Maximiliano Mollura, Christian Niklas, Stefanie Messner, M. Weigand, J. Larmann, R. Barbieri
{"title":"Characterization of Heart Rate Variability Dynamics in Heart Failure Patients Admitted to Intensive Care Unit","authors":"Maximiliano Mollura, Christian Niklas, Stefanie Messner, M. Weigand, J. Larmann, R. Barbieri","doi":"10.22489/CinC.2022.209","DOIUrl":null,"url":null,"abstract":"Introduction: The high mortality and difficulty of diagnosis make Heart failure $(HF)$ a severe burden for the healthcare system, especially in intensive care units $(ICU)$. Goal: This work proposes a method to characterize $HF$ patients using autonomic indices from electrocardiogram $(ECG)$ recordings in the $ICU$ Methods: We considered 52 $ICU$ patients from the MIMIC-III database subjected to brain natriuretic peptide (NT-proBNP) laboratory measurement during their stay, of which 41 showed a positive reading for likely $HF$ due to elevated levels of the peptide $(NT-proBNP > 300\\ pg/mL)$. RR intervals from 1 hour $ECG$ recordings in the hour preceding NT-proBNP measurements were selected, and a point process framework was applied to extract time-varying estimates of indices related to autonomic nervous system activity. A general linear mixed-effects model was used to analyze the dynamics of the two populations.Results: Results showed an increasing average $RR$ interval in the negative population $(p < 0.001)$. In parallel, $RR$ variability increased in negative subjects $(p < 0.001)$ and decreased in positive patients $(p < 0.001)$. High frequency power $(p < 0.001)$ further showed different dynamics between the two populations. Conclusions: Results point at different autonomic cardiac control dynamics in patients with positive NT-proBNP test in the hour preceding the measurement.","PeriodicalId":117840,"journal":{"name":"2022 Computing in Cardiology (CinC)","volume":"42 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-09-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 Computing in Cardiology (CinC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.22489/CinC.2022.209","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Introduction: The high mortality and difficulty of diagnosis make Heart failure $(HF)$ a severe burden for the healthcare system, especially in intensive care units $(ICU)$. Goal: This work proposes a method to characterize $HF$ patients using autonomic indices from electrocardiogram $(ECG)$ recordings in the $ICU$ Methods: We considered 52 $ICU$ patients from the MIMIC-III database subjected to brain natriuretic peptide (NT-proBNP) laboratory measurement during their stay, of which 41 showed a positive reading for likely $HF$ due to elevated levels of the peptide $(NT-proBNP > 300\ pg/mL)$. RR intervals from 1 hour $ECG$ recordings in the hour preceding NT-proBNP measurements were selected, and a point process framework was applied to extract time-varying estimates of indices related to autonomic nervous system activity. A general linear mixed-effects model was used to analyze the dynamics of the two populations.Results: Results showed an increasing average $RR$ interval in the negative population $(p < 0.001)$. In parallel, $RR$ variability increased in negative subjects $(p < 0.001)$ and decreased in positive patients $(p < 0.001)$. High frequency power $(p < 0.001)$ further showed different dynamics between the two populations. Conclusions: Results point at different autonomic cardiac control dynamics in patients with positive NT-proBNP test in the hour preceding the measurement.