bdaa4996590284c1f5b299dfad2c6e68 jouclimed_a2022v11n5p1266.pdf 033114821a4001e2491da49780d846c631d41034 jouclimed_a2022v11n5p1266.pdf 972a432d9c58291970e8102330091f24e274682aece9b45f0d0d7fc09b6cd43f jouclimed_a2022v11n5p1266.pdf Title: Risk Assessment after ST-Segment Elevation Myocardial Infarction: Can Biomarkers Improve the Performance of Clinical Variables? Subject: Introduction: Myocardial infarction with ST-segment elevation (STEMI) is the coronary artery disease associated with the highest risk of morbimortality; however, this risk is heterogeneous, usually being evaluated by clinical scores. Risk assessment is a key factor in personalized clinical management of patients with this disease. Aim: The aim of this study was to assess whether some new cardiac biomarkers considered alone, combined in a multibiomarker model or in association with clinical variables, improve the short- and long-term risk stratification of STEMI patients. Materials and Methods: This was a retrospective observational study of 253 patients with STEMI. Blood samples were obtained before or during the angiography. The assessed biomarkers were C-terminal fragment of insulin-like growth factor binding protein-4 (CT-IGFBP4), high sensitive cardiac troponin T (hs-cTnT), N-terminal fragment of probrain natriuretic peptide (NT-proBNP), and growth differentiation factor 15 (GDF-15); they reflect different cardiovascular (CV) physiopathological pathways and underlying pathologies. We registered in-hospital and follow-up mortalities and their causes (cardiovascular and all-cause) and major adverse cardiac events (MACE) during a two year follow-up. Discrimination, survival analysis, model calibration, and reclassification of the biomarkers were comprehensively evaluated. Results and Discussion: In total, 55 patients (21.7%) died, 33 in-hospital and 22 during the follow-up, most of them (69.1%) from CV causes; 37 MACE occurred during follow-up. Biomarkers showed good prognostic ability to predict mortality, alone and combined with the multibiomarker model. A predictive clinical model based on age, Killip–Kimball class, estimated glomerular filtration rate (eGFR), and heart rate was derived by multivariate analysis. GDF-15 and NT-proBNP significantly improved risk assessment of the clinical model, as shown by discrimination, calibration, and reclassification of all the end-points except for all-cause mortality. The combination of NT-proBNP and hs-cTnT improved CV mortality prediction. Conclusions: GDF-15 and NT-proBNP added value to the usual risk assessment of STEMI patients. Keywords: cardiovascular; STEMI; risk assessment; biomarkers; multibiomarker; clinical model; NT-proBNP; GDF-15; CT-IGFBP-4 Author: Alvaro Garcia-Osuna, Jordi Sans-Rosello, Andreu Ferrero-Gregori, Aitor Alquezar-Arbe, Alessandro Sionis and Jordi Ordóñez-Llanos Creator: LaTeX with hyperref Producer: pdfTeX-1.40.21 CreationDate: Mon Feb 28 09:38:04 2022 CET ModDate: Mon Feb 28 09:42:06 2022 CET Tagged: no UserProperties: no Suspects: no Form: none JavaScript: no Pages: 14 Encrypted: no Page size: 595.276 x 841.89 pts (A4) Page rot: 0 File size: 697377 bytes Optimized: no PDF version: 1.7 name type encoding emb sub uni object ID ------------------------------------ ----------------- ---------------- --- --- --- --------- IKDDMG+URWPalladioL-Bold Type 1 Custom yes yes no 10 0 BDPNIY+URWPalladioL-Roma Type 1 Custom yes yes no 15 0 TFRXXL+URWPalladioL-Ital Type 1 Custom yes yes no 19 0 SOZKOC+VnURWPalladioL-Bold Type 1 Custom yes yes no 23 0 MCBCCI+SourceSansRoman-Regular Type 1C Custom yes yes no 32 0 MCBCCM+SourceSansRoman.613wght Type 1C Custom yes yes no 36 0 MCBCCO+SourceSansRoman-Bold Type 1C Custom yes yes no 40 0 XPUSBJ+TimesNewRomanPS-BoldItalicMT Type 1C WinAnsi yes yes no 52 0 BSDWLC+TimesNewRomanPSMT Type 1C WinAnsi yes yes no 55 0 GGJWAI+EURM10 Type 1 Builtin yes yes no 77 0 YQOTQA+VnURWPalladioL Type 1 Custom yes yes no 84 0 VORBJF+CMSY10 Type 1 Builtin yes yes no 88 0 QLBIEB+URWPalladioL-BoldItal Type 1 Custom yes yes no 99 0 ULOILR+EURB5 Type 1 Builtin yes yes no 116 0 Jhove (Rel. 1.22.1, 2019-04-17) Date: 2022-03-16 02:27:33 CET RepresentationInformation: jouclimed_a2022v11n5p1266.pdf ReportingModule: PDF-hul, Rel. 1.12.1 (2019-04-17) LastModified: 2022-03-03 12:50:44 CET Size: 697377 Format: PDF Version: 1.7 Status: Well-Formed and valid SignatureMatches: PDF-hul MIMEtype: application/pdf PDFMetadata: Objects: 313 FreeObjects: 3 IncrementalUpdates: 0 DocumentCatalog: PageLayout: SinglePage PageMode: UseNone Outlines: Item: Title: Introduction Destination: edu.harvard.hul.ois.jhove.module.pdf.PdfSimpleObject@7b69c6ba Item: Title: Material and Methods Destination: edu.harvard.hul.ois.jhove.module.pdf.PdfSimpleObject@46daef40 Children: Item: Title: Study Design and Patients Destination: edu.harvard.hul.ois.jhove.module.pdf.PdfSimpleObject@12f41634 Item: Title: Laboratory Variables Destination: edu.harvard.hul.ois.jhove.module.pdf.PdfSimpleObject@13c27452 Item: Title: Statistical Analysis Destination: edu.harvard.hul.ois.jhove.module.pdf.PdfSimpleObject@262b2c86 Item: Title: Results Destination: edu.harvard.hul.ois.jhove.module.pdf.PdfSimpleObject@371a67ec Children: Item: Title: Basal Variables Destination: edu.harvard.hul.ois.jhove.module.pdf.PdfSimpleObject@5ed828d Item: Title: Cardiovascular Biomarkers Destination: edu.harvard.hul.ois.jhove.module.pdf.PdfSimpleObject@50d0686 Item: Title: Risk Assessment Destination: edu.harvard.hul.ois.jhove.module.pdf.PdfSimpleObject@7a3d45bd Item: Title: Discussion Destination: edu.harvard.hul.ois.jhove.module.pdf.PdfSimpleObject@1e7c7811 Item: Title: Conclusions Destination: edu.harvard.hul.ois.jhove.module.pdf.PdfSimpleObject@77ec78b9 Item: Title: Limitations Destination: edu.harvard.hul.ois.jhove.module.pdf.PdfSimpleObject@1a3869f4 Item: Title: References Destination: edu.harvard.hul.ois.jhove.module.pdf.PdfSimpleObject@a38d7a3 Info: Title: Risk Assessment after ST-Segment Elevation Myocardial Infarction: Can Biomarkers Improve the Performance of Clinical Variables? Author: Alvaro Garcia-Osuna, Jordi Sans-Rosello, Andreu Ferrero-Gregori, Aitor Alquezar-Arbe, Alessandro Sionis and Jordi Ordóñez-Llanos Subject: Introduction: Myocardial infarction with ST-segment elevation (STEMI) is the coronary artery disease associated with the highest risk of morbimortality; however, this risk is heterogeneous, usually being evaluated by clinical scores. Risk assessment is a key factor in personalized clinical management of patients with this disease. Aim: The aim of this study was to assess whether some new cardiac biomarkers considered alone, combined in a multibiomarker model or in association with clinical variables, improve the short- and long-term risk stratification of STEMI patients. Materials and Methods: This was a retrospective observational study of 253 patients with STEMI. Blood samples were obtained before or during the angiography. The assessed biomarkers were C-terminal fragment of insulin-like growth factor binding protein-4 (CT-IGFBP4), high sensitive cardiac troponin T (hs-cTnT), N-terminal fragment of probrain natriuretic peptide (NT-proBNP), and growth differentiation factor 15 (GDF-15); they reflect different cardiovascular (CV) physiopathological pathways and underlying pathologies. We registered in-hospital and follow-up mortalities and their causes (cardiovascular and all-cause) and major adverse cardiac events (MACE) during a two year follow-up. Discrimination, survival analysis, model calibration, and reclassification of the biomarkers were comprehensively evaluated. Results and Discussion: In total, 55 patients (21.7%) died, 33 in-hospital and 22 during the follow-up, most of them (69.1%) from CV causes; 37 MACE occurred during follow-up. Biomarkers showed good prognostic ability to predict mortality, alone and combined with the multibiomarker model. A predictive clinical model based on age, Killip Kimball class, estimated glomerular filtration rate (eGFR), and heart rate was derived by multivariate analysis. GDF-15 and NT-proBNP significantly improved risk assessment of the clinical model, as shown by discrimination, calibration, and reclassification of all the end-points except for all-cause mortality. The combination of NT-proBNP and hs-cTnT improved CV mortality prediction. Conclusions: GDF-15 and NT-proBNP added value to the usual risk assessment of STEMI patients. 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