Derivation of an Outcome-Driven Threshold for Aortic Pulse Wave Velocity: An Individual-Participant Meta-Analysis

Author:

An De-Wei123ORCID,Hansen Tine W.24ORCID,Aparicio Lucas S.5,Chori Babangida267,Huang Qi-Fang1ORCID,Wei Fang-Fei8ORCID,Cheng Yi-Bang1ORCID,Yu Yu-Ling23ORCID,Sheng Chang-Sheng1ORCID,Gilis-Malinowska Natasza9,Boggia José10ORCID,Wojciechowska Wiktoria11ORCID,Niiranen Teemu J.1213,Tikhonoff Valérie14ORCID,Casiglia Edoardo14ORCID,Narkiewicz Krzysztof9ORCID,Stolarz-Skrzypek Katarzyna11,Kawecka-Jaszcz Kalina11,Jula Antti M.1213ORCID,Yang Wen-Yi15ORCID,Woodiwiss Angela J.16ORCID,Filipovský Jan17ORCID,Wang Ji-Guang1ORCID,Rajzer Marek W.11ORCID,Verhamme Peter18ORCID,Nawrot Tim S.36ORCID,Staessen Jan A.219ORCID,Li Yan1ORCID,

Affiliation:

1. Department of Cardiovascular Medicine, Shanghai Key Laboratory of Hypertension, Shanghai Institute of Hypertension, State Key Laboratory of Medical Genomics, National Research Centre for Translational Medicine, Ruijin Hospital, Shanghai Jiaotong University School of Medicine, China (D.-W.A., Q.-F.H., Y. B.C., C. S.S., J. G.W., Y.L.).

2. Non-Profit Research Association Alliance for the Promotion of Preventive Medicine, Belgium (D.-W.A, T.W.H, B.C., Y.-L.Y., J.A.S.).

3. Research Unit Environment and Health, Department of Public Health and Primary Care, University of Leuven, Belgium (D.-W.A, Y.-L.Y., T.S.N.).

4. The Steno Diabetes Center Copenhagen, Herlev, and Center for Health, Capital Region of Denmark, Copenhagen (T.W.H.).

5. Servicio de Clínica Médica, Sección Hipertensión Arterial, Hospital Italiano de Buenos Aires, Argentina (L.S.A.).

6. Centre for Environmental Sciences, Hasselt University, Belgium (B.C., T.S.N.).

7. Department of Internal Medicine, Faculty of Clinical Sciences, College of Health Sciences, University of Abuja, Nigeria (B.C.).

8. Department of Cardiology, the First Affiliated Hospital of Sun Yat-Sen University, Guangzhou, China (F.-F.W.).

9. Hypertension Unit, Department of Hypertension and Diabetology, Medical University of Gdańsk, Poland (N.G.-M., K.N.).

10. Centro de Nefrología and Departamento de Fisiopatología, Hospital de Clínicas, Universidad de la República, Montevideo, Uruguay (J.B.).

11. First Department of Cardiology, Interventional Electrocardiology and Hypertension, Jagiellonian University Medical College, Kraków, Poland (W.W., K.S.-S., M.R., K.K.-J).

12. Department of Chronic Disease Prevention, Finnish Institute for Health and Welfare, Turku, Finland (T.J.N., A.M.J.).

13. Department of Medicine, Turku University Hospital and University of Turku, Finland (T.J.N., A.M.J.).

14. Department of Medicine, University of Padova, Italy (V.T., E.C.).

15. Department of Cardiology, Shanghai General Hospital, China (W.-Y.Y.).

16. School of Physiology, University of the Witwatersrand, Johannesburg, South Africa (A.W.).

17. Faculty of Medicine, Charles University, Pilsen, Czech Republic (J.F.).

18. Center for Molecular and Vascular Biology, KU Leuven Department of Cardiovascular Sciences, University of Leuven, Belgium (P.V.).

19. Biomedical Science Group, Faculty of Medicine, University of Leuven, Belgium (J.A.S.).

Abstract

BACKGROUND: Aortic pulse wave velocity (PWV) predicts cardiovascular events (CVEs) and total mortality (TM), but previous studies proposing actionable PWV thresholds have limited generalizability. This individual-participant meta-analysis is aimed at defining, testing calibration, and validating an outcome-driven threshold for PWV, using 2 populations studies, respectively, for derivation IDCARS (International Database of Central Arterial Properties for Risk Stratification) and replication MONICA (Monitoring of Trends and Determinants in Cardiovascular Disease Health Survey – Copenhagen). METHODS: A risk-carrying PWV threshold for CVE and TM was defined by multivariable Cox regression, using stepwise increasing PWV thresholds and by determining the threshold yielding a 5-year risk equivalent with systolic blood pressure of 140 mm Hg. The predictive performance of the PWV threshold was assessed by computing the integrated discrimination improvement and the net reclassification improvement. RESULTS: In well-calibrated models in IDCARS, the risk-carrying PWV thresholds converged at 9 m/s (10 m/s considering the anatomic pulse wave travel distance). With full adjustments applied, the threshold predicted CVE (hazard ratio [CI]: 1.68 [1.15–2.45]) and TM (1.61 [1.01–2.55]) in IDCARS and in MONICA (1.40 [1.09–1.79] and 1.55 [1.23–1.95]). In IDCARS and MONICA, the predictive accuracy of the threshold for both end points was ≈0.75. Integrated discrimination improvement was significant for TM in IDCARS and for both TM and CVE in MONICA, whereas net reclassification improvement was not for any outcome. CONCLUSIONS: PWV integrates multiple risk factors into a single variable and might replace a large panel of traditional risk factors. Exceeding the outcome-driven PWV threshold should motivate clinicians to stringent management of risk factors, in particular hypertension, which over a person’s lifetime causes stiffening of the elastic arteries as waypoint to CVE and death.

Publisher

Ovid Technologies (Wolters Kluwer Health)

Subject

Internal Medicine

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