Evaluation of Home-based Sensor System to Detect Health Decompensation in Elderly Patients With History of CHF

Sponsor

Sensorum Health Inc. (Industry)

Overall Status

Recruiting

CT.gov ID

NCT05865197

Collaborator

(none)

Enrollment

Location

17.1

Anticipated Duration (Months)

1.2

Patients Per Site Per Month

Study Details

Study Description

Brief Summary

Sensorum Health (Sensorum) is conducting a pilot study to determine if Sensorum's proprietary passive sensor network can be used to identify signals of early health decompensation in subjects prior to a hospitalization for chronic disease exacerbation or other ambulatory care sensitive conditions. Successful early detection would provide a window of opportunity to intervene outside of the acute setting in future interventional studies.

Condition or Disease	Intervention/Treatment	Phase
CHF Congestive Heart Failure	Other: Data collection

Study Design

Study Type:

Observational

Anticipated Enrollment :

20 participants

Observational Model:

Cohort

Time Perspective:

Prospective

Official Title:

Feasibility of Home-based, Ambient Passive Sensor Technology to Provide Early Warning of Health Decompensation by Detecting Deviations in Activities of Daily Living (ADLs) of Elderly Subjects With Diagnosed Chronic Heart Failure

Actual Study Start Date :

Nov 28, 2022

Anticipated Primary Completion Date :

Jan 1, 2024

Anticipated Study Completion Date :

May 1, 2024

Arms and Interventions

Arm	Intervention/Treatment
Passive monitoring No intervention	Other: Data collection Data collection of clinically relevant signals using home-based sensor system

Arm

Intervention/Treatment

Passive monitoring

No intervention

Other: Data collection

Data collection of clinically relevant signals using home-based sensor system

Outcome Measures

Primary Outcome Measures

Recall of AI in passive sensor system [6 months]
Evaluation of AI ability to prospectively detect hospital utilization event
Precision of AI in passive sensor system [6 months]
Evaluation of AI ability to precisely predict hospital utilization event

Secondary Outcome Measures

Recall of sensor data review by trained nurses [6 months]
Evaluation of nurse ability to prospectively detect hospital utilization event
Precision of sensor data review by trained nurses [6 months]
Evaluation of nurse ability to precisely predict hospital utilization event

Eligibility Criteria

Criteria

Ages Eligible for Study:

55 Years and Older

Sexes Eligible for Study:

All

Accepts Healthy Volunteers:

Inclusion Criteria:

Current Patient at Weill Cornell Medicine
Aged 55 years or older
Able to consent
Documented diagnosis of congestive heart failure (CHF)
At least 1 of the following prior hospital utilization events in the past 12 months
Inpatient admission for any reason
Facility observation stay for any reason
Emergency Department visit for any reason

Exclusion Criteria:

Significant cardiac valvular disease
End-Stage Renal Disease (ESRD)
End-Stage CHF
End-Stage COPD

Contacts and Locations

Locations

	Site	City	State	Country	Postal Code
1	Weill Cornell Medicine	New York	New York	United States	10021

Sponsors and Collaborators

Sensorum Health Inc.

Investigators

Principal Investigator: Parag Goyal, M.D., MSc, Weill Medical College of Cornell University

Study Documents (Full-Text)

None provided.

More Information

Publications

None provided.

Responsible Party:

Sensorum Health Inc.

ClinicalTrials.gov Identifier:

NCT05865197

Other Study ID Numbers:

Sensorum P-002

First Posted:

May 18, 2023

Last Update Posted:

May 18, 2023

Last Verified:

May 1, 2023

Individual Participant Data (IPD) Sharing Statement:

Plan to Share IPD:

Additional relevant MeSH terms:

Heart Failure

Study Results

No Results Posted as of May 18, 2023