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Performance of a guideline-recommended algorithm for prognostication of poor neurological outcome after cardiac arrest
PURPOSE: To assess the performance of a 4-step algorithm for neurological prognostication after cardiac arrest recommended by the European Resuscitation Council (ERC) and the European Society of Intensive Care Medicine (ESICM). METHODS: Retrospective descriptive analysis with data from the Target Te...
Autores principales: | , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer Berlin Heidelberg
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7527324/ https://www.ncbi.nlm.nih.gov/pubmed/32494928 http://dx.doi.org/10.1007/s00134-020-06080-9 |
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author | Moseby-Knappe, Marion Westhall, Erik Backman, Sofia Mattsson-Carlgren, Niklas Dragancea, Irina Lybeck, Anna Friberg, Hans Stammet, Pascal Lilja, Gisela Horn, Janneke Kjaergaard, Jesper Rylander, Christian Hassager, Christian Ullén, Susann Nielsen, Niklas Cronberg, Tobias |
author_facet | Moseby-Knappe, Marion Westhall, Erik Backman, Sofia Mattsson-Carlgren, Niklas Dragancea, Irina Lybeck, Anna Friberg, Hans Stammet, Pascal Lilja, Gisela Horn, Janneke Kjaergaard, Jesper Rylander, Christian Hassager, Christian Ullén, Susann Nielsen, Niklas Cronberg, Tobias |
author_sort | Moseby-Knappe, Marion |
collection | PubMed |
description | PURPOSE: To assess the performance of a 4-step algorithm for neurological prognostication after cardiac arrest recommended by the European Resuscitation Council (ERC) and the European Society of Intensive Care Medicine (ESICM). METHODS: Retrospective descriptive analysis with data from the Target Temperature Management (TTM) Trial. Associations between predicted and actual neurological outcome were investigated for each step of the algorithm with results from clinical neurological examinations, neuroradiology (CT or MRI), neurophysiology (EEG and SSEP) and serum neuron-specific enolase. Patients examined with Glasgow Coma Scale Motor Score (GCS-M) on day 4 (72–96 h) post-arrest and available 6-month outcome were included. Poor outcome was defined as Cerebral Performance Category 3–5. Variations of the ERC/ESICM algorithm were explored within the same cohort. RESULTS: The ERC/ESICM algorithm identified poor outcome patients with 38.7% sensitivity (95% CI 33.1–44.7) and 100% specificity (95% CI 98.8–100) in a cohort of 585 patients. An alternative cut-off for serum neuron-specific enolase, an alternative EEG-classification and variations of the GCS-M had minor effects on the sensitivity without causing false positive predictions. The highest overall sensitivity, 42.5% (95% CI 36.7–48.5), was achieved when prognosticating patients irrespective of GCS-M score, with 100% specificity (95% CI 98.8–100) remaining. CONCLUSION: The ERC/ESICM algorithm and all exploratory multimodal variations thereof investigated in this study predicted poor outcome without false positive predictions and with sensitivities 34.6–42.5%. Our results should be validated prospectively, preferably in patients where withdrawal of life-sustaining therapy is uncommon to exclude any confounding from self-fulfilling prophecies. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1007/s00134-020-06080-9) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-7527324 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Springer Berlin Heidelberg |
record_format | MEDLINE/PubMed |
spelling | pubmed-75273242020-10-14 Performance of a guideline-recommended algorithm for prognostication of poor neurological outcome after cardiac arrest Moseby-Knappe, Marion Westhall, Erik Backman, Sofia Mattsson-Carlgren, Niklas Dragancea, Irina Lybeck, Anna Friberg, Hans Stammet, Pascal Lilja, Gisela Horn, Janneke Kjaergaard, Jesper Rylander, Christian Hassager, Christian Ullén, Susann Nielsen, Niklas Cronberg, Tobias Intensive Care Med Original PURPOSE: To assess the performance of a 4-step algorithm for neurological prognostication after cardiac arrest recommended by the European Resuscitation Council (ERC) and the European Society of Intensive Care Medicine (ESICM). METHODS: Retrospective descriptive analysis with data from the Target Temperature Management (TTM) Trial. Associations between predicted and actual neurological outcome were investigated for each step of the algorithm with results from clinical neurological examinations, neuroradiology (CT or MRI), neurophysiology (EEG and SSEP) and serum neuron-specific enolase. Patients examined with Glasgow Coma Scale Motor Score (GCS-M) on day 4 (72–96 h) post-arrest and available 6-month outcome were included. Poor outcome was defined as Cerebral Performance Category 3–5. Variations of the ERC/ESICM algorithm were explored within the same cohort. RESULTS: The ERC/ESICM algorithm identified poor outcome patients with 38.7% sensitivity (95% CI 33.1–44.7) and 100% specificity (95% CI 98.8–100) in a cohort of 585 patients. An alternative cut-off for serum neuron-specific enolase, an alternative EEG-classification and variations of the GCS-M had minor effects on the sensitivity without causing false positive predictions. The highest overall sensitivity, 42.5% (95% CI 36.7–48.5), was achieved when prognosticating patients irrespective of GCS-M score, with 100% specificity (95% CI 98.8–100) remaining. CONCLUSION: The ERC/ESICM algorithm and all exploratory multimodal variations thereof investigated in this study predicted poor outcome without false positive predictions and with sensitivities 34.6–42.5%. Our results should be validated prospectively, preferably in patients where withdrawal of life-sustaining therapy is uncommon to exclude any confounding from self-fulfilling prophecies. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1007/s00134-020-06080-9) contains supplementary material, which is available to authorized users. Springer Berlin Heidelberg 2020-06-03 2020 /pmc/articles/PMC7527324/ /pubmed/32494928 http://dx.doi.org/10.1007/s00134-020-06080-9 Text en © The Author(s) 2020 Open AccessThis article is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License, which permits any non-commercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder.To view a copy of this licence, visit http://creativecommons.org/licenses/by-nc/4.0/. |
spellingShingle | Original Moseby-Knappe, Marion Westhall, Erik Backman, Sofia Mattsson-Carlgren, Niklas Dragancea, Irina Lybeck, Anna Friberg, Hans Stammet, Pascal Lilja, Gisela Horn, Janneke Kjaergaard, Jesper Rylander, Christian Hassager, Christian Ullén, Susann Nielsen, Niklas Cronberg, Tobias Performance of a guideline-recommended algorithm for prognostication of poor neurological outcome after cardiac arrest |
title | Performance of a guideline-recommended algorithm for prognostication of poor neurological outcome after cardiac arrest |
title_full | Performance of a guideline-recommended algorithm for prognostication of poor neurological outcome after cardiac arrest |
title_fullStr | Performance of a guideline-recommended algorithm for prognostication of poor neurological outcome after cardiac arrest |
title_full_unstemmed | Performance of a guideline-recommended algorithm for prognostication of poor neurological outcome after cardiac arrest |
title_short | Performance of a guideline-recommended algorithm for prognostication of poor neurological outcome after cardiac arrest |
title_sort | performance of a guideline-recommended algorithm for prognostication of poor neurological outcome after cardiac arrest |
topic | Original |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7527324/ https://www.ncbi.nlm.nih.gov/pubmed/32494928 http://dx.doi.org/10.1007/s00134-020-06080-9 |
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