An observational study in Cardiac Failure, sponsored by Josef Stehlik. Completed at 4 sites in United States. Open to participants aged 18 Years and older. Per ClinicalTrials.gov, last updated 2020-08-05.
Sponsored by Josef Stehlik · Observational
This is a multi-center, non-randomized, non-interventional study to evaluate the accuracy of a remote monitoring and analytical platform for prediction of heart failure exacerbation. The platform acquires continuous multivariate vital signs from HF patients using a new ambulatory wearable (attached by an adhesive) multi-sensor device and analyzes the data using a novel machine learning algorithm.
The analytics being investigated includes a Similarity-Based Modeling technique, that empirically estimates the expected physiological behavior of a subject based on prior learned dynamic data, for comparison to actual measured behavior from the subject, to reveal discrepancies hidden by normal variation. The measurements are typically an ensemble of vital signs that effectively characterizes the physiological "control system" of the subject. This technique is multivariate: multiple variables are leveraged, because single variables in isolation have little context - 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.
A wearable adhesive multi-sensor device will be used to collect continuous vital sign and other data from study subjects, including heart rate, respiration rate, bodily motion/activity, skin temperature, pulse, electrocardiogram and peripheral capillary oxygen saturation. Subjects are provided with a smartphone or cellular tablet that will be paired with the multi-sensor device to receive data and upload it to the analytics server via cellular network or WiFi internet. Study staff will interact with the subject 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 will be collected as they occur.
5,701 studies on the registry are indexed under Heart Failure; 1,220 are open to participants now.
This study's enrollment of 100 is below the median of 200 across 1,679 observational studies indexed under Heart Failure.
Browse Heart Failure studies →Josef Stehlik is the lead sponsor of 2 studies on the registry; none are open to participants now.
Counted across the registry records on this site, refreshed daily.
Individuals with heart failure, NYHA Class II-IV
Exclusion Criteria:
A multi-sensor device to collect continuous vital signs
Detection of Heart Failure Exacerbation Event
Correlation of algorithmic alerts generated by a non-invasive telemonitoring system to a verified heart failure exacerbation event, measured in percent accuracy
Time frame: 90 Days
Plan to share: No
This study is completed, as verified in Aug 2020. You cannot join it, but the record below documents what was studied.
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Josef Stehlik