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Clinical and infarction patterns of PFO‐related cryptogenic strokes and a prediction model

OBJECTIVES: The higher than expected PFO rate in CS patients has raised concerns that paradoxical embolism maybe the pathophysiologic mechanism for strokes. However, only a small proportion of pathogenic PFOs cause CS. Therefore, accurate recognition of patients with pathogenic PFOs among all CS pat...

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Autores principales: He, Dan, Shi, Qiang, Xu, Guangjing, Hu, Zheng, Li, Xuefei, Li, Qian, Guo, Yinping, Xu, Shabei, Lin, Yongbo, Yu, Zhiyuan, Wang, Wei, Luo, Xiang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6243387/
https://www.ncbi.nlm.nih.gov/pubmed/30480027
http://dx.doi.org/10.1002/acn3.647
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author He, Dan
Shi, Qiang
Xu, Guangjing
Hu, Zheng
Li, Xuefei
Li, Qian
Guo, Yinping
Xu, Shabei
Lin, Yongbo
Yu, Zhiyuan
Wang, Wei
Luo, Xiang
author_facet He, Dan
Shi, Qiang
Xu, Guangjing
Hu, Zheng
Li, Xuefei
Li, Qian
Guo, Yinping
Xu, Shabei
Lin, Yongbo
Yu, Zhiyuan
Wang, Wei
Luo, Xiang
author_sort He, Dan
collection PubMed
description OBJECTIVES: The higher than expected PFO rate in CS patients has raised concerns that paradoxical embolism maybe the pathophysiologic mechanism for strokes. However, only a small proportion of pathogenic PFOs cause CS. Therefore, accurate recognition of patients with pathogenic PFOs among all CS patients could guide clinical decision making in selecting the most appropriate treatment. The aim of this study was to devise a new algorithm to stratify cryptogenic stroke (CS) patients into pathogenic patent foramen ovale (p‐PFO)‐ and non‐p‐PFO‐related patients. METHODS: A total of 1201 patients with acute ischemic stroke were recruited from two different medical centers, and 253 CS patients were identified. Of the 253 patients, 111 were diagnosed with PFO using contrast transcranial Doppler. Data on medical histories, neuroimaging and laboratory tests were compared in CS patients with or without PFO. RESULTS: Compared with PFO‐negative CS patients, PFO‐positive CS patients showed younger onset age, lower incidence of hypertension and dyslipidemia, characteristic infarction pattern in magnetic resonance imaging and specifically altered platelet activity and coagulation function. Based on the above information, we constructed a PFO judgment formula (Hr‐PFOJ) by means of feature weight estimation and predictive performance evaluation to predict pathogenic PFO in CS patients with a sensitivity of 76.3% and a specificity of 66.5%. INTERPRETATIONS: Hr‐PFOJ judgment formula is a useful screening tool for identification of patients with pathogenic PFO who may benefit from PFO‐related treatment.
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spelling pubmed-62433872018-11-26 Clinical and infarction patterns of PFO‐related cryptogenic strokes and a prediction model He, Dan Shi, Qiang Xu, Guangjing Hu, Zheng Li, Xuefei Li, Qian Guo, Yinping Xu, Shabei Lin, Yongbo Yu, Zhiyuan Wang, Wei Luo, Xiang Ann Clin Transl Neurol Research Articles OBJECTIVES: The higher than expected PFO rate in CS patients has raised concerns that paradoxical embolism maybe the pathophysiologic mechanism for strokes. However, only a small proportion of pathogenic PFOs cause CS. Therefore, accurate recognition of patients with pathogenic PFOs among all CS patients could guide clinical decision making in selecting the most appropriate treatment. The aim of this study was to devise a new algorithm to stratify cryptogenic stroke (CS) patients into pathogenic patent foramen ovale (p‐PFO)‐ and non‐p‐PFO‐related patients. METHODS: A total of 1201 patients with acute ischemic stroke were recruited from two different medical centers, and 253 CS patients were identified. Of the 253 patients, 111 were diagnosed with PFO using contrast transcranial Doppler. Data on medical histories, neuroimaging and laboratory tests were compared in CS patients with or without PFO. RESULTS: Compared with PFO‐negative CS patients, PFO‐positive CS patients showed younger onset age, lower incidence of hypertension and dyslipidemia, characteristic infarction pattern in magnetic resonance imaging and specifically altered platelet activity and coagulation function. Based on the above information, we constructed a PFO judgment formula (Hr‐PFOJ) by means of feature weight estimation and predictive performance evaluation to predict pathogenic PFO in CS patients with a sensitivity of 76.3% and a specificity of 66.5%. INTERPRETATIONS: Hr‐PFOJ judgment formula is a useful screening tool for identification of patients with pathogenic PFO who may benefit from PFO‐related treatment. John Wiley and Sons Inc. 2018-09-24 /pmc/articles/PMC6243387/ /pubmed/30480027 http://dx.doi.org/10.1002/acn3.647 Text en © 2018 The Authors. Annals of Clinical and Translational Neurology published by Wiley Periodicals, Inc on behalf of American Neurological Association. This is an open access article under the terms of the http://creativecommons.org/licenses/by-nc-nd/4.0/ License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non‐commercial and no modifications or adaptations are made.
spellingShingle Research Articles
He, Dan
Shi, Qiang
Xu, Guangjing
Hu, Zheng
Li, Xuefei
Li, Qian
Guo, Yinping
Xu, Shabei
Lin, Yongbo
Yu, Zhiyuan
Wang, Wei
Luo, Xiang
Clinical and infarction patterns of PFO‐related cryptogenic strokes and a prediction model
title Clinical and infarction patterns of PFO‐related cryptogenic strokes and a prediction model
title_full Clinical and infarction patterns of PFO‐related cryptogenic strokes and a prediction model
title_fullStr Clinical and infarction patterns of PFO‐related cryptogenic strokes and a prediction model
title_full_unstemmed Clinical and infarction patterns of PFO‐related cryptogenic strokes and a prediction model
title_short Clinical and infarction patterns of PFO‐related cryptogenic strokes and a prediction model
title_sort clinical and infarction patterns of pfo‐related cryptogenic strokes and a prediction model
topic Research Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6243387/
https://www.ncbi.nlm.nih.gov/pubmed/30480027
http://dx.doi.org/10.1002/acn3.647
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