of Medicine (R.N., R.B., A.K.), New Haven, CT; Medical University of South Carolina (K.R., I.-H.A.C.), Columbia; University of Florida (M.T.P., S.M.L., Gainesville; University of Kansas Medical Center (M.P.), Kansas City; and University of Virginia School of Medicine (T.M.B.), Charlottesville
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Conjaerts SHP, Bruijnes JE, Beerhorst K, Beekman R. [Nitrous oxide-induced polyneuropathy]. Ned Tijdschr Geneeskd 2017; 161:D2044. [PMID: 29192578] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 06/07/2023]
Abstract
Nitrous oxide, laughing gas, is used as a party drug to achieve a euphoric effect. It has been gaining popularity in recent years and is considered a relatively innocent substance. Nitrous oxide is known to cause subacute degeneration of the spinal cord by inactivation of active vitamin B12. Vitamin B12 plays an essential role in the synthesis of myelin. Hence, vitamin B12 deficiency can lead to degeneration of the dorsal and lateral columns of the spinal cord. Polyneuropathy is a less known complication. We present a 17-year-old woman and a 19-year-old man with subacute axonal polyneuropathy caused by laughing gas abuse. Abstinence of laughing gas and treatment with intramuscular and oral vitamin B12 suppletion respectively have led to improvement of their symptoms. Our cases demonstrate a less-known but treatable complication of laughing gas.
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Affiliation(s)
- S H P Conjaerts
- Zuyderland Medisch Centrum, afd. Neurologie, locatie Heerlen
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30
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Visser LH, Beekman R, Tijssen CC, Uitdehaag BMJ, Lee ML, Movig KLL, Lenderink AW. A randomized, double-blind, placebo-controlled pilot study of IV immune globulins in combination with IV methylprednisolone in the treatment of relapses in patients with MS. Mult Scler 2016; 10:89-91. [PMID: 14760960 DOI: 10.1191/1352458504ms978sr] [Citation(s) in RCA: 64] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/05/2022]
Abstract
Background: Some patients with multiple sclerosis (MS) do not show a clear improvement of acute relapses after treatment with intravenous methylprednisolone (IVMP). We compared the efficacy of the combination of intravenous immunoglobulins (IVIg) and IVMP with the standard treatment of IVMP alone in promoting recovery from moderate to severe acute relapses in MS. Methods: Patients with clinically definite MS having a relapse with at least a one point increase in Kurtzke’s expanded disability status scale (EDSS) in comparison to the preattack EDSS were randomized to IVMP-IVIg or IVMP-placebo treatment. The primary outcome criterion was the EDSS grade at four weeks. A preplanned interim analysis was performed after inclusion of 19 consecutive MS patients to evaluate the sample size necessary for a larger trial. Findings: Both groups had improved one point on the EDSS four weeks after start of treatment (P =0.81) and one of the stopping rules of the interim analysis was fulfilled. There were also no differences in secondary outcomes: EDSS at eight and 12 weeks, time to improve]-1 EDSS points, difference in Scripps score and ambulation index. Five patients in the IVMP-IVIg group and two in the IVMP group had a new relapse in the six month follow-up. Interpretation: O ur study could not show superiority of IVMP-IVIg in the treatment of moderate to severe acute relapses in MS.
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Affiliation(s)
- L H Visser
- Department of Neurology, St. Elisabeth Hospital, Tilburg, The Netherlands.
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31
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Charvet LE, Beekman R, Amadiume N, Belman AL, Krupp LB. The Symbol Digit Modalities Test is an effective cognitive screen in pediatric onset multiple sclerosis (MS). J Neurol Sci 2014; 341:79-84. [DOI: 10.1016/j.jns.2014.04.006] [Citation(s) in RCA: 41] [Impact Index Per Article: 4.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/04/2014] [Revised: 03/08/2014] [Accepted: 04/05/2014] [Indexed: 11/29/2022]
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32
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Goedee HS, Brekelmans GJF, van Asseldonk JTH, Beekman R, Mess WH, Visser LH. High resolution sonography in the evaluation of the peripheral nervous system in polyneuropathy - a review of the literature. Eur J Neurol 2013; 20:1342-51. [DOI: 10.1111/ene.12182] [Citation(s) in RCA: 88] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/15/2013] [Accepted: 03/25/2013] [Indexed: 12/20/2022]
Affiliation(s)
- H. S. Goedee
- Department of Neurology and Clinical Neurophysiology; St Elisabeth Hospital; Tilburg; The Netherlands
| | - G. J. F. Brekelmans
- Department of Neurology and Clinical Neurophysiology; St Elisabeth Hospital; Tilburg; The Netherlands
| | | | - R. Beekman
- Department of Neurology; Atrium Medical Centre; Heerlen; The Netherlands
| | - W. H. Mess
- Department of Clinical Neurophysiology; Maastricht University Medical Centre; Maastricht; The Netherlands
| | - L. H. Visser
- Department of Neurology and Clinical Neurophysiology; St Elisabeth Hospital; Tilburg; The Netherlands
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33
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Skokowa J, Steinemann D, Zeidler C, Makaryan V, Beekman R, Klimiankou M, Ünalan M, Kandabarau S, Schnittger S, Kohlmann A, Valkhof MG, Hoogenboezem R, Göhring G, Schlegelberger B, Stanulla M, Vandenberghe P, Donadieu J, Touw IP, Dale DC, Welte K. The Association of Mutations in RUNX1 and CSF3R with the Development of Leukemia in Severe Congenital Neutropenia: A unique pathway in leukemogenesis. Klin Padiatr 2013. [DOI: 10.1055/s-0033-1343625] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/26/2022]
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34
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Beekman R, Schreuder AHCML, Rozeman CAM, Koehler PJ, Uitdehaag BMJ. The diagnostic value of provocative clinical tests in ulnar neuropathy at the elbow is marginal. J Neurol Neurosurg Psychiatry 2009; 80:1369-74. [PMID: 19553231 DOI: 10.1136/jnnp.2009.180844] [Citation(s) in RCA: 29] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/03/2022]
Abstract
BACKGROUND Provocative clinical tests are often performed in the diagnosis of ulnar neuropathy at the elbow (UNE) although the evidence for the usefulness of these tests is limited. The aim of this study was to determine the diagnostic value of provocative clinical tests in the diagnosis of UNE in a relevant spectrum of patients and controls. METHODS A prospective cohort study was performed in consecutive patients clinically suspected of having UNE. All patients underwent a neurological examination and four commonly used provocative clinical tests (Tinel's test, flexion compression test, palpating for local ulnar nerve tenderness and nerve thickening). Subsequently, in all patients a reference standard test comprising electrophysiological studies and neurosonography was independently assessed. RESULTS 192 eligible patients completed the study protocol. UNE was diagnosed in 137 and an alternative diagnosis was made in 55 patients. The sensitivity, specificity, and positive and negative predictive values were as follows: Tinel's test 62%, 53%, 77% and 30%; flexion compression test 61%, 40%, 72% and 29%; palpating for nerve thickening 28%, 87%, 84% and 33%; and palpating for nerve tenderness 32%, 80%, 80% and 32%. Logistic regression and receiver operating characteristic curves showed that the added value of one or more provocative tests over routine clinical examination is minimal. CONCLUSION The diagnostic value of provocative clinical tests in UNE is poor.
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Affiliation(s)
- R Beekman
- Department of Neurology, Atrium Medical Centre, Heerlen, The Netherlands.
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35
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Klomp CMC, van den Broek MWC, Buijs J, Beekman R. [Reversible posterior leucoencephalopathy due to hypercalcaemia]. Ned Tijdschr Geneeskd 2006; 150:505-8. [PMID: 16553051] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 05/07/2023]
Abstract
A 60-year-old woman presented with changes in behaviour, cognition, cortical blindness and headache. These symptoms were caused by a reversible posterior leucoencephalopathy syndrome due to hypercalcaemia caused by a multiple myeloma, type IgD wavelength. She was treated with isotonic saline and pamidronate; the serum calcium levels normalised and the radiological brain abnormalities disappeared as did the clinical neurological abnormalities. Hypercalcaemia probably affects cerebral perfusion and has direct neurotoxic effects which can lead to cerebral oedema. This case history illustrates a rare cause of a syndrome that can be easily treated and is completely reversible.
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Affiliation(s)
- C M C Klomp
- Atrium Medisch Centrum, Postbus 4446, 6401 CX Heerlen.
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36
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Beekman R, van den Berg LH, Franssen H, Visser LH, van Asseldonk JTH, Wokke JHJ. Ultrasonography shows extensive nerve enlargements in multifocal motor neuropathy. Neurology 2006; 65:305-7. [PMID: 16043806 DOI: 10.1212/01.wnl.0000169179.67764.30] [Citation(s) in RCA: 148] [Impact Index Per Article: 8.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/19/2022] Open
Abstract
Using ultrasonography we found multiple sites with nerve enlargement along the course of the brachial plexus, median, ulnar, and radial nerves in the majority of 21 patients with multifocal motor neuropathy. Sonography and electrophysiologic studies showed more abnormalities than expected on purely clinical grounds. Moreover, sonography revealed nerve enlargement without clinical or electrophysiologic abnormalities.
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Affiliation(s)
- R Beekman
- Department of Neurology, Rudolf Magnus Institute of Neuroscience, University Medical Centre, Utrecht, The Netherlands.
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37
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Beekman R, Schoemaker MC, Van Der Plas JPL, Van Den Berg LH, Franssen H, Wokke JHJ, Uitdehaag BMJ, Visser LH. Diagnostic value of high-resolution sonography in ulnar neuropathy at the elbow. Neurology 2004; 62:767-73. [PMID: 15007128 DOI: 10.1212/01.wnl.0000113733.62689.0d] [Citation(s) in RCA: 178] [Impact Index Per Article: 8.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/25/2022] Open
Abstract
OBJECTIVE To determine the diagnostic value of high-resolution sonography in ulnar neuropathy at the elbow (UNE). METHODS Sonographic ulnar nerve diameter measurement was compared at three levels around the medial epicondyle with a criterion standard including clinical and electrophysiologic characteristics in a cohort of 123 patients presenting with clinical signs of UNE. UNE or probable UNE was diagnosed in 84 patients and a different condition in 39 patient controls. Reference values were obtained in 56 healthy volunteers. RESULTS One hundred thirty-six affected arms were studied in 123 patients (UNE in 82, probable UNE in 9, and a different condition in 45 affected arms). Patients with UNE had a larger ulnar nerve diameter than patient controls (p < 0.0001). The sensitivity of sonography was 80%, specificity 91%, positive likelihood ratio 9, and negative likelihood ratio 0.2. The highest diagnostic yield was found in patients in whom electrodiagnostic studies showed signs of ulnar neuropathy but could not localize the lesion (17/20 cases, 86%) and in patients who had motor conduction velocity slowing across the elbow without conduction block (32/37 cases, 86%). CONCLUSIONS High-resolution sonography is an accurate and easily applied test for the diagnosis of UNE. The authors recommend its use in addition to electrodiagnostic studies because it improves the reliability of the diagnosis of UNE.
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Affiliation(s)
- R Beekman
- Department of Neurology, St. Elisabeth Hospital, TweeSteden Hospital, Tilburg, VU Medical Centre, Amsterdam, the Netherlands.
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Abstract
OBJECTIVE To determine the outcome in patients with ulnar neuropathy at the elbow (UNE) treated surgically or conservatively, and the prognostic value of clinical, sonographic, and electrophysiologic features. METHODS After a median follow-up of 14 months, 69 of 84 patients initially included in a prospective blinded study on the diagnostic value of sonography in UNE were re-evaluated. The patients underwent renewed systematic clinical and sonographic examination. Patients were scored as having a poor (stable or progressive symptoms) or favorable (complete remission of symptoms or improvement) outcome. RESULTS Of the 74 initially affected arms, 12 (16%) had a complete remission, 21 (28%) improved, 25 (34%) remained stable, and 16 (22%) had progression. Surgically treated patients (28 arms) had a more favorable outcome than those treated conservatively (p = 0.03). After surgery, the mean ulnar nerve diameter decreased from 3.2 to 2.9 mm (p = 0.03), while this was not seen after conservative treatment. Multiple logistic regression analysis showed that more outspoken nerve enlargement found during sonography at the time of the diagnosis was associated with a poor outcome (OR: 2.9, p = 0.009). Furthermore, the presence of a motor conduction block (OR: 0.2, p = 0.03) and motor velocity slowing across the elbow (OR: 0.1, p = 0.01) were associated with a favorable outcome. CONCLUSION More pronounced ulnar nerve thickening at the time of the diagnosis is associated with poor outcome at follow-up, especially in conservatively treated cases, while electrodiagnostic signs of demyelination on testing indicate favorable outcome.
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Affiliation(s)
- R Beekman
- Department of Neurology, Atrium Medical Center, PO Box 4446, 6401 CX Heerlen, The Netherlands.
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39
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Abstract
High-resolution sonography is capable of depicting peripheral nerves and the brachial plexus. In this study we review the literature on this subject. Normal peripheral nerves have a characteristic echotexture. Most nerves are readily visualized, although this is not always the case with the nerves of the lower extremity. The main pathological changes that can be demonstrated are nerve enlargement and increased hypoechogenicity. In order to demonstrate nerve enlargement, measurements should be performed and compared with a set of reference values. Several neuropathies have been studied by means of ultrasonography. However, many studies concern case reports and show methodological shortcomings. The best studied peripheral neuropathy is the carpal tunnel syndrome in which ultrasonography seems to have an additional value when combined with nerve conduction studies. Nerve enlargement has also been demonstrated in radial neuropathy at the humerus and in ulnar neuropathy at the elbow. The role of sonography in various hereditary and inflammatory neuropathies is uncertain although diffuse nerve thickening could be demonstrated. Further systematic studies are needed to determine the role of sonography in the diagnostic process of the various neuropathies. It would be important to study the subcategories of patients in whom electrodiagnostic studies are normal or show equivocal findings.
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Affiliation(s)
- R Beekman
- Department of Neurology, University Medical Centre, Utrecht, The Netherlands.
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40
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Abstract
OBJECTIVE To describe three cases of migraine (two with aura) after an intracranial endovascular procedure. Method.-Retrospective. RESULTS One patient had an attack of migraine with prolonged aura after embolization of a dural arteriovenous fistula. Another patient had an attack of migraine with aura (and hemiparesis) after a diagnostic angiogram. The third patient already suffered from migraine with aura and had a migraine attack after embolization of an occipital arteriovenous malformation. A quadrantanopia persisted in this patient. Outcome of the other two patients was good. CONCLUSION Intracranial endovascular procedures can induce migraine with aura. We could not identify the underlying pathophysiological mechanism, but mechanical, chemical, immunological, or hemodynamic factors could be involved.
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Affiliation(s)
- R Beekman
- Departments of Neurology, St. Elisabeth Hospital, Tilburg, The Netherlands; Radiology, St. Elisabeth Hospital, Tilburg, The Netherlands; Neurosurgery, St. Elisabeth Hospital, Tilburg, The Netherlands
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41
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Heinrichs M, Beekman R, Limburg M. Simulation to estimate the capacity of a stroke unit. Stud Health Technol Inform 2001; 77:47-50. [PMID: 11187595] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/19/2023]
Abstract
Preceding the implementation of a Stroke Unit (SU), data have been collected and used for building a simulation model of patient flow. This model was subsequently used to estimate the optimal capacity of the SU to be implemented. Because stroke patients require acute hospital care, this implies a highly variable number of immediate admissions. This variability complicates optimizing the capacity. In order to support decisions with regard to staffing (i.e. capacity) of the SU, different scenarios are simulated and compared to provide insight in the trade-off between regular understaffing and a low bed occupancy rate. In 1996 the Department of Neurology of the Academic Medical Center in the Netherlands implemented its SU to improve the quality of care for stroke patients. Data collected in the years 1997 and 1998 that the SU has been operational were evaluated and confirm the predictions made from simulating different scenarios. We conclude that simulation models provide a powerful tool for supporting decision making with regard to resource planning at the departmental level in our hospital.
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Affiliation(s)
- M Heinrichs
- Dept. Clinical Informatics, Academic Medical Center, Amsterdam, The Netherlands
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Abstract
One hundred consecutive patients with myasthenia gravis (MG) referred between 1985 and 1989 were analysed for epidemiological characteristics, evolution of early signs, delay in diagnosis, yield of diagnostic tests and effects of treatment. The female to male ratio was 1.6:1.0. Sixteen patients had a thymoma. Ocular MG occurred in 14. Associated autoimmune diseases were found in 15 patients. In 34% of the women and 10% of the men the diagnosis was delayed for more than 2 years. In the first 3 months progression was more rapid in men than in women. Anti-acetylcholine receptor antibodies were found in 94% of the patients with generalized MG and in 29% of the ocular patients. The neostigmine or the edrophonium test was positive in 84% of the generalized and in 60% of the ocular patients. Electromyography was diagnostic in 71% of the generalized and in 42% of the ocular patients tested. Thymectomy was performed in 56 patients (12 with thymomas). Fifty-one per cent were treated with one or more immunosuppressive drugs, at any time. After a mean follow-up of 9.6 years after onset remissions had occurred in 43%, considerable improvement in 25%, moderate improvement in 20% and 12% remained unchanged. There were no deaths due to MG. Thirty-six per cent remained dependent on immunosuppressive drugs. Medication-free remission was most frequent (35%) in the early-onset (< 50 years) group. Side-effects of pyridostigmine were noted in 34% of 99 patients, of prednisone in 65% of 49 patients, and of azathioprine in 54% of 28 patients, but these necessitated stopping the drug in only 1%, 10% and 14% respectively.
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Affiliation(s)
- R Beekman
- Department of Neurology, University Hospital, Groningen, The Netherlands
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43
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Beekman R, Kuks J, Oosterhuis H. Myasthenia gravis, diagnosis and follow up. Neuromuscul Disord 1994. [DOI: 10.1016/0960-8966(94)90117-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/27/2022]
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Beekman R, Oosterhuis HJ. [Use of alternative treatments by patients with myasthenia gravis]. Ned Tijdschr Geneeskd 1994; 138:294-6. [PMID: 8121511] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 01/28/2023]
Abstract
OBJECTIVE To analyse the use of alternative treatments by patients before and after myasthenia gravis was diagnosed, and the influence on the diagnostic delay. DESIGN Retrospective study. SETTING University Hospital Groningen, Netherlands. METHOD A questionnaire was sent to 90 consecutive patients with myasthenia gravis to inquire about their use of alternative treatments. RESULTS Of the 72 respondents 18 had used alternative treatments. Of these 11 had even done so before diagnosis. The most important reason for the use was the lack of understanding and trust that these patients said they experienced from their regular doctors. Almost all patients discontinued alternative treatment when it became clear that it had no effect. Compared with those not using alternatives, the diagnosis was delayed in the group of patients using alternative treatments, but not significantly. CONCLUSION More attention for patients with chronic and undefined complaints may shorten the delay in diagnosing and treating myasthenia gravis adequately.
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Affiliation(s)
- R Beekman
- Academisch Ziekenhuis, afd. Neurologie, Groningen
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Christos S, Katch VL, Beekman R, Eakin D, Lindauer A, Crowley D, Katch FI. HEMODYNAMIC RESPONSES TO UPRIGHT CYCLING OF ADOLESCENT CARDIAC TRANSPLANT PATIENTS. Med Sci Sports Exerc 1992. [DOI: 10.1249/00005768-199205001-00520] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022]
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Beekman R, Ehling T, Kuks J, Oosterhuis H. Epidemiological data of 100 recent myasthenic patients. J Autoimmun 1991. [DOI: 10.1016/0896-8411(91)90102-i] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/26/2022]
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47
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Abstract
Prior to echocardiography, the recognition of serious heart disease in the cyanotic newborn or young infant could be extremely difficult. The profound hemodynamic changes taking place in the heart and lungs after birth influence the clinical manifestations of many cardiac disorders, and sometimes suggest the existence of a cardiac disorder when none is present. Real time echocardiography has revolutionalized the diagnosis of the cyanotic infant. If the reason for the infant's cyanosis or respiratory distress is not apparent from the history, physical examination, laboratory values, and chest radiograph; real time echocardiography should be performed to exclude or diagnose cyanotic congenital heart disease and persistent fetal circulation. This will prevent misdiagnosis in cyanotic infants and assure rapid and appropriate treatment.
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Affiliation(s)
- F M Unger
- Department of Radiology, Children's Medical Center, Dayton, OH 45404
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48
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49
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Abstract
This article reviews the available literature on the validity and reliability of the non-invasive techniques, commonly known as CO2 rebreathing, for estimating cardiac output. The differing indirect methodologies are described and illustrated. A table, constructed from the available literature, comparing criterion versus estimated cardiac outputs is presented. The varying combinations of methods employed, differing measurement conditions, i.e. rest and exercise, and divergent populations are illustrated and discussed. The correlation between criterion and estimated cardiac output for these studies ranged from r = 0.09 to 0.96, with a % standard deviation of the differences of 1.5 to 176.8%. The Collier and end-tidal methods, in conjunction with either the Comroe or McHardy CO2 dissociation curve appears to be the most established, valid and reliable combination of methods for estimating resting cardiac output. These methods appear to be comparable to the combination of the Defares, end-tidal and Comroe curve methods for estimating cardiac output during exercise. Because of the potential for large errors, caution is urged when interpreting cardiac output results based on indirect estimation for individual assessment, or for subjects with certain types of pulmonary or heart diseases.
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Gidding SS, Rocchini AP, Beekman R, Szpunar CA, Moorehead C, Behrendt D, Rosenthal A. Therapeutic effect of propranolol on paradoxical hypertension after repair of coarctation of the aorta. N Engl J Med 1985; 312:1224-8. [PMID: 3887159 DOI: 10.1056/nejm198505093121904] [Citation(s) in RCA: 53] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/07/2023]
Abstract
Patients undergoing repair of coarctation of the aorta often have self-limited but severe hypertension in the first week after surgery (paradoxical hypertension). We conducted a controlled trial of treatment with propranolol before repair of coarctation of the aorta in 14 children to determine whether the drug would prevent paradoxical hypertension. Seven patients were randomly assigned to receive propranolol for two weeks before surgery and throughout the first postoperative week, and seven patients were assigned to receive standard postoperative care. Both groups had a similar significant (P less than 0.05) increase in the plasma norepinephrine level in response to surgery; however, when compared with no treatment, treatment with propranolol reduced not only the rise in systolic (P = 0.004) and diastolic (P = 0.003) blood pressure but also the postoperative increase in plasma renin activity (P less than 0.01). We conclude that prophylactic propranolol can prevent paradoxical hypertension and should therefore become a routine part of the operative care of patients with coarctation of the aorta.
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