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Risk Prediction Model Based on Biomarkers of Remodeling in Patients with Acute Anterior ST-Segment Elevation Myocardial Infarction
BACKGROUND: The aim of the present study was to develop a risk prediction model in patients with acute anterior ST-segment elevation myocardial infarction (STEMI). MATERIAL/METHODS: Clinical data from 333 patients with acute anterior STEMI were retrospectively analyzed. Clinical echocardiographic an...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
International Scientific Literature, Inc.
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8306886/ https://www.ncbi.nlm.nih.gov/pubmed/34282109 http://dx.doi.org/10.12659/MSM.927404 |
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author | Liu, Zeyan Liu, Lijun Cheng, Jinglin Zhang, Hao |
author_facet | Liu, Zeyan Liu, Lijun Cheng, Jinglin Zhang, Hao |
author_sort | Liu, Zeyan |
collection | PubMed |
description | BACKGROUND: The aim of the present study was to develop a risk prediction model in patients with acute anterior ST-segment elevation myocardial infarction (STEMI). MATERIAL/METHODS: Clinical data from 333 patients with acute anterior STEMI were retrospectively analyzed. Clinical echocardiographic and angiographic data from patients with left ventricular remodeling (LVR) and those without LVR were compared. Factors that influenced risk were identified using multivariate logistic regression analysis. The area under the curve (AUC) of the receiver operating characteristic curve was used to assess the diagnostic performance of the model. RESULTS: After 6-month follow-up, 135 of the patients experienced LVR (LVR group), whereas 198 did not (non-LVR group). Results of multivariate analysis showed that the number of stenosed coronary vessels, left ventricular end-diastolic volume (LVEDV), left ventricular ejection fraction (LVEF), transforming growth factor-beta (TGF-β) at admission, and cardiac troponin I 3 days after admission (3-d cTnI) were all factors predictive of LVR in patients with acute anterior STEMI (all P<0.05). The established prediction model was Y=−20.639+0.711×number of stenosed coronary vessels + 0.137×LVEDV-0.129×LVEF+0.026×TGF-β at admission + 0.162×3-d cTnI. The estimated AUC of this model was 0.978 (95% confidence interval [CI] 0.955–0.991), significantly superior to the single-factor numbers for stenosed coronary vessel of 0.650 (95% CI 0.597–0.702), LVEDV of 0.876 (95% CI 0.836–0.910), LVEF of 0.684 (95% CI 0.631–0.734), TGF-β at admission of 0.696 (95% CI 0.644–0.745), cTnI at admission of 0.913 (95% CI 0.877–0.941), and 3-d cTnI of 0.945 (95% CI 0.914–0.967). CONCLUSIONS: The established model had excellent diagnostic accuracy for predicting LVR in patients with acute anterior STEMI. |
format | Online Article Text |
id | pubmed-8306886 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | International Scientific Literature, Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-83068862021-08-02 Risk Prediction Model Based on Biomarkers of Remodeling in Patients with Acute Anterior ST-Segment Elevation Myocardial Infarction Liu, Zeyan Liu, Lijun Cheng, Jinglin Zhang, Hao Med Sci Monit Clinical Research BACKGROUND: The aim of the present study was to develop a risk prediction model in patients with acute anterior ST-segment elevation myocardial infarction (STEMI). MATERIAL/METHODS: Clinical data from 333 patients with acute anterior STEMI were retrospectively analyzed. Clinical echocardiographic and angiographic data from patients with left ventricular remodeling (LVR) and those without LVR were compared. Factors that influenced risk were identified using multivariate logistic regression analysis. The area under the curve (AUC) of the receiver operating characteristic curve was used to assess the diagnostic performance of the model. RESULTS: After 6-month follow-up, 135 of the patients experienced LVR (LVR group), whereas 198 did not (non-LVR group). Results of multivariate analysis showed that the number of stenosed coronary vessels, left ventricular end-diastolic volume (LVEDV), left ventricular ejection fraction (LVEF), transforming growth factor-beta (TGF-β) at admission, and cardiac troponin I 3 days after admission (3-d cTnI) were all factors predictive of LVR in patients with acute anterior STEMI (all P<0.05). The established prediction model was Y=−20.639+0.711×number of stenosed coronary vessels + 0.137×LVEDV-0.129×LVEF+0.026×TGF-β at admission + 0.162×3-d cTnI. The estimated AUC of this model was 0.978 (95% confidence interval [CI] 0.955–0.991), significantly superior to the single-factor numbers for stenosed coronary vessel of 0.650 (95% CI 0.597–0.702), LVEDV of 0.876 (95% CI 0.836–0.910), LVEF of 0.684 (95% CI 0.631–0.734), TGF-β at admission of 0.696 (95% CI 0.644–0.745), cTnI at admission of 0.913 (95% CI 0.877–0.941), and 3-d cTnI of 0.945 (95% CI 0.914–0.967). CONCLUSIONS: The established model had excellent diagnostic accuracy for predicting LVR in patients with acute anterior STEMI. International Scientific Literature, Inc. 2021-07-20 /pmc/articles/PMC8306886/ /pubmed/34282109 http://dx.doi.org/10.12659/MSM.927404 Text en © Med Sci Monit, 2021 https://creativecommons.org/licenses/by-nc-nd/4.0/This work is licensed under Creative Common Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0 (https://creativecommons.org/licenses/by-nc-nd/4.0/) ) |
spellingShingle | Clinical Research Liu, Zeyan Liu, Lijun Cheng, Jinglin Zhang, Hao Risk Prediction Model Based on Biomarkers of Remodeling in Patients with Acute Anterior ST-Segment Elevation Myocardial Infarction |
title | Risk Prediction Model Based on Biomarkers of Remodeling in Patients with Acute Anterior ST-Segment Elevation Myocardial Infarction |
title_full | Risk Prediction Model Based on Biomarkers of Remodeling in Patients with Acute Anterior ST-Segment Elevation Myocardial Infarction |
title_fullStr | Risk Prediction Model Based on Biomarkers of Remodeling in Patients with Acute Anterior ST-Segment Elevation Myocardial Infarction |
title_full_unstemmed | Risk Prediction Model Based on Biomarkers of Remodeling in Patients with Acute Anterior ST-Segment Elevation Myocardial Infarction |
title_short | Risk Prediction Model Based on Biomarkers of Remodeling in Patients with Acute Anterior ST-Segment Elevation Myocardial Infarction |
title_sort | risk prediction model based on biomarkers of remodeling in patients with acute anterior st-segment elevation myocardial infarction |
topic | Clinical Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8306886/ https://www.ncbi.nlm.nih.gov/pubmed/34282109 http://dx.doi.org/10.12659/MSM.927404 |
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