Ignite Creation Date:
2025-12-24 @ 11:39 PM
Ignite Modification Date:
2025-12-25 @ 9:29 PM
Study NCT ID:
NCT05494151
Status:
WITHDRAWN
Last Update Posted:
2024-08-23
First Post:
2022-08-06
Is NOT Gene Therapy:
False
Has Adverse Events:
False
Brief Title:
Metabolic Substrate of Patients With Myocardial Infarction With and Without Modifiable Cardiovascular Risk Factors
Sponsor:
Aristotle University Of Thessaloniki
Organization:
Study Overview
Official Title:
Investigation of the Metabolic Substrate of Patients With Myocardial Infarction and Derivation of a Risk Estimation Algorithm to Evaluate Cardiovascular Risk Beyond Standard Modifiable Risk Factors (SMuRFs) - (The MetaSMuRF Study)
Status:
WITHDRAWN
Status Verified Date:
2024-08
Last Known Status:
None
Delayed Posting:
No
If Stopped, Why?:
Due to unforeseen challenges in participant recruitment and retention, the study was early terminated to maintain the integrity of the data and ensure ethical standards were upheld.
Has Expanded Access:
False
If Expanded Access, NCT#:
N/A
Has Expanded Access, NCT# Status:
N/A
Acronym:
Meta-SMuRF
Brief Summary:
Coronary heart disease (CHD) is the leading cause of mortality worldwide. Every year, millions of people suffer its most adverse manifestation, an acute myocardial infraction (AMI). The majority of these patients present at least one of the standard modifiable risk factors (SMuRFs). These include smoking, hypertension, dyslipidemia, and diabetes mellitus (DM). However, emerging scientific evidence recognizes a clinically significant proportion of patients presenting with life-threatening AMI without any SMuRF (SMuRF-less patients). This proportion of patients with ACS without SMuRF appears to be increasing during the last two decades and has recently been reported as high as 20% (of total AMIs). To date, there are no scientific data capable of highlighting specific risk factors-biomarkers responsible for the development of AMIs SMuRF-less patients. Concurrently, metabolomics is rapidly evolving as a novel technique of studying small molecule substrates, intermediates and products of cell metabolism. This technique could be utilized to flag patients with higher risk for increased atherosclerotic burden, and subsequent future adverse clinical events. Besides the already established biomarkers, several metabolomic indicators, such as ceramides (C16, C18 και C24), acylcarnitines, apolipoproteins (ApoΒ and ApoA1) and adiponectin, have been separately shown to increase the risk for coronary artery disease development and progression. Therefore, the two groups of patients (with SMuRFs vs SMuRF-less) will be compared regarding their metabolic fingerprints -specifically the aforementioned novel metabolomic biomarkers- and possible predictive factors leading to SMuRF-less AMI will be evaluated. On the basis of the above, the aim is to prospectively analyze a cohort of well-characterized patients with AMI. The rationale of the study is to investigate potential correlations between metabolic profile of patients and SMuRF-less AMI. This could lead to the development of predictive risk stratification algorithms for patients without SMuRFs and coronary artery disease.
Detailed Description:
Coronary heart disease (CHD) is the leading cause of mortality worldwide. Every year, millions of people suffer its most adverse manifestation, an acute myocardial infraction (AMI). The majority of these patients present at least one of the standard modifiable risk factors (SMuRFs). These include smoking, hypertension, dyslipidemia, and diabetes mellitus (DM). However, emerging scientific evidence recognizes a clinically significant proportion of patients presenting with life-threatening AMI without any SMuRF (SMuRF-less patients). This proportion of patients with ACS without SMuRF appears to be increasing during the last two decades and has recently been reported as high as 20% (of total AMIs). To date, there are no scientific data capable of highlighting specific risk factors-biomarkers responsible for the development of AMIs SMuRF-less patients.
Concurrently, metabolomics is rapidly evolving as a novel technique of studying small molecule substrates, intermediates and products of cell metabolism. This technique could be utilized to flag patients with higher risk for increased atherosclerotic burden, and subsequent future adverse clinical events. Besides the already established biomarkers, several metabolomic indicators, such as ceramides (C16, C18 και C24), acylcarnitines, apolipoproteins (ApoΒ and ApoA1) and adiponectin, have been separately shown to increase the risk for coronary artery disease development and progression. Therefore, the two groups of patients (with SMuRFs vs SMuRF-less) will be compared regarding their metabolic fingerprints -specifically the aforementioned novel metabolomic biomarkers- and possible predictive factors leading to SMuRF-less AMI will be evaluated. On the basis of the above, the aim is to prospectively analyze a cohort of well-characterized patients with AMI. The rationale of the study is to investigate potential correlations between metabolic profile of patients and SMuRF-less AMI. This could lead to the development of predictive risk stratification algorithms for patients without SMuRFs and coronary artery disease.
Blood tests (blood chemistry) will be received from each patient on admission and will be analyzed to assess patients' metabolic profile. In order to achieve full coverage of all compounds, different analytical platforms and methods, such as Enzyme-LInked Immunosorbent Assay (ELISA), Reversed Phase Liquid Chromatography tandem Mass Spectrometry (RPLC-MS/MS) and Hydrophilic Interaction Liquid Chromatography tandem Mass Spectrometry (HILIC-MS/MS) will be applied. Univariate and multivariate analysis with linear and logistic regression models will be used to investigate independent prognostic factors contributing to the occurrence of SMuRF-less AMIs. The potential application in daily clinical practice of a derived clinical predictive model-algorithm, possibly including a new panel of metabolomic biomarkers, will contribute to the early prognosis and personalized prevention of such a particular category of AMIs.
Concurrently, metabolomics is rapidly evolving as a novel technique of studying small molecule substrates, intermediates and products of cell metabolism. This technique could be utilized to flag patients with higher risk for increased atherosclerotic burden, and subsequent future adverse clinical events. Besides the already established biomarkers, several metabolomic indicators, such as ceramides (C16, C18 και C24), acylcarnitines, apolipoproteins (ApoΒ and ApoA1) and adiponectin, have been separately shown to increase the risk for coronary artery disease development and progression. Therefore, the two groups of patients (with SMuRFs vs SMuRF-less) will be compared regarding their metabolic fingerprints -specifically the aforementioned novel metabolomic biomarkers- and possible predictive factors leading to SMuRF-less AMI will be evaluated. On the basis of the above, the aim is to prospectively analyze a cohort of well-characterized patients with AMI. The rationale of the study is to investigate potential correlations between metabolic profile of patients and SMuRF-less AMI. This could lead to the development of predictive risk stratification algorithms for patients without SMuRFs and coronary artery disease.
Blood tests (blood chemistry) will be received from each patient on admission and will be analyzed to assess patients' metabolic profile. In order to achieve full coverage of all compounds, different analytical platforms and methods, such as Enzyme-LInked Immunosorbent Assay (ELISA), Reversed Phase Liquid Chromatography tandem Mass Spectrometry (RPLC-MS/MS) and Hydrophilic Interaction Liquid Chromatography tandem Mass Spectrometry (HILIC-MS/MS) will be applied. Univariate and multivariate analysis with linear and logistic regression models will be used to investigate independent prognostic factors contributing to the occurrence of SMuRF-less AMIs. The potential application in daily clinical practice of a derived clinical predictive model-algorithm, possibly including a new panel of metabolomic biomarkers, will contribute to the early prognosis and personalized prevention of such a particular category of AMIs.
Study Oversight
Has Oversight DMC:
False
Is a FDA Regulated Drug?:
False
Is a FDA Regulated Device?:
False
Is an Unapproved Device?:
None
Is a PPSD?:
None
Is a US Export?:
None
Is an FDA AA801 Violation?: