title: How many measurements are needed to estimate blood pressure variability without loss of prognostic information?
abstract: BACKGROUND
  Average real variability (ARV) is a recently proposed index for short-term blood pressure (BP) variability. We aimed to determine the minimum number of BP readings required to compute ARV without loss of prognostic information.
  
  
  METHODS
  ARV was calculated from a discovery dataset that included 24-hour ambulatory BP measurements for 1,254 residents (mean age = 56.6 years; 43.5% women) of Copenhagen, Denmark. Concordance between ARV from full (≥80 BP readings) and randomly reduced 24-hour BP recordings was examined, as was prognostic accuracy. A test dataset that included 5,353 subjects (mean age = 54.0 years; 45.6% women) with at least 48 BP measurements from 11 randomly recruited population cohorts was used to validate the results.
  
  
  RESULTS
  In the discovery dataset, a minimum of 48 BP readings allowed an accurate assessment of the association between cardiovascular risk and ARV. In the test dataset, over 10.2 years (median), 806 participants died (335 cardiovascular deaths, 206 cardiac deaths) and 696 experienced a major fatal or nonfatal cardiovascular event. Standardized multivariable-adjusted hazard ratios (HRs) were computed for associations between outcome and BP variability. Higher diastolic ARV in 24-hour ambulatory BP recordings predicted (P < 0.01) total (HR = 1.12), cardiovascular (HR = 1.19), and cardiac (HR = 1.19) mortality and fatal combined with nonfatal cerebrovascular events (HR = 1.16). Higher systolic ARV in 24-hour ambulatory BP recordings predicted (P < 0.01) total (HR = 1.12), cardiovascular (HR = 1.17), and cardiac (HR = 1.24) mortality.
  
  
  CONCLUSIONS
  Forty-eight BP readings over 24 hours were observed to be adequate to compute ARV without meaningful loss of prognostic information.
authors: Departamento de Informática, Universidad Politécnica de Sinaloa, Mazatlán, México.
authors: Luis J
authors: LJ
authors: Mena
authors: Gladys E
authors: GE
authors: Maestre
authors: Tine W
authors: TW
authors: Hansen
authors: Lutgarde
authors: L
authors: Thijs
authors: Yanping
authors: Y
authors: Liu
authors: José
authors: J
authors: Boggia
authors: Yan
authors: Y
authors: Li
authors: Masahiro
authors: M
authors: Kikuya
authors: Kristina
authors: K
authors: Björklund-Bodegård
authors: Takayoshi
authors: T
authors: Ohkubo
authors: Jørgen
authors: J
authors: Jeppesen
authors: Christian
authors: C
authors: Torp-Pedersen
authors: Eamon
authors: E
authors: Dolan
authors: Tatiana
authors: T
authors: Kuznetsova
authors: Katarzyna
authors: K
authors: Stolarz-Skrzypek
authors: Valérie
authors: V
authors: Tikhonoff
authors: Sofia
authors: S
authors: Malyutina
authors: Edoardo
authors: E
authors: Casiglia
authors: Yuri
authors: Y
authors: Nikitin
authors: Lars
authors: L
authors: Lind
authors: Edgardo
authors: E
authors: Sandoya
authors: Kalina
authors: K
authors: Kawecka-Jaszcz
authors: Jan
authors: J
authors: Filipovsky
authors: Yutaka
authors: Y
authors: Lmai
authors: Jiguang
authors: J
authors: Wang
authors: Eoin
authors: E
authors: O'Brien
authors: Jan A
authors: JA
authors: Staessen
mesh_terms: D000368:Aged; D000959:Antihypertensive Agents / Q000627:therapeutic use; D001794:Blood Pressure / Q000187:drug effects; D018660:Blood Pressure Monitoring, Ambulatory; D002423:Cause of Death; D016009:Chi-Square Distribution; D003718:Denmark; D005260:Female; D006801:Humans; D006973:Hypertension / Q000175:diagnosis* / Q000188:drug therapy / Q000401:mortality / Q000503:physiopathology; D008297:Male; D008875:Middle Aged; D015999:Multivariate Analysis; D011237:Predictive Value of Tests; D011379:Prognosis; D016016:Proportional Hazards Models; D015203:Reproducibility of Results; D012307:Risk Factors; D013997:Time Factors
chemical_list: D000959:Antihypertensive Agents
keywords: ambulatory blood pressure; blood pressure; blood pressure variability; epidemiology; hypertension; population science; risk factors.
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