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NCT03575533

Bayesian Hemodynamics Model for Personalized Monitoring of Congestive Heart Failure Patients

Status unknown Last updated 28 February 2019
What this trial tests

trial testing Bayesian network 'Sherlock' in Heart Failure in 20 participants. Status unknown.

Timeline
1 January 2019
Primary endpoint
1 September 2019
1 January 2020

Quick facts

Lead sponsorLeiden University Medical Center
StatusStatus unknown
Study typeOBSERVATIONAL
Enrollment20
Start date1 January 2019
Primary completion1 September 2019
Estimated completion1 January 2020
Sites1 location across Netherlands

Drugs / interventions tested

Conditions studied

Sponsor

Leiden University Medical Center

Who can join

45 and older, any sex, with Heart Failure. Patients with the condition only — healthy volunteers not accepted.

Sponsor's own description

Heart failure (HF) is a serious and challenging syndrome. Globally 26 million people are living with this chronic disease and the prevalence is still increasing. Besides this growing number in prevalence, HF is also responsible for almost 1 million hospitalizations a year in the US and in Europe. Consequently, this has a major economic impact especially due to recurrent admissions of these patients. Adequate prediction of decompensation could prevent (un)necessary admissions as a result of heart failure. Philips is developing a Bayesian Hemodynamics model for general practitioners. This model uses different observables, which can be measured at home. The outcome of the model could be used as an aid in clinical decision making in HF patients.

Publications & conference data

No peer-reviewed publications indexed yet for this trial.

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Other recruiting trials for Heart Failure

Currently open trials in the same condition.

Other Leiden University Medical Center trials

Trials by the same sponsor.

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Data sources for this page

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