title: Fractal dimensions of skin microcirculation flow in subjects with familial predisposition or newly diagnosed hypertension.
abstract: BACKGROUND
  Fractal analysis has been shown to be capable of characterizing irregular time series generated in non-linear systems. Fluctuations in skin flow signals have a fractal nature, but to date there has been no analysis of subjects with hypertension. The aim of this study is to assess the fractal dimensions of skin microcirculation flows in subjects with a familial predisposition or newly diagnosed hypertension.
  
  
  METHODS
  A four-minutes rest flow (RF), minimal flow (BZ) during three-minutes ischemia and eight-minutes heat flow (HF) were recorded (using laser Doppler flowmetry) in patients with untreated hypertension, and in normotensives with no [NT(-)] or with a familial predisposition to hypertension [NT(+)]. Average one-minute surface areas under the curve of flow records and box dimensions (D) were calculated. Anova Kruskall-Wallis, c2 statistic and multivariate reverse regression analysis were used for calculation.
  
  
  RESULTS
  We studied 70 people (average age 36.1 ± 10.3 years, 39 men). Hypertensives (n = 31) had significantly higher values of both clinical blood pressure and 24-hour ambulatory blood pressure, body mass index, glucose, triglycerides and insulin than the NT(-), (n = 17) and NT(+), (n = 22) groups. Mean values of flows and surface area under the curve of RF, BZ, HF records, D RF and D HF were comparable in studied groups, but D BZ differed (1.13 ± ± 0.05 vs 1.15 ± 0.05 vs 1.11 ± 0.05, respectively; p = 0.04). A family history of hypertension, insulin level and variability of 24-hour diastolic blood pressure were significant predictors of D BZ lower values in the multiple regression model.
  
  
  CONCLUSIONS
  Subjects with a familial predisposition to hypertension reveal altered homeodynamics of microvascular flow, with diminished chaotic ischemic flow.
authors.forename: Barbara
authors.initials: B
authors.lastname: Gryglewska
authors.forename: Mirosław
authors.initials: M
authors.lastname: Nęcki
authors.forename: Marcin
authors.initials: M
authors.lastname: Zelawski
authors.forename: Marcin
authors.initials: M
authors.lastname: Cwynar
authors.forename: Tomasz
authors.initials: T
authors.lastname: Baron
authors.forename: Marian
authors.initials: M
authors.lastname: Mrozek
authors.forename: Tomasz
authors.initials: T
authors.lastname: Grodzicki
mesh_terms: D000328:Adult; D001783:Blood Flow Velocity; D001794:Blood Pressure; D018660:Blood Pressure Monitoring, Ambulatory; D016022:Case-Control Studies; D016009:Chi-Square Distribution; D005260:Female; D017709:Fractals; D020022:Genetic Predisposition to Disease; D040941:Heredity; D006801:Humans; D006973:Hypertension / Q000000981:diagnostic imaging* / Q000235:genetics / Q000503:physiopathology*; D017078:Laser-Doppler Flowmetry; D008297:Male; D008833:Microcirculation; D008875:Middle Aged; D010375:Pedigree; D011044:Poland; D012039:Regional Blood Flow; D012044:Regression Analysis; D012815:Signal Processing, Computer-Assisted; D012867:Skin / Q000098:blood supply*; D013997:Time Factors; D014463:Ultrasonography; D055815:Young Adult