This paper is in the following e-collection/theme issue:

Non-randomized Protocols and Methods (ehealth) (567)

Published on in Vol 4, No 4 (2015): Oct-Dec

Detecting Heart Failure Decompensation by Measuring Transthoracic Bioimpedance in the Outpatient Setting: Rationale and Design of the SENTINEL-HF Study

Detecting Heart Failure Decompensation by Measuring Transthoracic Bioimpedance in the Outpatient Setting: Rationale and Design of the SENTINEL-HF Study

Detecting Heart Failure Decompensation by Measuring Transthoracic Bioimpedance in the Outpatient Setting: Rationale and Design of the SENTINEL-HF Study

Authors of this article:

Silviu Dovancescu1 Author Orcid Image ;   Jane S. Saczynski2, 3, 4 Author Orcid Image ;   Chad E. Darling5 Author Orcid Image ;   Jarno Riistama1 Author Orcid Image ;   Fatima Sert Kuniyoshi6 Author Orcid Image ;   Theo Meyer2 Author Orcid Image ;   Robert Goldberg2, 3, 4 Author Orcid Image ;   David D. McManus2, 3, 4 Author Orcid Image
Article Authors Cited by (21) Tweetations (1) Metrics

Journals

  1. Ding E, Ensom E, Hafer N, Buchholz B, Picard M, Dunlap D, Rogers E, Lawton C, Koren A, Lilly C, Fitzgibbons T, McManus D. Point-of-care technologies in heart, lung, blood and sleep disorders from the Center for Advancing Point-of-Care Technologies. Current Opinion in Biomedical Engineering 2019;11:58 View
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  3. Dovancescu S, Pellicori P, Mabote T, Torabi A, Clark A, Cleland J. The effects of short‐term omission of daily medication on the pathophysiology of heart failure. European Journal of Heart Failure 2017;19(5):643 View
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  5. Darling C, Dovancescu S, Saczynski J, Riistama J, Sert Kuniyoshi F, Rock J, Meyer T, McManus D. Bioimpedance-Based Heart Failure Deterioration Prediction Using a Prototype Fluid Accumulation Vest-Mobile Phone Dyad: An Observational Study. JMIR Cardio 2017;1(1):e1 View
  6. Reljin N, Posada-Quintero H, Eaton-Robb C, Binici S, Ensom E, Ding E, Hayes A, Riistama J, Darling C, McManus D, Chon K. Machine Learning Model Based on Transthoracic Bioimpedance and Heart Rate Variability for Lung Fluid Accumulation Detection: Prospective Clinical Study. JMIR Medical Informatics 2020;8(8):e18715 View
  7. Faragli A, Abawi D, Quinn C, Cvetkovic M, Schlabs T, Tahirovic E, Düngen H, Pieske B, Kelle S, Edelmann F, Alogna A. The role of non-invasive devices for the telemonitoring of heart failure patients. Heart Failure Reviews 2021;26(5):1063 View
  8. Iqbal S, Mahgoub I, Du E, Leavitt M, Asghar W. Advances in healthcare wearable devices. npj Flexible Electronics 2021;5(1) View
  9. Krzesinski P, Sobotnicki A, Gacek A, Siebert J, Walczak A, Murawski P, Gielerak G. Noninvasive Bioimpedance Methods From the Viewpoint of Remote Monitoring in Heart Failure. JMIR mHealth and uHealth 2021;9(5):e25937 View
  10. Iqbal S, Mahgoub I, Du E, Leavitt M, Asghar W. Development of a wearable belt with integrated sensors for measuring multiple physiological parameters related to heart failure. Scientific Reports 2022;12(1) View
  11. Krzesiński P. Digital Health Technologies for Post-Discharge Care after Heart Failure Hospitalisation to Relieve Symptoms and Improve Clinical Outcomes. Journal of Clinical Medicine 2023;12(6):2373 View
  12. Pan X, Wang C, Yu Y, Reljin N, McManus D, Darling C, Chon K, Mendelson Y, Lee K. Deep cross-modal feature learning applied to predict acutely decompensated heart failure using in-home collected electrocardiography and transthoracic bioimpedance. Artificial Intelligence in Medicine 2023;140:102548 View
  13. Iqbal S, Leavitt M, Pedilus G, Mahgoub I, Asghar W. A wearable telehealth system for the monitoring of parameters related to heart failure. Heliyon 2024;10(5):e26841 View
  14. Iqbal S, Leavitt M, Mahgoub I, Asghar W. A Wearable Internet of Things Device for Noninvasive Remote Monitoring of Vital Signs Related to Heart Failure. IoT 2024;5(1):155 View
  15. Petmezas G, Papageorgiou V, Vassilikos V, Pagourelias E, Tsaklidis G, Katsaggelos A, Maglaveras N. Recent advancements and applications of deep learning in heart failure: Α systematic review. Computers in Biology and Medicine 2024;176:108557 View
  16. Faragli A, Herrmann A, Cvetkovic M, Perna S, Khorsheed E, Lo Muzio F, La Porta E, Fassina L, Günther A, Oetvoes J, Düngen H, Alogna A. In-hospital bioimpedance-derived total body water predicts short-term cardiovascular mortality and re-hospitalizations in acute decompensated heart failure patients. Clinical Research in Cardiology 2024 View

Books/Policy Documents

  1. Kunhoth J, Subramanian N, Bouridane A. Predicting Heart Failure. View
  2. Kulkarni K, Isselbacher E, Armoundas A. Predicting Heart Failure. View
  3. Salman H, Al‐Ruweidi M, Ouakad H, Yalcin H. Predicting Heart Failure. View