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A Risk Score to Diagnose Cardiac Involvement and Provide Prognosis Information in Patients at Risk of Cardiac Light-Chain Amyloidosis
BACKGROUND: Cardiac light-chain amyloidosis (AL CA) portends poor prognosis. Contrast cardiac magnetic resonance (CMR) with late gadolinium enhancement (LGE) imaging is an important tool in recognizing AL CA. But contraindications to contrast CMR would significantly restrict its clinical application...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8959494/ https://www.ncbi.nlm.nih.gov/pubmed/35355963 http://dx.doi.org/10.3389/fcvm.2022.817456 |
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author | Wu, Yan Pu, Cailing Zhu, Wenchao He, Chengbin Fei, Jingle Hu, Hongjie |
author_facet | Wu, Yan Pu, Cailing Zhu, Wenchao He, Chengbin Fei, Jingle Hu, Hongjie |
author_sort | Wu, Yan |
collection | PubMed |
description | BACKGROUND: Cardiac light-chain amyloidosis (AL CA) portends poor prognosis. Contrast cardiac magnetic resonance (CMR) with late gadolinium enhancement (LGE) imaging is an important tool in recognizing AL CA. But contraindications to contrast CMR would significantly restrict its clinical application value. Our study aims to construct a convenient risk score to help identify cardiac involvement in patients at risk of AL CA. Moreover, we also investigate whether this risk score could provide prognosis information. MATERIALS AND METHODS: Sixty-three patients at risk of AL CA were retrospectively included in our study. Basic clinical characters, lab results, 12-lead electrocardiogram data, and cardiac magnetic resonance image data were collected. AL CA was diagnosed according to typical CA LGE pattern. Logistic analysis was used to figure out predictive parameters of AL CA and their β coefficients, further constructing the risk score. Receiver operating characteristics (ROC) curve was used to find the cut-off point best distinguishing AL CA+ from AL CA–patients. Bootstrapping was used for internal validation. All patients were divided into high-risk and low-risk group according to the diagnostic cut-off point, and followed up for survival information. Kaplan-Meier plots and log-rank test were performed to analyze if this score had prognostic value. RESULTS: The risk score finally consisted of 4 parameters: pericardial effusion (PE) (1 point), low electrocardiographic QRS voltages (LQRSV) (1 point), CMR-derived impaired global radial strain (GRS) (<15.14%) (1 point) and increased left ventricular maximum wall thickness (LVMWT) (>13 mm) (2 points). Total score ranged from 0 to 5 points. A cut-off point of 1.5 showed highest accuracy in diagnosing AL CA with an AUC of 0.961 (95% CI: 0.924–0.997, sensitivity: 90.6%, specificity: 83.9%). Kaplan-Meier plots and log-rank test showed that the high-risk group had significantly poor overall survival rates. CONCLUSION: In patients at risk of AL CA, a risk score incorporating the presence of PE, LQRSV, and CMR-derived impaired GRS and increased LVMWT is predictive of a diagnosis of AL CA by LGE criteria. This risk score may be helpful especially when contrast CMR is not available or contraindicated, and further studies should be considered to validate this score. |
format | Online Article Text |
id | pubmed-8959494 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-89594942022-03-29 A Risk Score to Diagnose Cardiac Involvement and Provide Prognosis Information in Patients at Risk of Cardiac Light-Chain Amyloidosis Wu, Yan Pu, Cailing Zhu, Wenchao He, Chengbin Fei, Jingle Hu, Hongjie Front Cardiovasc Med Cardiovascular Medicine BACKGROUND: Cardiac light-chain amyloidosis (AL CA) portends poor prognosis. Contrast cardiac magnetic resonance (CMR) with late gadolinium enhancement (LGE) imaging is an important tool in recognizing AL CA. But contraindications to contrast CMR would significantly restrict its clinical application value. Our study aims to construct a convenient risk score to help identify cardiac involvement in patients at risk of AL CA. Moreover, we also investigate whether this risk score could provide prognosis information. MATERIALS AND METHODS: Sixty-three patients at risk of AL CA were retrospectively included in our study. Basic clinical characters, lab results, 12-lead electrocardiogram data, and cardiac magnetic resonance image data were collected. AL CA was diagnosed according to typical CA LGE pattern. Logistic analysis was used to figure out predictive parameters of AL CA and their β coefficients, further constructing the risk score. Receiver operating characteristics (ROC) curve was used to find the cut-off point best distinguishing AL CA+ from AL CA–patients. Bootstrapping was used for internal validation. All patients were divided into high-risk and low-risk group according to the diagnostic cut-off point, and followed up for survival information. Kaplan-Meier plots and log-rank test were performed to analyze if this score had prognostic value. RESULTS: The risk score finally consisted of 4 parameters: pericardial effusion (PE) (1 point), low electrocardiographic QRS voltages (LQRSV) (1 point), CMR-derived impaired global radial strain (GRS) (<15.14%) (1 point) and increased left ventricular maximum wall thickness (LVMWT) (>13 mm) (2 points). Total score ranged from 0 to 5 points. A cut-off point of 1.5 showed highest accuracy in diagnosing AL CA with an AUC of 0.961 (95% CI: 0.924–0.997, sensitivity: 90.6%, specificity: 83.9%). Kaplan-Meier plots and log-rank test showed that the high-risk group had significantly poor overall survival rates. CONCLUSION: In patients at risk of AL CA, a risk score incorporating the presence of PE, LQRSV, and CMR-derived impaired GRS and increased LVMWT is predictive of a diagnosis of AL CA by LGE criteria. This risk score may be helpful especially when contrast CMR is not available or contraindicated, and further studies should be considered to validate this score. Frontiers Media S.A. 2022-03-09 /pmc/articles/PMC8959494/ /pubmed/35355963 http://dx.doi.org/10.3389/fcvm.2022.817456 Text en Copyright © 2022 Wu, Pu, Zhu, He, Fei and Hu. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Cardiovascular Medicine Wu, Yan Pu, Cailing Zhu, Wenchao He, Chengbin Fei, Jingle Hu, Hongjie A Risk Score to Diagnose Cardiac Involvement and Provide Prognosis Information in Patients at Risk of Cardiac Light-Chain Amyloidosis |
title | A Risk Score to Diagnose Cardiac Involvement and Provide Prognosis Information in Patients at Risk of Cardiac Light-Chain Amyloidosis |
title_full | A Risk Score to Diagnose Cardiac Involvement and Provide Prognosis Information in Patients at Risk of Cardiac Light-Chain Amyloidosis |
title_fullStr | A Risk Score to Diagnose Cardiac Involvement and Provide Prognosis Information in Patients at Risk of Cardiac Light-Chain Amyloidosis |
title_full_unstemmed | A Risk Score to Diagnose Cardiac Involvement and Provide Prognosis Information in Patients at Risk of Cardiac Light-Chain Amyloidosis |
title_short | A Risk Score to Diagnose Cardiac Involvement and Provide Prognosis Information in Patients at Risk of Cardiac Light-Chain Amyloidosis |
title_sort | risk score to diagnose cardiac involvement and provide prognosis information in patients at risk of cardiac light-chain amyloidosis |
topic | Cardiovascular Medicine |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8959494/ https://www.ncbi.nlm.nih.gov/pubmed/35355963 http://dx.doi.org/10.3389/fcvm.2022.817456 |
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