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21 results on '"Rhyne, Rhonda F."'

2. Gaining Efficiency in Clinical Trials With Cardiac Biomarkers: JACC Review Topic of the Week

Author

Januzzi, James L., Jr., Canty, John M., Das, Saumya, DeFilippi, Christopher R., Gintant, Gary A., Gutstein, David E., Jaffe, Allan, Kaushik, Emily P., Leptak, Christopher, Mehta, Cyrus, Pina, Ileana, Povsic, Thomas J., Rambaran, Curtis, Rhyne, Rhonda F., Salas, Maribel, Shi, Victor C., Udell, Jacob A., Unger, Ellis F., Zabka, Tanja S., and Seltzer, Jonathan H.

Published
2021
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5. Usefulness of Multiple Biomarkers for Predicting Incident Major Adverse Cardiac Events in Patients Who Underwent Diagnostic Coronary Angiography (from the Catheter Sampled Blood Archive in Cardiovascular Diseases [CASABLANCA] Study)

Author

McCarthy, Cian P., van Kimmenade, Roland R.J., Gaggin, Hanna K., Simon, Mandy L., Ibrahim, Nasrien E., Gandhi, Parul, Kelly, Noreen, Motiwala, Shweta R., Belcher, Arianna M., Harisiades, Jamie, Magaret, Craig A., Rhyne, Rhonda F., and Januzzi, James L., Jr.

Published
2017
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7. Abstract 18948: A Clinical and Biomarker Scoring System to Predict the Presence of Obstructive Peripheral Artery Disease: Results From the Catheter Sampled Blood Archive in Cardiovascular Diseases (CASABLANCA) Study

Author

McCarthy, Cian P, Ibrahim, Nasrien E, van Kimmenade, Roland R, Gaggin, Hanna K, Simon, Mandy L, Gandhi, Parul, Kelly, Noreen, Motiwala, Shweta R, Harisiades, Jamie, Mukai, Renata, Magaret, Craig A, Barnes, Grady, Rhyne, Rhonda F, Garasic, Joseph M, and Januzzi, James L, Jr

Published
2017

8. Abstract 10637: A Pooled Multi-National Validation Study of a Machine Learning, High-Sensitivity Troponin-Based Multi-Proteomic Model to Predict the Presence of Obstructive Coronary Artery Disease as Compared to High Sensitivity Troponin Alone in a Subset of Patients with Diabetes

Author

Gattani, Raghav, primary, Ekanem, Emmanuel, additional, Ofosu-Somuah, Araba, additional, Neumann, Johannes T, additional, McCarthy, Cian, additional, Shah, Palak, additional, Magaret, Craig, additional, Rhyne, Rhonda F, additional, Barnes, Grady, additional, Peters, Celine, additional, Westermann, Dirk, additional, Defilippi, Christopher, additional, and Januzzi, James L, additional

Published
2021
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9. Derivation and External Validation of a High‐Sensitivity Cardiac Troponin–Based Proteomic Model to Predict the Presence of Obstructive Coronary Artery Disease

Author

McCarthy, Cian P., primary, Neumann, Johannes T., additional, Michelhaugh, Sam A., additional, Ibrahim, Nasrien E., additional, Gaggin, Hanna K., additional, Sörensen, Nils A., additional, Schäefer, Sarina, additional, Zeller, Tanja, additional, Magaret, Craig A., additional, Barnes, Grady, additional, Rhyne, Rhonda F., additional, Westermann, Dirk, additional, and Januzzi, James L., additional

Published
2020
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10. Application of a machine learning-driven, multibiomarker panel for prediction of incident cardiovascular events in patients with suspected myocardial infarction

Author

Neumann, Johannes T, primary, Sörensen, Nils A, additional, Zeller, Tanja, additional, Magaret, Craig A, additional, Barnes, Grady, additional, Rhyne, Rhonda F, additional, Peters, Celine, additional, Goßling, Alina, additional, Hartikainen, Tau S, additional, Haller, Paul M, additional, Lehmacher, Jonas, additional, Schäfer, Sarina, additional, Januzzi, James L, additional, and Westermann, Dirk, additional

Published
2020
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11. 543-P: A Clinical, Proteomics and Artificial Intelligence-Driven Model to Predict Acute Kidney Injury in Diabetic Patients Undergoing Coronary Angiography—Results from the Catheter Sampled Blood Archive in Cardiovascular Diseases Study

Author

IBRAHIM, NASRIEN E., primary, MCCARTHY, CIAN P., additional, SHRESTHA, SHREYA, additional, GAGGIN, HANNA, additional, MUKAI, RENATA, additional, MAGARET, CRAIG A., additional, RHYNE, RHONDA F., additional, and JANUZZI, JAMES, additional

Published
2019
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15. Performance of Clinical/Proteomic Biomarker Panels to Predict Coronary Artery Disease Presence or Cardiovascular Prognosis in Patients With and Without Diabetes Mellitus

Author

SHRESTHA, SHREYA, primary, MCCARTHY, CIAN P., additional, IBRAHIM, NASRIEN E., additional, KIMMENADE, ROLAND VAN, additional, GAGGIN, HANNA, additional, MUKAI, RENATA, additional, MAGARET, CRAIG A., additional, BARNES, GRADY, additional, RHYNE, RHONDA F., additional, and JANUZZI, JAMES, additional

Published
2018
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16. A clinical and proteomics approach to predict the presence of obstructive peripheral arterial disease: From the Catheter Sampled Blood Archive in Cardiovascular Diseases (CASABLANCA) Study

Author

McCarthy, Cian P., primary, Ibrahim, Nasrien E., additional, van Kimmenade, Roland R.J., additional, Gaggin, Hanna K., additional, Simon, Mandy L., additional, Gandhi, Parul, additional, Kelly, Noreen, additional, Motiwala, Shweta R., additional, Mukai, Renata, additional, Magaret, Craig A., additional, Barnes, Grady, additional, Rhyne, Rhonda F., additional, Garasic, Joseph M., additional, and Januzzi, James L., additional

Published
2018
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17. A Clinical and Biomarker Scoring System to Predict the Presence of Obstructive Coronary Artery Disease

Author

Ibrahim, Nasrien E., primary, Januzzi, James L., additional, Magaret, Craig A., additional, Gaggin, Hanna K., additional, Rhyne, Rhonda F., additional, Gandhi, Parul U., additional, Kelly, Noreen, additional, Simon, Mandy L., additional, Motiwala, Shweta R., additional, Belcher, Arianna M., additional, and van Kimmenade, Roland R.J., additional

Published
2017
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19. Abstract 12850: Derivation and External Validation of a High Sensitivity Troponin Based Proteomic Model to Predict the Presence of Obstructive Coronary Artery Disease

Author

McCarthy, Cian P, Neumann, Johannes T, Michelhaugh, Sam A, Ibrahim, Nasrien E, Gaggin, Hanna K, S?rensen, Nils A, Magaret, Craig A, Barnes, Grady, Rhyne, Rhonda F, Westermann, Dirk, and Januzzi, James L

Abstract

Introduction:Current non-invasive modalities utilized to diagnose obstructive coronary artery disease (CAD) are limited by variable sensitivity and specificity, the need for ionizing radiation or contrast, and cost. Concentrations of high sensitivity cardiac troponin (hs-cTn) are associated with presence of obstructive CAD but are poorly specific.Hypothesis:A combination of clinical risk factors and biomarkers may offer an attractive alternative diagnostic strategy for obstructive CAD.Methods:In a derivation cohort of 636 patients referred for coronary angiography, predictors of ?70% stenosis in at least 1 major coronary vessel were identified from six clinical variables and 109 biomarkers. The final model was first internally validated on a separate cohort (n=275) and then externally validated on a cohort of 241 patients presenting to the ED with suspicion for acute MI where ? 50% stenosis in at least one coronary artery was considered significant.Results:The resulting model (HART CADhs) consisted of three clinical variables (male sex, age, and previous percutaneous coronary intervention) and 3 biomarkers (hs-cTnI, adiponectin, and kidney injury molecule-1). In the internal validation cohort, the system had an area under the receiver-operating characteristic curve (AUC) of 0.85 for coronary stenosis ?70% (p<0.001). At the optimal cut-off, the score had 80% sensitivity, 71% specificity, a PPV of 83% and NPV of 66% for ?70% stenosis. Partitioning the model result into 5 levels resulted in a PPV of 97% and NPV of 89% at the highest and lowest levels respectively. In the external validation cohort, the score performed similarly well for predicting ?50% stenosis with an AUC of 0.86 (p<0.001), sensitivity of 78%, specificity of 79%, PPV of 95%, and NPV of 43% at the optimal cut-off. In patients who neither ruled in or ruled out for acute MI (indeterminate zone patients, N=69), the score had an AUC of 0.88 (p<0.001), sensitivity of 82%, specificity of 71%, PPV of 92% and NPV of 50% for at least ?50% stenosis.Conclusion:We have derived and externally-validated a model including hs-cTnI that can predict the presence of obstructive CAD with high accuracy.

Published
2019
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21. Multiple Biomarkers to Predict Major Adverse Cardiovascular Events in Patients With Coronary Chronic Total Occlusions.

Author

Adusumalli S, Mohebi R, McCarthy CP, Megaret CA, Rhyne RF, Jaffer FA, and Januzzi JL

Abstract

Background: There are limited tools available to predict the long-term prognosis of persons with coronary chronic total occlusions (CTO)., Objectives: We evaluated performance of a blood biomarker panel to predict cardiovascular (CV) events in patients with CTO., Methods: From 1251 patients in the CASABLANCA study, 241 participants with a CTO were followed for an average of 4 years for occurrence of major adverse CV events (MACE, CV death, non-fatal myocardial infarction or stroke) and CV death/heart failure (HF) hospitalization. Results of a biomarker panel (kidney injury molecule-1, N-terminal pro-B-type natriuretic peptide, osteopontin, and tissue inhibitor of metalloproteinase-1) from baseline samples were expressed as low-, moderate-, and high-risk., Results: By 4 years, a total of 67 (27.8%) MACE events and 56 (23.2%) CV death/HF hospitalization events occurred. The C-statistic of the panel for MACE through 4 years was 0.79. Considering patients in the low-risk group as a reference, the hazard ratio of MACE by 4 years was 6.65 (95% confidence interval [CI]: 2.98-14.8) and 12.4 (95% CI:5.17-29.6) for the moderate and high-risk groups (both P <0.001). The C-statistic for CVD/HF hospitalization by 4 years was 0.84. Compared to the low-risk score group, the moderate and high-risk groups had hazard ratios of 5.61 (95% CI: 2.33-13.5) and 15.6 (95% CI: 6.18, 39.2; both P value <0.001)., Conclusion: A multiple biomarker panel assists in evaluating the risk of adverse outcomes in patients with coronary CTO. These results may have implications for patient care and could have a role for clinical trial enrichment., Clinical Trial: CASABLANCA, ClinicalTrials.gov Identifier: NCT00842868.

Published
2023
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