Multi-marker network in ST-elevation myocardial infarction (STEMI) patients undergoing primary percutaneous coronary intervention : when and what to measure
Poster
Data di Pubblicazione:
2013
Citazione:
Multi-marker network in ST-elevation myocardial infarction (STEMI) patients undergoing primary percutaneous coronary intervention : when and what to measure / S. Ferraro, I. Ardoino, F. Braga, N. Bassani, E. Biganzoli, A.S. Bongo, M. Panteghini. - In: BIOCHIMICA CLINICA. - ISSN 0393-0564. - 37:SS(2013), pp. W071.S529-W071.S529. (Intervento presentato al convegno EUROMEDLAB Milano 2013 tenutosi a Milano nel 2013).
Abstract:
Background: A multi-marker strategy including biomarkers contributing independent information is expected to improve the prognostic evaluation of STEMI patients. We sought to
explore the relationship between cardiac troponin I (cTnI), Creactive
protein (CRP), B-type natriuretic peptide (BNP) and chromogranin A (CgA), accounting for biomarker profiles
detected within 48 h from successful primary percutaneous coronary intervention (PPCI).
Methods: We evaluated cTnI, CRP, BNP and CgA profiles based on measurements performed before PPCI and 6, 24 and
48 h later in 73 STEMI patients. DIRECT STATIS and DUAL STATIS based on Principal Components Analysis (PCA) were
employed to assess similarities between average profiles of patients and the relationship between markers measured at
different times of sampling.
Results: In evaluating ‘similarities between patients’, measurements at 24 h and 48 h contributed most variability to
subject profiles (score =0.942 and 0.915, respectively) as highly associated with the first principal component (accounting for 77.4% of explained variance). Patients’ profiles at these times resulted highly correlated (correlation coefficient, 0.91).
In evaluating ‘similarities between patterns of markers’, the sampling time mainly contributing to average biomarker profiles was 24 h. Concerning different biomarkers, BNP and cTnI were
highly correlated and mainly explained the first component (accounting for 40.1% of explained variance). The second
component (accounting for 26.3% of variance) was mainly explained by CgA, contributing independent information to
previous markers, and partially by CRP. CRP as inflammatory marker partially overlapped BNP and cTnI and seemed to have correlated but opposite effects with respect to CgA.
Conclusions: The sampling time contributing most information
from biomarker measurements to the definition of patients’ profile was 24 h after PPCI. BNP and cTnI resulted
interchangeable in a multi-marker panel for reporting about the extent of necrosis, whereas independent information derived from CgA. This marker may reflect a pathophysiologic
mechanism opposite to inflammatory response and orthogonal to the one explained by BNP, which resulted the most informative marker.
explore the relationship between cardiac troponin I (cTnI), Creactive
protein (CRP), B-type natriuretic peptide (BNP) and chromogranin A (CgA), accounting for biomarker profiles
detected within 48 h from successful primary percutaneous coronary intervention (PPCI).
Methods: We evaluated cTnI, CRP, BNP and CgA profiles based on measurements performed before PPCI and 6, 24 and
48 h later in 73 STEMI patients. DIRECT STATIS and DUAL STATIS based on Principal Components Analysis (PCA) were
employed to assess similarities between average profiles of patients and the relationship between markers measured at
different times of sampling.
Results: In evaluating ‘similarities between patients’, measurements at 24 h and 48 h contributed most variability to
subject profiles (score =0.942 and 0.915, respectively) as highly associated with the first principal component (accounting for 77.4% of explained variance). Patients’ profiles at these times resulted highly correlated (correlation coefficient, 0.91).
In evaluating ‘similarities between patterns of markers’, the sampling time mainly contributing to average biomarker profiles was 24 h. Concerning different biomarkers, BNP and cTnI were
highly correlated and mainly explained the first component (accounting for 40.1% of explained variance). The second
component (accounting for 26.3% of variance) was mainly explained by CgA, contributing independent information to
previous markers, and partially by CRP. CRP as inflammatory marker partially overlapped BNP and cTnI and seemed to have correlated but opposite effects with respect to CgA.
Conclusions: The sampling time contributing most information
from biomarker measurements to the definition of patients’ profile was 24 h after PPCI. BNP and cTnI resulted
interchangeable in a multi-marker panel for reporting about the extent of necrosis, whereas independent information derived from CgA. This marker may reflect a pathophysiologic
mechanism opposite to inflammatory response and orthogonal to the one explained by BNP, which resulted the most informative marker.
Tipologia IRIS:
01 - Articolo su periodico
Elenco autori:
S. Ferraro, I. Ardoino, F. Braga, N. Bassani, E. Biganzoli, A.S. Bongo, M. Panteghini
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