Application of a machine learning-driven, multibiomarker panel for prediction of incident cardiovascular events in patients with suspected myocardial infarction
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Application of a machine learning-driven, multibiomarker panel for prediction of incident cardiovascular events in patients with suspected myocardial infarction. / Neumann, Johannes T; Sörensen, Nils A; Zeller, Tanja; Magaret, Craig A; Barnes, Grady; Rhyne, Rhonda F; Peters, Celine; Goßling, Alina; Hartikainen, Tau S; Haller, Paul M; Lehmacher, Jonas; Schäfer, Sarina; Januzzi, James L; Westermann, Dirk.
in: BIOMARK MED, Jahrgang 14, Nr. 9, 06.2020, S. 775-784.Publikationen: SCORING: Beitrag in Fachzeitschrift/Zeitung › SCORING: Zeitschriftenaufsatz › Forschung › Begutachtung
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T1 - Application of a machine learning-driven, multibiomarker panel for prediction of incident cardiovascular events in patients with suspected myocardial infarction
AU - Neumann, Johannes T
AU - Sörensen, Nils A
AU - Zeller, Tanja
AU - Magaret, Craig A
AU - Barnes, Grady
AU - Rhyne, Rhonda F
AU - Peters, Celine
AU - Goßling, Alina
AU - Hartikainen, Tau S
AU - Haller, Paul M
AU - Lehmacher, Jonas
AU - Schäfer, Sarina
AU - Januzzi, James L
AU - Westermann, Dirk
PY - 2020/6
Y1 - 2020/6
N2 - Background: In patients with suspected myocardial infarction (MI), we sought to validate a machine learning-driven, multibiomarker panel for prediction of incident major adverse cardiovascular events (MACE). Methodology & results: A previously described prognostic panel for MACE consisting of four biomarkers was measured in 748 patients with suspected MI. The investigated end point was incident MACE within 1 year. The prognostic value of a continuous score and an optimal cut-off was investigated. The area under the curve was 0.86 for the overall model. Using the optimal cut-off resulted in a negative predictive value of 99.4% for incident MACE. Patients with an elevated prognostic score were at high risk for MACE. Conclusion: Among patients with suspected MI, we validated a multibiomarker panel for predicting 1-year MACE. Clinical Trial Registration: NCT02355457 (ClinicalTrials.gov).
AB - Background: In patients with suspected myocardial infarction (MI), we sought to validate a machine learning-driven, multibiomarker panel for prediction of incident major adverse cardiovascular events (MACE). Methodology & results: A previously described prognostic panel for MACE consisting of four biomarkers was measured in 748 patients with suspected MI. The investigated end point was incident MACE within 1 year. The prognostic value of a continuous score and an optimal cut-off was investigated. The area under the curve was 0.86 for the overall model. Using the optimal cut-off resulted in a negative predictive value of 99.4% for incident MACE. Patients with an elevated prognostic score were at high risk for MACE. Conclusion: Among patients with suspected MI, we validated a multibiomarker panel for predicting 1-year MACE. Clinical Trial Registration: NCT02355457 (ClinicalTrials.gov).
KW - Aged
KW - Biomarkers/metabolism
KW - Female
KW - Humans
KW - Machine Learning
KW - Male
KW - Middle Aged
KW - Myocardial Infarction/diagnosis
KW - Predictive Value of Tests
KW - Prognosis
KW - Risk Assessment
U2 - 10.2217/bmm-2019-0584
DO - 10.2217/bmm-2019-0584
M3 - SCORING: Journal article
C2 - 32462911
VL - 14
SP - 775
EP - 784
JO - BIOMARK MED
JF - BIOMARK MED
SN - 1752-0363
IS - 9
ER -