Detecting EARLY Heart Failure in Greater Manchester

Recruiting

Brief Summary: Heart failure represents a growing public health problem within the UK and particularly within the North West of England. A major challenge is that heart failure is currently diagnosed too late.

The researchers have previously developed a risk calculator that accurately identifies individuals at risk of heart failure admission or death before they have developed heart failure.

Most risk calculators are never implemented into clinical practice. The researchers will l perform a pilot study to evaluate the risk calculator within primary care in Greater Manchester.

Detailed Description: The researchers have previously developed and externally validated a novel multimodal risk calculator that accurately identifies individuals at-risk of heart failure admission or death before they have developed heart failure. This risk calculator includes key co-morbidities, circulating biomarkers and cardiac magnetic resonance imaging (CMR) measurements of cardiac structure and function. It identifies those individuals at highest risk of developing heart failure and therefore those who may most benefit from targeted cardiometabolic therapeutics in the future.

The researchers will l perform a pilot study to evaluate the risk calculator within primary care in Greater Manchester. A qualitative and quantitative assessment of risk calculator uptake will be performed within local GP practices and primary care populations. The research team will determine how effectively they can recruit participants from socioeconomically deprived and ethnically diverse backgrounds. A preliminary analysis will be performed to determine risk calculator accuracy within a prospective primary care cohort, and dynamically refine the model aiming to improve performance. The study will also involve conducting an initial cost effectiveness analysis to determine the real-world economic impact of model implementation.

Recruitment & Eligibility

Inclusion Criteria

Written informed consent
Aged 50 and over
Two or more of the following conditions: type 2 diabetes, chronic obstructive pulmonary disease, ischaemic heart disease, atrial fibrillation, hypertension, chronic kidney disease stage 3, body mass index ≥ 30 kg/m2

Exclusion Criteria

Established diagnosis of one or more of the following: heart failure, cardiomyopathy, moderate or severe valvular heart disease, congenital heart disease, heart transplant, idiopathic, heritable or drug-induced pulmonary arterial hypertension, any medical condition, which in the opinion of the Investigator, may place the patient at higher risk from his/her participation in the study, or is likely to prevent the patient from complying with the requirements of the study or completing the study.
Contraindication to cardiovascular magnetic resonance (CMR) scanning, including pacemaker, defibrillator, intraocular metal, intracranial aneurysm clips, severe claustrophobia, estimated glomerular filtration rate < 30 ml/min/1.73m2, previous severe allergic reaction or anaphylaxis to gadolinium-based contrast agent, pregnancy or breastfeeding.

Arm && Interventions

Group	Intervention	Description
Participants in primary care with risk factors for heart failure	No intervention	-

Primary Outcome Measures

Name	Time	Method
Preliminary measures of risk calculator validation and accuracy in Greater Manchester	5 years	Risk calculator will predict incident heart failure, first heart failure hospitalisation, cardiovascular death and all cause death

Secondary Outcome Measures

Name	Time	Method
Measures of cost effectiveness of the model in Greater Manchester	5 years	Examples include decision curve analysis
Proportion of participants recruited from socioeconomically deprived and ethnically diverse backgrounds	5 years	Ability to recruit participants from socioeconomically deprived and ethnically diverse backgrounds within Greater Manchester
Causal statistical analysis to determine effect of hypothetical interventions	5 years	Mediation analysis to determine causative effects of hypothetical interventions
Qualitative measures of primary care uptake and engagement	5 years	Number of participant identification sites, methods of participant identification, proportion of eligible participants contacted and recruited
Measures of prognostic model calibration and discrimination in a primary care population	5 years	Examples include calibration slope, intercept and Harrell's C statistic
Measures of prognostic model optimisation and accuracy with iterative variable inclusion or exclusion	5 years	Assess variable inclusion and exclusion using stepwise model selection and Wald statistic

Locations (1): Manchester University NHS Foundation Trust
🇬🇧
Manchester, Greater Manchester, United Kingdom