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Abubakar M, Irfan U, Abdelkhalek A, Javed I, Khokhar MI, Shakil F, Raza S, Salim SS, Altaf MM, Habib R, Ahmed S, Ahmed F. Comprehensive Quality Analysis of Conventional and Novel Biomarkers in Diagnosing and Predicting Prognosis of Coronary Artery Disease, Acute Coronary Syndrome, and Heart Failure, a Comprehensive Literature Review. J Cardiovasc Transl Res 2024:10.1007/s12265-024-10540-8. [PMID: 38995611 DOI: 10.1007/s12265-024-10540-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/30/2024] [Accepted: 06/25/2024] [Indexed: 07/13/2024]
Abstract
Coronary artery disease (CAD), acute coronary syndrome (ACS), and heart failure (HF) are major global health issues with high morbidity and mortality rates. Biomarkers like cardiac troponins (cTn) and natriuretic peptides (NPs) are crucial tools in cardiology, but numerous new biomarkers have emerged, proving increasingly valuable in CAD/ACS. These biomarkers are classified based on their mechanisms, such as fibrosis, metabolism, inflammation, and congestion. The integration of established and emerging biomarkers into clinical practice is an ongoing process, and recognizing their strengths and limitations is crucial for their accurate interpretation, incorporation into clinical settings, and improved management of CVD patients. We explored established biomarkers like cTn, NPs, and CRP, alongside newer biomarkers such as Apo-A1, IL-17E, IgA, Gal-3, sST2, GDF-15, MPO, H-FABP, Lp-PLA2, and ncRNAs; provided evidence of their utility in CAD/ACS diagnosis and prognosis; and empowered clinicians to confidently integrate these biomarkers into clinical practice based on solid evidence.
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Affiliation(s)
- Muhammad Abubakar
- Department of Internal Medicine, Ameer-Ud-Din Medical College, 6 Birdwood Road, Jinnah Town, Lahore, 54000, Punjab, Pakistan.
| | - Umema Irfan
- Department of Internal Medicine, Deccan College of Medical Sciences, Hyderabad, India
| | - Ahmad Abdelkhalek
- Department of Internal Medicine, Zhejiang University, Zhejiang, China
| | - Izzah Javed
- Department of Internal Medicine, Ameer-Ud-Din Medical College, 6 Birdwood Road, Jinnah Town, Lahore, 54000, Punjab, Pakistan
| | | | - Fraz Shakil
- Department of Emergency Medicine, Mayo Hospital, Lahore, Pakistan
| | - Saud Raza
- Department of Anesthesia, Social Security Teaching Hospital, Lahore, Punjab, Pakistan
| | - Siffat Saima Salim
- Department of Surgery, Holy Family Red Crescent Medical College Hospital, Dhaka, Bangladesh
| | - Muhammad Mahran Altaf
- Department of Internal Medicine, Ameer-Ud-Din Medical College, 6 Birdwood Road, Jinnah Town, Lahore, 54000, Punjab, Pakistan
| | - Rizwan Habib
- Department of Internal Medicine and Emergency, Indus Hospital, Lahore, Pakistan
| | - Simra Ahmed
- Department of Internal Medicine, Ziauddin Medical College, Karachi, Pakistan
| | - Farea Ahmed
- Department of Internal Medicine, Ziauddin Medical College, Karachi, Pakistan
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Zhang J, Zhang J, Huang C, Wu T, Jin P. Integrated biomarker profiling for enhanced heart failure management: a comprehensive study on the application of chemiluminescence detection of GDF-15 and multi-index models. Lab Med 2024:lmae045. [PMID: 38916138 DOI: 10.1093/labmed/lmae045] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/26/2024] Open
Abstract
BACKGROUND Growth differentiation factor 15 (GDF-15) holds promise as a novel marker for heart failure. However, current detection methods fall short of meeting essential clinical requirements. OBJECTIVES The aim of this investigation was to assess the clinical significance of serum GDF-15 detection through the chemiluminescence method and to enhance its clinical application for predicting and evaluating heart failure in patients. METHODS A total of 122 patients were included in the study. Serum GDF-15 levels were assessed using the chemiluminescence method and compared with results for NT-proBNP, N-terminal pro-brain natriuretic peptide (NT-proBNP), growth stimulation expressed gene 2 (ST2), high-sensitivity C-reactive protein (hs-CRP), and left ventricular ejection fraction (LVEF). Additionally, we conducted an analysis to evaluate the correlation between these indicators and heart failure events. RESULTS LVEF, ST2, NT-proBNP, and GDF-15 exhibited significant associations with heart failure. In the multivariate proportional hazard analysis, subsequent to adjusting for the effects of other markers, however, only LVEF and GDF-15 retained their associations with heart failure events. Notably, GDF-15 emerged as the exclusive marker suitable for diagnosing heart failure with preserved ejection fraction. CONCLUSION The chemiluminescence method proved efficient in the rapid and sensitive detection of GDF-15 in patients with heart failure. Additionally, GDF-15 combined with other markers created a robust multi-index model. This model is valuable for heart failure diagnosis, treatment, and monitoring, with broad clinical applicability.
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Affiliation(s)
- Ju Zhang
- Department of Laboratory Medicine, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, China
- Core Unit of National Clinical Research Center for Laboratory Medicine, Hefei, China
- Department of Clinical Laboratory Diagnostics, Bengbu Medical College, Bengbu, China
| | - Jiajia Zhang
- Department of Clinical Laboratory Diagnostics, Bengbu Medical College, Bengbu, China
| | | | - Ting Wu
- Maccura Biotechnology, Chengdu, China
| | - Peipei Jin
- Department of Laboratory Medicine, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, China
- Core Unit of National Clinical Research Center for Laboratory Medicine, Hefei, China
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Wang H, Wang C. Prognostic Value of Endothelin-1 or Related Peptides in Patients With Coronary Artery Disease: A Systematic Review and Meta-Analysis. Angiology 2023:33197231223616. [PMID: 38128149 DOI: 10.1177/00033197231223616] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/23/2023]
Abstract
There is increasing evidence that endothelin-1 (ET-1) or related peptides play a prognostic value in coronary artery disease (CAD). The objective of this systematic review and meta-analysis was to evaluate the predictive role of ET-1 or related peptides in CAD patients. We comprehensively searched PubMed and Embase databases until January 15, 2023. Studies examining the association of ET-1, big ET-1, or C-terminal proendothelin-1 (CT-proET-1) level with all-cause mortality or major adverse cardiovascular events (MACEs) in CAD patients were included. Fourteen studies with 30,181 patients were identified. Comparison of the top and the lowest ET-1 level, the pooled risk ratio (RR) of all-cause mortality was 3.77 (95% confidence interval [CI] 1.59-8.94) for ET-1 and 1.65 (95% CI 1.25-2.18) for big ET-1. The pooled RR of MACEs was 2.24 (95% CI 1.85-2.72) for ET-1, 1.49 (95% CI 1.10-2.03) for big ET-1, and 3.55 (95% CI 2.12-5.96) for CT-proET-1, respectively. Subgroup analysis indicated that elevated ET-1 level was associated with 2.66-fold and 2.09-fold higher risk of in-hospital/30-day and long-term MACEs. Elevated ET-1, big ET-1, or CT-proET-1 may be independently associated with higher risk of all-cause mortality and MACEs in patients with CAD.
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Affiliation(s)
- Hao Wang
- Department of cardiovascular medicine, Qilu Hospital (Qingdao), Cheeloo College of Medicine, Shandong University, Qingdao, China
| | - Ci Wang
- Department of Senior Cadre Ward, 980 Hospital of PLA Joint Logistics Support Force, Shijiazhuang, China
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Guler A, Turkmen I, Atmaca S, Karakurt H, Kahraman S, Aydin S, Sevinc S, Tukenmez Karakurt S, Turkvatan Cansever A, Erturk M, Babur Guler G. Influence of cardiac biomarkers on predicting significant coronary artery disease in hypertrophic cardiomyopathy patients. Heart Vessels 2023; 38:1329-1336. [PMID: 37414867 DOI: 10.1007/s00380-023-02287-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/27/2023] [Accepted: 06/29/2023] [Indexed: 07/08/2023]
Abstract
BACKGROUND In this study, our aim was to investigate the role of cardiac biomarkers in predicting the presence of significant coronary artery disease in hypertrophic cardiomyopathy (HCM) patients. METHODS The study population was composed of hypertrophic cardiomyopathy patients who underwent coronary angiography at a single center between June 2021 and March 2023, and whose cardiac biomarkers were evaluated before the procedure. HCM patients were screened retrospectively. Significant CAD was defined as > 50% stenosis of the left main coronary artery or > 70% stenosis in a major coronary vessel. Demographic, echocardiographic and cardiac biomarker values were compared between the two groups. RESULTS A total of 123 patients were evaluated. Significant CAD was detected in 39 (31.7%) patients. Patients with significant CAD had higher CK-MB values than those without CAD [2.8 (2.1-4.0) vs. 3.4 (2.8-4.6), p = 0.036], and a higher level of high-sensitivity troponin T (hs-TnT) than those without CAD (24 vs. 17.8, p = 0.022). the NT-proBNP/hs-TnT ratio was found to be significantly lower in patients with CAD than in those with CAD (31.4 vs. 21.4, p = 0.019). In multivariate anaylsis, NT-proBNP/hs-TnT was determined as an independent predictor for significant CAD. In ROC analysis, NT-proBNP/hs-TnT ratio lower than the cut-off value of 30.7 could detect the presence of significant CAD with 76.9% sensitivity and 53.6% specificity (AUC: 0.632, 95% CI: 0.528-0.736, p = 0.019). CONCLUSION To sum up, we suggest that cardiac biomarkers were valuable and simple parameters in terms of significant CAD in HCM patients.
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Affiliation(s)
- Arda Guler
- Department of Cardiology, Mehmet Akif Ersoy Thoracic and Cardiovascular Surgery Training and Research Hospital, University of Health Sciences, Istasyon Mahallesi, Turgut Ozal Bulvarı, No: 11, Küçükçekmece/Istanbul, Turkey.
| | - Irem Turkmen
- Department of Cardiology, Mehmet Akif Ersoy Thoracic and Cardiovascular Surgery Training and Research Hospital, University of Health Sciences, Istasyon Mahallesi, Turgut Ozal Bulvarı, No: 11, Küçükçekmece/Istanbul, Turkey
| | - Sezgin Atmaca
- Department of Cardiology, Mehmet Akif Ersoy Thoracic and Cardiovascular Surgery Training and Research Hospital, University of Health Sciences, Istasyon Mahallesi, Turgut Ozal Bulvarı, No: 11, Küçükçekmece/Istanbul, Turkey
| | - Huseyin Karakurt
- Department of Cardiology, Mehmet Akif Ersoy Thoracic and Cardiovascular Surgery Training and Research Hospital, University of Health Sciences, Istasyon Mahallesi, Turgut Ozal Bulvarı, No: 11, Küçükçekmece/Istanbul, Turkey
| | - Serkan Kahraman
- Department of Cardiology, Mehmet Akif Ersoy Thoracic and Cardiovascular Surgery Training and Research Hospital, University of Health Sciences, Istasyon Mahallesi, Turgut Ozal Bulvarı, No: 11, Küçükçekmece/Istanbul, Turkey
| | - Sinem Aydin
- Department of Radiology, Mehmet Akif Ersoy Thoracic and Cardiovascular Surgery Training and Research Hospital, University of Health Sciences, Istanbul, Turkey
| | - Samet Sevinc
- Department of Cardiology, Mehmet Akif Ersoy Thoracic and Cardiovascular Surgery Training and Research Hospital, University of Health Sciences, Istasyon Mahallesi, Turgut Ozal Bulvarı, No: 11, Küçükçekmece/Istanbul, Turkey
| | - Seda Tukenmez Karakurt
- Department of Cardiology, Mehmet Akif Ersoy Thoracic and Cardiovascular Surgery Training and Research Hospital, University of Health Sciences, Istasyon Mahallesi, Turgut Ozal Bulvarı, No: 11, Küçükçekmece/Istanbul, Turkey
| | - Aysel Turkvatan Cansever
- Department of Radiology, Mehmet Akif Ersoy Thoracic and Cardiovascular Surgery Training and Research Hospital, University of Health Sciences, Istanbul, Turkey
| | - Mehmet Erturk
- Department of Cardiology, Mehmet Akif Ersoy Thoracic and Cardiovascular Surgery Training and Research Hospital, University of Health Sciences, Istasyon Mahallesi, Turgut Ozal Bulvarı, No: 11, Küçükçekmece/Istanbul, Turkey
| | - Gamze Babur Guler
- Department of Cardiology, Mehmet Akif Ersoy Thoracic and Cardiovascular Surgery Training and Research Hospital, University of Health Sciences, Istasyon Mahallesi, Turgut Ozal Bulvarı, No: 11, Küçükçekmece/Istanbul, Turkey
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5
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Yang R, Duan Y, Wang D, Liu Q. Developing a Preliminary Clinical Prediction Model for Prognosis of Pneumonia Complicated with Heart Failure Based on Metagenomic Sequencing. Crit Care Res Pract 2023; 2023:5930742. [PMID: 37497269 PMCID: PMC10368513 DOI: 10.1155/2023/5930742] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/16/2022] [Revised: 01/23/2023] [Accepted: 07/05/2023] [Indexed: 07/28/2023] Open
Abstract
Background The predictive factors of prognosis in patients with pneumonia complicated with heart failure (HF) have not been fully investigated yet, especially with the use of next-generation sequencing (NGS) of metagenome. Methods Patients diagnosed with pneumonia complicated with HF were collected and divided into control group and NGS group. Univariate and multivariate logistic regression and LASSO regression analysis were conducted to screen the predictive factors for the prognosis, followed by nomogram construction, ROC curve plot, and internal validation. Data analysis was conducted in SPSS and R software. Results The NGS of metagenome detected more microbial species. Univariate and multivariate logistic regression and LASSO regression analysis revealed that Enterococcus (χ2 = 7.449, P = 0.006), Hb (Wals = 6.289, P = 0.012), and ProBNP (Wals = 4.037, P = 0.045) were screened out as potential predictive factors for the prognosis. Nomogram was constructed with these 3 parameters, and the performance of nomogram was checked in ROC curves (AUC = 0.772). The specificity and sensitivity of this model were calculated as 0.579 and 0.851, respectively, with the threshold of 0.630 in ROC curve. Further internal verification indicated that the predictive value of our constructed model was efficient. Conclusion This study developed a preliminary clinical prediction model for the prognosis of pneumonia complicated with HF based on NGS of metagenome. More objects will be collected and tested to improve the predictive model in the near future.
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Affiliation(s)
- Rongyuan Yang
- The Second Clinical School of Medicine, Guangzhou University of Chinese Medicine, Guangdong Provincial Hospital of Chinese Medicine-Zhuhai Hospital, Guangzhou, Guangdong 519015, China
| | - Yong Duan
- Department of Cardiovascular Medicine, The Third Hospital of Changsha, Changsha 410000, China
| | - Dawei Wang
- The First Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, Guangdong 510405, China
| | - Qing Liu
- The Second Clinical School of Medicine, Guangzhou University of Chinese Medicine, Guangdong Provincial Hospital of Chinese Medicine-Zhuhai Hospital, Guangzhou, Guangdong 519015, China
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Slieker RC, Donnelly LA, Akalestou E, Lopez-Noriega L, Melhem R, Güneş A, Abou Azar F, Efanov A, Georgiadou E, Muniangi-Muhitu H, Sheikh M, Giordano GN, Åkerlund M, Ahlqvist E, Ali A, Banasik K, Brunak S, Barovic M, Bouland GA, Burdet F, Canouil M, Dragan I, Elders PJM, Fernandez C, Festa A, Fitipaldi H, Froguel P, Gudmundsdottir V, Gudnason V, Gerl MJ, van der Heijden AA, Jennings LL, Hansen MK, Kim M, Leclerc I, Klose C, Kuznetsov D, Mansour Aly D, Mehl F, Marek D, Melander O, Niknejad A, Ottosson F, Pavo I, Duffin K, Syed SK, Shaw JL, Cabrera O, Pullen TJ, Simons K, Solimena M, Suvitaival T, Wretlind A, Rossing P, Lyssenko V, Legido Quigley C, Groop L, Thorens B, Franks PW, Lim GE, Estall J, Ibberson M, Beulens JWJ, 't Hart LM, Pearson ER, Rutter GA. Identification of biomarkers for glycaemic deterioration in type 2 diabetes. Nat Commun 2023; 14:2533. [PMID: 37137910 PMCID: PMC10156700 DOI: 10.1038/s41467-023-38148-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/19/2021] [Accepted: 04/18/2023] [Indexed: 05/05/2023] Open
Abstract
We identify biomarkers for disease progression in three type 2 diabetes cohorts encompassing 2,973 individuals across three molecular classes, metabolites, lipids and proteins. Homocitrulline, isoleucine and 2-aminoadipic acid, eight triacylglycerol species, and lowered sphingomyelin 42:2;2 levels are predictive of faster progression towards insulin requirement. Of ~1,300 proteins examined in two cohorts, levels of GDF15/MIC-1, IL-18Ra, CRELD1, NogoR, FAS, and ENPP7 are associated with faster progression, whilst SMAC/DIABLO, SPOCK1 and HEMK2 predict lower progression rates. In an external replication, proteins and lipids are associated with diabetes incidence and prevalence. NogoR/RTN4R injection improved glucose tolerance in high fat-fed male mice but impaired it in male db/db mice. High NogoR levels led to islet cell apoptosis, and IL-18R antagonised inflammatory IL-18 signalling towards nuclear factor kappa-B in vitro. This comprehensive, multi-disciplinary approach thus identifies biomarkers with potential prognostic utility, provides evidence for possible disease mechanisms, and identifies potential therapeutic avenues to slow diabetes progression.
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Affiliation(s)
- Roderick C Slieker
- Department of Epidemiology and Data Science, Amsterdam Public Health Institute, Amsterdam Cardiovascular Sciences, Amsterdam UMC, location VUMC, Amsterdam, the Netherlands
- Department of Cell and Chemical Biology, Leiden University Medical Center, Leiden, the Netherlands
| | - Louise A Donnelly
- Population Health & Genomics, School of Medicine, University of Dundee, Dundee, UK
| | - Elina Akalestou
- Section of Cell Biology and Functional Genomics, Division of Diabetes, Endocrinology and Metabolism, Department of Metabolism, Digestion and Reproduction, Imperial College London, London, UK
| | - Livia Lopez-Noriega
- Section of Cell Biology and Functional Genomics, Division of Diabetes, Endocrinology and Metabolism, Department of Metabolism, Digestion and Reproduction, Imperial College London, London, UK
| | - Rana Melhem
- CHUM Research Centre and University of Montreal, Montreal, QC, Canada
| | - Ayşim Güneş
- IRCM and University of Montreal, Montreal, QC, Canada
| | | | - Alexander Efanov
- Lilly Research Laboratories, Eli Lilly and Company, Indianapolis, US
| | - Eleni Georgiadou
- Section of Cell Biology and Functional Genomics, Division of Diabetes, Endocrinology and Metabolism, Department of Metabolism, Digestion and Reproduction, Imperial College London, London, UK
| | - Hermine Muniangi-Muhitu
- Section of Cell Biology and Functional Genomics, Division of Diabetes, Endocrinology and Metabolism, Department of Metabolism, Digestion and Reproduction, Imperial College London, London, UK
| | - Mahsa Sheikh
- Section of Cell Biology and Functional Genomics, Division of Diabetes, Endocrinology and Metabolism, Department of Metabolism, Digestion and Reproduction, Imperial College London, London, UK
| | | | - Mikael Åkerlund
- Department of Clinical Sciences, Lund University, Malmö, Sweden
| | - Emma Ahlqvist
- Department of Clinical Sciences, Lund University, Malmö, Sweden
| | - Ashfaq Ali
- Steno Diabetes Center Copenhagen, Gentofte, Denmark
| | - Karina Banasik
- Novo Nordisk Foundation Center for Protein Research, Copenhagen, Denmark
| | - Søren Brunak
- Novo Nordisk Foundation Center for Protein Research, Copenhagen, Denmark
| | - Marko Barovic
- Paul Langerhans Institute Dresden (PLID) of the Helmholtz Center Munich at the University Hospital Carl Gustav Carus and Medical Faculty, Dresden, Germany
| | - Gerard A Bouland
- Department of Cell and Chemical Biology, Leiden University Medical Center, Leiden, the Netherlands
| | - Frédéric Burdet
- Vital-IT Group, SIB Swiss Institute of Bioinformatics, Lausanne, Switzerland
| | - Mickaël Canouil
- INSERM U1283, CNRS UMR 8199, European Genomic Institute for Diabetes (EGID), Institut Pasteur de Lille, University of Lille, Lille University Hospital, Lille, F-59000, France
| | - Iulian Dragan
- Vital-IT Group, SIB Swiss Institute of Bioinformatics, Lausanne, Switzerland
| | - Petra J M Elders
- Department of General Practice and Elderly Care Medicine, Amsterdam Public Health Research Institute, Amsterdam UMC-location VUmc, Amsterdam, the Netherlands
| | | | - Andreas Festa
- Eli Lilly Regional Operations GmbH, Vienna, Austria
- 1st Medical Department, LK Stockerau, Niederösterreich, Austria
| | - Hugo Fitipaldi
- Department of Clinical Sciences, Lund University, Malmö, Sweden
| | - Phillippe Froguel
- INSERM U1283, CNRS UMR 8199, European Genomic Institute for Diabetes (EGID), Institut Pasteur de Lille, University of Lille, Lille University Hospital, Lille, F-59000, France
- Division of Systems Biology, Department of Diabetes, Endocrinology and Metabolism, Imperial College London, London, UK
| | - Valborg Gudmundsdottir
- Faculty of Medicine, University of Iceland, Reykjavik, Iceland
- Icelandic Heart Association, Kopavogur, Iceland
| | - Vilmundur Gudnason
- Faculty of Medicine, University of Iceland, Reykjavik, Iceland
- Icelandic Heart Association, Kopavogur, Iceland
| | | | - Amber A van der Heijden
- Department of General Practice and Elderly Care Medicine, Amsterdam Public Health Research Institute, Amsterdam UMC-location VUmc, Amsterdam, the Netherlands
| | - Lori L Jennings
- Novartis Institutes for Biomedical Research, Cambridge, MA, 02139, USA
| | - Michael K Hansen
- Cardiovascular and Metabolic Disease Research, Janssen Research & Development, Spring House, PA, USA
| | - Min Kim
- Steno Diabetes Center Copenhagen, Gentofte, Denmark
- Institute of Pharmaceutical Science, Faculty of Life Sciences and Medicines, King's College London, London, UK
| | - Isabelle Leclerc
- Section of Cell Biology and Functional Genomics, Division of Diabetes, Endocrinology and Metabolism, Department of Metabolism, Digestion and Reproduction, Imperial College London, London, UK
- CHUM Research Centre and University of Montreal, Montreal, QC, Canada
| | | | - Dmitry Kuznetsov
- Vital-IT Group, SIB Swiss Institute of Bioinformatics, Lausanne, Switzerland
| | | | - Florence Mehl
- Vital-IT Group, SIB Swiss Institute of Bioinformatics, Lausanne, Switzerland
| | - Diana Marek
- Vital-IT Group, SIB Swiss Institute of Bioinformatics, Lausanne, Switzerland
| | - Olle Melander
- Department of Clinical Sciences, Lund University, Malmö, Sweden
| | - Anne Niknejad
- Vital-IT Group, SIB Swiss Institute of Bioinformatics, Lausanne, Switzerland
| | - Filip Ottosson
- Department of Clinical Sciences, Lund University, Malmö, Sweden
- Section for Clinical Mass Spectrometry, Danish Center for Neonatal Screening, Department of Congenital Disorders, Statens Serum Institut, Copenhagen, Denmark
| | - Imre Pavo
- Eli Lilly Regional Operations GmbH, Vienna, Austria
| | - Kevin Duffin
- Lilly Research Laboratories, Eli Lilly and Company, Indianapolis, US
| | - Samreen K Syed
- Lilly Research Laboratories, Eli Lilly and Company, Indianapolis, US
| | - Janice L Shaw
- Lilly Research Laboratories, Eli Lilly and Company, Indianapolis, US
| | - Over Cabrera
- Lilly Research Laboratories, Eli Lilly and Company, Indianapolis, US
| | - Timothy J Pullen
- Section of Cell Biology and Functional Genomics, Division of Diabetes, Endocrinology and Metabolism, Department of Metabolism, Digestion and Reproduction, Imperial College London, London, UK
- Department of Diabetes, Guy's Campus King's College London, London, UK
| | | | - Michele Solimena
- Paul Langerhans Institute Dresden (PLID) of the Helmholtz Center Munich at the University Hospital Carl Gustav Carus and Medical Faculty, Dresden, Germany
- Molecular Diabetology, University Hospital and Medical Faculty Carl Gustav Carus, TU Dresden, Dresden, Germany
| | | | | | - Peter Rossing
- Steno Diabetes Center Copenhagen, Gentofte, Denmark
- Department of Clinical Medicine, University of Copenhagen, Copenhagen, Denmark
| | - Valeriya Lyssenko
- Department of Clinical Science, Center for Diabetes Research, University of Bergen, Bergen, Norway
- Genomics, Diabetes and Endocrinology Unit, Department of Clinical Sciences Malmö, Lund University Diabetes Centre, Skåne University Hospital, Malmö, Sweden
| | - Cristina Legido Quigley
- Steno Diabetes Center Copenhagen, Gentofte, Denmark
- Institute of Pharmaceutical Science, Faculty of Life Sciences and Medicines, King's College London, London, UK
| | - Leif Groop
- Department of Clinical Sciences, Lund University, Malmö, Sweden
- Finnish Institute of Molecular Medicine, Helsinki University, Helsinki, Finland
| | - Bernard Thorens
- Center for Integrative Genomics, University of Lausanne, CH-1015, Lausanne, Switzerland
| | - Paul W Franks
- Department of Clinical Sciences, Lund University, Malmö, Sweden
- Department of Nutrition, Harvard School of Public Health, Boston, MA, USA
| | - Gareth E Lim
- CHUM Research Centre and University of Montreal, Montreal, QC, Canada
| | | | - Mark Ibberson
- Vital-IT Group, SIB Swiss Institute of Bioinformatics, Lausanne, Switzerland
| | - Joline W J Beulens
- Department of Epidemiology and Data Science, Amsterdam Public Health Institute, Amsterdam Cardiovascular Sciences, Amsterdam UMC, location VUMC, Amsterdam, the Netherlands
- Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht, the Netherlands
| | - Leen M 't Hart
- Department of Epidemiology and Data Science, Amsterdam Public Health Institute, Amsterdam Cardiovascular Sciences, Amsterdam UMC, location VUMC, Amsterdam, the Netherlands.
- Department of Cell and Chemical Biology, Leiden University Medical Center, Leiden, the Netherlands.
- Department of Biomedical Data Sciences, Section Molecular Epidemiology, Leiden University Medical Center, Leiden, the Netherlands.
| | - Ewan R Pearson
- Population Health & Genomics, School of Medicine, University of Dundee, Dundee, UK.
| | - Guy A Rutter
- Section of Cell Biology and Functional Genomics, Division of Diabetes, Endocrinology and Metabolism, Department of Metabolism, Digestion and Reproduction, Imperial College London, London, UK.
- CHUM Research Centre and University of Montreal, Montreal, QC, Canada.
- Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore, Singapore.
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7
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Zhang P, Ge X, Li Z, Nie M, Yu J, Ou W, Wu K, Li J, Wang L, Ni W, Shi Z, Song J, Li S, Dai C. The proGnostic role of caRdiac rehAbilitation in patients with left ventriCular anEurysm formation after anterior myocardial infarction (the GRACE study): Study rationale and design of a prospective randomized controlled trial. Front Cardiovasc Med 2023; 9:991521. [PMID: 36704464 PMCID: PMC9871449 DOI: 10.3389/fcvm.2022.991521] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/11/2022] [Accepted: 12/28/2022] [Indexed: 01/11/2023] Open
Abstract
Background Cardiac rehabilitation (CR) is an essential intervention after acute myocardial infarction (MI). However, it is still unclear whether patients with left ventricular aneurysm (LVA) formation after anterior MI would benefit from CR programs. This clinical trial is designed to assess the role of CR in patients with LVA formation after anterior MI. Trial design The GRACE study is a single-center, single-blind, prospective, randomized controlled clinical trial in China. 100 subjects aged 18-75 years with LVA formation after anterior MI will be recruited and randomized 1:1 to the CR or control group. Both groups will receive standard drug treatment and routine health education according to the guidelines. Participants in the CR group will additionally receive tailored CR programs delivered over a period of 36 sessions. These participants will then be followed up for 1-year. The primary outcome is peak oxygen uptake measured by cardiopulmonary exercise testing after CR programs. The secondary outcomes are cardiac function and EuroQol 5-Dimension-3 Level index scores after CR program and 1-year and major adverse cardiac cerebrovascular events, a composite of cardiovascular mortality, non-fatal MI, non-fatal stroke, malignant arrhythmia or hospitalization for heart failure during the follow-up period. Conclusions This single-center, single-blind, prospective, randomized controlled clinical trial will determine whether CR improves physical capacity and clinical outcomes in patients with LVA formation after anterior MI. Trial registration Chinese Clinical Trial Registry ChiCTR2200058852. Registered on 18 April 2022.
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Affiliation(s)
- Peng Zhang
- Department of Cardiology, Xiamen Cardiovascular Hospital of Xiamen University, School of Medicine, Xiamen University, Xiamen, China,Xiamen Key Laboratory of Cardiovascular Disease, Xiamen Cardiovascular Hospital of Xiamen University, School of Medicine, Xiamen University, Xiamen, China
| | - Xiaofeng Ge
- Department of Cardiology, Xiamen Cardiovascular Hospital of Xiamen University, School of Medicine, Xiamen University, Xiamen, China,Xiamen Key Laboratory of Cardiovascular Disease, Xiamen Cardiovascular Hospital of Xiamen University, School of Medicine, Xiamen University, Xiamen, China
| | - Zhaokai Li
- Department of Cardiology, Xiamen Cardiovascular Hospital of Xiamen University, School of Medicine, Xiamen University, Xiamen, China,Xiamen Key Laboratory of Cardiovascular Disease, Xiamen Cardiovascular Hospital of Xiamen University, School of Medicine, Xiamen University, Xiamen, China
| | - Meiling Nie
- Department of Cardiology, Xiamen Cardiovascular Hospital of Xiamen University, School of Medicine, Xiamen University, Xiamen, China,Xiamen Key Laboratory of Cardiovascular Disease, Xiamen Cardiovascular Hospital of Xiamen University, School of Medicine, Xiamen University, Xiamen, China
| | - Jing Yu
- Department of Cardiology, Xiamen Cardiovascular Hospital of Xiamen University, School of Medicine, Xiamen University, Xiamen, China,Xiamen Key Laboratory of Cardiovascular Disease, Xiamen Cardiovascular Hospital of Xiamen University, School of Medicine, Xiamen University, Xiamen, China
| | - Weimei Ou
- Department of Cardiology, Xiamen Cardiovascular Hospital of Xiamen University, School of Medicine, Xiamen University, Xiamen, China,Xiamen Key Laboratory of Cardiovascular Disease, Xiamen Cardiovascular Hospital of Xiamen University, School of Medicine, Xiamen University, Xiamen, China
| | - Kaimin Wu
- Department of Cardiology, Xiamen Cardiovascular Hospital of Xiamen University, School of Medicine, Xiamen University, Xiamen, China,Xiamen Key Laboratory of Cardiovascular Disease, Xiamen Cardiovascular Hospital of Xiamen University, School of Medicine, Xiamen University, Xiamen, China
| | - Jiahua Li
- Department of Cardiology, Xiamen Cardiovascular Hospital of Xiamen University, School of Medicine, Xiamen University, Xiamen, China
| | - Lin Wang
- Department of Cardiology, Xiamen Cardiovascular Hospital of Xiamen University, School of Medicine, Xiamen University, Xiamen, China,Xiamen Key Laboratory of Cardiovascular Disease, Xiamen Cardiovascular Hospital of Xiamen University, School of Medicine, Xiamen University, Xiamen, China
| | - Wei Ni
- Department of Cardiology, Xiamen Cardiovascular Hospital of Xiamen University, School of Medicine, Xiamen University, Xiamen, China,Xiamen Key Laboratory of Cardiovascular Disease, Xiamen Cardiovascular Hospital of Xiamen University, School of Medicine, Xiamen University, Xiamen, China
| | - Zaixing Shi
- Key Laboratory of Health Technology Assessment of Fujian Province, School of Public Health, Xiamen University, Xiamen, China
| | - Juan Song
- Department of Cardiology, Xiamen Cardiovascular Hospital of Xiamen University, School of Medicine, Xiamen University, Xiamen, China,Xiamen Key Laboratory of Cardiovascular Disease, Xiamen Cardiovascular Hospital of Xiamen University, School of Medicine, Xiamen University, Xiamen, China,*Correspondence: Juan Song ✉
| | - Suiji Li
- Department of Cardiology, Xiamen Cardiovascular Hospital of Xiamen University, School of Medicine, Xiamen University, Xiamen, China,Xiamen Key Laboratory of Cardiovascular Disease, Xiamen Cardiovascular Hospital of Xiamen University, School of Medicine, Xiamen University, Xiamen, China,Suiji Li ✉
| | - Cuilian Dai
- Department of Cardiology, Xiamen Cardiovascular Hospital of Xiamen University, School of Medicine, Xiamen University, Xiamen, China,Xiamen Key Laboratory of Cardiovascular Disease, Xiamen Cardiovascular Hospital of Xiamen University, School of Medicine, Xiamen University, Xiamen, China,Cuilian Dai ✉
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Serafimov A, Donevski D, Karakolevska Ilova M, Joveva E, Todosieva Serafimova K, Kedev S, Vavlukis M. Incremental Value of Cardiac Biomarkers in Mid-term Prognosis of Patients with Acute Coronary Syndrome. Open Access Maced J Med Sci 2022. [DOI: 10.3889/oamjms.2022.7978] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/05/2022] Open
Abstract
Background: Given the number of prognostic studies, both short- and long-termed, in patients with myocardial infarction (MI), the data on predicting major adverse cardiac events (MACE) following discharge still remains limited. Aim: to identify early predictors of MACE in MI patients, that underwent Primary Percutaneous Coronary Intervention (pPCI), with special emphasis on multiple cardiac biomarkers. Materials and methods: we analysed clinical, LV functional, angiographic variables, as well cardiac troponin, a marker of myocardial necrosis, natriuretic peptide (NT-proBNP), a marker of myocardial stress, and white blood cells (WBC), as a marker of inflammation. The study population were 150 consecutive patients treated for acute myocardial infarction. Results: The average follow-up period was 31 months. In total, 26 patients suffered from at least one MACE. Multivariate logistic regression analysis identified several independent predictors: NT-proBNP (p=0,07), number of diseased vessels (p=0,027), and need for loop diuretic therapy (p=0,050). ROC curve demonstrated excellent discriminatory function for MACE of NT-proBNP and WBC (area under the curve .640, and .658, p=0.025 and 0.011 respectively). Conclusion: The combination of biomarkers for myocardial stress and inflammation improves the prediction of major adverse cardiac events in MI survivors.
Keywords: myocardial infarction, cardiac biomarkers, cardiac troponin, natriuretic peptide, prognosis, major adverse cardiac events (MACE), cardiac death
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