Serum GFAP and UCH-L1 for the prediction of neurological outcome in comatose cardiac arrest patients

Ebner, Florian; Moseby-Knappe, Marion; Mattsson‐Carlgren, Niklas; Lilja, Gisela; Dragancea, Irina; Undén, Johan; Friberg, Hans; Erlinge, David; Kjærgaard, Jesper; Hassager, Christian; Wise, Matt P.; Kuiper, Michael; Stammet, Pascal; Wanscher, Michael; Horn, Janneke; Ullén, Susann; Cronberg, Tobias; Nielsen, Niklas

doi:10.1016/j.resuscitation.2020.05.016

Cited by 38 publications

(51 citation statements)

References 36 publications

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“…197,201 A recent study of 717 patients reported that UCH-L1 and GFAP were optimal BB predictors of outcome as early as 24 h after cardiac arrest. 205 Use of BBs as an adjunct to other diagnostic modalities was recommended. Monitoring of plasma concentrations of GFAP and other brain injury biomarkers, including S100B and NSE, has also been shown to detect brain injury in children on extracorporeal membrane oxygenation (ECMO).…”

Section: Use Of Blood Biomarkersmentioning

confidence: 99%

“…Monitoring the status of possible CNS injury in these patients is vital given that cognitive deficits are observed even in ICU patients receiving care for other medical complications not associated with a primary brain injury. 199,205,241,[332][333][334] Even a year after leaving the ICU, many people experience PTSD, cognitive deficits, and depression. 335 Thus, the presence or absence of CNS injury in the ICU will be important in determining subsequent neurological deficits and neuropsychiatric problems.…”

Section: Clinical Applications In Acute Care Facilities and Emergencymentioning

confidence: 99%

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Blood Biomarkers for Detection of Brain Injury in COVID-19 Patients

DeKosky

Kochanek

Valadka

et al. 2021

Journal of Neurotrauma

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The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus attacks multiple organs of coronavirus disease 2019 (COVID-19) patients, including the brain. There are worldwide descriptions of neurological deficits in COVID-19 patients. Central nervous system (CNS) symptoms can be present early in the course of the disease. As many as 55% of hospitalized COVID-19 patients have been reported to have neurological disturbances three months after infection by SARS-CoV-2. The mutability of the SARS-COV-2 virus and its potential to directly affect the CNS highlight the urgency of developing technology to diagnose, manage, and treat brain injury in COVID-19 patients. The pathobiology of CNS infection by SARS-CoV-2 and the associated neurological sequelae of this infection remain poorly understood. In this review, we outline the rationale for the use of blood biomarkers (BBs) for diagnosis of brain injury in COVID-19 patients, the research needed to incorporate their use into clinical practice, and the improvements in patient management and outcomes that can result. BBs of brain injury could potentially provide tools for detection of brain injury in COVID-19

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Section: Use Of Blood Biomarkersmentioning

confidence: 99%

Section: Clinical Applications In Acute Care Facilities and Emergencymentioning

confidence: 99%

Blood Biomarkers for Detection of Brain Injury in COVID-19 Patients

DeKosky

Kochanek

Valadka

et al. 2021

Journal of Neurotrauma

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“…Amongst many novel biomarkers that have been studied for brain injury after cardiac arrest, the most promising so far is neurofilament light (NFL), with an area under the receiver operating characteristic curve (AUROC) of 94-98% for discrimination of longterm neurological outcome as early as 24 h after ROSC [5,6]. Other biomarkers of brain injury, including S100 calcium-binding protein B (S100B), tau protein, glial fibrillary acidic protein (GFAP), and ubiquitin C-terminal hydrolase-L1 (UCHL1), have also shown potential in cardiac arrest prognostication [7][8][9][10][11]. Biomarkers of cardiac injury such as troponin T (TnT), N-terminal pro-B-type natriuretic peptide (BNP) and copeptin along with biomarkers of systemic inflammation such as procalcitonin (PCT) and interleukin-6 (IL-6) are also associated with neurological outcome [12][13][14][15][16].…”

Section: Introductionmentioning

confidence: 99%

Predicting neurological outcome after out-of-hospital cardiac arrest with cumulative information; development and internal validation of an artificial neural network algorithm

et al. 2021

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Background Prognostication of neurological outcome in patients who remain comatose after cardiac arrest resuscitation is complex. Clinical variables, as well as biomarkers of brain injury, cardiac injury, and systemic inflammation, all yield some prognostic value. We hypothesised that cumulative information obtained during the first three days of intensive care could produce a reliable model for predicting neurological outcome following out-of-hospital cardiac arrest (OHCA) using artificial neural network (ANN) with and without biomarkers. Methods We performed a post hoc analysis of 932 patients from the Target Temperature Management trial. We focused on comatose patients at 24, 48, and 72 h post-cardiac arrest and excluded patients who were awake or deceased at these time points. 80% of the patients were allocated for model development (training set) and 20% for internal validation (test set). To investigate the prognostic potential of different levels of biomarkers (clinically available and research-grade), patients’ background information, and intensive care observation and treatment, we created three models for each time point: (1) clinical variables, (2) adding clinically accessible biomarkers, e.g., neuron-specific enolase (NSE) and (3) adding research-grade biomarkers, e.g., neurofilament light (NFL). Patient outcome was the dichotomised Cerebral Performance Category (CPC) at six months; a good outcome was defined as CPC 1–2 whilst a poor outcome was defined as CPC 3–5. The area under the receiver operating characteristic curve (AUROC) was calculated for all test sets. Results AUROC remained below 90% when using only clinical variables throughout the first three days in the ICU. Adding clinically accessible biomarkers such as NSE, AUROC increased from 82 to 94% (p < 0.01). The prognostic accuracy remained excellent from day 1 to day 3 with an AUROC at approximately 95% when adding research-grade biomarkers. The models which included NSE after 72 h and NFL on any of the three days had a low risk of false-positive predictions while retaining a low number of false-negative predictions. Conclusions In this exploratory study, ANNs provided good to excellent prognostic accuracy in predicting neurological outcome in comatose patients post OHCA. The models which included NSE after 72 h and NFL on all days showed promising prognostic performance.

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“…The copyright holder for this preprint this version posted May 27, 2021. ; https://doi.org/10.1101/2021.05. 25.21257353 doi: medRxiv preprint surrogate markers of neuronal and astrocytic injury in non-neurological diseases like HIV [18][19][20] , cardiac arrest [21][22][23] and sepsis 24 as well. Among them, we measured six validated BIMs including glial fibrillary acidic protein (GFAP), neuron specific enolase (NSE), S100B, ubiquitin carboxyl-terminal hydrolase isozyme L1 (UCHL1), Syndecan-1 and microtubule-associated protein 2 (MAP 2) in plasma drawn from hospitalized COVID-19 subjects and matched controls.…”

mentioning

confidence: 99%

Markers of brain and endothelial Injury and inflammation are acutely and sex specifically regulated in SARS-CoV-2 infection

Savarraj

Park

Copo

et al. 2021

Preprint

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Objective: To investigate brain injury markers (BIM), endothelial injury markers (EIM) and cytokine/chemokine (CC) markers of systemic inflammation in coronavirus disease 2019 (COVID-19) and across sex. Methods: Plasma samples from 57 subjects at <48 hours of COVID 19 hospitalization, 14 subjects at 3 months of COVID 19 hospitalization and 20 matched controls were interrogated for the levels of six BIMs, including GFAP, S100B, Syndecan1, UCHLI, MAP2 and NSE, two EIMs, including sICAM1 and sVCAM1 and thirty eight CCs. Statistical and bioinformatics methods were used to measure differences in the marker profiles across (a) COVID 19 vs controls and (b) men vs women. Results: Three BIMs: MAP2, NSE and S100B, two EIMs: sICAM1 and sVCAM1 and seven CCs: GRO IL10, sCD40L, IP10, IL1Ra, MCP1 and TNFa; were significantly (p<0.05) elevated in the COVID 19 cohort compared to controls. Two CCs: MDC and MIP1a; were significantly lower in the COVID-19 cohort. Bioinformatics analysis reveal a stronger positive association between BIM/CC/EIMs in the COVID-19 cohort. Analysis across sex revealed that several BIMs and CCs including NSE, IL10, IL15 and IL8 were significantly (p<0.05) higher in men compared to women. Men also expressed a more robust BIM/ EIM/CC association profile compared to women. At 3 months, BIMs and CCs were not significantly different in the COVID-19 cohort compared to controls. Conclusion: The acute elevation of BIMs, CCs, and EIMs and the robust associations among them at COVID-19 hospitalization suggest that brain injury is mediated by endotheliopathy and inflammation. Higher BIM and inflammatory markers in men additionally suggest that men are more susceptible to the risk compared to women.

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Serum GFAP and UCH-L1 for the prediction of neurological outcome in comatose cardiac arrest patients

Cited by 38 publications

References 36 publications

Blood Biomarkers for Detection of Brain Injury in COVID-19 Patients

Blood Biomarkers for Detection of Brain Injury in COVID-19 Patients

Predicting neurological outcome after out-of-hospital cardiac arrest with cumulative information; development and internal validation of an artificial neural network algorithm

Markers of brain and endothelial Injury and inflammation are acutely and sex specifically regulated in SARS-CoV-2 infection

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