title: Blood pressure variability: cardiovascular risk integrator or independent risk factor?
abstract: Blood pressure (BP) variability is associated with several cardiovascular (CV) risk factors. Is BP variability measurement of any additive value, in terms of CV risk assessment strategies? To answer this question, we analyzed data from the SU.FOL.OM3 secondary prevention trial that included 2501 patients with background of CV disease history (coronary or cerebrovascular disease). BP was measured every year allowing calculation of variability of BP, expressed as s.d. and coefficient of variability (s.d./mean systolic BP) in 2157 patients. We found that systolic BP variability was associated with several CV risk factors: principally hypertension, age, and diabetes. Furthermore, all antihypertensives were positively associated with variability. Logistic regression analysis revealed that three factors were independent predictors of major CV event: coefficient of variability of systolic BP (OR=1.23 per s.d., 95% CI: 1.04-1.46, P=0.016), current smoking (OR=1.94, 95% CI: 1.03-3.66, P=0.039), and inclusion for cerebrovascular disease (OR=1.92, 95% CI: 1.29-2.87, P=0.001). Finally, when comparing logistic regression models characteristics without, and then with, inclusion of BP variability, there was a modest but statistically significant improvement (P=0.04). In conclusion, age, BP and diabetes were the major determinants of BP variability. Furthermore, BP variability has an independent prognostic value in the prediction of major CV events; but improvement in the prediction model was quite modest. This last finding is more in favor of BP variability acting as an integrator of CV risk than acting as a robust independent CV risk factor in this high-risk population.
authors.affiliation: 1] Faculty of Medicine, Paris-Descartes University, Hôtel-Dieu Hospital, AP-HP, Diagnosis and Therapeutic Center, Paris, France [2] Nutritional Epidemiology Research Unit-UMR U1153 INSERM, U1125 INRA, CNAM, Paris 13, Centre de Recherche en Epidémiologies et Biostatistiques Sorbonne Paris Cité, UFR SMBH, Bobigny, France.
authors.forename: J
authors.initials: J
authors.lastname: Blacher
authors.affiliation: Faculty of Medicine, Paris-Descartes University, Hôtel-Dieu Hospital, AP-HP, Diagnosis and Therapeutic Center, Paris, France.
authors.forename: M E
authors.initials: ME
authors.lastname: Safar
authors.affiliation: Faculty of Medicine, Paris-Descartes University, Hôtel-Dieu Hospital, AP-HP, Diagnosis and Therapeutic Center, Paris, France.
authors.forename: C
authors.initials: C
authors.lastname: Ly
authors.affiliation: Nutritional Epidemiology Research Unit-UMR U1153 INSERM, U1125 INRA, CNAM, Paris 13, Centre de Recherche en Epidémiologies et Biostatistiques Sorbonne Paris Cité, UFR SMBH, Bobigny, France.
authors.forename: F
authors.initials: F
authors.lastname: Szabo de Edelenyi
authors.affiliation: 1] Nutritional Epidemiology Research Unit-UMR U1153 INSERM, U1125 INRA, CNAM, Paris 13, Centre de Recherche en Epidémiologies et Biostatistiques Sorbonne Paris Cité, UFR SMBH, Bobigny, France [2] Department of Public Health, Avicenne Hospital, Bobigny, France.
authors.forename: S
authors.initials: S
authors.lastname: Hercberg
authors.affiliation: Nutritional Epidemiology Research Unit-UMR U1153 INSERM, U1125 INRA, CNAM, Paris 13, Centre de Recherche en Epidémiologies et Biostatistiques Sorbonne Paris Cité, UFR SMBH, Bobigny, France.
authors.forename: P
authors.initials: P
authors.lastname: Galan
mesh_terms: D000368:Aged; D001794:Blood Pressure; D002318:Cardiovascular Diseases / Q000453:epidemiology*; D005260:Female; D005602:France / Q000453:epidemiology; D006801:Humans; D008297:Male; D008875:Middle Aged; D011237:Predictive Value of Tests; D012044:Regression Analysis; D012307:Risk Factors