Heart failure (HF) is a growing public health problem, expected to increase in prevalence and incidence due to population aging. This challenge is compounded by the healthcare overload following the COVID-19 pandemic, particularly in primary care (PC). Early diagnosis of HF is critical for improving outcomes, reducing complications, and optimizing resource use. However, there is no robust scientific evidence supporting the effectiveness of early screening for HF in PC settings. This study aims to evaluate whether an early cardiology assessment model for patients with suspected HF and elevated NT-proBNP levels (\>300 pg/mL) improves clinical outcomes compared to the standard referral pathway. The hypothesis is that early intervention will reduce emergency visits, hospitalizations, and mortality related to HF. This is a prospective, single-center, open-label, phase II randomized controlled trial with parallel group allocation (1:1). Patients presenting to PC with HF symptoms and no prior HF diagnosis, who have NT-proBNP levels \>300 pg/mL, will be invited to participate. After informed consent, participants will be randomized to one of two groups: * Intervention group: Early cardiology assessment within 7 days. * Control group: Standard referral by PC physician per usual care. Randomization will be computer-generated and managed independently to ensure allocation concealment. Patients will be followed for 12 months from the date of NT-proBNP testing. Outcomes will be collected through both cardiology and PC visits. Our primary outcome measure will be the clinical benefit, defined as a hierarchical composite endpoint of: 1. Cardiovascular mortality 2. All-cause mortality 3. Number of hospitalizations due to HF 4. Number of urgent care visits due to HF 5. Number of GDMT (Guideline-Directed Medical Therapy) drugs initiated 6. Number of GDMT drugs with dose escalation 7. Proportional change in log (NT-proBNP) at 12 months The primary analysis will use a win ratio methodology to maximize statistical efficiency and clinical interpretability. Secondary outcomes include: * Each component of the primary endpoint * Stratified analysis by confirmed or excluded HF diagnosis * Stratified analysis by HF phenotype (HFrEF vs HFpEF) * Stratified analysis by sex A sample size of 304 patients (152 per group) has been calculated to detect a win ratio of 1.7 with 80% power, based on expected clinical benefit and statistical assumptions from prior literature. The study is expected to complete recruitment within 12 months, with a total study duration of 24 months including follow-up and data analysis.
leads to better clinical outcomes compared to the usual referral pathway. Patients are randomized 1:1 to early cardiology evaluation (within 7 days of NT-proBNP result) versus standard PC-driven referral. This approach seeks to bridge the gap between suspicion and diagnosis, allowing for timely initiation or optimization of therapy when appropriate. The study will be conducted in collaboration with the Córdoba-Guadalquivir Primary Care District. A training session has been held with primary care providers, and informed consent materials have been distributed throughout the district. The primary outcome is a composite hierarchical endpoint, assessed using a win ratio approach. The components of this outcome include cardiovascular mortality, all-cause mortality, number of HF hospitalizations, number of urgent visits due to HF, number of GDMT drugs initiated (when indicated), number of GDMT drugs up-titrated (when indicated), and proportional change in log-transformed NT-proBNP at 12 months. The win ratio methodology allows for an ordered comparison of outcomes, giving greater weight to more severe events (e.g., death) while preserving statistical efficiency in detecting clinical benefit across multiple domains. This design aligns with real-world priorities: reducing hard endpoints (mortality, hospitalization), improving evidence-based pharmacologic management, and optimizing biomarker control. It also recognizes the heterogeneity in HF diagnosis and severity among patients presenting to PC with unexplained dyspnea or fatigue. The trial includes stratified secondary analyses in patients with and without confirmed HF, in those with HFpEF vs HFrEF phenotypes, and by sex, to explore differential responses to early intervention and inform future implementation strategies. All patients are followed for 12 months, with data collected from both cardiology and primary care visits. The target sample size of 304 participants provides adequate power to detect a clinically meaningful win ratio based on prior observational and interventional data. This total includes 152 patients per arm (early cardiology intervention vs. standard care), with a 1:1 allocation ratio The study has received approval from the local ethics committee (reference number 6145). All participants are required to provide written informed consent before enrolling in the study, and are informed of their right to withdraw from the study at any time without giving any impact on their standard medical care. Participant confidentially is strictly maintained and all data are securely stored in compliance with data protection regulations. The study results will be disseminated through scientific publications and conference presentations.
Study Type
INTERVENTIONAL
Allocation
RANDOMIZED
Purpose
DIAGNOSTIC
Masking
NONE
Enrollment
304
The intervention involves early referral, allowing patients to be assessed by a cardiologist prior to the standard referral process. During this visit, the cardiologist will perform a comprehensive medical history and a detailed physical examination to assess signs of central and peripheral congestion. A standardized echocardiogram will also be conducted, including a series of objective measurements.
Clinical benefit based on a hierarchical composite outcome (win ratio approach)
Our primary outcome measure will be the clinical benefit, defined as a hierarchical composite endpoint of: 1. Cardiovascular mortality. 2. All-cause mortality. 3. Number of hospitalizations for heart failure (HF). 4. Number of urgent visits due to worsening HF symptoms requiring intravenous therapy, emergency department care or specialist evaluation. 5. Number of guideline-directed medical therapy (GDMT) drugs for HF initiated, if indicated (beta-blockers, RAAS inhibitors, SGLT2 inhibitors, MRAs). 6. Number of GDMT drugs with document dose up-titration (in those with indication). 7. Proportional 1-year change in plasma log(NT-proBNP) levels, as a biomarker of cardiac stress and congestion. The hierarchical structure of the primary endpoint and its components, along with the proposed statistical methodology, have been selected to ensure the feasibility of the study, efficient use of resources, and adequate statistical power.
Time frame: From enrollment, the patients will be followed 12 months
Stratified analysis of the primary endpoint in patients with elevated NT-proBNP, with a confirmed or ruled-out diagnosis of heart failure (HF).
This outcome assesses the primary hierarchical composite clinical benefit endpoint (as defined in Outcome 1), stratifying patients with elevated NT-proBNP levels according to whether they ultimately receive a confirmed diagnosis of heart failure (HF) or not, based on clinical, imaging, and biomarker data. The analysis will evaluate whether the presence or absence of a confirmed HF diagnosis affects the patient's clinical benefit profile, as measured by the win ratio method across the predefined components: mortality, HF events, GDMT optimization, and biomarker change.
Time frame: From enrollment, the patients will be followed 12 months
Stratified analysis of the hierarchical clinical benefit composite endpoint by heart failure phenotype (HFpEF vs. HFrEF)
This outcome will analyze the primary hierarchical composite clinical benefit endpoint (as defined in Outcome 1), stratified by HF phenotype: HFpEF (heart failure with preserved ejection fraction), and HFrEF (heart failure with reduced ejection fraction), as defined by left ventricular ejection fraction (LVEF) thresholds per guideline criteria. The goal is to assess whether the type of HF modifies the relative clinical benefit observed, using the same win ratio methodology.
Time frame: From enrollment, the patients will be followed 12 months
Stratified analysis of the hierarchical clinical benefit composite endpoint by sex (male vs. female)
This outcome will evaluate the primary hierarchical composite clinical benefit endpoint (as defined in Outcome 1) stratified by biological sex (male vs female). The aim is to explore potential sex-related differences in the clinical response and benefit profile across the components of the composite endpoint, using the same hierarchical win ratio analysis.
Time frame: From enrollment, the patients will be followed 12 months
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