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Harr KE, Gordon SG, Baumwart RD, Feldgreber R, Spiro MR. Analytical validation of a novel point‐of‐care immunoassay for canine N‐terminal pro‐brain natriuretic peptide analysis. Vet Clin Pathol 2022; 51:398-407. [PMID: 35312100 PMCID: PMC9544283 DOI: 10.1111/vcp.13101] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/16/2021] [Revised: 11/12/2021] [Accepted: 11/16/2021] [Indexed: 11/30/2022]
Abstract
Background N‐terminal pro‐brain natriuretic peptide (NT‐proBNP) is a widely used point‐of‐care (POC) cardiac biomarker in human medicine. Canine NT‐proBNP is used less in veterinary medicine, possibly due to the lack of a POC canine NT‐proBNP assay resulting in temporal delay, increased degradation in transport, and high reported variability in the available assay. A new quantitative POC analyzer allows fast, onsite measurement of NT‐proBNP, minimizing preanalytical error and reducing variability. Objective We aimed to analytically validate an NT‐proBNP assay (Vcheck) according to American Society of Veterinary Clinical Pathology (ASVCP) and Clinical Laboratory Improvement Amendments (CLIA) specifications. Methods Archived and prospective plasma and serum samples were collected from male and female, client‐owned dogs of various breeds with cardiac abnormalities (n = 81) and a healthy control population (n = 225). Precision, accuracy, analytical sensitivity, and specificity, and other statistical analyses were performed. Results Imprecision was considered acceptable with a coefficient of variation ranging from 9% at 4000 pmol/L to 20% at 600 pmol/L. The lower limit of quantitation was 650 pmol/L based on repetitive measures evaluation. Comparison of the Vcheck assay with the Cardiopet NT‐proBNP assay revealed an excellent correlation with minimal bias when preanalytical factors were controlled. Significant degradation of NT‐proBNP occurred when current methods were used at refrigerated and room temperatures, which could change diagnostic and prognostic decision‐making. Age‐partitioned reference intervals have high reference values of 750 pmol/L and 1280 pmol/L for juvenile and adult dogs, respectively. Conclusions The Vcheck NT‐ProBNP assay provides analytically acceptable results. Onsite testing can minimize variability related to preanalytical error and provide clinically useful contemporaneous results. Samples should be centrifuged immediately and analyzed within 2 hours of collection.
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Affiliation(s)
| | - Sonya G. Gordon
- Department of Small Animal Clinical Science, College of Veterinary Medicine and Biomedical Science Texas A&M University College Station TX USA
| | - Ryan D. Baumwart
- Department of Veterinary Clinical Sciences, College of Veterinary Medicine Washington State University Pullman WA USA
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Álvarez-García J, García-Osuna Á, Vives-Borrás M, Ferrero-Gregori A, Martínez-Sellés M, Vázquez R, González-Juanatey JR, Rivera M, Segovia J, Pascual-Figal D, Bover R, Bascompte R, Delgado J, Grau Sepúlveda A, Bardají A, Pérez-Villa F, Zamorano JL, Crespo-Leiro M, Sánchez PL, Ordoñez-Llanos J, Cinca J. A 3-Biomarker 2-Point-Based Risk Stratification Strategy in Acute Heart Failure. Front Physiol 2021; 12:708890. [PMID: 34744758 PMCID: PMC8569896 DOI: 10.3389/fphys.2021.708890] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/12/2021] [Accepted: 10/04/2021] [Indexed: 01/02/2023] Open
Abstract
Introduction and Objectives: Most multi-biomarker strategies in acute heart failure (HF) have only measured biomarkers in a single-point time. This study aimed to evaluate the prognostic yielding of NT-proBNP, hsTnT, Cys-C, hs-CRP, GDF15, and GAL-3 in HF patients both at admission and discharge. Methods: We included 830 patients enrolled consecutively in a prospective multicenter registry. Primary outcome was 12-month mortality. The gain in the C-index, calibration, net reclassification improvement (NRI), and integrated discrimination improvement (IDI) was calculated after adding each individual biomarker value or their combination on top of the best clinical model developed in this study (C-index 0.752, 0.715-0.789) and also on top of 4 currently used scores (MAGGIC, GWTG-HF, Redin-SCORE, BCN-bioHF). Results: After 12-month, death occurred in 154 (18.5%) cases. On top of the best clinical model, the addition of NT-proBNP, hs-CRP, and GDF-15 above the respective cutoff point at admission and discharge and their delta during compensation improved the C-index to 0.782 (0.747-0.817), IDI by 5% (p < 0.001), and NRI by 57% (p < 0.001) for 12-month mortality. A 4-risk grading categories for 12-month mortality (11.7, 19.2, 26.7, and 39.4%, respectively; p < 0.001) were obtained using combination of these biomarkers. Conclusion: A model including NT-proBNP, hs-CRP, and GDF-15 measured at admission and discharge afforded a mortality risk prediction greater than our clinical model and also better than the most currently used scores. In addition, this 3-biomarker panel defined 4-risk categories for 12-month mortality.
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Affiliation(s)
- Jesús Álvarez-García
- Cardiology Department, Hospital de la Santa Creu i Sant Pau, IIb-SantPau, Centro de Investigación en Red en Enfermedades Cardiovasculares (CIBERCV), Barcelona, Spain.,Cardiology Department, Hospital Ramón y Cajal, Centro de Investigación en Red en Enfermedades Cardiovasculares (CIBERCV), Madrid, Spain
| | - Álvaro García-Osuna
- Biochemistry Department, Hospital de la Santa Creu i Sant Pau, IIb-SantPau, Barcelona, Spain
| | - Miquel Vives-Borrás
- Cardiology Department, Hospital de la Santa Creu i Sant Pau, IIb-SantPau, Centro de Investigación en Red en Enfermedades Cardiovasculares (CIBERCV), Barcelona, Spain
| | - Andreu Ferrero-Gregori
- Cardiology Department, Hospital de la Santa Creu i Sant Pau, IIb-SantPau, Centro de Investigación en Red en Enfermedades Cardiovasculares (CIBERCV), Barcelona, Spain
| | - Manuel Martínez-Sellés
- Cardiology Department, Hospital Universitario Gregorio Marañón, Centro de Investigación en Red en Enfermedades Cardiovasculares (CIBERCV), Madrid, Spain
| | - Rafael Vázquez
- Cardiology Department, Hospital Puerta del Mar, Centro de Investigación en Red en Enfermedades Cardiovasculares (CIBERCV), Cádiz, Spain
| | - José R González-Juanatey
- Cardiology Department, Hospital Clínico, Centro de Investigación en Red en Enfermedades Cardiovasculares (CIBERCV), Santiago de Compostela, Spain
| | - Miguel Rivera
- Cardiology Department, Hospital La Fe, Centro de Investigación en Red en Enfermedades Cardiovasculares (CIBERCV), Valencia, Spain
| | - Javier Segovia
- Cardiology Department, Hospital Puerta de Hierro-Majadahonda, Centro de Investigación en Red en Enfermedades Cardiovasculares (CIBERCV), Madrid, Spain
| | - Domingo Pascual-Figal
- Cardiology Department, Hospital Virgen de la Arrixaca, Centro de Investigación en Red en Enfermedades Cardiovasculares (CIBERCV), Murcia, Spain
| | - Ramón Bover
- Cardiology Department, Hospital Clínico San Carlos, Centro de Investigación en Red en Enfermedades Cardiovasculares (CIBERCV), Madrid, Spain
| | - Ramón Bascompte
- Cardiology Department, Hospital Arnau de Vilanova, Centro de Investigación en Red en Enfermedades Cardiovasculares (CIBERCV), Lleida, Spain
| | - Juan Delgado
- Cardiology Department, Hospital 12 de Octubre, Centro de Investigación en Red en Enfermedades Cardiovasculares (CIBERCV), Madrid, Spain
| | - Andrés Grau Sepúlveda
- Cardiology Department, Hospital Universitario Son Espases, Centro de Investigación en Red en Enfermedades Cardiovasculares (CIBERCV), Palma de Mallorca, Spain
| | - Alfredo Bardají
- Cardiology Department, Hospital Juan XXIII, Centro de Investigación en Red en Enfermedades Cardiovasculares (CIBERCV), Tarragona, Spain
| | - Félix Pérez-Villa
- Cardiology Department, Hospital Clinic, Centro de Investigación en Red en Enfermedades Cardiovasculares (CIBERCV), Barcelona, Spain
| | - José Luis Zamorano
- Cardiology Department, Hospital Ramón y Cajal, Centro de Investigación en Red en Enfermedades Cardiovasculares (CIBERCV), Madrid, Spain
| | - Marisa Crespo-Leiro
- Cardiology Department, Hospital Universitario A Coruna, Centro de Investigación en Red en Enfermedades Cardiovasculares (CIBERCV), A Coruna, Spain
| | - Pedro Luis Sánchez
- Cardiology Department, Hospital Clínico Universitario, Centro de Investigación en Red en Enfermedades Cardiovasculares (CIBERCV), Salamanca, Spain
| | - Jordi Ordoñez-Llanos
- Biochemistry Department, Hospital de la Santa Creu i Sant Pau, IIb-SantPau, Barcelona, Spain
| | - Juan Cinca
- Cardiology Department, Hospital de la Santa Creu i Sant Pau, IIb-SantPau, Centro de Investigación en Red en Enfermedades Cardiovasculares (CIBERCV), Barcelona, Spain
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Clark AL, Cherif M, McDonagh TA, Squire IB. In-hospital worsening heart failure: a clinically relevant endpoint? ESC Heart Fail 2018; 5:9-18. [PMID: 29385659 PMCID: PMC5793965 DOI: 10.1002/ehf2.12195] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/20/2016] [Revised: 05/10/2017] [Accepted: 06/20/2017] [Indexed: 12/11/2022] Open
Abstract
Outcome measures used for the clinical evaluation of patients with acute heart failure differ between studies and may neither adequately address the characteristic presenting symptoms and signs nor reflect the pathophysiological processes involved. In-hospital worsening of heart failure (WHF) is associated with poor outcomes and thus a potential endpoint conveying clinically meaningful prognostic information. Current definitions of WHF are based on the combination of worsening symptoms and signs and the intensification of treatment during admission. Definitions vary across studies and do not fully account for baseline therapy or circumstances in which there is failure to respond to treatment. Further, there are limited data to inform healthcare professionals as to which patients are most at risk of developing in-hospital WHF. In this opinion piece, we review the definitions for WHF used in recent and ongoing clinical trials and propose a novel definition, which captures failure to respond to treatment as well as clinical worsening (deterioration of symptoms and signs) of the patient's condition. Such a definition, applied consistently across studies, would help clarify the characteristics of patients likely to develop in-hospital WHF, allow comparative assessments of the effectiveness of interventions, and help guide appropriate patient management in order to improve outcomes.
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Affiliation(s)
- Andrew L. Clark
- Department of Cardiology, Hull York Medical SchoolCastle Hill HospitalKingston‐upon‐HullUK
| | | | | | - Iain B. Squire
- Department of Cardiovascular SciencesUniversity of Leicester, NIHR Cardiovascular Biomedical Research Unit, Glenfield General HospitalLeicesterUK
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The utility of biomarker risk prediction score in patients with chronic heart failure. Clin Hypertens 2016; 22:3. [PMID: 26973794 PMCID: PMC4787185 DOI: 10.1186/s40885-016-0041-1] [Citation(s) in RCA: 24] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/07/2015] [Accepted: 01/08/2016] [Indexed: 12/14/2022] Open
Abstract
Background Chronic heart failure (CHF) has been remained a leading cause of cardiovascular morbidity and mortaluty. The risk stratification of CHF individuals based on clinical criteria and biomarkers' models may improve medical care and probably increase efficacy of treatment strategy. However, various predictive models approved for CHF patients appear to be distinguished in their prognostications. The study aim was to evaluate whether biomarker risk prediction score is powerful tool for risk assessment of three-year fatal and non-fatal cardiovascular events in CHF patients. Methods It was studied prospectively the incidence of fatal and non-fatal cardiovascular events in a cohort of 388 patients with ischemic-induced CHF within 3 years. Circulating biomarkers were collected at baseline of the study. Results Independent predictors of clinical outcomes in patients with CHF were NT-pro-BNP, galectin-3, hs-CRP, osteoprotegerin, CD31+/annexin V+ endothelail-derived microparticles (EMPs) and CD31+/annexin V+ EMPs to CD14+CD309+ monuclear progenitor cells (MPCs) ratio. Index of cardiovascular risk was calculated by mathematical summation of all ranks of independent predictors, which occurred in the patients included in the study. Kaplan-Meier analysis showed that patients with CHF and the magnitude of the risk of less than 4 units have an advantage in survival when compared with patients for whom obtained higher values of cardiovascular risk score ranks. Conclusion Biomarker risk score for cumulative cardiovascular events, constructed by measurement of circulating NT-pro-BNP, galectin-3, hs-CRP, osteoprotegerin, CD31+/annexin V+ EMPs and CD31+/annexin V+ EMPs to CD14+CD309+ MPCs ratio, allowing reliably predict the probability survival of patients with CHF.
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Huang WM, Hsu PF, Cheng HM, Lu DY, Cheng YL, Guo CY, Sung SH, Yu WC, Chen CH. Determinants and Prognostic Impact of Hyperuricemia in Hospitalization for Acute Heart Failure. Circ J 2015; 80:404-10. [PMID: 26597355 DOI: 10.1253/circj.cj-15-0964] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Abstract
BACKGROUND Hyperuricemia is a prognostic factor in patients with chronic heart failure, but whether uric acid level can predict clinical outcome of acute heart failure (AHF) remains to be elucidated. We therefore investigated the association of uric acid with mortality in patients hospitalized for AHF. METHODS AND RESULTS Data for patients hospitalized for AHF were drawn from an intramural registry. Biochemistry data, echocardiographic characteristics, and uric acid level were collected. National Death Registry was linked for the identification of mortality data. Among a total of 1,835 participants (age, 75 ± 13 years, 68% men), 794 patients died during follow-up. Patients who died were older, had lower hemoglobin and estimated glomerular filtration rate, and higher pulmonary artery systolic pressure, NT-proBNP, and uric acid. Uric acid was a significant predictor of mortality on univariate analysis (HR per 1 SD, 1.18; 95% CI: 1.11-1.26) and in multivariate Cox models (HR, 1.15; 95% CI: 1.02-1.29). Survival analysis showed an increasing risk of death along the quartile distribution of uric acid level. Given renal function, cardiac performance, and kidney perfusion as major determinants of hyperuricemia, the prognostic impact of uric acid level was diminished as renal function deteriorated. CONCLUSIONS Uric acid level was an independent predictor of mortality in patients hospitalized for AHF, but the prognostic impact of hyperuricemia was attenuated by worsening renal function.
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Affiliation(s)
- Wei-Ming Huang
- Department of Medicine, Taipei Veterans General Hospital
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