Maurice W J de Ronde1, Amir Khoshiwal1, R Nils Planken2, S Matthijs Boekholdt3, Mariette Biemond1, Matthew J Budoff4, Bruce Cooil5, Paulo A Lotufo6, Isabela M Bensenor6, Yuki Ohmoto-Sekine7, Vilmundur Gudnason8, Thor Aspelund8, Elias Freyr Gudmundsson8, Aeilko H Zwinderman9, Paolo Raggi10, Sara-Joan Pinto-Sietsma11. 1. Department of Vascular Medicine, Amsterdam University Medical Center, Academic Medical Centre, Meibergdreef 5, 1105, AZ, Amsterdam, the Netherlands; Department of Clinical Epidemiology, Biostatistics and Bioinformatics, Amsterdam University Medical Center, Location Academic Medical Centre, Meibergdreef 5, 1105, AZ, Amsterdam, the Netherlands. 2. Department of Radiology and Nuclear Medicine, Amsterdam University Medical Center, Location Academic Medical Centre, Meibergdreef 5, 1105, AZ, Amsterdam, the Netherlands. 3. Department of Cardiology, Amsterdam University Medical Center, Location Academic Medical Centre, Meibergdreef 5, 1105, AZ, Amsterdam, the Netherlands. 4. Harbor-UCLA Los Angeles Biomedical Research Institute, 1000 W Carson St, Torrance, 90509, California, United States. 5. Owen Graduate School of Management, Vanderbilt University, 2201 West End Ave, Nashville, TN, 37235, United States. 6. Department for Clinical and Epidemiologic Research, University of São Paulo, Rua da Reitoria, 374, 05508-010, São Paulo, Estado de Sao Paulo, Brazil. 7. Health Management Center, Toranomon Hospital, 107-0052 Tokyo5th Fl., Akasaka Intercity AIR, 1-8-1 Akasaka Minato-ku, Tokyo, Japan. 8. Icelandic Heart Association, Holtasmári 1, Kópavogur, Iceland. 9. Department of Vascular Medicine, Amsterdam University Medical Center, Academic Medical Centre, Meibergdreef 5, 1105, AZ, Amsterdam, the Netherlands. 10. Department of Medicine and Division of Cardiology, University of Alberta, 11220 83 Ave NW, Edmonton, AB T6G 2J2, Canada. 11. Department of Vascular Medicine, Amsterdam University Medical Center, Academic Medical Centre, Meibergdreef 5, 1105, AZ, Amsterdam, the Netherlands; Department of Clinical Epidemiology, Biostatistics and Bioinformatics, Amsterdam University Medical Center, Location Academic Medical Centre, Meibergdreef 5, 1105, AZ, Amsterdam, the Netherlands. Electronic address: s.j.pinto@amsterdamumc.nl.
Abstract
BACKGROUND: Age and sex based coronary artery calcium score (CAC) percentiles have been used to improve coronary artery disease (CAD) risk prediction. However, the main limitation of the CACs percentiles currently in use is that they are often based on single studies. We performed a pooled analysis of all available studies that reported on CAC percentiles, in order to develop more generalizable age and sex nomograms. METHODS: PubMed/Medline and Embase were searched for studies that reported nomograms of age and sex-based CACs percentiles. Studies were included if they reported data collected among asymptomatic individuals without a history of cardiovascular disease. Absolute CACs for each specific percentile stratum were pooled and new percentiles were generated taking into account the sample size of the study. RESULTS: We found 831 studies, of which 12 met the inclusion criteria. Data on CACs percentiles of 134,336 Western and 33,488 Asians were pooled separately, rendering a weighted CACs percentile nomogram available at https://www.calciumscorecalculator.com. Our weighted percentiles differed by up to 24% from the nomograms in use today. CONCLUSIONS: Our pooled age and sex based CACs percentiles based on over 155,000 individuals should provide a measure of risk that is more applicable to a wider population than the ones currently in use and hopefully will lead to better risk assessment and treatment decisions.
BACKGROUND: Age and sex based coronary artery calcium score (CAC) percentiles have been used to improve coronary artery disease (CAD) risk prediction. However, the main limitation of the CACs percentiles currently in use is that they are often based on single studies. We performed a pooled analysis of all available studies that reported on CAC percentiles, in order to develop more generalizable age and sex nomograms. METHODS: PubMed/Medline and Embase were searched for studies that reported nomograms of age and sex-based CACs percentiles. Studies were included if they reported data collected among asymptomatic individuals without a history of cardiovascular disease. Absolute CACs for each specific percentile stratum were pooled and new percentiles were generated taking into account the sample size of the study. RESULTS: We found 831 studies, of which 12 met the inclusion criteria. Data on CACs percentiles of 134,336 Western and 33,488 Asians were pooled separately, rendering a weighted CACs percentile nomogram available at https://www.calciumscorecalculator.com. Our weighted percentiles differed by up to 24% from the nomograms in use today. CONCLUSIONS: Our pooled age and sex based CACs percentiles based on over 155,000 individuals should provide a measure of risk that is more applicable to a wider population than the ones currently in use and hopefully will lead to better risk assessment and treatment decisions.
Authors: Todd C Villines; Subhi J Al'Aref; Daniele Andreini; Marcus Y Chen; Andrew D Choi; Carlo N De Cecco; Damini Dey; James P Earls; Maros Ferencik; Heidi Gransar; Harvey Hecht; Jonathon A Leipsic; Michael T Lu; Mohamed Marwan; Pál Maurovich-Horvat; Edward Nicol; Gianluca Pontone; Jonathan Weir-McCall; Seamus P Whelton; Michelle C Williams; Armin Arbab-Zadeh; Gudrun M Feuchtner Journal: J Cardiovasc Comput Tomogr Date: 2021-02-22
Authors: Sumaya Al Helali; Muhamed Abid Hanif; Nura Alshugair; Ahmad Al Majed; Abdullah Belfageih; Hamad Al Qahtani; Sameer Al Dulikan; Hussain Hamed; Adnan Al Mousa Journal: Int J Cardiol Heart Vasc Date: 2021-10-27