Abstract 19477: Transthoracic Bioimpedance Monitoring Predicts Readmission After Hospitalization for Heart Failure: Preliminary Results From the SENTINEL-HF Study
IntroductionPatients and health systems are focused on reducing readmissions for patients with acute decompensated heart failure (ADHF). Readmission after hospitalization is often secondary to HF decompensation, but it remains challenging to identify patients at-risk. Bioimpedance is a validated mar...
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Published in | Circulation (New York, N.Y.) Vol. 132; no. Suppl_3 Suppl 3; p. A19477 |
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Main Authors | , , , , , , , , , |
Format | Journal Article |
Language | English |
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by the American College of Cardiology Foundation and the American Heart Association, Inc
10.11.2015
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Abstract | IntroductionPatients and health systems are focused on reducing readmissions for patients with acute decompensated heart failure (ADHF). Readmission after hospitalization is often secondary to HF decompensation, but it remains challenging to identify patients at-risk. Bioimpedance is a validated marker of thoracic fluid accumulation. We examined whether changes in bioimpedance, measured using a Fluid Accumulation Vest (FAV), predicted subsequent HF decompensation in patients discharged after ADHF.MethodsParticipants included 83 patients hospitalized for ADHF. Subjects were trained on the use of a FAV-smartphone dyad to obtain and transmit a 5-minute bioimpedance measurement once daily for 45-days after discharge.(see Figure) The outcome of interest, HF-related readmission was assessed using participant report and medical records. Sensitivity, specificity, negative and positive predictive values were calculated to describe the efficacy of the bioimpedance alert algorithm as a predictor of HF readmission.ResultsSubject characteristicsmean age 68 ± 11 years, 36% female, 92% white, mean ejection fraction of 44 ± 19%. 49 participants completed the 45-day follow-up and had sufficient, daily FAV data for analysis. Our main outcome of HF-related rehospitalization occurred in 8% of patients during follow-up. The decompensation detection algorithm demonstrated a sensitivity of 75%, specificity of 47%, positive/negative predictive values of 11% and 96%, respectively.ConclusionsThe preliminary results of this ongoing study suggest that HF readmissions may be predicted with modest sensitivity by our current decompensation detection algorithm. Further refinement of our transthoracic bioimpedance system may offer possibilities for reducing HF readmissions by enabling identification and treatment of outpatients at risk for readmission. |
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AbstractList | Abstract only
Introduction:
Patients and health systems are focused on reducing readmissions for patients with acute decompensated heart failure (ADHF). Readmission after hospitalization is often secondary to HF decompensation, but it remains challenging to identify patients at-risk. Bioimpedance is a validated marker of thoracic fluid accumulation. We examined whether changes in bioimpedance, measured using a Fluid Accumulation Vest (FAV), predicted subsequent HF decompensation in patients discharged after ADHF.
Methods:
Participants included 83 patients hospitalized for ADHF. Subjects were trained on the use of a FAV-smartphone dyad to obtain and transmit a 5-minute bioimpedance measurement once daily for 45-days after discharge.(see Figure) The outcome of interest, HF-related readmission was assessed using participant report and medical records. Sensitivity, specificity, negative and positive predictive values were calculated to describe the efficacy of the bioimpedance alert algorithm as a predictor of HF readmission.
Results:
Subject characteristics: mean age 68 ± 11 years, 36% female, 92% white, mean ejection fraction of 44 ± 19%. 49 participants completed the 45-day follow-up and had sufficient, daily FAV data for analysis. Our main outcome of HF-related rehospitalization occurred in 8% of patients during follow-up. The decompensation detection algorithm demonstrated a sensitivity of 75%, specificity of 47%, positive/negative predictive values of 11% and 96%, respectively.
Conclusions:
The preliminary results of this ongoing study suggest that HF readmissions may be predicted with modest sensitivity by our current decompensation detection algorithm. Further refinement of our transthoracic bioimpedance system may offer possibilities for reducing HF readmissions by enabling identification and treatment of outpatients at risk for readmission. IntroductionPatients and health systems are focused on reducing readmissions for patients with acute decompensated heart failure (ADHF). Readmission after hospitalization is often secondary to HF decompensation, but it remains challenging to identify patients at-risk. Bioimpedance is a validated marker of thoracic fluid accumulation. We examined whether changes in bioimpedance, measured using a Fluid Accumulation Vest (FAV), predicted subsequent HF decompensation in patients discharged after ADHF.MethodsParticipants included 83 patients hospitalized for ADHF. Subjects were trained on the use of a FAV-smartphone dyad to obtain and transmit a 5-minute bioimpedance measurement once daily for 45-days after discharge.(see Figure) The outcome of interest, HF-related readmission was assessed using participant report and medical records. Sensitivity, specificity, negative and positive predictive values were calculated to describe the efficacy of the bioimpedance alert algorithm as a predictor of HF readmission.ResultsSubject characteristicsmean age 68 ± 11 years, 36% female, 92% white, mean ejection fraction of 44 ± 19%. 49 participants completed the 45-day follow-up and had sufficient, daily FAV data for analysis. Our main outcome of HF-related rehospitalization occurred in 8% of patients during follow-up. The decompensation detection algorithm demonstrated a sensitivity of 75%, specificity of 47%, positive/negative predictive values of 11% and 96%, respectively.ConclusionsThe preliminary results of this ongoing study suggest that HF readmissions may be predicted with modest sensitivity by our current decompensation detection algorithm. Further refinement of our transthoracic bioimpedance system may offer possibilities for reducing HF readmissions by enabling identification and treatment of outpatients at risk for readmission. |
Author | Meyer, Theo E Riistama, Jarno Saczynski, Jane McManus, David D Kini, Nisha Darling, Chad E Dovancescu, Silviu Sert Kuniyoshi, Fatima Rock, Joseph Goldberg, Robert J |
AuthorAffiliation | 1Emergency Medicine, Univ of Massachusetts Med Sch, Worcester, MA 2Philips Rsch, Philips Rsch Eindhoven, Eindhoven, Netherlands 3Medicine, Univ of Massachusetts Med Sch, Worcester, MA 4Quantitative Health Sciences, Univ of Massachusetts Med Sch, Worcester, MA 5Philips Home Healthcare Solutions, Philips Home Healthcare Solutions, Murrysville, PA 6Philips Healthcare, Philips Healthcare Hosp-to-Home, Andover, MA 7Medicine- Cardiology, Univ of Massachusetts Med Sch, Worcester, MA |
AuthorAffiliation_xml | – name: 1Emergency Medicine, Univ of Massachusetts Med Sch, Worcester, MA 2Philips Rsch, Philips Rsch Eindhoven, Eindhoven, Netherlands 3Medicine, Univ of Massachusetts Med Sch, Worcester, MA 4Quantitative Health Sciences, Univ of Massachusetts Med Sch, Worcester, MA 5Philips Home Healthcare Solutions, Philips Home Healthcare Solutions, Murrysville, PA 6Philips Healthcare, Philips Healthcare Hosp-to-Home, Andover, MA 7Medicine- Cardiology, Univ of Massachusetts Med Sch, Worcester, MA |
Author_xml | – sequence: 1 givenname: Chad surname: Darling middlename: E fullname: Darling, Chad E organization: 1Emergency Medicine, Univ of Massachusetts Med Sch, Worcester, MA 2Philips Rsch, Philips Rsch Eindhoven, Eindhoven, Netherlands 3Medicine, Univ of Massachusetts Med Sch, Worcester, MA 4Quantitative Health Sciences, Univ of Massachusetts Med Sch, Worcester, MA 5Philips Home Healthcare Solutions, Philips Home Healthcare Solutions, Murrysville, PA 6Philips Healthcare, Philips Healthcare Hosp-to-Home, Andover, MA 7Medicine- Cardiology, Univ of Massachusetts Med Sch, Worcester, MA – sequence: 2 givenname: Silviu surname: Dovancescu fullname: Dovancescu, Silviu – sequence: 3 givenname: Jarno surname: Riistama fullname: Riistama, Jarno – sequence: 4 givenname: Jane surname: Saczynski fullname: Saczynski, Jane – sequence: 5 givenname: Nisha surname: Kini fullname: Kini, Nisha – sequence: 6 givenname: Fatima surname: Sert Kuniyoshi fullname: Sert Kuniyoshi, Fatima – sequence: 7 givenname: Joseph surname: Rock fullname: Rock, Joseph – sequence: 8 givenname: Theo surname: Meyer middlename: E fullname: Meyer, Theo E – sequence: 9 givenname: Robert surname: Goldberg middlename: J fullname: Goldberg, Robert J – sequence: 10 givenname: David surname: McManus middlename: D fullname: McManus, David D |
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Snippet | IntroductionPatients and health systems are focused on reducing readmissions for patients with acute decompensated heart failure (ADHF). Readmission after... Abstract only Introduction: Patients and health systems are focused on reducing readmissions for patients with acute decompensated heart failure (ADHF).... |
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Title | Abstract 19477: Transthoracic Bioimpedance Monitoring Predicts Readmission After Hospitalization for Heart Failure: Preliminary Results From the SENTINEL-HF Study |
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