Literature DB >> 31467464

Cardiac ScoreCard: A Diagnostic Multivariate Index Assay System for Predicting a Spectrum of Cardiovascular Disease.

Michael P McRae1, Biykem Bozkurt2,3, Christie M Ballantyne3, Ximena Sanchez1,4, Nicolaos Christodoulides1,4, Glennon Simmons1,4, Vijay Nambi2,3, Arunima Misra5, Craig S Miller6, Jeffrey L Ebersole6, Charles Campbell7, John T McDevitt1,4.   

Abstract

Clinical decision support systems (CDSSs) have the potential to save lives and reduce unnecessary costs through early detection and frequent monitoring of both traditional risk factors and novel biomarkers for cardiovascular disease (CVD). However, the widespread adoption of CDSSs for the identification of heart diseases has been limited, likely due to the poor interpretability of clinically relevant results and the lack of seamless integration between measurements and disease predictions. In this paper we present the Cardiac ScoreCard-a multivariate index assay system with the potential to assist in the diagnosis and prognosis of a spectrum of CVD. The Cardiac ScoreCard system is based on lasso logistic regression techniques which utilize both patient demographics and novel biomarker data for the prediction of heart failure (HF) and cardiac wellness. Lasso logistic regression models were trained on a merged clinical dataset comprising 579 patients with 6 traditional risk factors and 14 biomarker measurements. The prediction performance of the Cardiac ScoreCard was assessed with 5-fold cross-validation and compared with reference methods. The experimental results reveal that the ScoreCard models improved performance in discriminating disease versus non-case (AUC = 0.8403 and 0.9412 for cardiac wellness and HF, respectively), and the models exhibit good calibration. Clinical insights to the prediction of HF and cardiac wellness are provided in the form of logistic regression coefficients which suggest that augmenting the traditional risk factors with a multimarker panel spanning a diverse cardiovascular pathophysiology provides improved performance over reference methods. Additionally, a framework is provided for seamless integration with biomarker measurements from point-of-care medical microdevices, and a lasso-based feature selection process is described for the down-selection of biomarkers in multimarker panels.

Entities:  

Keywords:  Cardiovascular disease (CVD); biomarkers; cardiac wellness; heart failure (HF); lasso logistic regression; programmable bio-nano-chip (p-BNC)

Year:  2016        PMID: 31467464      PMCID: PMC6715313          DOI: 10.1016/j.eswa.2016.01.029

Source DB:  PubMed          Journal:  Expert Syst Appl        ISSN: 0957-4174            Impact factor:   6.954


  5 in total

1.  Clinical decision support tool and rapid point-of-care platform for determining disease severity in patients with COVID-19.

Authors:  Michael P McRae; Glennon W Simmons; Nicolaos J Christodoulides; Zhibing Lu; Stella K Kang; David Fenyo; Timothy Alcorn; Isaac P Dapkins; Iman Sharif; Deniz Vurmaz; Sayli S Modak; Kritika Srinivasan; Shruti Warhadpande; Ravi Shrivastav; John T McDevitt
Journal:  Lab Chip       Date:  2020-06-03       Impact factor: 6.799

2.  Smart Diagnostics: Combining Artificial Intelligence and In Vitro Diagnostics.

Authors:  Michael P McRae; Kritika S Rajsri; Timothy M Alcorn; John T McDevitt
Journal:  Sensors (Basel)       Date:  2022-08-24       Impact factor: 3.847

3.  A Rapid and Sensitive Microfluidics-Based Tool for Seroprevalence Immunity Assessment of COVID-19 and Vaccination-Induced Humoral Antibody Response at the Point of Care.

Authors:  Kritika Srinivasan Rajsri; Michael P McRae; Glennon W Simmons; Nicolaos J Christodoulides; Hanover Matz; Helen Dooley; Akiko Koide; Shohei Koide; John T McDevitt
Journal:  Biosensors (Basel)       Date:  2022-08-10

4.  Clinical Decision Support Tool and Rapid Point-of-Care Platform for Determining Disease Severity in Patients with COVID-19.

Authors:  Michael P McRae; Glennon W Simmons; Nicolaos J Christodoulides; Zhibing Lu; Stella K Kang; David Fenyo; Timothy Alcorn; Isaac P Dapkins; Iman Sharif; Deniz Vurmaz; Sayli S Modak; Kritika Srinivasan; Shruti Warhadpande; Ravi Shrivastav; John T McDevitt
Journal:  medRxiv       Date:  2020-04-22

5.  Managing COVID-19 With a Clinical Decision Support Tool in a Community Health Network: Algorithm Development and Validation.

Authors:  Michael P McRae; Isaac P Dapkins; Iman Sharif; Judd Anderman; David Fenyo; Odai Sinokrot; Stella K Kang; Nicolaos J Christodoulides; Deniz Vurmaz; Glennon W Simmons; Timothy M Alcorn; Marco J Daoura; Stu Gisburne; David Zar; John T McDevitt
Journal:  J Med Internet Res       Date:  2020-08-24       Impact factor: 5.428

  5 in total

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