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A predictive nomogram of bleeding risk in patients with atrial fibrillation after drug-eluting stent implantation

BACKGROUND: The use of anticoagulants and antiplatelet therapies is associated with a higher risk of bleeding in atrial fibrillation (AF) patients after percutaneous coronary intervention, especially after stent implantation. However, no accurate bleeding risk prediction tool has been developed for...

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Autores principales: Qian, Jun, Zan, Jiyong, Kuang, Lijun, Che, Lin, Yu, Yunan, Shen, Ting, Tang, Jiani, Chen, Fei, Liu, Xuebo
Formato: Online Artículo Texto
Lenguaje:English
Publicado: AME Publishing Company 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7940957/
https://www.ncbi.nlm.nih.gov/pubmed/33708820
http://dx.doi.org/10.21037/atm-20-3971
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author Qian, Jun
Zan, Jiyong
Kuang, Lijun
Che, Lin
Yu, Yunan
Shen, Ting
Tang, Jiani
Chen, Fei
Liu, Xuebo
author_facet Qian, Jun
Zan, Jiyong
Kuang, Lijun
Che, Lin
Yu, Yunan
Shen, Ting
Tang, Jiani
Chen, Fei
Liu, Xuebo
author_sort Qian, Jun
collection PubMed
description BACKGROUND: The use of anticoagulants and antiplatelet therapies is associated with a higher risk of bleeding in atrial fibrillation (AF) patients after percutaneous coronary intervention, especially after stent implantation. However, no accurate bleeding risk prediction tool has been developed for these patients. The aim of this study was thus to establish a bleeding risk prediction model (predictive nomogram) for patients with AF after stent implantation. METHODS: Construction of the predictive nomogram was based on a retrospective study, which enrolled 943 AF patients who underwent drug-eluting stent implantation between May 2012 and September 2016. A range of factors, including demographics, comorbidities, medication strategies, arterial access, and laboratory tests, were collected as baseline data. The least absolute shrinkage and selection operator (LASSO) and multivariate logistic regression analysis were used to identify the key clinical features for construction of the predictive nomogram. The concordance index (C-index) and internal validation were used to evaluate the efficacy of the nomogram. RESULTS: Of the 943 AF patients that underwent stent implantation, the occurrence of bleeding events was 8.2% (77 out of 943). Key predictors included the number of antiplatelet drugs, peptic ulcer, cerebral infarction, type 2 diabetes, thrombocytopenia, anemia, prior myocardial infarction, sex (male), use of anticoagulant drugs, liver dysfunction, hypertension, and acute myocardial infarction. These predictors were used to construct the nomogram. The C-index for the prediction of bleeding risk by the nomogram was 0.841 (95% CI: 0.79–0.89), which indicated good discrimination and calibration. The C-index of internal validation was 0.795, which demonstrated good efficacy of the model. CONCLUSIONS: This study suggests that our novel nomogram can accurately predict bleeding risk in AF patients after stent implantation during hospitalization, thereby helping to avoid complications. The nomogram may also be helpful for the creation of individualized post-discharge medication strategies.
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spelling pubmed-79409572021-03-10 A predictive nomogram of bleeding risk in patients with atrial fibrillation after drug-eluting stent implantation Qian, Jun Zan, Jiyong Kuang, Lijun Che, Lin Yu, Yunan Shen, Ting Tang, Jiani Chen, Fei Liu, Xuebo Ann Transl Med Original Article BACKGROUND: The use of anticoagulants and antiplatelet therapies is associated with a higher risk of bleeding in atrial fibrillation (AF) patients after percutaneous coronary intervention, especially after stent implantation. However, no accurate bleeding risk prediction tool has been developed for these patients. The aim of this study was thus to establish a bleeding risk prediction model (predictive nomogram) for patients with AF after stent implantation. METHODS: Construction of the predictive nomogram was based on a retrospective study, which enrolled 943 AF patients who underwent drug-eluting stent implantation between May 2012 and September 2016. A range of factors, including demographics, comorbidities, medication strategies, arterial access, and laboratory tests, were collected as baseline data. The least absolute shrinkage and selection operator (LASSO) and multivariate logistic regression analysis were used to identify the key clinical features for construction of the predictive nomogram. The concordance index (C-index) and internal validation were used to evaluate the efficacy of the nomogram. RESULTS: Of the 943 AF patients that underwent stent implantation, the occurrence of bleeding events was 8.2% (77 out of 943). Key predictors included the number of antiplatelet drugs, peptic ulcer, cerebral infarction, type 2 diabetes, thrombocytopenia, anemia, prior myocardial infarction, sex (male), use of anticoagulant drugs, liver dysfunction, hypertension, and acute myocardial infarction. These predictors were used to construct the nomogram. The C-index for the prediction of bleeding risk by the nomogram was 0.841 (95% CI: 0.79–0.89), which indicated good discrimination and calibration. The C-index of internal validation was 0.795, which demonstrated good efficacy of the model. CONCLUSIONS: This study suggests that our novel nomogram can accurately predict bleeding risk in AF patients after stent implantation during hospitalization, thereby helping to avoid complications. The nomogram may also be helpful for the creation of individualized post-discharge medication strategies. AME Publishing Company 2021-02 /pmc/articles/PMC7940957/ /pubmed/33708820 http://dx.doi.org/10.21037/atm-20-3971 Text en 2021 Annals of Translational Medicine. All rights reserved. https://creativecommons.org/licenses/by-nc-nd/4.0/Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0 (https://creativecommons.org/licenses/by-nc-nd/4.0/) .
spellingShingle Original Article
Qian, Jun
Zan, Jiyong
Kuang, Lijun
Che, Lin
Yu, Yunan
Shen, Ting
Tang, Jiani
Chen, Fei
Liu, Xuebo
A predictive nomogram of bleeding risk in patients with atrial fibrillation after drug-eluting stent implantation
title A predictive nomogram of bleeding risk in patients with atrial fibrillation after drug-eluting stent implantation
title_full A predictive nomogram of bleeding risk in patients with atrial fibrillation after drug-eluting stent implantation
title_fullStr A predictive nomogram of bleeding risk in patients with atrial fibrillation after drug-eluting stent implantation
title_full_unstemmed A predictive nomogram of bleeding risk in patients with atrial fibrillation after drug-eluting stent implantation
title_short A predictive nomogram of bleeding risk in patients with atrial fibrillation after drug-eluting stent implantation
title_sort predictive nomogram of bleeding risk in patients with atrial fibrillation after drug-eluting stent implantation
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7940957/
https://www.ncbi.nlm.nih.gov/pubmed/33708820
http://dx.doi.org/10.21037/atm-20-3971
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