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Development of a Risk Score for QT Prolongation in the Intensive Care Unit Using Time-Series Electrocardiogram Data and Electronic Medical Records
OBJECTIVES: Drug-induced QT prolongation can lead to life-threatening arrhythmia. In the intensive care unit (ICU), various drugs are administered concurrently, which can increase the risk of QT prolongation. However, no well-validated method to evaluate the risk of QT prolongation in real-world cli...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Korean Society of Medical Informatics
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8369048/ https://www.ncbi.nlm.nih.gov/pubmed/34384200 http://dx.doi.org/10.4258/hir.2021.27.3.182 |
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author | Kim, Tae Young Choi, Byung Jin Koo, Yeryung Lee, Sukhoon Yoon, Dukyong |
author_facet | Kim, Tae Young Choi, Byung Jin Koo, Yeryung Lee, Sukhoon Yoon, Dukyong |
author_sort | Kim, Tae Young |
collection | PubMed |
description | OBJECTIVES: Drug-induced QT prolongation can lead to life-threatening arrhythmia. In the intensive care unit (ICU), various drugs are administered concurrently, which can increase the risk of QT prolongation. However, no well-validated method to evaluate the risk of QT prolongation in real-world clinical practice has been established. We developed a risk scoring model to continuously evaluate the quantitative risk of QT prolongation in real-world clinical practice in the ICU. METHODS: Continuous electrocardiogram (ECG) signals measured by patient monitoring devices and Electronic Medical Records data were collected for ICU patients. QT and RR intervals were measured from raw ECG data, and a corrected QT interval (QTc) was calculated by Bazett’s formula. A case-crossover study design was adopted. A case was defined as an occurrence of QT prolongation ≥12 hours after any previous QT prolongation. The patients served as their own controls. Conditional logistic regression was conducted to analyze prescription, surgical history, and laboratory test data. Based on the regression analysis, a QTc prolongation risk scoring model was established. RESULTS: In total, 811 ICU patients who experienced QT prolongation were included in this study. Prescription information for 13 drugs was included in the risk scoring model. In the validation dataset, the high-risk group showed a higher rate of QT prolongation than the low-and low moderate-risk groups. CONCLUSIONS: Our proposed model may facilitate risk stratification for QT prolongation during ICU care as well as the selection of appropriate drugs to prevent QT prolongation. |
format | Online Article Text |
id | pubmed-8369048 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Korean Society of Medical Informatics |
record_format | MEDLINE/PubMed |
spelling | pubmed-83690482021-08-26 Development of a Risk Score for QT Prolongation in the Intensive Care Unit Using Time-Series Electrocardiogram Data and Electronic Medical Records Kim, Tae Young Choi, Byung Jin Koo, Yeryung Lee, Sukhoon Yoon, Dukyong Healthc Inform Res Original Article OBJECTIVES: Drug-induced QT prolongation can lead to life-threatening arrhythmia. In the intensive care unit (ICU), various drugs are administered concurrently, which can increase the risk of QT prolongation. However, no well-validated method to evaluate the risk of QT prolongation in real-world clinical practice has been established. We developed a risk scoring model to continuously evaluate the quantitative risk of QT prolongation in real-world clinical practice in the ICU. METHODS: Continuous electrocardiogram (ECG) signals measured by patient monitoring devices and Electronic Medical Records data were collected for ICU patients. QT and RR intervals were measured from raw ECG data, and a corrected QT interval (QTc) was calculated by Bazett’s formula. A case-crossover study design was adopted. A case was defined as an occurrence of QT prolongation ≥12 hours after any previous QT prolongation. The patients served as their own controls. Conditional logistic regression was conducted to analyze prescription, surgical history, and laboratory test data. Based on the regression analysis, a QTc prolongation risk scoring model was established. RESULTS: In total, 811 ICU patients who experienced QT prolongation were included in this study. Prescription information for 13 drugs was included in the risk scoring model. In the validation dataset, the high-risk group showed a higher rate of QT prolongation than the low-and low moderate-risk groups. CONCLUSIONS: Our proposed model may facilitate risk stratification for QT prolongation during ICU care as well as the selection of appropriate drugs to prevent QT prolongation. Korean Society of Medical Informatics 2021-07 2021-07-31 /pmc/articles/PMC8369048/ /pubmed/34384200 http://dx.doi.org/10.4258/hir.2021.27.3.182 Text en © 2021 The Korean Society of Medical Informatics https://creativecommons.org/licenses/by-nc/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/ (https://creativecommons.org/licenses/by-nc/4.0/) ) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Original Article Kim, Tae Young Choi, Byung Jin Koo, Yeryung Lee, Sukhoon Yoon, Dukyong Development of a Risk Score for QT Prolongation in the Intensive Care Unit Using Time-Series Electrocardiogram Data and Electronic Medical Records |
title | Development of a Risk Score for QT Prolongation in the Intensive Care Unit Using Time-Series Electrocardiogram Data and Electronic Medical Records |
title_full | Development of a Risk Score for QT Prolongation in the Intensive Care Unit Using Time-Series Electrocardiogram Data and Electronic Medical Records |
title_fullStr | Development of a Risk Score for QT Prolongation in the Intensive Care Unit Using Time-Series Electrocardiogram Data and Electronic Medical Records |
title_full_unstemmed | Development of a Risk Score for QT Prolongation in the Intensive Care Unit Using Time-Series Electrocardiogram Data and Electronic Medical Records |
title_short | Development of a Risk Score for QT Prolongation in the Intensive Care Unit Using Time-Series Electrocardiogram Data and Electronic Medical Records |
title_sort | development of a risk score for qt prolongation in the intensive care unit using time-series electrocardiogram data and electronic medical records |
topic | Original Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8369048/ https://www.ncbi.nlm.nih.gov/pubmed/34384200 http://dx.doi.org/10.4258/hir.2021.27.3.182 |
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