TY - JOUR
T1 - Advanced Hemodynamic Monitoring Allows Recognition of Early Response Patterns to Diuresis in Congestive Heart Failure Patients
AU - Dagan, Maya
AU - Kolben, Yotam
AU - Goldstein, Nir
AU - Ben Ishay, Arik
AU - Fons, Meir
AU - Merin, Roei
AU - Eisenkraft, Arik
AU - Amir, Offer
AU - Asleh, Rabea
AU - Ben-Yehuda, Arie
AU - Nachman, Dean
N1 - Publisher Copyright:
© 2022 by the authors.
PY - 2022/12/21
Y1 - 2022/12/21
N2 - There are no clear guidelines for diuretic administration in heart failure (HF), and reliable markers are needed to tailor treatment. Continuous monitoring of multiple advanced physiological parameters during diuresis may allow better differentiation of patients into subgroups according to their responses. In this study, 29 HF patients were monitored during outpatient intravenous diuresis, using a noninvasive wearable multi-parameter monitor. Analysis of changes in these parameters during the course of diuresis aimed to recognize subgroups with different response patterns. Parameters did not change significantly, however, subgroup analysis of the last quartile of treatment showed significant differences in cardiac output, cardiac index, stroke volume, pulse rate, and systemic vascular resistance according to gender, and in systolic blood pressure according to habitus. Changes in the last quartile could be differentiated using k-means, a technique of unsupervised machine learning. Moreover, patients’ responses could be best clustered into four groups. Analysis of baseline parameters showed that two of the clusters differed by baseline parameters, body mass index, and diabetes status. To conclude, we show that physiological changes during diuresis in HF patients can be categorized into subgroups sharing similar response trends, making noninvasive monitoring a potential key to personalized treatment in HF.
AB - There are no clear guidelines for diuretic administration in heart failure (HF), and reliable markers are needed to tailor treatment. Continuous monitoring of multiple advanced physiological parameters during diuresis may allow better differentiation of patients into subgroups according to their responses. In this study, 29 HF patients were monitored during outpatient intravenous diuresis, using a noninvasive wearable multi-parameter monitor. Analysis of changes in these parameters during the course of diuresis aimed to recognize subgroups with different response patterns. Parameters did not change significantly, however, subgroup analysis of the last quartile of treatment showed significant differences in cardiac output, cardiac index, stroke volume, pulse rate, and systemic vascular resistance according to gender, and in systolic blood pressure according to habitus. Changes in the last quartile could be differentiated using k-means, a technique of unsupervised machine learning. Moreover, patients’ responses could be best clustered into four groups. Analysis of baseline parameters showed that two of the clusters differed by baseline parameters, body mass index, and diabetes status. To conclude, we show that physiological changes during diuresis in HF patients can be categorized into subgroups sharing similar response trends, making noninvasive monitoring a potential key to personalized treatment in HF.
KW - congestive heart failure
KW - digital health
KW - diuresis
KW - personalized medicine
KW - remote patient monitoring
UR - http://www.scopus.com/inward/record.url?scp=85145940348&partnerID=8YFLogxK
U2 - 10.3390/jcm12010045
DO - 10.3390/jcm12010045
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C2 - 36614848
AN - SCOPUS:85145940348
SN - 2077-0383
VL - 12
JO - Journal of Clinical Medicine
JF - Journal of Clinical Medicine
IS - 1
M1 - 45
ER -