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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...

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Autores principales: Liu, Zeyan, Liu, Lijun, Cheng, Jinglin, Zhang, Hao
Formato: Online Artículo Texto
Lenguaje:English
Publicado: International Scientific Literature, Inc. 2021
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.
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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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