Related Experiment Video
Updated: Mar 30, 2026
Coronary Progenitor Cells and Soluble Biomarkers in Cardiovascular Prognosis after Coronary Angioplasty
Published on: January 28, 2020
Hematological Parameters Improve Prediction of Mortality and Secondary Adverse Events in Coronary Angiography
Crystel M Gijsberts1, Hester M den Ruijter, Dominique P V de Kleijn
1From the Experimental Cardiology Laboratory, University Medical Center Utrecht (CMG, HMDR, DPVDK, GP, IEH); ICIN-Netherlands Heart Institute, Utrecht, The Netherlands (CMG, DPVDK); Department of Surgery, Yong Loo Lin School of Medicine, National University of Singapore (DPVDK); Cardiovascular Research Institute (CVRI), National University Heart Centre (NUHCS), National University Health System, Singapore, Singapore (DPVDK); Department of Clinical Chemistry and Hematology (AH, MJTB, RHAVW, WWVS, IEH); Department of Cardiology, University Medical Center Utrecht (FWA, MV); Durrer Center for Cardiogenetic Research, ICIN-Netherlands Heart Institute, Utrecht, The Netherlands (FWA); and Institute of Cardiovascular Science, Faculty of Population Health Sciences, University College London, London, UK (FWA).
Insights
Hematological parameters significantly improve prediction of secondary cardiovascular events in coronary angiography patients. Red cell distribution width (RDW) was a key predictor, aiding in identifying high-risk individuals for better clinical decisions.
Area of Science:
- Cardiology
- Hematology
- Predictive Analytics
Background:
- Predicting primary cardiovascular events is established, but secondary event prediction post-coronary artery disease (CAD) requires enhanced methods.
- Traditional risk scores need augmentation for accurate prognostication in patients with existing CAD.
Purpose of the Study:
- To evaluate the predictive value of readily available hematological parameters for secondary cardiovascular events in coronary angiography patients.
- To assess the incremental predictive improvement offered by hematological parameters over traditional risk factors.
Main Methods:
- A cohort of 1760 coronary angiography patients was analyzed using data from the Utrecht Patient Oriented Database (UPOD).
- Backward stepwise multivariable Cox regression was employed to identify predictive hematological parameters.
- Continuous net reclassification improvement (cNRI) and integrated discrimination improvement (IDI) were calculated to quantify prediction enhancement.
Main Results:
- Panels of 3-8 hematological parameters significantly improved the prediction of death and major adverse cardiovascular events (MACE).
- Integrated discrimination improvement (IDI) ranged from 0.02 to 0.07 (P < 0.001), and continuous net reclassification improvement (cNRI) ranged from 0.11 to 0.40.
- Red cell distribution width (RDW) was frequently identified in predictive panels, with a multivariable adjusted hazard ratio of 1.19 (P < 0.001) per 1 SD increase for MACE.
Conclusions:
- Routinely measured hematological parameters significantly enhance the prediction of mortality and adverse events in patients undergoing coronary angiography.
- Incorporating these parameters, particularly RDW, can improve the identification of high-risk patients, informing clinical decision-making.
Abstract:
Prediction of primary cardiovascular events has been thoroughly investigated since the landmark Framingham risk score was introduced. However, prediction of secondary events after initial events of coronary artery disease (CAD) poses a new challenge. In a cohort of coronary angiography patients (n = 1760), we examined readily available hematological parameters from the UPOD (Utrecht Patient Oriented Database) and their addition to prediction of secondary cardiovascular events. Backward stepwise multivariable Cox regression analysis was used to test their ability to predict death and major adverse cardiovascular events (MACE). Continuous net reclassification improvement (cNRI) and integrated discrimination improvement (IDI) measures were calculated for the hematological parameters on top of traditional risk factors to assess prediction improvement. Panels of 3 to 8 hematological parameters significantly improved prediction of death and adverse events. The IDIs ranged from 0.02 to 0.07 (all P < 0.001) among outcome measures and the cNRIs from 0.11 to 0.40 (P < 0.001 in 5 of 6 outcome measures). In the hematological panels red cell distribution width (RDW) appeared most often. The multivariable adjusted hazard ratio of RDW per 1 standard deviation (SD) increase for MACE was 1.19 [1.08-1.32], P < 0.001. Routinely measured hematological parameters significantly improved prediction of mortality and adverse events in coronary angiography patients. Accurately indicating high-risk patients is of paramount importance in clinical decision-making.
More Related Videos
05:16Cutoff Value of Phase Angle by Bioelectrical Impedance Analysis at Admission as a Prognostic Factor in Patients with Acute Heart Failure
Published on: June 10, 2025
07:25Predicting Amputation using Local Circulating Mononuclear Progenitor Cells in Angioplasty-treated Patients with Critical Limb Ischemia
Published on: September 22, 2020
Related Concept Videos
01:20Blood Studies for Cardiovascular System I: Cardiac Biomarkers
The essential diagnostic tools for detecting myocardial necrosis and monitoring individuals suspected of having acute coronary syndrome (ACS) include:
Troponins
Troponins, particularly cardiac troponins I and T, are the most precise and sensitive markers of myocardial injury. They are detectable within 4-6 hours of myocardial injury and remain...
01:19Blood Studies for Cardiovascular System II: CRP, Hcy, and Cardiac Natriuretic Peptide Markers
These markers indicate stress or strain on the heart muscle:
Natriuretic Peptides (BNP)
Cardiac myocytes produce these hormones in response to ventricular stretching...
01:30Acute Coronary Syndrome III: Diagnostic Studies
01:28Cardiac Catheterization I: Pre-Procedure Overview