Single and multiple cardiovascular biomarkers in subjects without a previous cardiovascular event
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Deepak L. Bhatt | T. Biering-Sørensen | P. Nilsson | M. Vaduganathan | M. Magnusson | M. Olsen | M. Pareek | A. Diederichsen | J. Møller | P. Hindersson | M. Leósdóttir | A. Qamar | Arman Qamar
[1] Deepak L. Bhatt,et al. Prognostic implications of fasting plasma glucose in subjects with echocardiographic abnormalities. , 2017, International journal of cardiology.
[2] T. Aye,et al. Risk stratification in stable coronary artery disease , 2017 .
[3] C. Cannon,et al. Biomarkers and Coronary Lesions Predict Outcomes after Revascularization in Non-ST-Elevation Acute Coronary Syndrome. , 2017, Clinical chemistry.
[4] L. Wallentin,et al. Growth Differentiation Factor 15 as a Biomarker in Cardiovascular Disease. , 2017, Clinical chemistry.
[5] C. Held,et al. Growth Differentiation Factor 15 Predicts All-Cause Morbidity and Mortality in Stable Coronary Heart Disease. , 2017, Clinical chemistry.
[6] Deepak L. Bhatt,et al. Prognostic Implications of Biomarker Assessments in Patients With Type 2 Diabetes at High Cardiovascular Risk: A Secondary Analysis of a Randomized Clinical Trial. , 2016, JAMA cardiology.
[7] E. Antman,et al. Cardiovascular Biomarker Score and Clinical Outcomes in Patients With Atrial Fibrillation: A Subanalysis of the ENGAGE AF-TIMI 48 Randomized Clinical Trial. , 2016, JAMA cardiology.
[8] J. Coresh,et al. 60 A comparison of HFrEF vs HFpEF’s clinical workload and cost in the first year following hospitalisation and enrollment in a disease management program , 2016, Journal of the American College of Cardiology.
[9] Deepak L. Bhatt. Troponin and the J-Curve of Diastolic Blood Pressure: When Lower Is Not Better. , 2016, Journal of the American College of Cardiology.
[10] J. Danesh,et al. Natriuretic peptides and integrated risk assessment for cardiovascular disease: an individual-participant-data meta-analysis , 2016 .
[11] Daniel F. Freitag,et al. Natriuretic peptides and integrated risk assessment for cardiovascular disease: an individual-participant-data meta-analysis , 2016, The lancet. Diabetes & endocrinology.
[12] A. Hsu,et al. Intestinal Microbial Metabolites Are Linked to Severity of Myocardial Infarction in Rats , 2016, PloS one.
[13] S. Solomon,et al. Six-Year Change in High-Sensitivity Cardiac Troponin T and Risk of Subsequent Coronary Heart Disease, Heart Failure, and Death. , 2016, JAMA cardiology.
[14] R. Prager,et al. Targeted multiple biomarker approach in predicting cardiovascular events in patients with diabetes , 2016, Heart.
[15] Deepak L. Bhatt,et al. Adaptive Designs for Clinical Trials. , 2016, The New England journal of medicine.
[16] G. Collins,et al. Prediction models for cardiovascular disease risk in the general population: systematic review , 2016, British Medical Journal.
[17] A. Peters,et al. Troponin I and cardiovascular risk prediction in the general population: the BiomarCaRE consortium , 2016, European heart journal.
[18] M. Sabatine,et al. Multimarker Risk Stratification in Patients With Acute Myocardial Infarction , 2016, Journal of the American Heart Association.
[19] E. Hagström,et al. Growth differentiation factor-15 level predicts major bleeding and cardiovascular events in patients with acute coronary syndromes: results from the PLATO study. , 2016, European heart journal.
[20] A. Low,et al. Growth differentiation factor 15 in heart failure with preserved vs. reduced ejection fraction , 2016, European journal of heart failure.
[21] P. Nilsson,et al. Untreated diabetes mellitus, but not impaired fasting glucose, is associated with increased left ventricular mass and concentric hypertrophy in an elderly, healthy, Swedish population , 2015 .
[22] A. Gavazzi,et al. Role of biomarkers in cardiac structure phenotyping in heart failure with preserved ejection fraction: critical appraisal and practical use , 2015, European journal of heart failure.
[23] Deepak L. Bhatt,et al. Troponin and Cardiac Events in Stable Ischemic Heart Disease and Diabetes. , 2015, The New England journal of medicine.
[24] P. Nilsson,et al. Worsening diastolic function is associated with elevated fasting plasma glucose and increased left ventricular mass in a supra-additive fashion in an elderly, healthy, Swedish population. , 2015, International journal of cardiology.
[25] Victor Mor-Avi,et al. Recommendations for cardiac chamber quantification by echocardiography in adults: an update from the American Society of Echocardiography and the European Association of Cardiovascular Imaging. , 2015, European heart journal cardiovascular Imaging.
[26] Jennifer G. Robinson,et al. 2013 ACC/AHA Guideline on the Assessment of Cardiovascular Risk: A Report of the American College of Cardiology/American Heart Association Task Force on Practice Guidelines , 2014, Circulation.
[27] J. Mariani,et al. Evaluating the Utility of Circulating Biomarkers of Collagen Synthesis in Hypertrophic Cardiomyopathy , 2014, Circulation. Heart failure.
[28] D. DeMets,et al. Management of patients with atrial fibrillation (compilation of 2006 ACCF/AHA/ESC and 2011 ACCF/AHA/HRS recommendations): a report of the American College of Cardiology/American Heart Association Task Force on practice guidelines. , 2013, Circulation.
[29] E. Falk,et al. Traditional SCORE-based health check fails to identify individuals who develop acute myocardial infarction. , 2013, Danish medical journal.
[30] J. Ioannidis,et al. Bias in associations of emerging biomarkers with cardiovascular disease. , 2013, JAMA internal medicine.
[31] C. Ayers,et al. Biomarkers of chronic cardiac injury and hemodynamic stress identify a malignant phenotype of left ventricular hypertrophy in the general population. , 2013, Journal of the American College of Cardiology.
[32] D. Goff,et al. Comparison of novel risk markers for improvement in cardiovascular risk assessment in intermediate-risk individuals. , 2012, JAMA.
[33] V. Salomaa,et al. A multiple biomarker risk score for guiding clinical decisions using a decision curve approach , 2012, European journal of preventive cardiology.
[34] J. Ioannidis,et al. Minimal and null predictive effects for the most popular blood biomarkers of cardiovascular disease. , 2012, Circulation research.
[35] J. Ludvigsson,et al. External review and validation of the Swedish national inpatient register , 2011, BMC public health.
[36] E. Barrett-Connor,et al. Growth-Differentiation Factor-15 Is a Robust, Independent Predictor of 11-Year Mortality Risk in Community-Dwelling Older Adults: The Rancho Bernardo Study , 2011, Circulation.
[37] Ruth M. Pfeiffer,et al. The impact of sample storage time on estimates of association in biomarker discovery studies , 2011, Journal of Clinical Bioinformatics.
[38] Ewout W Steyerberg,et al. Extensions of net reclassification improvement calculations to measure usefulness of new biomarkers , 2011, Statistics in medicine.
[39] D. Lloyd‐Jones,et al. Risk Prediction in Cardiovascular Medicine Cardiovascular Risk Prediction Basic Concepts, Current Status, and Future Directions , 2010 .
[40] V. Gudnason,et al. Myocardial structure and function by echocardiography in relation to glucometabolic status in elderly subjects from 2 population-based cohorts: a cross-sectional study. , 2010, American heart journal.
[41] Paul M Ridker,et al. Inflammation in atherosclerosis: from pathophysiology to practice. , 2009, Journal of the American College of Cardiology.
[42] L. Lind,et al. Growth-differentiation factor-15 is an independent marker of cardiovascular dysfunction and disease in the elderly: results from the Prospective Investigation of the Vasculature in Uppsala Seniors (PIVUS) Study. , 2009, European heart journal.
[43] M. Pencina,et al. Novel and conventional biomarkers for prediction of incident cardiovascular events in the community. , 2009, JAMA.
[44] G. Boysen,et al. European Guidelines on Cardiovascular Disease Prevention , 2009, International journal of stroke : official journal of the International Stroke Society.
[45] Arturo Evangelista,et al. Recommendations for the evaluation of left ventricular diastolic function by echocardiography. , 2009, Journal of the American Society of Echocardiography : official publication of the American Society of Echocardiography.
[46] J. Sundström,et al. Use of multiple biomarkers to improve the prediction of death from cardiovascular causes , 2008 .
[47] T. Hansen,et al. N-terminal pro-brain natriuretic peptide, but not high sensitivity C-reactive protein, improves cardiovascular risk prediction in the general population. , 2007, European heart journal.
[48] K. Bibbins-Domingo,et al. N-terminal fragment of the prohormone brain-type natriuretic peptide (NT-proBNP), cardiovascular events, and mortality in patients with stable coronary heart disease. , 2007, JAMA.
[49] D. Levy,et al. Multiple biomarkers for the prediction of first major cardiovascular events and death. , 2006, The New England journal of medicine.
[50] H. Tunstall-Pedoe,et al. Estimation of ten-year risk of fatal cardiovascular disease in Europe: the SCORE project. , 2003, European heart journal.
[51] D. Levy,et al. Prediction of coronary heart disease using risk factor categories. , 1998, Circulation.
[52] Pickering,et al. Relation of arterial pressure level and variability to left ventricular geometry in normotensive and hypertensive adults. , 1996, Blood pressure monitoring.
[53] Ørnulf Borgan,et al. A method for checking regression models in survival analysis based on the risk score , 1996, Lifetime data analysis.
[54] F. Harrell,et al. Evaluating the yield of medical tests. , 1982, JAMA.