Cargando…

Stepwise stroke recognition through clinical information, vital signs, and initial labs (CIVIL): Electronic health record-based observational cohort study

BACKGROUND: Stroke recognition systems have been developed to reduce time delays, however, a comprehensive triaging score identifying stroke subtypes is needed to guide appropriate management. We aimed to develop a prehospital scoring system for rapid stroke recognition and identify stroke subtype s...

Descripción completa

Detalles Bibliográficos
Autores principales: Lee, Sung Eun, Choi, Mun Hee, Kang, Hyo Jung, Lee, Seong-Joon, Lee, Jin Soo, Lee, Yunhwan, Hong, Ji Man
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7159200/
https://www.ncbi.nlm.nih.gov/pubmed/32294085
http://dx.doi.org/10.1371/journal.pone.0231113
_version_ 1783522614605512704
author Lee, Sung Eun
Choi, Mun Hee
Kang, Hyo Jung
Lee, Seong-Joon
Lee, Jin Soo
Lee, Yunhwan
Hong, Ji Man
author_facet Lee, Sung Eun
Choi, Mun Hee
Kang, Hyo Jung
Lee, Seong-Joon
Lee, Jin Soo
Lee, Yunhwan
Hong, Ji Man
author_sort Lee, Sung Eun
collection PubMed
description BACKGROUND: Stroke recognition systems have been developed to reduce time delays, however, a comprehensive triaging score identifying stroke subtypes is needed to guide appropriate management. We aimed to develop a prehospital scoring system for rapid stroke recognition and identify stroke subtype simultaneously. METHODS AND FINDINGS: In prospective database of regional emergency and stroke center, Clinical Information, Vital signs, and Initial Labs (CIVIL) of 1,599 patients suspected of acute stroke was analyzed from an automatically-stored electronic health record. Final confirmation was performed with neuroimaging. Using multiple regression analyses, we determined independent predictors of tier 1 (true-stroke or not), tier 2 (hemorrhagic stroke or not), and tier 3 (emergent large vessel occlusion [ELVO] or not). The diagnostic performance of the stepwise CIVIL scoring system was investigated using internal validation. A new scoring system characterized by a stepwise clinical assessment has been developed in three tiers. Tier 1: Seven CIVIL-AS(3)A(2)P items (total score from –7 to +6) were deduced for true stroke as Age (≥ 60 years); Stroke risks without Seizure or psychiatric disease, extreme Sugar; “any Asymmetry”, “not Ambulating”; abnormal blood Pressure at a cut-off point ≥ 1 with diagnostic sensitivity of 82.1%, specificity of 56.4%. Tier 2: Four items for hemorrhagic stroke were identified as the CIVIL-MAPS indicating Mental change, Age below 60 years, high blood Pressure, no Stroke risks with cut-point ≥ 2 (sensitivity 47.5%, specificity 85.4%). Tier 3: For ELVO diagnosis: we applied with CIVIL-GFAST items (Gaze, Face, Arm, Speech) with cut-point ≥ 3 (sensitivity 66.5%, specificity 79.8%). The main limitation of this study is its retrospective nature and require a prospective validation of the CIVIL scoring system. CONCLUSIONS: The CIVIL score is a comprehensive and versatile system that recognizes strokes and identifies the stroke subtype simultaneously.
format Online
Article
Text
id pubmed-7159200
institution National Center for Biotechnology Information
language English
publishDate 2020
publisher Public Library of Science
record_format MEDLINE/PubMed
spelling pubmed-71592002020-04-22 Stepwise stroke recognition through clinical information, vital signs, and initial labs (CIVIL): Electronic health record-based observational cohort study Lee, Sung Eun Choi, Mun Hee Kang, Hyo Jung Lee, Seong-Joon Lee, Jin Soo Lee, Yunhwan Hong, Ji Man PLoS One Research Article BACKGROUND: Stroke recognition systems have been developed to reduce time delays, however, a comprehensive triaging score identifying stroke subtypes is needed to guide appropriate management. We aimed to develop a prehospital scoring system for rapid stroke recognition and identify stroke subtype simultaneously. METHODS AND FINDINGS: In prospective database of regional emergency and stroke center, Clinical Information, Vital signs, and Initial Labs (CIVIL) of 1,599 patients suspected of acute stroke was analyzed from an automatically-stored electronic health record. Final confirmation was performed with neuroimaging. Using multiple regression analyses, we determined independent predictors of tier 1 (true-stroke or not), tier 2 (hemorrhagic stroke or not), and tier 3 (emergent large vessel occlusion [ELVO] or not). The diagnostic performance of the stepwise CIVIL scoring system was investigated using internal validation. A new scoring system characterized by a stepwise clinical assessment has been developed in three tiers. Tier 1: Seven CIVIL-AS(3)A(2)P items (total score from –7 to +6) were deduced for true stroke as Age (≥ 60 years); Stroke risks without Seizure or psychiatric disease, extreme Sugar; “any Asymmetry”, “not Ambulating”; abnormal blood Pressure at a cut-off point ≥ 1 with diagnostic sensitivity of 82.1%, specificity of 56.4%. Tier 2: Four items for hemorrhagic stroke were identified as the CIVIL-MAPS indicating Mental change, Age below 60 years, high blood Pressure, no Stroke risks with cut-point ≥ 2 (sensitivity 47.5%, specificity 85.4%). Tier 3: For ELVO diagnosis: we applied with CIVIL-GFAST items (Gaze, Face, Arm, Speech) with cut-point ≥ 3 (sensitivity 66.5%, specificity 79.8%). The main limitation of this study is its retrospective nature and require a prospective validation of the CIVIL scoring system. CONCLUSIONS: The CIVIL score is a comprehensive and versatile system that recognizes strokes and identifies the stroke subtype simultaneously. Public Library of Science 2020-04-15 /pmc/articles/PMC7159200/ /pubmed/32294085 http://dx.doi.org/10.1371/journal.pone.0231113 Text en © 2020 Lee et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Lee, Sung Eun
Choi, Mun Hee
Kang, Hyo Jung
Lee, Seong-Joon
Lee, Jin Soo
Lee, Yunhwan
Hong, Ji Man
Stepwise stroke recognition through clinical information, vital signs, and initial labs (CIVIL): Electronic health record-based observational cohort study
title Stepwise stroke recognition through clinical information, vital signs, and initial labs (CIVIL): Electronic health record-based observational cohort study
title_full Stepwise stroke recognition through clinical information, vital signs, and initial labs (CIVIL): Electronic health record-based observational cohort study
title_fullStr Stepwise stroke recognition through clinical information, vital signs, and initial labs (CIVIL): Electronic health record-based observational cohort study
title_full_unstemmed Stepwise stroke recognition through clinical information, vital signs, and initial labs (CIVIL): Electronic health record-based observational cohort study
title_short Stepwise stroke recognition through clinical information, vital signs, and initial labs (CIVIL): Electronic health record-based observational cohort study
title_sort stepwise stroke recognition through clinical information, vital signs, and initial labs (civil): electronic health record-based observational cohort study
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7159200/
https://www.ncbi.nlm.nih.gov/pubmed/32294085
http://dx.doi.org/10.1371/journal.pone.0231113
work_keys_str_mv AT leesungeun stepwisestrokerecognitionthroughclinicalinformationvitalsignsandinitiallabscivilelectronichealthrecordbasedobservationalcohortstudy
AT choimunhee stepwisestrokerecognitionthroughclinicalinformationvitalsignsandinitiallabscivilelectronichealthrecordbasedobservationalcohortstudy
AT kanghyojung stepwisestrokerecognitionthroughclinicalinformationvitalsignsandinitiallabscivilelectronichealthrecordbasedobservationalcohortstudy
AT leeseongjoon stepwisestrokerecognitionthroughclinicalinformationvitalsignsandinitiallabscivilelectronichealthrecordbasedobservationalcohortstudy
AT leejinsoo stepwisestrokerecognitionthroughclinicalinformationvitalsignsandinitiallabscivilelectronichealthrecordbasedobservationalcohortstudy
AT leeyunhwan stepwisestrokerecognitionthroughclinicalinformationvitalsignsandinitiallabscivilelectronichealthrecordbasedobservationalcohortstudy
AT hongjiman stepwisestrokerecognitionthroughclinicalinformationvitalsignsandinitiallabscivilelectronichealthrecordbasedobservationalcohortstudy