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Bioimpedance-Based Heart Failure Deterioration Prediction Using a Prototype Fluid Accumulation Vest-Mobile Phone Dyad: An Observational Study

机译:基于生物阻抗的心力衰竭恶化的预测使用原型积液背心-手机双dyad:一项观察性研究。

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Background: Recurrent heart failure (HF) events are common in patients discharged after acute decompensated heart failure (ADHF). New patient-centered technologies are needed to aid in detecting HF decompensation. Transthoracic bioimpedance noninvasively measures pulmonary fluid retention. Objective: The objectives of our study were to (1) determine whether transthoracic bioimpedance can be measured daily with a novel, noninvasive, wearable fluid accumulation vest (FAV) and transmitted using a mobile phone and (2) establish whether an automated algorithm analyzing daily thoracic bioimpedance values would predict recurrent HF events. Methods: We prospectively enrolled patients admitted for ADHF. Participants were trained to use a FAV–mobile phone dyad and asked to transmit bioimpedance measurements for 45 consecutive days. We examined the performance of an algorithm analyzing changes in transthoracic bioimpedance as a predictor of HF events (HF readmission, diuretic uptitration) over a 75-day follow-up. Results: We observed 64 HF events (18 HF readmissions and 46 diuretic uptitrations) in the 106 participants (67 years; 63.2%, 67/106, male; 48.1%, 51/106, with prior HF) who completed follow-up. History of HF was the only clinical or laboratory factor related to recurrent HF events ( P =.04). Among study participants with sufficient FAV data (n=57), an algorithm analyzing thoracic bioimpedance showed 87% sensitivity (95% CI 82-92), 70% specificity (95% CI 68-72), and 72% accuracy (95% CI 70-74) for identifying recurrent HF events. Conclusions: Patients discharged after ADHF can measure and transmit daily transthoracic bioimpedance using a FAV–mobile phone dyad. Algorithms analyzing thoracic bioimpedance may help identify patients at risk for recurrent HF events after hospital discharge.
机译:背景:急性失代偿性心力衰竭(ADHF)后出院的患者经常发生复发性心力衰竭(HF)事件。需要新的以患者为中心的技术,以帮助检测HF代偿失调。经胸生物阻抗无创测量肺液fluid留。目的:我们的研究目的是(1)确定是否每天可以使用新型无创,可穿戴式积液背心(FAV)测量胸廓生物阻抗并使用手机进行传输,以及(2)确定是否每天自动分析算法胸腔生物阻抗值可预测复发性HF事件。方法:我们前瞻性招募了接受ADHF的患者。对参加者进行了使用FAV-手机双核的培训,并要求他们连续45天发送生物阻抗测量值。我们检查了经过75天的随访,分析了经胸生物阻抗变化作为HF事件(HF再入,利尿剂升高)的预测指标的算法的性能。结果:我们观察了完成随访的106名参与者(67岁; 63.2%,67/106,男性; 48.1%,51/106,先前有HF)的64例HF事件(18 HF再入院和46例利尿剂激化)。 HF病史是唯一与复发HF事件相关的临床或实验室因素(P = .04)。在具有足够FAV数据(n = 57)的研究参与者中,分析胸腔生物阻抗的算法显示出87%的敏感性(95%CI 82-92),70%的特异性(95%CI 68-72)和72%的准确性(95%) CI 70-74),用于识别复发性HF事件。结论:ADHF后出院的患者可以使用FAV手机双象素测量并传输每日经胸生物阻抗。分析胸腔生物阻抗的算法可能有助于确定出院后有HF反复发作风险的患者。

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