SALT LAKE CITY, UT — While implantable devices have shown promise in reducing rehospitalization for heart failure (HF), VA researchers sought to determine if options that are less expensive and non-invasive would have comparable results.
To do that, the LINK-HF study analyzed the performance of removable patch, using continuous multivariate data streams to predict rehospitalization after HF admission. Results were published recently in the Journal of the American College of Cardiology after presentation at ACC.18, the 67th Annual Scientific Sessions and Expo for the American College of Cardiology.1
In proposing the research, the investigators said multiple variables were used, because single variables in isolation have little context, pointing out that “a high heart rate by itself could mean a person is exerting himself, or it could mean his physiology is in distress even though he is not exerting himself. With reference to several other variables, however, such as respiration rate, oximetry and motion/activity, a high heart rate might be recognized as a normal state when accompanied by the corroborating data showing a high respiration rate, a normal oximetry and a high level of motion — the person is exercising.”
The VA Salt Lake City Health System-led researchers monitored participants for up to three months using the small disposable chest-adhesive multi-sensor patch. The device recorded physiological data including heart rate, heart rate variability, accelerometry, respiratory rate and temperature.
All data were uploaded continuously via smartphone to a cloud analytics platform for the 100 patients enrolled at four VAMCs. Mean age of the 98% male participants was 68.5.
In addition, study staff interacted with the patients during visits scheduled for routine heart failure follow-up to capture pre-specified heart failure medical events. All standard of care clinic and hospitalization notes and procedure reports including echocardiograms, right heart catheterizations, pulmonary function tests, six minute walk tests and radiology reports were collected as they occurred.
Over the course of the study, 33 of the patients were readmitted for heart failure, with 86% completed all study procedures.
Results indicated that the platform analytics for prediction of HF readmission achieved a receiver operating characteristic (ROC) area under the curve (AUC) of 0.88 vs. an AUC of 0.58 for an equivalent random decision generator. At specificity of 85.9%, sensitivity was 84.2%, the researchers reported.
The study found that mean and median time between initial alert and readmission was 10.8±9.7 days and 6.0 [4.2; 13.7] days, respectively.
“The results of this study suggest a highly favorable relationship between sensitivity and specificity of event detection, as well as a sufficient warning lead time for clinicians tasked with managing patients at risk for admission for heart failure exacerbation,” said principal investigator Josef Stehlik, MD, MPH, in a press release from physIQ, Inc., which manufactured the devices tested. “Furthermore, the study demonstrated that patients were highly compliant with wearing the biosensors throughout the monitoring period, making this a promising solution for a patient population with significant unmet clinical needs.”
1Stehlik J, Schmalfuss C, Bozkurt B, Nativi-Nicolau, et. Al. Continuous Wearable Monitoring Analytics Predict Heart Failure Decompensation: The LINK-HF Multi-Center Study. Journal of the American College of Cardiology. Volume 71, Issue 11 Supplement, March 2018DOI: 10.1016/S0735-1097(18)31187-2
