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Calabrese E, Gandhi S, Shih J, Otero M, Randazzo D, Hemphill C, Huie R, Talbott JF, Amorim E. Parieto-Occipital Injury on Diffusion MRI Correlates with Poor Neurologic Outcome following Cardiac Arrest. AJNR Am J Neuroradiol 2023; 44:254-260. [PMID: 36797027 PMCID: PMC10187825 DOI: 10.3174/ajnr.a7779] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/28/2022] [Accepted: 01/03/2023] [Indexed: 02/18/2023]
Abstract
BACKGROUND AND PURPOSE MR imaging of the brain provides unbiased neuroanatomic evaluation of brain injury and is useful for neurologic prognostication following cardiac arrest. Regional analysis of diffusion imaging may provide additional prognostic value and help reveal the neuroanatomic underpinnings of coma recovery. The purpose of this study was to evaluate global, regional, and voxelwise differences in diffusion-weighted MR imaging signal in patients in a coma after cardiac arrest. MATERIALS AND METHODS We retrospectively analyzed diffusion MR imaging data from 81 subjects who were comatose for >48 hours following cardiac arrest. Poor outcome was defined as the inability to follow simple commands at any point during hospitalization. ADC differences between groups were evaluated across the whole brain, locally by using voxelwise analysis and regionally by using ROI-based principal component analysis. RESULTS Subjects with poor outcome had more severe brain injury as measured by lower average whole-brain ADC (740 [SD, 102] × 10-6 mm2/s versus 833 [SD, 23] × 10-6 mm2/s, P < .001) and larger average volumes of tissue with ADC below 650 × 10-6 mms/s (464 [SD, 469] mL versus 62 [SD, 51] mL, P < .001). Voxelwise analysis showed lower ADC in the bilateral parieto-occipital areas and perirolandic cortices for the poor outcome group. ROI-based principal component analysis showed an association between lower ADC in parieto-occipital regions and poor outcome. CONCLUSIONS Brain injury affecting the parieto-occipital region measured with quantitative ADC analysis was associated with poor outcomes after cardiac arrest. These results suggest that injury to specific brain regions may influence coma recovery.
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Affiliation(s)
- E Calabrese
- From the Department of Radiology and Biomedical Imaging (E.C., S.G., J.F.T.)
| | - S Gandhi
- From the Department of Radiology and Biomedical Imaging (E.C., S.G., J.F.T.)
- Department of Radiology and Biomedical Imaging (S.G., J.F.T., E.A.), Zuckerberg San Francisco General Hospital, San Francisco, California
| | - J Shih
- Department of Neurology (J.S., M.O., D.R., C.H., E.A.), Weill Institute for Neurosciences
| | - M Otero
- Department of Neurology (J.S., M.O., D.R., C.H., E.A.), Weill Institute for Neurosciences
| | - D Randazzo
- Department of Neurology (J.S., M.O., D.R., C.H., E.A.), Weill Institute for Neurosciences
| | - C Hemphill
- Department of Neurology (J.S., M.O., D.R., C.H., E.A.), Weill Institute for Neurosciences
| | - R Huie
- Department of Neurological Surgery (R.H.), University of California, San Francisco, San Francisco, California
| | - J F Talbott
- From the Department of Radiology and Biomedical Imaging (E.C., S.G., J.F.T.)
- Department of Radiology and Biomedical Imaging (S.G., J.F.T., E.A.), Zuckerberg San Francisco General Hospital, San Francisco, California
| | - E Amorim
- Department of Neurology (J.S., M.O., D.R., C.H., E.A.), Weill Institute for Neurosciences
- Department of Radiology and Biomedical Imaging (S.G., J.F.T., E.A.), Zuckerberg San Francisco General Hospital, San Francisco, California
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Free water corrected diffusion tensor imaging discriminates between good and poor outcomes of comatose patients after cardiac arrest. Eur Radiol 2023; 33:2139-2148. [PMID: 36418623 PMCID: PMC9935650 DOI: 10.1007/s00330-022-09245-w] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/25/2022] [Revised: 08/26/2022] [Accepted: 10/16/2022] [Indexed: 11/25/2022]
Abstract
OBJECTIVES Approximately 50% of comatose patients after cardiac arrest never regain consciousness. Cerebral ischaemia may lead to cytotoxic and/or vasogenic oedema, which can be detected by diffusion tensor imaging (DTI). Here, we evaluate the potential value of free water corrected mean diffusivity (MD) and fractional anisotropy (FA) based on DTI, for the prediction of neurological recovery of comatose patients after cardiac arrest. METHODS A total of 50 patients after cardiac arrest were included in this prospective cohort study in two Dutch hospitals. DTI was obtained 2-4 days after cardiac arrest. Outcome was assessed at 6 months, dichotomised as poor (cerebral performance category 3-5; n = 20) or good (n = 30) neurological outcome. We calculated the whole brain mean MD and FA and compared between patients with good and poor outcomes. In addition, we compared a preliminary prediction model based on clinical parameters with or without the addition of MD and FA. RESULTS We found significant differences between patients with good and poor outcome of mean MD (good: 726 [702-740] × 10-6 mm2/s vs. poor: 663 [575-736] × 10-6 mm2/s; p = 0.01) and mean FA (0.30 ± 0.03 vs. 0.28 ± 0.03; p = 0.03). An exploratory prediction model combining clinical parameters, MD and FA increased the sensitivity for reliable prediction of poor outcome from 60 to 85%, compared to the model containing clinical parameters only, but confidence intervals are overlapping. CONCLUSIONS Free water-corrected MD and FA discriminate between patients with good and poor outcomes after cardiac arrest and hold the potential to add to multimodal outcome prediction. KEY POINTS • Whole brain mean MD and FA differ between patients with good and poor outcome after cardiac arrest. • Free water-corrected MD can better discriminate between patients with good and poor outcome than uncorrected MD. • A combination of free water-corrected MD (sensitive to grey matter abnormalities) and FA (sensitive to white matter abnormalities) holds potential to add to the prediction of outcome.
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Qureshi AY, Stevens RD. Mapping the Unconscious Brain: Insights From Advanced Neuroimaging. J Clin Neurophysiol 2022; 39:12-21. [PMID: 34474430 DOI: 10.1097/wnp.0000000000000846] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/18/2023] Open
Abstract
SUMMARY Recent advances in neuroimaging have been a preeminent factor in the scientific effort to unravel mechanisms of conscious awareness and the pathophysiology of disorders of consciousness. In the first part of this review, we selectively discuss operational models of consciousness, the biophysical signal that is measured using different imaging modalities, and knowledge on disorders of consciousness that has been gleaned with each neuroimaging modality. Techniques considered include diffusion-weighted imaging, diffusion tensor imaging, different types of nuclear medicine imaging, functional MRI, magnetoencephalography, and the combined transcranial magnetic stimulation-electroencephalography approach. In the second part of this article, we provide an overview of how advanced neuroimaging can be leveraged to support neurological prognostication, the use of machine learning to process high-dimensional imaging data, potential applications in clinical practice, and future directions.
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Affiliation(s)
- Abid Y Qureshi
- Department of Neurology, University of Kansas Medical Center, Kansas City, Missouri, U.S.A.; and
| | - Robert D Stevens
- Departments of Anesthesiology and Critical Care, Neurology, Radiology, and Neurosurgery, Johns Hopkins University School of Medicine, Baltimore, Maryland, U.S.A
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Bauerschmidt A, Eliseyev A, Doyle KW, Velasquez A, Egbebike J, Chiu W, Kumar V, Alkhachroum A, Der Nigoghossian C, Al-Mufti F, Rabbani L, Brodie D, Rubinos C, Park S, Roh D, Agarwal S, Claassen J. Predicting early recovery of consciousness after cardiac arrest supported by quantitative electroencephalography. Resuscitation 2021; 165:130-137. [PMID: 34166746 PMCID: PMC10008439 DOI: 10.1016/j.resuscitation.2021.06.008] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/17/2021] [Revised: 06/03/2021] [Accepted: 06/16/2021] [Indexed: 01/27/2023]
Abstract
OBJECTIVE To determine the ability of quantitative electroencephalography (QEEG) to improve the accuracy of predicting recovery of consciousness by post-cardiac arrest day 10. METHODS Unconscious survivors of cardiac arrest undergoing daily clinical and EEG assessments through post-cardiac arrest day 10 were studied in a prospective observational cohort study. Power spectral density, local coherence, and permutation entropy were calculated from daily EEG clips following a painful stimulus. Recovery of consciousness was defined as following at least simple commands by day 10. We determined the impact of EEG metrics to predict recovery when analyzed with established predictors of recovery using partial least squares regression models. Explained variance analysis identified which features contributed most to the predictive model. RESULTS 367 EEG epochs from 98 subjects were analyzed in conjunction with clinical measures. Highest prediction accuracy was achieved when adding QEEG features from post-arrest days 4-6 to established predictors (area under the receiver operating curve improved from 0.81 ± 0.04 to 0.86 ± 0.05). Prediction accuracy decreased from 0.84 ± 0.04 to 0.79 ± 0.04 when adding QEEG features from post-arrest days 1-3. Patients with recovery of command-following by day 10 showed higher coherence across the frequency spectrum and higher centro-occipital delta-frequency spectral power by days 4-6, and globally-higher theta range permutation entropy by days 7-10. CONCLUSIONS Adding quantitative EEG metrics to established predictors of recovery allows modest improvement of prediction accuracy for recovery of consciousness, when obtained within a week of cardiac arrest. Further research is needed to determine the best strategy for integration of QEEG data into prognostic models in this patient population.
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Affiliation(s)
- Andrew Bauerschmidt
- Department of Neurology, Columbia University Medical Center, New York, NY, USA
| | - Andrey Eliseyev
- Department of Neurology, Columbia University Medical Center, New York, NY, USA
| | - Kevin W Doyle
- Department of Neurology, Columbia University Medical Center, New York, NY, USA
| | - Angela Velasquez
- Department of Neurology, Columbia University Medical Center, New York, NY, USA
| | - Jennifer Egbebike
- Department of Neurology, Columbia University Medical Center, New York, NY, USA
| | - Wendy Chiu
- Department of Neurology, Columbia University Medical Center, New York, NY, USA
| | - Vedika Kumar
- Department of Neurology, Columbia University Medical Center, New York, NY, USA
| | - Ayham Alkhachroum
- Department of Neurology, Columbia University Medical Center, New York, NY, USA
| | | | - Fawaz Al-Mufti
- Department of Neurology, Columbia University Medical Center, New York, NY, USA
| | - LeRoy Rabbani
- Cardiac Care Unit, Department of Medicine, Columbia University Medical Center, New York, NY, USA
| | - Daniel Brodie
- Division of Pulmonary, Allergy and Critical Care Medicine, Department of Medicine, Columbia University Medical Center, New York, NY, USA
| | - Clio Rubinos
- Department of Neurology, Columbia University Medical Center, New York, NY, USA
| | - Soojin Park
- Department of Neurology, Columbia University Medical Center, New York, NY, USA
| | - David Roh
- Department of Neurology, Columbia University Medical Center, New York, NY, USA
| | - Sachin Agarwal
- Department of Neurology, Columbia University Medical Center, New York, NY, USA
| | - Jan Claassen
- Department of Neurology, Columbia University Medical Center, New York, NY, USA.
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Forgacs PB, Devinsky O, Schiff ND. Independent Functional Outcomes after Prolonged Coma following Cardiac Arrest: A Mechanistic Hypothesis. Ann Neurol 2020; 87:618-632. [PMID: 31994749 PMCID: PMC7393600 DOI: 10.1002/ana.25690] [Citation(s) in RCA: 24] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2019] [Revised: 01/23/2020] [Accepted: 01/23/2020] [Indexed: 01/26/2023]
Abstract
OBJECTIVE Survivors of prolonged (>2 weeks) post-cardiac arrest (CA) coma are expected to remain permanently disabled. We aimed to investigate 3 outlier patients who ultimately achieved independent functional outcomes after prolonged post-CA coma to identify electroencephalographic (EEG) markers of their recovery potential. For validation purposes, we also aimed to evaluate these markers in an independent cohort of post-CA patients. METHODS We identified 3 patients with late recovery from coma (17-37 days) following CA who recovered to functionally independent behavioral levels. We performed spectral power analyses of available EEGs during prominent burst suppression patterns (BSP) present in all 3 patients. Using identical methods, we also assessed the relationship of intraburst spectral power and outcomes in a prospectively enrolled cohort of post-CA patients. We performed chart reviews of common clinical, imaging, and EEG prognostic variables and clinical outcomes for all patients. RESULTS All 3 patients with late recovery from coma lacked evidence of overwhelming cortical injury but demonstrated prominent BSP on EEG. Spectral analyses revealed a prominent theta (~4-7Hz) feature dominating the bursts during BSP in these patients. In the prospective cohort, similar intraburst theta spectral features were evident in patients with favorable outcomes; patients with BSP and unfavorable outcomes showed either no features, transient burst features, or decreasing intraburst frequencies with time. INTERPRETATION BSP with theta (~4-7Hz) peak intraburst spectral power after CA may index a recovery potential. We discuss our results in the context of optimizing metabolic substrate availability and stimulating the corticothalamic system during recovery from prolonged post-CA coma. ANN NEUROL 2020;87:618-632.
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Affiliation(s)
- Peter B. Forgacs
- Feil Family Brain and Mind Research Institute, Weill Cornell Medical College, New York, NY 10065, USA
- Department of Neurology, Weill Cornell Medical College, New York, NY 10065, USA
- The Rockefeller University, New York, NY 10065, USA
| | | | - Nicholas D. Schiff
- Feil Family Brain and Mind Research Institute, Weill Cornell Medical College, New York, NY 10065, USA
- Department of Neurology, Weill Cornell Medical College, New York, NY 10065, USA
- The Rockefeller University, New York, NY 10065, USA
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Park JS, In YN, You YH, Min JH, Ahn HJ, Yoo IS, Kim SW, Lee JW, Ryu S, Jeong WJ, Cho YC, Oh SK, Cho SU, Kang CS, Lee IH, Lee BK, Lee DH, Lee DH. Ultra-early neurologic outcome prediction of out-of-hospital cardiac arrest survivors using combined diffusion-weighted imaging findings and quantitative analysis of apparent diffusion coefficient. Resuscitation 2020; 148:39-48. [DOI: 10.1016/j.resuscitation.2019.12.021] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/06/2019] [Revised: 12/13/2019] [Accepted: 12/22/2019] [Indexed: 12/15/2022]
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Yang XA, Song CG, Yuan F, Zhao JJ, Jiang YL, Yang F, Kang XG, Jiang W. Prognostic roles of sleep electroencephalography pattern and circadian rhythm biomarkers in the recovery of consciousness in patients with coma: a prospective cohort study. Sleep Med 2020; 69:204-212. [PMID: 32143064 DOI: 10.1016/j.sleep.2020.01.026] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/31/2019] [Revised: 01/07/2020] [Accepted: 01/24/2020] [Indexed: 11/15/2022]
Abstract
OBJECTIVE To investigate the potential prognostic value of sleep electroencephalography (EEG) pattern and serum circadian rhythm biomarkers in the recovery of consciousness in patients at the acute stage of coma. METHODS A prospective observational study which included 75 patients with coma was conducted. Twenty-four-hour continuous polysomnography (PSG) was performed to determine the sleep EEG pattern according to the modified Valente's Grade (mVG) that we proposed. Serum levels of melatonin and orexin-A at four consecutive time points during the PSG were examined. Patients were then followed for one month to determine their level of consciousness. Multivariate logistic regression analysis was performed to examine associations between demographics, aetiology, baseline clinical features (pupillary and corneal reflex, and neuron-specific enolase [NSE]), clinical scores (Glasgow Coma Scale-Motor Response [GCS-M], Full Outline of Unresponsiveness [FOUR] scale, Acute Physiology and Chronic Health Evaluation II [APACHE II] scale), mVG, serum circadian biomarkers, and recovery of consciousness within one month. RESULTS Within one month of enrolment, 34 patients regained consciousness and 36 patients remained non-conscious. Spearman rank correlation revealed a significant association between mVG and state of consciousness after one month. Significant variation in serum melatonin or orexin-A was not detected in either the conscious or non-conscious groups. Hypoxic aetiology, APACHE II, and mVG were independently associated with recovery of consciousness within one month. CONCLUSION Sleep EEG structure, hypoxic aetiology, and APACHE II can independently predict recovery of consciousness in patients with acute coma. Taken together, we encourage neurologists to use sleep elements to assess patients with acute coma.
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Affiliation(s)
- Xi-Ai Yang
- Department of Neurology, Xijing Hospital, Fourth Military Medical University, Xi'an, 710032, China
| | - Chang-Geng Song
- Department of Neurology, Xijing Hospital, Fourth Military Medical University, Xi'an, 710032, China
| | - Fang Yuan
- Department of Neurology, Xijing Hospital, Fourth Military Medical University, Xi'an, 710032, China
| | - Jing-Jing Zhao
- Department of Neurology, Xijing Hospital, Fourth Military Medical University, Xi'an, 710032, China
| | - Yong-Li Jiang
- Department of Neurology, Xijing Hospital, Fourth Military Medical University, Xi'an, 710032, China
| | - Fang Yang
- Department of Neurology, Xijing Hospital, Fourth Military Medical University, Xi'an, 710032, China
| | - Xiao-Gang Kang
- Department of Neurology, Xijing Hospital, Fourth Military Medical University, Xi'an, 710032, China.
| | - Wen Jiang
- Department of Neurology, Xijing Hospital, Fourth Military Medical University, Xi'an, 710032, China.
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Lopez Soto C, Dragoi L, Heyn CC, Kramer A, Pinto R, Adhikari NKJ, Scales DC. Imaging for Neuroprognostication After Cardiac Arrest: Systematic Review and Meta-analysis. Neurocrit Care 2020; 32:206-216. [PMID: 31549351 DOI: 10.1007/s12028-019-00842-0] [Citation(s) in RCA: 36] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/01/2023]
Abstract
BACKGROUND Predicting neurological outcome in comatose survivors of cardiac arrest relies on clinical findings, radiological and neurophysiological test results. To evaluate the predictive accuracy of brain computed tomography (CT) and magnetic resonance imaging (MRI) for prognostication of neurological outcomes after cardiac arrest. METHODS We searched MEDLINE (database inception to August 2018) and included all observational cohort studies or randomized controlled trials including adult (16 years or older) survivors of cardiac arrest which evaluated the diagnostic accuracy of CT or MRI for predicting neurologic outcome or mortality. Study quality was assessed using the Quality Assessment of Diagnostic Accuracy Studies 2 tool. All review stages were conducted independently by 2 reviewers, and where possible data were pooled using bivariate meta-analysis. The main outcome was to evaluate the of accuracy of CT and MRI in neuroprognostication of patients after cardiac arrest. RESULTS We included 44 studies that examined brain CT (n = 24) or MRI (n = 21) in 4008 (n per study, 9-398) patients. Decreased grey to white matter ratio on CT (20 studies) was useful for predicting poor neurological outcome (sensitivity 0.44, 95% CI 0.29-0.60; specificity 0.97, 95% CI 0.93-0.99; positive likelihood ratio [LR+] 13.8, 95% CI 6.9-27.7). Similarly, diffusion-weighted imaging (DWI) on MRI (16 studies; sensitivity 0.77, 95% CI 0.65-0.85; specificity 0.92, 95% CI 0.85-0.96; LR+ 9.2, 95% CI 5.2-16.4) and DWI and fluid-attenuated inversion recovery (FLAIR) MRI (4 studies, sensitivity 0.70, 95% CI 0.43-0.88; specificity 0.95, 95% CI 0.79-0.99; LR+ 13.4, 95% CI 3.5-51.2) were useful for predicting poor neurological outcomes. We found marked heterogeneity in timing of radiological examinations and neurological assessments relative to the cardiac arrest. CONCLUSION Decreased grey to white matter ratio on CT and DWI or DWI and FLAIR on MRI are useful adjuncts for predicting poor early neurological outcome after cardiac arrest.
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Affiliation(s)
- Carmen Lopez Soto
- Department of Critical Care Medicine, Sunnybrook Health Sciences Centre, 2075 Bayview Avenue, Toronto, ON, M4N 3M5, Canada
- Interdepartmental Division of Critical Care Medicine, University of Toronto, Toronto, ON, Canada
- Department of Critical Care Medicine, King's College Hospital NHS Foundation Trust, London, UK
| | - Laura Dragoi
- Department of Critical Care Medicine, Sunnybrook Health Sciences Centre, 2075 Bayview Avenue, Toronto, ON, M4N 3M5, Canada
- Interdepartmental Division of Critical Care Medicine, University of Toronto, Toronto, ON, Canada
| | - Chinthaka C Heyn
- Department of Medical Imaging, Sunnybrook Health Sciences Centre, University of Toronto, Toronto, ON, Canada
| | - Andreas Kramer
- Departments of Critical Care Medicine and Clinical Neurosciences, University of Calgary, Calgary, AB, Canada
| | - Ruxandra Pinto
- Department of Critical Care Medicine, Sunnybrook Health Sciences Centre, 2075 Bayview Avenue, Toronto, ON, M4N 3M5, Canada
| | - Neill K J Adhikari
- Department of Critical Care Medicine, Sunnybrook Health Sciences Centre, 2075 Bayview Avenue, Toronto, ON, M4N 3M5, Canada
- Interdepartmental Division of Critical Care Medicine, University of Toronto, Toronto, ON, Canada
| | - Damon C Scales
- Department of Critical Care Medicine, Sunnybrook Health Sciences Centre, 2075 Bayview Avenue, Toronto, ON, M4N 3M5, Canada.
- Interdepartmental Division of Critical Care Medicine, University of Toronto, Toronto, ON, Canada.
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Wei R, Wang C, He F, Hong L, Zhang J, Bao W, Meng F, Luo B. Prediction of poor outcome after hypoxic-ischemic brain injury by diffusion-weighted imaging: A systematic review and meta-analysis. PLoS One 2019; 14:e0226295. [PMID: 31881032 PMCID: PMC6934311 DOI: 10.1371/journal.pone.0226295] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/23/2019] [Accepted: 11/24/2019] [Indexed: 01/16/2023] Open
Abstract
Accurate prediction of the neurological outcome following hypoxic-ischemic brain injury (HIBI) remains difficult. Diffusion-weighted imaging (DWI) can detect acute and subacute brain abnormalities following global cerebral hypoxia. Therefore, DWI can be used to predict the outcomes of HIBI. To this end, we searched the PubMed, EMBASE, and Cochrane Library databases for studies that examine the diagnostic accuracy of DWI in predicting HIBI outcomes in adult patients between January1995 and September 2019. Next, we conducted a comprehensive meta-analysis using the Meta-DiSc and several complementary techniques. Following the application of inclusion and exclusion criteria, a total of 28 studies were included with 98 data subsets. The overall sensitivity and specificity, with 95% confidence interval, were 0.613(0.599-0.628) and 0.958(0.947-0.967), respectively, and the area under the curve was 0.9090. Significant heterogeneity among the included studies and a threshold effect were observed (p<0.001). Different positive indices were the major sources for the heterogeneity, followed by the anatomical region examined, both of which significantly affected the prognostic accuracy. In conclusion, we demonstrated that DWI can be an instrumental modality in predicting the outcome of HIBI with good prognostic accuracy. However, the lack of clear and generally accepted positive indices limits its clinical application. Therefore, using more reliable positive indices and combining DWI with other clinical predictors may improve the diagnostic accuracy of HIBI.
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Affiliation(s)
- Ruili Wei
- Department of Neurology, Brain Medical Centre, First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Chaonan Wang
- Department of Geriatrics, Shulan (Hangzhou) Hospital, Hangzhou, China
| | - Fangping He
- Department of Neurology, Brain Medical Centre, First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Lirong Hong
- Department of Rehabilitation Medicine, Zhejiang Provincial People's Hospital, People's Hospital of Hangzhou Medical College, Hangzhou, China
| | - Jie Zhang
- Department of Rehabilitation, Hangzhou Hospital of Zhejiang CAPR, Hangzhou, China
| | - Wangxiao Bao
- Department of Neurology, Brain Medical Centre, First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Fangxia Meng
- Department of Neurology, Brain Medical Centre, First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Benyan Luo
- Department of Neurology, Brain Medical Centre, First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
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Agarwal S, Morris N, Der-Nigoghossian C, May T, Brodie D. The Influence of Therapeutics on Prognostication After Cardiac Arrest. Curr Treat Options Neurol 2019; 21:60. [PMID: 31768661 DOI: 10.1007/s11940-019-0602-1] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/22/2023]
Abstract
PURPOSE OF REVIEW The goal of this review is to highlight the influence of therapeutic maneuvers on neuro-prognostication measures administered to comatose survivors of cardiac arrest. We focus on the effect of sedation regimens in the setting of targeted temperature management (TTM), one of the principle interventions known to improve neurological recovery after cardiac arrest. Further, we discuss the critical need for novel markers, as well as refinement of existing markers, among patients receiving extracorporeal membrane oxygenation (ECMO) in the setting of failed conventional resuscitation, known as extracorporeal cardiopulmonary resuscitation (ECPR). RECENT FINDINGS Automated pupillometry may have some advantage over standard pupillary examination for prognostication following TTM, sedation, or the use of ECMO after cardiac arrest. New serum biomarkers such as Neurofilament light chain have shown good predictive abilities and need further validation in these populations. There is a high-level uncertainty in brain death declaration protocols particularly related to apnea testing and appropriate ancillary tests in patients receiving ECMO. Both sedation and TTM alone and in combination have been shown to affect prognostic markers to varying degrees. The optimal approach to analog-sedation is unknown, and requires further study. Moreover, validation of known prognostic markers, as well as brain death declaration processes in patients receiving ECMO is warranted. Data on the effects of TTM, sedation, and ECMO on biomarkers (e.g., neuron-specific enolase) and electrophysiology measures (e.g., somatosensory-evoked potentials) is sparse. The best approach may be one customized to the individual patient, a precision-medicine approach.
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Affiliation(s)
- Sachin Agarwal
- Division of Neurocritical Care and Hospitalist Neurology, Department of Neurology, New York-Presbyterian Hospital/Columbia University Irving Medical Center, New York, NY, USA.
| | - Nicholas Morris
- Department of Neurology, Program in Trauma, University of Maryland Medical Center, Baltimore, MD, USA
| | - Caroline Der-Nigoghossian
- Clinical Pharmacy, New York-Presbyterian Hospital/Columbia University Irving Medical Center, New York, NY, USA
| | - Teresa May
- Division of Pulmonary and Critical Care Medicine, Maine Medical Center, Portland, ME, USA
| | - Daniel Brodie
- Division of Pulmonary, Allergy and Critical Care Medicine, Department of Medicine, New York-Presbyterian Hospital/Columbia University Irving Medical Center, New York, NY, USA
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Understanding the metabolite-function relationship after cardiac arrest. Resuscitation 2018; 134:133-135. [PMID: 30562598 DOI: 10.1016/j.resuscitation.2018.11.005] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2018] [Accepted: 11/03/2018] [Indexed: 11/20/2022]
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12
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Nguyen PL, Alreshaid L, Poblete RA, Konye G, Marehbian J, Sung G. Targeted Temperature Management and Multimodality Monitoring of Comatose Patients After Cardiac Arrest. Front Neurol 2018; 9:768. [PMID: 30254606 PMCID: PMC6141756 DOI: 10.3389/fneur.2018.00768] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/11/2018] [Accepted: 08/24/2018] [Indexed: 01/14/2023] Open
Abstract
Out-of-hospital cardiac arrest (CA) remains a leading cause of sudden morbidity and mortality; however, outcomes have continued to improve in the era of targeted temperature management (TTM). In this review, we highlight the clinical use of TTM, and provide an updated summary of multimodality monitoring possible in a modern ICU. TTM is neuroprotective for survivors of CA by inhibiting multiple pathophysiologic processes caused by anoxic brain injury, with a final common pathway of neuronal death. Current guidelines recommend the use of TTM for out-of-hospital CA survivors who present with a shockable rhythm. Further studies are being completed to determine the optimal timing, depth and duration of hypothermia to optimize patient outcomes. Although a multidisciplinary approach is necessary in the CA population, neurologists and neurointensivists are central in selecting TTM candidates and guiding patient care and prognostic evaluation. Established prognostic tools include clinal exam, SSEP, EEG and MR imaging, while functional MRI and invasive monitoring is not validated to improve outcomes in CA or aid in prognosis. We recommend that an evidence-based TTM and prognostication algorithm be locally implemented, based on each institution's resources and limitations. Given the high incidence of CA and difficulty in predicting outcomes, further study is urgently needed to determine the utility of more recent multimodality devices and studies.
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Affiliation(s)
- Peggy L Nguyen
- Department of Neurology, Keck School of Medicine, University of Southern California, Los Angeles, CA, United States
| | - Laith Alreshaid
- Department of Neurology, Keck School of Medicine, University of Southern California, Los Angeles, CA, United States
| | - Roy A Poblete
- Department of Neurology, Keck School of Medicine, University of Southern California, Los Angeles, CA, United States
| | - Geoffrey Konye
- Department of Neurology, Keck School of Medicine, University of Southern California, Los Angeles, CA, United States
| | - Jonathan Marehbian
- Department of Neurology, Keck School of Medicine, University of Southern California, Los Angeles, CA, United States
| | - Gene Sung
- Department of Neurology, Keck School of Medicine, University of Southern California, Los Angeles, CA, United States
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