Clinical Characteristics and Predictors of Adverse Outcomes in HFpEF
NCT ID: NCT06228807
Last Updated: 2024-12-02
Study Results
The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.
Basic Information
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COMPLETED
584 participants
OBSERVATIONAL
2015-03-09
2023-09-30
Brief Summary
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Detailed Description
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The aim of this study is to investigate the impact of parameters reflecting the metabolic phenotype, coronary microvascular dysfunction in HFpEF and establish their correlation with clinical outcomes. The objective is to identify novel predictors for adverse prognosis in HFpEF, potentially serving as targets for drug therapy. This research aims to pave the way for targeted drug interventions in cardiometabolic diseases, offering new avenues for therapeutic approaches.
Conditions
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Study Design
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COHORT
RETROSPECTIVE
Study Groups
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HFpEF patients with metabolic abnormalities
The study involved a comparison of clinical characteristics, medical history, laboratory biomarkers, echocardiographic measurements, angiographic findings, and clinical outcomes between two groups.
Differences in clinical characteristics, history, laboratory biomarkers, echocardiographic measurements, angiographic findings, coronary microvascular function using caIMR and clinical outcomes were assessed between the two groups to identify potential risk factors. Subsequently, the incidence of clinical outcomes and mortality was compared. Univariate logistic regression and multivariate logistic regression analyses, adjusted for significant risk factors, were conducted to identify independent predictive factors. Finally, a Receiver Operating Characteristic (ROC) curve was generated, and the area under the curve was evaluated to assess the predictive accuracy of the regression model.
HFpEF patients without metabolic abnormalities
The study involved a comparison of clinical characteristics, medical history, laboratory biomarkers, echocardiographic measurements, angiographic findings, and clinical outcomes between two groups.
Differences in clinical characteristics, history, laboratory biomarkers, echocardiographic measurements, angiographic findings, coronary microvascular function using caIMR and clinical outcomes were assessed between the two groups to identify potential risk factors. Subsequently, the incidence of clinical outcomes and mortality was compared. Univariate logistic regression and multivariate logistic regression analyses, adjusted for significant risk factors, were conducted to identify independent predictive factors. Finally, a Receiver Operating Characteristic (ROC) curve was generated, and the area under the curve was evaluated to assess the predictive accuracy of the regression model.
Interventions
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The study involved a comparison of clinical characteristics, medical history, laboratory biomarkers, echocardiographic measurements, angiographic findings, and clinical outcomes between two groups.
Differences in clinical characteristics, history, laboratory biomarkers, echocardiographic measurements, angiographic findings, coronary microvascular function using caIMR and clinical outcomes were assessed between the two groups to identify potential risk factors. Subsequently, the incidence of clinical outcomes and mortality was compared. Univariate logistic regression and multivariate logistic regression analyses, adjusted for significant risk factors, were conducted to identify independent predictive factors. Finally, a Receiver Operating Characteristic (ROC) curve was generated, and the area under the curve was evaluated to assess the predictive accuracy of the regression model.
Eligibility Criteria
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Inclusion Criteria
* Presence of heart failure signs/symptoms symptoms
* Preserved left ventricular ejection fraction (EF) ≥50%
* BNP≥35 pg/mL and/or NTproBNP≥125 pg/mL;
* At least one additional criteria: presence of cardiac functional and structural abnormalities or diastolic dysfunction.
Exclusion Criteria
* Patients with serious hepatic and renal failure,
* Non-cardiac causes of dyspnea, such as, asthma
* Primary pulmonary hypertension.
* Severe valvular heart disease.
* Pericardial disease.
* Recent history of myocardial infarction.
* Coronary artery disease (stenosis\>50).
* Reduced contrast opacification (for caIMR assessment).
18 Years
ALL
No
Sponsors
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Ya-Wei Xu
OTHER
Responsible Party
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Ya-Wei Xu
Chief Physician
Other Identifiers
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HFpEF-CCPO
Identifier Type: -
Identifier Source: org_study_id