Proteomics-Enriched Prediction Model for Poor Neurologic Outcome in Cardiac Arrest Survivors.


Journal

Critical care medicine
ISSN: 1530-0293
Titre abrégé: Crit Care Med
Pays: United States
ID NLM: 0355501

Informations de publication

Date de publication:
02 2020
Historique:
entrez: 16 1 2020
pubmed: 16 1 2020
medline: 25 8 2020
Statut: ppublish

Résumé

Neurologic outcome prediction in out-of-hospital cardiac arrest survivors is highly limited due to the lack of consistent predictors of clinically relevant brain damage. The present study aimed to identify novel biomarkers of neurologic recovery to improve early prediction of neurologic outcome. Prospective, single-center study, SETTING:: University-affiliated tertiary care center. We prospectively enrolled 96 out-of-hospital cardiac arrest survivors into our study. None. Neurologic outcome was assessed by the Cerebral Performance Categories score. To identify plasma biomarkers for poor neurologic outcome (Cerebral Performance Categories score ≥ 3), we performed a three-step proteomics strategy of preselection by shotgun analyses, crosschecking in brain tissue samples, and verification by targeted proteomic analyses using a multistep statistical modeling approach. Sixty-three patients (66%) had a poor neurologic outcome. Out of a total of 299 proteins, we identified α-enolase, 14-3-3 protein ζ/δ, cofilin-1, and heat shock cognate 71 kDa protein as novel biomarkers for poor neurologic outcome. The implementation of these biomarkers into a clinical multimarker model, consisting of previously identified covariates associated to outcome, resulted in a significant improvement of neurologic outcome prediction (C-index, 0.70; explained variation, 11.9%; p for added value, 0.019). This study identified four novel biomarkers for the prediction of poor neurologic outcome in out-of-hospital cardiac arrest survivors. The implementation of α-enolase, 14-3-3 protein ζ/δ, cofilin-1, and heat shock cognate 71 kDa protein into a multimarker predictive model along with previously identified risk factors significantly improved neurologic outcome prediction. Each of the proteomically identified biomarkers did not only outperform current risk stratification models but may also reflect important pathophysiologic pathways undergoing during cerebral ischemia.

Identifiants

pubmed: 31939784
doi: 10.1097/CCM.0000000000004105
pii: 00003246-202002000-00005
doi:

Substances chimiques

Biomarkers 0

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

167-175

Commentaires et corrections

Type : CommentIn

Auteurs

Klaus Distelmaier (K)

Department of Internal Medicine II, Medical University of Vienna, Vienna, Austria.

Besnik Muqaku (B)

Department of Analytical Chemistry, Faculty of Chemistry, University of Vienna, Vienna, Austria.

Raphael Wurm (R)

Department of Internal Medicine II, Medical University of Vienna, Vienna, Austria.
Department of Neurology, Medical University of Vienna, Vienna, Austria.

Henrike Arfsten (H)

Department of Internal Medicine II, Medical University of Vienna, Vienna, Austria.

Stefan Seidel (S)

Department of Neurology, Medical University of Vienna, Vienna, Austria.

Gabor G Kovacs (GG)

Institute of Neurology, Medical University of Vienna, Vienna, Austria.

Thomas Szekeres (T)

Department of Medical and Chemical Laboratory Diagnostics, Medical University of Vienna, Vienna, Austria.

Pia Hubner (P)

Department of Emergency Medicine, Medical University of Vienna, Vienna, Austria.

Georg Goliasch (G)

Department of Internal Medicine II, Medical University of Vienna, Vienna, Austria.

Georg Heinze (G)

Center for Medical Statistics, Informatics and Intelligent Systems, Section for Clinical Biometrics, Medical University of Vienna, Vienna, Austria.

Gottfried Heinz (G)

Department of Internal Medicine II, Medical University of Vienna, Vienna, Austria.

Fritz Sterz (F)

Department of Emergency Medicine, Medical University of Vienna, Vienna, Austria.

Christopher Gerner (C)

Department of Analytical Chemistry, Faculty of Chemistry, University of Vienna, Vienna, Austria.

Christopher Adlbrecht (C)

Department of Internal Medicine II, Medical University of Vienna, Vienna, Austria.
Department of Cardiology, Vienna North Hospital - Clinic Floridsdorf and the Karl Landsteiner Institute for Cardiovascular and Critical Care Research, Vienna, Vienna, Austria.

Articles similaires

[Redispensing of expensive oral anticancer medicines: a practical application].

Lisanne N van Merendonk, Kübra Akgöl, Bastiaan Nuijen
1.00
Humans Antineoplastic Agents Administration, Oral Drug Costs Counterfeit Drugs

Smoking Cessation and Incident Cardiovascular Disease.

Jun Hwan Cho, Seung Yong Shin, Hoseob Kim et al.
1.00
Humans Male Smoking Cessation Cardiovascular Diseases Female
Humans United States Aged Cross-Sectional Studies Medicare Part C
1.00
Humans Yoga Low Back Pain Female Male

Classifications MeSH