Cargando…

337. Association of atrial fibrillation burden with in-hospital mortality in patients with sepsis: Analysis of MIMIC-III database

BACKGROUND: Atrial fibrillation (AF) is known as a poor prognostic factor in sepsis patients. Recently, research has been conducted on the clinical effects of AF burden, however, there have been no studies on the effect of AF burden in patients with sepsis. We aim to examine the effect of AF burden...

Descripción completa

Detalles Bibliográficos
Autores principales: Lee, Yongseop, Seo, Jihoon, Han, Min, Ahn, Sangmin, Ah Lee, Jung, Ho Kim, Jung, Young Ahn, Jin, Jin Jeong, Su, Su Ku, Nam, Yong Choi, Jun, Yeom, Joon-sup, Yoon Park, Se, Yoon, Dukyong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10678487/
http://dx.doi.org/10.1093/ofid/ofad500.408
_version_ 1785150373431869440
author Lee, Yongseop
Seo, Jihoon
Han, Min
Ahn, Sangmin
Ah Lee, Jung
Ho Kim, Jung
Young Ahn, Jin
Jin Jeong, Su
Su Ku, Nam
Yong Choi, Jun
Yeom, Joon-sup
Yoon Park, Se
Yoon, Dukyong
author_facet Lee, Yongseop
Seo, Jihoon
Han, Min
Ahn, Sangmin
Ah Lee, Jung
Ho Kim, Jung
Young Ahn, Jin
Jin Jeong, Su
Su Ku, Nam
Yong Choi, Jun
Yeom, Joon-sup
Yoon Park, Se
Yoon, Dukyong
author_sort Lee, Yongseop
collection PubMed
description BACKGROUND: Atrial fibrillation (AF) is known as a poor prognostic factor in sepsis patients. Recently, research has been conducted on the clinical effects of AF burden, however, there have been no studies on the effect of AF burden in patients with sepsis. We aim to examine the effect of AF burden on in-hospital mortality in patients with sepsis. METHODS: This study was conducted using patient and electrocardiogram (ECG) waveform data extracted from the Medical Information Mart for Intensive Care III (MIMIC-III) database, which was organized by the Beth Israel Deaconess Medical Center Intensive Care Unit (ICU) from 2001 to 2012. Sepsis was identified by ICD-9 code, and patients 18 years and older with lead II ECG waveform data were included in the analysis. AF classification convolutional neural network models were trained using a public ECG dataset (PTB-XL and 2017 PhysioNet/CinC Challenge), and external validation was performed using another public ECG dataset (Shaoxing and Ningbo hospital ECG database). ECG waveforms were analyzed using the SE-ResNet-34 model, which showed the best performance in external validation. Signal quality assessment was performed, and waveforms with poor signal quality were excluded. The entire waveform data of each patient was divided into 10-second segments, and the model was applied to each segment. AF burden was calculated as the ratio of AF waveforms to the total number of waveforms. The effect of AF burden on in-hospital mortality was analyzed with multivariate logistic regression, and clinical variables measured first after admission to the ICU were included in the analysis as covariates. [Figure: see text] Model performance was evaluated with cut-off value 0.5. PPV, positive predictive value; AUROC, area under receiver operating characteristic curve. RESULTS: A total of 795 patients with sepsis were included in the analysis. Median age was 67 (IQR, 54-79) years. Total 270 (34.0%) were in non-survivor group, and median AF burden was 2.86% (IQR 0.28%-22.07%). AF burden was significantly higher in non-survivor group (8.79% vs 1.62%, p ≤0.001). In the multivariate analysis, AF burden (10-unit increase) (OR, 1.13; 95% CI, 1.06-1.21; p ≤0.001), higher level of phosphate (OR, 1.17; 95% CI, 1.01-1.35; p=0.035), and higher level of lactate (OR, 1.42; 95% CI, 1.26-1.61; p ≤0.001) were identified as risk factors for in-hospital mortality. [Figure: see text] [Figure: see text] CONCLUSION: Higher AF burden is associated with in-hospital mortality in patients with sepsis. DISCLOSURES: All Authors: No reported disclosures
format Online
Article
Text
id pubmed-10678487
institution National Center for Biotechnology Information
language English
publishDate 2023
publisher Oxford University Press
record_format MEDLINE/PubMed
spelling pubmed-106784872023-11-27 337. Association of atrial fibrillation burden with in-hospital mortality in patients with sepsis: Analysis of MIMIC-III database Lee, Yongseop Seo, Jihoon Han, Min Ahn, Sangmin Ah Lee, Jung Ho Kim, Jung Young Ahn, Jin Jin Jeong, Su Su Ku, Nam Yong Choi, Jun Yeom, Joon-sup Yoon Park, Se Yoon, Dukyong Open Forum Infect Dis Abstract BACKGROUND: Atrial fibrillation (AF) is known as a poor prognostic factor in sepsis patients. Recently, research has been conducted on the clinical effects of AF burden, however, there have been no studies on the effect of AF burden in patients with sepsis. We aim to examine the effect of AF burden on in-hospital mortality in patients with sepsis. METHODS: This study was conducted using patient and electrocardiogram (ECG) waveform data extracted from the Medical Information Mart for Intensive Care III (MIMIC-III) database, which was organized by the Beth Israel Deaconess Medical Center Intensive Care Unit (ICU) from 2001 to 2012. Sepsis was identified by ICD-9 code, and patients 18 years and older with lead II ECG waveform data were included in the analysis. AF classification convolutional neural network models were trained using a public ECG dataset (PTB-XL and 2017 PhysioNet/CinC Challenge), and external validation was performed using another public ECG dataset (Shaoxing and Ningbo hospital ECG database). ECG waveforms were analyzed using the SE-ResNet-34 model, which showed the best performance in external validation. Signal quality assessment was performed, and waveforms with poor signal quality were excluded. The entire waveform data of each patient was divided into 10-second segments, and the model was applied to each segment. AF burden was calculated as the ratio of AF waveforms to the total number of waveforms. The effect of AF burden on in-hospital mortality was analyzed with multivariate logistic regression, and clinical variables measured first after admission to the ICU were included in the analysis as covariates. [Figure: see text] Model performance was evaluated with cut-off value 0.5. PPV, positive predictive value; AUROC, area under receiver operating characteristic curve. RESULTS: A total of 795 patients with sepsis were included in the analysis. Median age was 67 (IQR, 54-79) years. Total 270 (34.0%) were in non-survivor group, and median AF burden was 2.86% (IQR 0.28%-22.07%). AF burden was significantly higher in non-survivor group (8.79% vs 1.62%, p ≤0.001). In the multivariate analysis, AF burden (10-unit increase) (OR, 1.13; 95% CI, 1.06-1.21; p ≤0.001), higher level of phosphate (OR, 1.17; 95% CI, 1.01-1.35; p=0.035), and higher level of lactate (OR, 1.42; 95% CI, 1.26-1.61; p ≤0.001) were identified as risk factors for in-hospital mortality. [Figure: see text] [Figure: see text] CONCLUSION: Higher AF burden is associated with in-hospital mortality in patients with sepsis. DISCLOSURES: All Authors: No reported disclosures Oxford University Press 2023-11-27 /pmc/articles/PMC10678487/ http://dx.doi.org/10.1093/ofid/ofad500.408 Text en © The Author(s) 2023. Published by Oxford University Press on behalf of Infectious Diseases Society of America. https://creativecommons.org/licenses/by/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Abstract
Lee, Yongseop
Seo, Jihoon
Han, Min
Ahn, Sangmin
Ah Lee, Jung
Ho Kim, Jung
Young Ahn, Jin
Jin Jeong, Su
Su Ku, Nam
Yong Choi, Jun
Yeom, Joon-sup
Yoon Park, Se
Yoon, Dukyong
337. Association of atrial fibrillation burden with in-hospital mortality in patients with sepsis: Analysis of MIMIC-III database
title 337. Association of atrial fibrillation burden with in-hospital mortality in patients with sepsis: Analysis of MIMIC-III database
title_full 337. Association of atrial fibrillation burden with in-hospital mortality in patients with sepsis: Analysis of MIMIC-III database
title_fullStr 337. Association of atrial fibrillation burden with in-hospital mortality in patients with sepsis: Analysis of MIMIC-III database
title_full_unstemmed 337. Association of atrial fibrillation burden with in-hospital mortality in patients with sepsis: Analysis of MIMIC-III database
title_short 337. Association of atrial fibrillation burden with in-hospital mortality in patients with sepsis: Analysis of MIMIC-III database
title_sort 337. association of atrial fibrillation burden with in-hospital mortality in patients with sepsis: analysis of mimic-iii database
topic Abstract
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10678487/
http://dx.doi.org/10.1093/ofid/ofad500.408
work_keys_str_mv AT leeyongseop 337associationofatrialfibrillationburdenwithinhospitalmortalityinpatientswithsepsisanalysisofmimiciiidatabase
AT seojihoon 337associationofatrialfibrillationburdenwithinhospitalmortalityinpatientswithsepsisanalysisofmimiciiidatabase
AT hanmin 337associationofatrialfibrillationburdenwithinhospitalmortalityinpatientswithsepsisanalysisofmimiciiidatabase
AT ahnsangmin 337associationofatrialfibrillationburdenwithinhospitalmortalityinpatientswithsepsisanalysisofmimiciiidatabase
AT ahleejung 337associationofatrialfibrillationburdenwithinhospitalmortalityinpatientswithsepsisanalysisofmimiciiidatabase
AT hokimjung 337associationofatrialfibrillationburdenwithinhospitalmortalityinpatientswithsepsisanalysisofmimiciiidatabase
AT youngahnjin 337associationofatrialfibrillationburdenwithinhospitalmortalityinpatientswithsepsisanalysisofmimiciiidatabase
AT jinjeongsu 337associationofatrialfibrillationburdenwithinhospitalmortalityinpatientswithsepsisanalysisofmimiciiidatabase
AT sukunam 337associationofatrialfibrillationburdenwithinhospitalmortalityinpatientswithsepsisanalysisofmimiciiidatabase
AT yongchoijun 337associationofatrialfibrillationburdenwithinhospitalmortalityinpatientswithsepsisanalysisofmimiciiidatabase
AT yeomjoonsup 337associationofatrialfibrillationburdenwithinhospitalmortalityinpatientswithsepsisanalysisofmimiciiidatabase
AT yoonparkse 337associationofatrialfibrillationburdenwithinhospitalmortalityinpatientswithsepsisanalysisofmimiciiidatabase
AT yoondukyong 337associationofatrialfibrillationburdenwithinhospitalmortalityinpatientswithsepsisanalysisofmimiciiidatabase