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Ragusa R, Masotti S, Musetti V, Rocchiccioli S, Prontera C, Perrone M, Passino C, Clerico A, Caselli C. Cardiac troponins: Mechanisms of release and role in healthy and diseased subjects. Biofactors 2022; 49:351-364. [PMID: 36518005 DOI: 10.1002/biof.1925] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/08/2022] [Accepted: 11/24/2022] [Indexed: 12/23/2022]
Abstract
The cardiac troponins (cTns), cardiac troponin C (cTnC), cTnT, and cTnI are key elements of myocardial apparatus, fixed as protein complex on the thin filament of sarcomere and are involved in the regulation of excitation-contraction coupling of cardiomyocytes in the presence of Ca2+ . Circulating cTnT and cTnI (cTns) increase following cardiac tissue necrosis, and they are consolidated biomarkers of acute myocardial infarction (AMI). However, the use of high sensitivity (hs)-immunoassay tests for cTnT and cTnI has made it possible to identify a multitude of other clinical conditions associated with increased circulating levels of cTns. cTns can be measured also in the peripheral circulation of healthy subjects or athletes, suggesting that different mechanisms are involved in the release of cTns in the blood independently of cardiac cell necrosis. In this review, the molecular/cellular mechanisms involved in cTns release in blood and the exploitation of cTnI and cTnT as biomarkers of cardiac adverse events, in addition to cardiac necrosis, are discussed.
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Affiliation(s)
| | - Silvia Masotti
- Scuola Superiore Sant'Anna, Institute of Life Sciences, Pisa, Italy
- Fondazione Toscana Gabriele Monasterio, Pisa, Italy
| | - Veronica Musetti
- Scuola Superiore Sant'Anna, Institute of Life Sciences, Pisa, Italy
- Fondazione Toscana Gabriele Monasterio, Pisa, Italy
| | | | | | - Marco Perrone
- Department of Cardiology, University of Rome Tor Vergata, Rome, Italy
| | - Claudio Passino
- Scuola Superiore Sant'Anna, Institute of Life Sciences, Pisa, Italy
- Fondazione Toscana Gabriele Monasterio, Pisa, Italy
| | - Aldo Clerico
- Scuola Superiore Sant'Anna, Institute of Life Sciences, Pisa, Italy
- Fondazione Toscana Gabriele Monasterio, Pisa, Italy
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Lu X, Jiang M, Lin MH. Diagnostic Value of Convolutional Neural Network Algorithm and High-Sensitivity Cardiac Troponin I Detection Under Machine Learning in Myocardial Infarction. J Biomed Nanotechnol 2022. [DOI: 10.1166/jbn.2022.3474] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/30/2023]
Abstract
Background: It aimed to the diagnosis and examination of acute myocardial infarction (AMI) using echocardiography under improved convolutional neural network (CNN) algorithm and high-sensitivity (Sen) cardiac troponin I (hs-cTnI) detection. The application effect was also evaluated.
Methods: Ninety AMI patients were recruited as the AMI group, and ninety healthy individuals who underwent physical examinations simultaneously were chosen as control (Ctrl) group. Improved CNN algorithm-based echocardiography combined with hs-cTnI detection was applied, and its diagnostic
efficiency was evaluated. Results: The optimal dataset scale (ODS), optimal image scale (OIS) and average precision (AP) of the proposed algorithm were better than those of manual labeling, Canny algorithm, and structured edge (SE) algorithm (P < 0.05). The left ventricular
ejection fraction (LVEF) of the patients in the AMI group was inferior to that of Ctrl group ((55.09±2.78)%) versus (65.01±3.19)%), the left ventricular end-diastolic dimension (LVEDD) was superior to that of Ctrl group ((54.89±6.56) mm vs. (45.98±5.77) mm), and
the cTnI level was also superior to that of Ctrl group ((2.90±0.31) pg/L vs. (0.73±0.42) pg/L) (P < 0.05). The diagnostic Sen (91.89%), specificity (Spe) (81.25%), accuracy (Acc) (90.00%) and consistency (0.56) of echocardiography combined with hs-cTnI were superior
to those of single echocardiography or cTnI detection (P < 0.05).
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Clerico A, Zaninotto M, Aimo A, Dittadi R, Cosseddu D, Perrone M, Padoan A, Masotti S, Belloni L, Migliardi M, Fortunato A, Trenti T, Malloggi L, Cappelletti P, Galli GA, Bernardini S, Sciacovelli L, Plebani M. Use of high-sensitivity cardiac troponins in the emergency department for the early rule-in and rule-out of acute myocardial infarction without persistent ST-segment elevation (NSTEMI) in Italy. Clin Chem Lab Med 2021; 60:169-182. [PMID: 34927403 DOI: 10.1515/cclm-2021-1085] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/07/2021] [Accepted: 11/26/2021] [Indexed: 12/15/2022]
Abstract
Serial measurements of cardiac troponin are recommended by international guidelines to diagnose myocardial infarction (MI) since 2000. However, some relevant differences exist between the three different international guidelines published between 2020 and 2021 for the management of patients with chest pain and no ST-segment elevation. In particular, there is no agreement on the cut-offs or absolute change values to diagnose non-ST-segment elevation MI (NSTEMI). Other controversial issues concern the diagnostic accuracy and cost-effectiveness of cut-off values for the most rapid algorithms (0 h/1 h or 0 h/2 h) to rule-in and rule-out NSTEMI. Finally, another important point is the possible differences between demographic and clinical characteristics of patients enrolled in multicenter trials compared to those routinely admitted to the Emergency Department in Italy. The Study Group of Cardiac Biomarkers, supported by the Italian Scientific Societies Società Italiana di Biochimica Clinica, Italian Society of the European Ligand Assay Society, and Società Italiana di Patolgia Clinica e Medicina di Laboratorio decided to revise the document previously published in 2013 about the management of patients with suspected NSTEMI, and to provide some suggestions for the use of these biomarkers in clinical practice, with a particular focus on the Italian setting.
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Affiliation(s)
- Aldo Clerico
- Fondazione CNR Regione Toscana G. Monasterio e Scuola Superiore Sant'Anna, Pisa, Italy
| | - Martina Zaninotto
- Department of Laboratory Medicine, University Hospital of Padova, Padova, Italy.,Department of Medicine-DIMED, University of Padova, Padova, Italy
| | - Alberto Aimo
- Fondazione CNR Regione Toscana G. Monasterio e Scuola Superiore Sant'Anna, Pisa, Italy
| | - Ruggero Dittadi
- Ospedale dell'Angelo ULSS 3 Serenissima, Laboratorio di Analisi Cliniche, Mestre, Italy
| | - Domenico Cosseddu
- S.C. Laboratorio Analisi, A.O. Ordine Mauriziano di Torino, Torino, Italy
| | - Marco Perrone
- Division of Cardiology and Clinical Biochemistry, University of Rome Tor Vergata, Rome, Italy
| | - Andrea Padoan
- Department of Laboratory Medicine, University Hospital of Padova, Padova, Italy
| | - Silvia Masotti
- Fondazione CNR Regione Toscana G. Monasterio e Scuola Superiore Sant'Anna, Pisa, Italy
| | - Lucia Belloni
- Dipartimento di Medicina di laboratorio, Arcispedale Santa Maria Nuova - IRCCS, Reggio Emilia, Italy
| | - Marco Migliardi
- S.C. Laboratorio Analisi, A.O. Ordine Mauriziano di Torino, Torino, Italy
| | | | - Tommaso Trenti
- Azienda Ospedaliero - Universitaria Policlinico di Modena c/o Ospedale Civile di Baggiovara, Modena, Italy
| | - Lucia Malloggi
- Laboratorio Analisi, Azienda Ospedaliera-Universitaria di Pisa, Pisa, Italy
| | | | | | - Sergio Bernardini
- Division of Cardiology and Clinical Biochemistry, University of Rome Tor Vergata, Rome, Italy
| | - Laura Sciacovelli
- Department of Laboratory Medicine, University Hospital of Padova, Padova, Italy
| | - Mario Plebani
- Department of Laboratory Medicine, University Hospital of Padova, Padova, Italy
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Fernández-Cisnal A, Valero E, García-Blas S, Pernias V, Pozo A, Carratalá A, González J, Noceda J, Miñana G, Núñez J, Sanchis J. Clinical History and Detectable Troponin Concentrations below the 99th Percentile for Risk Stratification of Patients with Chest Pain and First Normal Troponin. J Clin Med 2021; 10:jcm10081784. [PMID: 33923925 PMCID: PMC8073372 DOI: 10.3390/jcm10081784] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2021] [Revised: 04/15/2021] [Accepted: 04/18/2021] [Indexed: 11/16/2022] Open
Abstract
Decision-making is challenging in patients with chest pain and normal high-sensitivity cardiac troponin T (hs-cTnT; <99th percentile; <14 ng/L) at hospital arrival. Most of these patients might be discharged early. We investigated clinical data and hs-cTnT concentrations for risk stratification. This is a retrospective study including 4476 consecutive patients presenting to the emergency department with chest pain and first normal hs-cTnT. The primary endpoint was one-year death or acute myocardial infarction, and the secondary endpoint added urgent revascularization. The number of primary and secondary endpoints was 173 (3.9%) and 252 (5.6%). Mean hs-cTnT concentrations were 6.9 ± 2.5 ng/L. Undetectable (<5 ng/L) hs-cTnT (n = 1847, 41%) had optimal negative predictive value (99.1%) but suboptimal sensitivity (90.2%) and discrimination accuracy (AUC = 0.664) for the primary endpoint. Multivariable analysis was used to identify the predictive clinical variables. The clinical model showed good discrimination accuracy (AUC = 0.810). The addition of undetectable hs-cTnT (≥ or <5 ng/L; HR, hazard ratio = 3.80; 95% CI, confidence interval 2.27–6.35; p = 0.00001) outperformed the clinical model alone (AUC = 0.836, p = 0.002 compared to the clinical model). Measurable hs-cTnT concentrations (between detection limit and 99th percentile; per 0.1 ng/L, HR = 1.13; CI 1.06–1.20; p = 0.0001) provided further predictive information (AUC = 0.844; p = 0.05 compared to the clinical plus undetectable hs-cTnT model). The results were reproducible for the secondary endpoint and 30-day events. Clinical assessment, undetectable hs-cTnT and measurable hs-cTnT concentrations must be considered for decision-making after a single negative hs-cTnT result in patients presenting to the emergency department with acute chest pain.
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Affiliation(s)
- Agustín Fernández-Cisnal
- Cardiology Department, University Clinic Hospital of València, Instituto de Investigación Sanitaria (INCLIVA), University of València, Centro de Investigación Biomédica en Red Enfermedades Cardiovaculares (CIBERCV), 46010 València, Spain; (A.F.-C.); (E.V.); (S.G.-B.); (V.P.); (A.P.); (J.G.); (G.M.); (J.N.)
| | - Ernesto Valero
- Cardiology Department, University Clinic Hospital of València, Instituto de Investigación Sanitaria (INCLIVA), University of València, Centro de Investigación Biomédica en Red Enfermedades Cardiovaculares (CIBERCV), 46010 València, Spain; (A.F.-C.); (E.V.); (S.G.-B.); (V.P.); (A.P.); (J.G.); (G.M.); (J.N.)
| | - Sergio García-Blas
- Cardiology Department, University Clinic Hospital of València, Instituto de Investigación Sanitaria (INCLIVA), University of València, Centro de Investigación Biomédica en Red Enfermedades Cardiovaculares (CIBERCV), 46010 València, Spain; (A.F.-C.); (E.V.); (S.G.-B.); (V.P.); (A.P.); (J.G.); (G.M.); (J.N.)
| | - Vicente Pernias
- Cardiology Department, University Clinic Hospital of València, Instituto de Investigación Sanitaria (INCLIVA), University of València, Centro de Investigación Biomédica en Red Enfermedades Cardiovaculares (CIBERCV), 46010 València, Spain; (A.F.-C.); (E.V.); (S.G.-B.); (V.P.); (A.P.); (J.G.); (G.M.); (J.N.)
| | - Adela Pozo
- Cardiology Department, University Clinic Hospital of València, Instituto de Investigación Sanitaria (INCLIVA), University of València, Centro de Investigación Biomédica en Red Enfermedades Cardiovaculares (CIBERCV), 46010 València, Spain; (A.F.-C.); (E.V.); (S.G.-B.); (V.P.); (A.P.); (J.G.); (G.M.); (J.N.)
| | - Arturo Carratalá
- Clinical Biochemistry Department, University Clinic Hospital of València, Instituto de Investigación Sanitaria (INCLIVA), 46010 València, Spain;
| | - Jessika González
- Cardiology Department, University Clinic Hospital of València, Instituto de Investigación Sanitaria (INCLIVA), University of València, Centro de Investigación Biomédica en Red Enfermedades Cardiovaculares (CIBERCV), 46010 València, Spain; (A.F.-C.); (E.V.); (S.G.-B.); (V.P.); (A.P.); (J.G.); (G.M.); (J.N.)
| | - José Noceda
- Emergency Department, University Clinic Hospital of València, Instituto de Investigación Sanitaria (INCLIVA), 46010 València, Spain;
| | - Gema Miñana
- Cardiology Department, University Clinic Hospital of València, Instituto de Investigación Sanitaria (INCLIVA), University of València, Centro de Investigación Biomédica en Red Enfermedades Cardiovaculares (CIBERCV), 46010 València, Spain; (A.F.-C.); (E.V.); (S.G.-B.); (V.P.); (A.P.); (J.G.); (G.M.); (J.N.)
| | - Julio Núñez
- Cardiology Department, University Clinic Hospital of València, Instituto de Investigación Sanitaria (INCLIVA), University of València, Centro de Investigación Biomédica en Red Enfermedades Cardiovaculares (CIBERCV), 46010 València, Spain; (A.F.-C.); (E.V.); (S.G.-B.); (V.P.); (A.P.); (J.G.); (G.M.); (J.N.)
| | - Juan Sanchis
- Cardiology Department, University Clinic Hospital of València, Instituto de Investigación Sanitaria (INCLIVA), University of València, Centro de Investigación Biomédica en Red Enfermedades Cardiovaculares (CIBERCV), 46010 València, Spain; (A.F.-C.); (E.V.); (S.G.-B.); (V.P.); (A.P.); (J.G.); (G.M.); (J.N.)
- Correspondence:
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