Impact of model choice when studying the relationship between blood pressure variability and risk of stroke - 22/05/21
Résumé |
Introduction |
Long-term blood pressure variability (BPV), an increasingly recognized vascular risk factor, is challenging to define and to analyze. In order to take into account two major methodological issues - conditioning on the future and uncertainty around BPV value - we compared different models on the risk of stroke in a large dataset.
Methods |
We used data from the PROGRESS trial, a secondary stroke prevention trial which included 6105 subjects followed-up during four years. The median number of BP measurements was 12 and 727 strokes occurred. We compared a naive Cox model including BPV as a fixed covariate calculated on the entire follow-up, to other models aimed at avoiding conditioning on the future and taking into account uncertainty around BPV value.
Results |
We found that BPV was associated with an increased risk of stroke when using a naive Cox Model (HR=1.19, 95% CI: 1.10–1.30) but not when using other models dealing more appropriately with the issue of conditioning on the future.
Conclusion |
These results illustrate that the methods used to estimate the association between BPV and stroke may affect the estimates and that more appropriate models tend to reduce this association.
Figure: 99861-image.pdf
Le texte complet de cet article est disponible en PDF.Keywords : Blood pressure variability, Joint modelling, Stroke
Plan
Vol 69 - N° S1
P. S57 - juin 2021 Retour au numéroBienvenue sur EM-consulte, la référence des professionnels de santé.