Use of a Cardiac Scale to Predict Heart Failure Events: Design of SCALE-HF 1.
algorithms
electric impedance
heart failure
hospitalization
prospective studies
Journal
Circulation. Heart failure
ISSN: 1941-3297
Titre abrégé: Circ Heart Fail
Pays: United States
ID NLM: 101479941
Informations de publication
Date de publication:
05 2023
05 2023
Historique:
medline:
18
5
2023
pubmed:
16
5
2023
entrez:
16
5
2023
Statut:
ppublish
Résumé
There is a need for simple, noninvasive solutions to remotely monitor and predict worsening heart failure (HF) events. SCALE-HF 1 (Surveillance and Alert-Based Multiparameter Monitoring to Reduce Worsening Heart Failure Events) is a prospective, multicenter study that will develop and assess the accuracy of the heart function index-a composite algorithm of noninvasive hemodynamic biomarkers from a cardiac scale-in predicting worsening HF events. Approximately 300 patients with chronic HF and recent decompensation will be enrolled in this observational study for model development. Patients will be encouraged to take daily cardiac scale measurements. Approximately 50 HF events, defined as an urgent, unscheduled clinic, emergency department, or hospitalization for worsening HF will be used for model development. The composite index will be developed from hemodynamic biomarkers derived from ECG, ballistocardiogram, and impedance plethysmogram signals measured from the cardiac scale. Biomarkers of interest include weight, peripheral impedance, pulse rate and variability, and estimates of stroke volume, cardiac output, and blood pressure captured through the cardiac scale. The sensitivity, unexplained alert rate, and alerting time of the index in predicting worsening HF events will be evaluated and compared with the performance of simple weight-based rule-of-thumb algorithms (eg, weight increase of 3 lbs in 1 day or 5 lbs in 7 days) that are often used in practice. SCALE-HF 1 is the first study to develop and evaluate the performance of a composite index derived from noninvasive hemodynamic biomarkers measured from a cardiac scale in predicting worsening HF events. Subsequent studies will validate the heart function index and assess its ability to improve patient outcomes. URL: https://www. gov; Unique identifier: NCT04882449.
Sections du résumé
BACKGROUND
There is a need for simple, noninvasive solutions to remotely monitor and predict worsening heart failure (HF) events. SCALE-HF 1 (Surveillance and Alert-Based Multiparameter Monitoring to Reduce Worsening Heart Failure Events) is a prospective, multicenter study that will develop and assess the accuracy of the heart function index-a composite algorithm of noninvasive hemodynamic biomarkers from a cardiac scale-in predicting worsening HF events.
METHODS
Approximately 300 patients with chronic HF and recent decompensation will be enrolled in this observational study for model development. Patients will be encouraged to take daily cardiac scale measurements.
RESULTS
Approximately 50 HF events, defined as an urgent, unscheduled clinic, emergency department, or hospitalization for worsening HF will be used for model development. The composite index will be developed from hemodynamic biomarkers derived from ECG, ballistocardiogram, and impedance plethysmogram signals measured from the cardiac scale. Biomarkers of interest include weight, peripheral impedance, pulse rate and variability, and estimates of stroke volume, cardiac output, and blood pressure captured through the cardiac scale. The sensitivity, unexplained alert rate, and alerting time of the index in predicting worsening HF events will be evaluated and compared with the performance of simple weight-based rule-of-thumb algorithms (eg, weight increase of 3 lbs in 1 day or 5 lbs in 7 days) that are often used in practice.
CONCLUSIONS
SCALE-HF 1 is the first study to develop and evaluate the performance of a composite index derived from noninvasive hemodynamic biomarkers measured from a cardiac scale in predicting worsening HF events. Subsequent studies will validate the heart function index and assess its ability to improve patient outcomes.
REGISTRATION
URL: https://www.
CLINICALTRIALS
gov; Unique identifier: NCT04882449.
Identifiants
pubmed: 37192288
doi: 10.1161/CIRCHEARTFAILURE.122.010012
pmc: PMC10180020
doi:
Banques de données
ClinicalTrials.gov
['NCT04882449']
Types de publication
Observational Study
Multicenter Study
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
e010012Références
Circ Res. 2019 May 24;124(11):1598-1617
pubmed: 31120821
Europace. 2022 Feb 2;24(2):234-244
pubmed: 34392336
Lancet. 2021 Sep 11;398(10304):991-1001
pubmed: 34461042
Eur J Heart Fail. 2021 Jan;23(1):175-185
pubmed: 33111389
Lancet. 2016 Jan 30;387(10017):453-61
pubmed: 26560249
J Am Heart Assoc. 2014 Mar 20;3(2):e000745
pubmed: 24650926
Circ Heart Fail. 2017 Jan;10(1):
pubmed: 28062538
J Cardiovasc Transl Res. 2022 Oct;15(5):1212-1214
pubmed: 35396626
Circulation. 2013 Oct 15;128(16):e240-327
pubmed: 23741058
Curr Heart Fail Rep. 2009 Dec;6(4):287-92
pubmed: 19948098
Eur J Echocardiogr. 2010 Dec;11(10):834-44
pubmed: 20660604
Eur J Heart Fail. 2009 Apr;11(4):420-7
pubmed: 19252210
Heart Fail Rev. 2004 Jul;9(3):179-85
pubmed: 15809815
JACC Heart Fail. 2017 Mar;5(3):216-225
pubmed: 28254128
J Am Heart Assoc. 2021 Dec 21;10(24):e021893
pubmed: 34873927
Circ Heart Fail. 2020 Mar;13(3):e006513
pubmed: 32093506
Int J Cardiol. 2017 Aug 1;240:279-284
pubmed: 28341372
Sci Rep. 2016 Aug 09;6:31297
pubmed: 27503664
JAMA Intern Med. 2020 Oct 1;180(10):1386-1389
pubmed: 32744601
JACC Heart Fail. 2016 May;4(5):368-75
pubmed: 26874380
Circulation. 2004 Oct 19;110(16):2389-94
pubmed: 15313946
Circulation. 2022 May 3;145(18):e876-e894
pubmed: 35363500
Biomed Eng. 1974 Sep;9(9):410-6
pubmed: 4416602
N Engl J Med. 2011 Dec 15;365(24):2287-95
pubmed: 22168643
Eur J Heart Fail. 2020 Mar;22(3):391-412
pubmed: 32133741