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

Recruiting

• Conditions: Congestive Heart Failure; CHF
• Interventions: Other: Data collection

• Registration Number: NCT05865197
• Lead Sponsor: Sensorum Health Inc.

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.

Detailed Description

Not available

Study Timeline

• Study Start: 2022-11-28
• Study First Submitted: 2023-05-09
• Study First Submitted QC: 2023-05-09
• Study First Posted: 2023-05-18
• Status Verified: 2024-01
• Last Update Submitted: 2024-01-12
• Last Update Posted: 2024-01-16
• Primary Completion: 2024-08-01
• Study Completion: 2024-09-01

Recruitment & Eligibility

• Status: RECRUITING
• Sex: All
• Target Recruitment: 20

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

Study & Design

• Study Type: OBSERVATIONAL
• Study Design: Not specified

Arm && Interventions

Group	Intervention	Description
Passive monitoring	Data collection	No intervention

Primary Outcome Measures

Name	Time	Method
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

Name	Time	Method
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

Trial Locations

Locations (1)

Weill Cornell Medicine; 🇺🇸 New York, New York, United States