Medical Monitoring of Older Adults Patients After Discharged From Heart Failure Hospitalization

August 25, 2023 updated by: Presage

Introduction: PRESAGE CARE has developed a solution for early detection of the risk of emergency department visits and unscheduled hospitalizations. This smartphone-based solution is used by homecare workers and family caregivers to predict the risk of emergency department visits and unscheduled hospitalization within one to two weeks.

Objective: To study the feasibility of a multicenter randomized trial to assess the effects of a healthcare intervention based on the alert from the Présage Care device after discharge from hospital for patients hospitalized for heart failure (MCO and SSR).

Background and participants: This is a feasibility study carried out on two hospital wards for heart failure patients aged 65 and over (MCO and SSR). Patient's relative will be asked to fill in a short questionnaire twice a week for each beneficiary, relating to the beneficiary's daily life (input time not to exceed 2 minutes). This information will be transmitted in real time to PRESAGE CARE's secure platform (health data host). The study will last 6 months, with a 3-month inclusion period and an expected average follow-up of 3 months. It is planned to include 50 to 100 patients, with the same number of caregivers, and to study recruitment rates, participant satisfaction (hospital doctors, patients, caregivers, general practitioners), drop-out rates and the usefulness of updating the PRESAGE CARE algorithms in the context of the risk of re-hospitalization heart failure patients.

Data collected: In addition to inclusion data to describe the participant population, informations on emergency department visits, hospitalizations, drugs prescribed and dispensed, and long-term care status will be extracted from the hospital information system .

The study will establish the usefulness of conducting a subsequent randomized multicenter study on the added value of the PRESAGE CARE system for this specific population.

Study Overview

Status

Not yet recruiting

Intervention / Treatment

Detailed Description

Heart failure is a condition with a poor prognosis, especially in older adults with a difficult management. Overall, the mortality rate increases with age, rising by 27% per decade in men and 61% per decade in women.

The management and monitoring of heart failure rely on the appropriate prescription of drugs with beneficial effect on heart muscle remodeling (ACE inhibitors, beta-blockers), with a regular reevaluation for a best efficacy as well as a good bservance of hygienic-dietary rules such as regular weight control, simple nutritional rules (salt and water intake), and the maintenance of physical activity and training.

The main aim of ambulatory services is to detect episodes of decompensation early to treat it rapidly and prevent hospitalization. In the absence of improvement, hospitalization is necessary. Once discharged from the health care facility, coordination with the town or host structure is essential to ensure appropriate continuity of care.

Poor publications have already shown the benefits of Machine Learning (ML) for predicting hospitalization and death in heart failure patients. Predictive performance ranges from average (AUC: 0.55) to very good (AUC 0.8).

However, to work, these models require a large number of highly medicalized variables (typically over a hundred, including medication, medical history, ECG....), making them very difficult to apply in real life.

On the other hand, satisfactory predictive models (AUC>0.7) have large temporal prediction windows (1 to 3 years), making health actions difficult to implement.

To the best of our knowledge, no publication presents a short prediction window (a few weeks) based on simple models (less than 15 variables with little medicalization).

The PRESAGE Care medical device makes it possible to observe functional changes potentially heralding major medical events, and significantly improves predictions compared with conventional models.

  • Caregivers fill in an easy-to-use application (less than 2 minutes), create to predict the risk of a serious event (hospitalization, loss of autonomy, etc.).
  • An alert is sent to the end-users, who are the healthcare professionals, to trigger a healthcare intervention that could, in some cases, prevent the situation from deteriorating, or enable it to be managed in a non-emergency context.

This study is based on the hypothesize that the use of the PRESAGE CARE device coupled with a health intervention based on existing health networks could be associated with a lower incidence of unscheduled re-hospitalization, with no difference in mortality. This study is based on the hypothesize that the device will be well accepted by beneficiaries, their relatives and healthcare professionals (satisfaction > 80%), and that the intervention will not be associated with an increase in healthcare expenditure, as the additional costs associated with the use of PRESAGE CARE will be offset by the reduction in expenditure linked to avoided hospitalizations.

Study Type

Interventional

Enrollment (Estimated)

100

Phase

  • Not Applicable

Contacts and Locations

This section provides the contact details for those conducting the study, and information on where this study is being conducted.

Study Contact

Study Contact Backup

Participation Criteria

Researchers look for people who fit a certain description, called eligibility criteria. Some examples of these criteria are a person's general health condition or prior treatments.

Eligibility Criteria

Ages Eligible for Study

  • Older Adult

Accepts Healthy Volunteers

No

Description

Inclusion Criteria:

  • Person aged 65 or over.
  • Living at home
  • Moderately dependent, defined as GIR 3, 4 or 5.
  • Be or have been hospitalized in the last 30 days for heart failure
  • Have a relative volunteer to enter the PRESAGE questionnaire at least twice a week
  • Agreeing to take part in the study, or not objecting to the study being carried out, and whose relative agrees to take part.

Exclusion Criteria:

  • People under 65 years of age
  • With severe dependency defined by a GIR 1 or 2 group.
  • Not dependent as defined by a GIR 6 group.
  • Refusing to take part in the study, or whose relative refuses to take part.
  • Older adult benefiting from the Prado heart failure program on discharge from hospital.

Study Plan

This section provides details of the study plan, including how the study is designed and what the study is measuring.

How is the study designed?

Design Details

  • Primary Purpose: Prevention
  • Allocation: N/A
  • Interventional Model: Single Group Assignment
  • Masking: None (Open Label)

Arms and Interventions

Participant Group / Arm
Intervention / Treatment
Experimental: Intervention
PRESAGE Care informations from the application will be processed by the PRESAGE Care algorithm in real time, and may generate alerts indicating an increased risk of hospitalization or emergency department visits within 7 to 14 days. These alerts will be transmitted to a Care Manager platform, who will analyse the situation, initiate the healthcare intervention and coordinate its implementation. In practice, a care manager (coordinating nurse) will process the alert and carry out an initial assessment of the beneficiary's situation, using the information feedback platform, then by telephone, contacting the older adults beneficiary and the relative. The care manager may or may not implement preventive measures. If necessary, the patient may be offered an outpatient medical consultation, a home visit, a consultation with his or her GP and/or social or paramedical interventions.
Other Names:
  • Intervention (nurses and physicians)

What is the study measuring?

Primary Outcome Measures

Outcome Measure
Measure Description
Time Frame
Acceptability at inclusion by the patient-relative pair using PRESAGE Care
Time Frame: through study completion, an average of 6 months
Rate of relatives participating in the study (%)
through study completion, an average of 6 months

Secondary Outcome Measures

Outcome Measure
Measure Description
Time Frame
Acceptability of the relative
Time Frame: through study completion, an average of 6 months

a regular follow-up rate, characterization of the caregiver (gender ratio (%), average age (years), status (% of children, % of spouse % of husband, % of others).

Validation : more than 50%

through study completion, an average of 6 months
Relevance of follow-up
Time Frame: through study completion, an average of 6 months
Rate of alerts leading to intervention (%) Satisfaction level of referring physicians
through study completion, an average of 6 months
impact on emergency hospitalization
Time Frame: through study completion, an average of 6 months
Tracking of re-hospitalization and emergency room admission rates (%) Lost to follow-up rate (%) Average length of stay for re-hospitalization in the facility (days) Time to re-hospitalization or emergency (days)
through study completion, an average of 6 months

Collaborators and Investigators

This is where you will find people and organizations involved with this study.

Study record dates

These dates track the progress of study record and summary results submissions to ClinicalTrials.gov. Study records and reported results are reviewed by the National Library of Medicine (NLM) to make sure they meet specific quality control standards before being posted on the public website.

Study Major Dates

Study Start (Estimated)

December 1, 2023

Primary Completion (Estimated)

March 1, 2024

Study Completion (Estimated)

July 1, 2024

Study Registration Dates

First Submitted

August 22, 2023

First Submitted That Met QC Criteria

August 25, 2023

First Posted (Actual)

August 30, 2023

Study Record Updates

Last Update Posted (Actual)

August 30, 2023

Last Update Submitted That Met QC Criteria

August 25, 2023

Last Verified

August 1, 2023

More Information

Terms related to this study

Additional Relevant MeSH Terms

Other Study ID Numbers

  • Presage_IC

Plan for Individual participant data (IPD)

Plan to Share Individual Participant Data (IPD)?

NO

Drug and device information, study documents

Studies a U.S. FDA-regulated drug product

No

Studies a U.S. FDA-regulated device product

No

This information was retrieved directly from the website clinicaltrials.gov without any changes. If you have any requests to change, remove or update your study details, please contact register@clinicaltrials.gov. As soon as a change is implemented on clinicaltrials.gov, this will be updated automatically on our website as well.

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