Trial Outcomes & Findings for Improvement of a Digital Health Platform for Remote Monitoring of Patients With Heart Failure (NCT NCT05708846)

Last Updated: 2025-04-09

Results Overview

The dataset will contain the data from HF patients being telemonitored. This outcome shows the number of patients from which data will be used to build a dataset to train ML models for patient health prediction.

Recruitment status

COMPLETED

Target enrollment

154 participants

Primary outcome timeframe

6 months

Results posted on

2025-04-09

Participant Flow

Participant milestones

Participant milestones
Measure	Telemonitored Heart Failure Patients All patients in the observational study will be telemonitored following the same protocol.
Overall Study STARTED	154
Overall Study COMPLETED	129
Overall Study NOT COMPLETED	25

Reasons for withdrawal

Reasons for withdrawal
Measure	Telemonitored Heart Failure Patients All patients in the observational study will be telemonitored following the same protocol.
Overall Study Death	5
Overall Study Withdrawal by Subject	20

Baseline Characteristics

Improvement of a Digital Health Platform for Remote Monitoring of Patients With Heart Failure

Baseline characteristics by cohort

Baseline characteristics by cohort
Measure	Telemonitored Heart Failure Patients n=134 Participants All patients in the observational study will be telemonitored following the same protocol.
Age, Continuous	68 years STANDARD_DEVIATION 14 • n=5 Participants
Sex: Female, Male Female	38 Participants n=5 Participants
Sex: Female, Male Male	96 Participants n=5 Participants
Race/Ethnicity, Customized Ethnicity: · White	132 Participants n=5 Participants
Race/Ethnicity, Customized Ethnicity: · Latino	2 Participants n=5 Participants
NYHA class II	94 Participants n=5 Participants
NYHA class III	36 Participants n=5 Participants
NYHA class IV	4 Participants n=5 Participants
Level of Ejection Fraction (LVEF) <40	87 Participants n=5 Participants
Level of Ejection Fraction (LVEF) 40-50	21 Participants n=5 Participants
Level of Ejection Fraction (LVEF) >=50	26 Participants n=5 Participants
Employment status Retired	94 Participants n=5 Participants
Employment status Paid	32 Participants n=5 Participants
Employment status None	4 Participants n=5 Participants
Employment status Unemployed	3 Participants n=5 Participants
Employment status Voluntary	1 Participants n=5 Participants
Education level Without education	20 Participants n=5 Participants
Education level Primary	32 Participants n=5 Participants
Education level Secondary	37 Participants n=5 Participants
Education level High	45 Participants n=5 Participants
The patient has a caretaker? Yes	61 Participants n=5 Participants
The patient has a caretaker? No	73 Participants n=5 Participants
Number of people living with the patient	2 people STANDARD_DEVIATION 1 • n=5 Participants
Smoker Yes	27 Participants n=5 Participants
Smoker No	59 Participants n=5 Participants
Smoker Ex-smoker	48 Participants n=5 Participants
Alcohol use Yes	21 Participants n=5 Participants
Alcohol use Yes, occasionally	71 Participants n=5 Participants
Alcohol use No	42 Participants n=5 Participants
Diabetes Yes	41 Participants n=5 Participants
Diabetes No	93 Participants n=5 Participants
Hypertension Yes	103 Participants n=5 Participants
Hypertension No	31 Participants n=5 Participants
History of heart disease Yes	86 Participants n=5 Participants
History of heart disease No	48 Participants n=5 Participants

PRIMARY outcome

Timeframe: 6 months

Population: All enrolled patients, except the withdrawn ones, are included in the dataset to train ML models.

Outcome measures

Outcome measures
Measure	Telemonitored Heart Failure Patients n=134 Participants All patients in the observational study will be telemonitored following the same protocol.
Number of Patients Included in the Dataset	134 Participants

PRIMARY outcome

Timeframe: 6 months

The models should: Provide a relevance level for each new alarm by reducing the number of irrelevant alarms and thus fostering personalized follow-up. Be robust across different new hospitals and reliable and fair across different target populations, considering the diverse sociodemographic data that will be available in the dataset.

Outcome measures

Outcome data not reported

SECONDARY outcome

Timeframe: 6 months

With the registered information, develop and implement ML event prediction algorithms that will add new self-generated alarms to the system. These alarms should forecast: Untracked hospital interventions, such as UCI visits or hospital readmissions. Changes of medication with their particular estimated dose. Clinical events, such as mortality.

Outcome measures

Outcome data not reported

SECONDARY outcome

Timeframe: 6 months

Assess patient and medical professional satisfaction with the digital platform at the study's end by using the "Post-Study Usability Questionnaire" (PSSUQ).

Outcome measures

Outcome data not reported

SECONDARY outcome

Timeframe: 6 months

Population: We show the results of the SUS score for the patients that answered the questionnaire

Assess the usability of the digital platform at the end of the study by means of the "System Usability Scale" (SUS). The SUS is a standardized tool used to evaluate the usability of digital platforms through a 10-item questionnaire. Each item is rated on a 5-point Likert scale, ranging from "Strongly Disagree" (1) to "Strongly Agree" (5). Scale from 0 to 100. The higher the score the better usablity.

Outcome measures

Outcome measures
Measure	Telemonitored Heart Failure Patients n=73 Participants All patients in the observational study will be telemonitored following the same protocol.
Mean SUS Score to Assess the Usability of the Digital Platform App	69.83 score on a scale Standard Deviation 17.97

Adverse Events

Telemonitored Heart Failure Patients

Serious events: 18 serious events

Other events: 3 other events

Deaths: 5 deaths

Serious adverse events

Serious adverse events
Measure	Telemonitored Heart Failure Patients n=134 participants at risk All patients in the observational study will be telemonitored following the same protocol.
Cardiac disorders Hospitalization Heart Failure	7.5% 10/134 • Number of events 14 • 6 months
Cardiac disorders Hospitalization Cardiovascular	3.7% 5/134 • Number of events 6 • 6 months
Cardiac disorders Hospitalization non CV	2.2% 3/134 • Number of events 3 • 6 months
Cardiac disorders Urgent visit with intravenous decongestive therapy	1.5% 2/134 • Number of events 3 • 6 months

Other adverse events

Other adverse events
Measure	Telemonitored Heart Failure Patients n=134 participants at risk All patients in the observational study will be telemonitored following the same protocol.
Cardiac disorders Visit to medical emergencies	2.2% 3/134 • Number of events 3 • 6 months

Additional Information

Data Scientist of vitalera

vitalera (FollowHealth SL)

Phone: +34644499760

Email: [email protected]

Results disclosure agreements

Principal investigator is a sponsor employee
Publication restrictions are in place