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Relationship of Platelet Counts and Inflammatory Markers to 30-Day Mortality Risk in Patients with Acute Type A Aortic Dissection
Markers of prothrombotic state and inflammation are associated with the prognosis of patients with acute type A aortic dissection (AAAD). However, it is unclear that the relationship between these biomarkers and their combined impact on risk stratification. The present study evaluated the prognostic...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Hindawi
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7191390/ https://www.ncbi.nlm.nih.gov/pubmed/32382526 http://dx.doi.org/10.1155/2020/1057496 |
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author | Chen, Yiping Lin, Yanjuan Zhang, Haoruo Peng, Yanchun Li, Sailan Huang, Xizhen |
author_facet | Chen, Yiping Lin, Yanjuan Zhang, Haoruo Peng, Yanchun Li, Sailan Huang, Xizhen |
author_sort | Chen, Yiping |
collection | PubMed |
description | Markers of prothrombotic state and inflammation are associated with the prognosis of patients with acute type A aortic dissection (AAAD). However, it is unclear that the relationship between these biomarkers and their combined impact on risk stratification. The present study evaluated the prognostic value of platelet counts, lymphocyte to neutrophil ratio (LNR), and lymphocyte to monocyte ratio (LMR), alone and in combination. A retrospective analysis of clinical data of 744 AAAD patients was conducted to identify whether these biomarkers were related to the 30-day mortality risk. A Kaplan-Meier analysis and log-rank test were used to compare survival between groups. A Cox hazard regression multivariable analysis was performed for 30-day mortality. Individual biomarker (platelet count, LNR, or LMR) was unable to predict 30-day mortality. However, combinations of all three biomarkers provided additive predictive value over either marker alone, the receiver operating characteristic (ROC) model had a prediction probability of 0.739 when platelet counts, LNR, and LMR were included. Cox hazard regression multivariable analysis showed that combinations of all three biomarkers were the strongest predictor of 30-day mortality (p < 0.021). Combined with these three easily measurable biomarkers at admission, they could help identify AAAD patients with a high risk of 30-day mortality. |
format | Online Article Text |
id | pubmed-7191390 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Hindawi |
record_format | MEDLINE/PubMed |
spelling | pubmed-71913902020-05-07 Relationship of Platelet Counts and Inflammatory Markers to 30-Day Mortality Risk in Patients with Acute Type A Aortic Dissection Chen, Yiping Lin, Yanjuan Zhang, Haoruo Peng, Yanchun Li, Sailan Huang, Xizhen Biomed Res Int Research Article Markers of prothrombotic state and inflammation are associated with the prognosis of patients with acute type A aortic dissection (AAAD). However, it is unclear that the relationship between these biomarkers and their combined impact on risk stratification. The present study evaluated the prognostic value of platelet counts, lymphocyte to neutrophil ratio (LNR), and lymphocyte to monocyte ratio (LMR), alone and in combination. A retrospective analysis of clinical data of 744 AAAD patients was conducted to identify whether these biomarkers were related to the 30-day mortality risk. A Kaplan-Meier analysis and log-rank test were used to compare survival between groups. A Cox hazard regression multivariable analysis was performed for 30-day mortality. Individual biomarker (platelet count, LNR, or LMR) was unable to predict 30-day mortality. However, combinations of all three biomarkers provided additive predictive value over either marker alone, the receiver operating characteristic (ROC) model had a prediction probability of 0.739 when platelet counts, LNR, and LMR were included. Cox hazard regression multivariable analysis showed that combinations of all three biomarkers were the strongest predictor of 30-day mortality (p < 0.021). Combined with these three easily measurable biomarkers at admission, they could help identify AAAD patients with a high risk of 30-day mortality. Hindawi 2020-04-21 /pmc/articles/PMC7191390/ /pubmed/32382526 http://dx.doi.org/10.1155/2020/1057496 Text en Copyright © 2020 Yiping Chen et al. http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Article Chen, Yiping Lin, Yanjuan Zhang, Haoruo Peng, Yanchun Li, Sailan Huang, Xizhen Relationship of Platelet Counts and Inflammatory Markers to 30-Day Mortality Risk in Patients with Acute Type A Aortic Dissection |
title | Relationship of Platelet Counts and Inflammatory Markers to 30-Day Mortality Risk in Patients with Acute Type A Aortic Dissection |
title_full | Relationship of Platelet Counts and Inflammatory Markers to 30-Day Mortality Risk in Patients with Acute Type A Aortic Dissection |
title_fullStr | Relationship of Platelet Counts and Inflammatory Markers to 30-Day Mortality Risk in Patients with Acute Type A Aortic Dissection |
title_full_unstemmed | Relationship of Platelet Counts and Inflammatory Markers to 30-Day Mortality Risk in Patients with Acute Type A Aortic Dissection |
title_short | Relationship of Platelet Counts and Inflammatory Markers to 30-Day Mortality Risk in Patients with Acute Type A Aortic Dissection |
title_sort | relationship of platelet counts and inflammatory markers to 30-day mortality risk in patients with acute type a aortic dissection |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7191390/ https://www.ncbi.nlm.nih.gov/pubmed/32382526 http://dx.doi.org/10.1155/2020/1057496 |
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