title: A composite autonomic index as unitary metric for heart rate variability: a proof of concept.
abstract: BACKGROUND
  This study addresses whether a unitary cardiac autonomic nervous system index (ANSI), obtained combining multiple metrics from heart rate variability (HRV) into a radar plot could provide an easy appreciation of autonomic performance in a clinical setting.
  
  
  METHODS
  Data are standardized using percentile ranking of autonomic proxies from a relatively large reference population (n = 1593, age 39 ± 13 years). Autonomic indices are obtained from autoregressive spectral analysis of (ECG derived) HRV at rest and during standing up. A reduced ANSI (using RR, RR variance and rest-stand difference of LFnu) is then constructed as a radar plot, quantified according to its combined area and tested against different risk subgroups.
  
  
  RESULTS
  With growing risk profile, there is a marked reduction of the rank value of ANSI, quantified individually by the radar plot area. The practical usefulness of the approach was tested in small groups of additional subjects putatively characterized by elevated or poor autonomic performance. Data show that elite endurance athletes are characterized by elevated values of ANSI (80·6 ± 14·9, P < 0·001) while subjects with either Type 1 or Type 2 diabetes show lower values (DM1 = 37·0 ± 18·9 and DM2 = 26·8 ± 23·3, P = 0·002), and patients with coronary artery disease (CAD) represent a nadir (17 ± 20, P < 0·001).
  
  
  CONCLUSIONS
  This observational study shows the feasibility of testing simpler metrics of cardiac autonomic regulation based on a multivariate unitary index in a preventive setting. This simple approach might foster a wider application of HRV in the clinical arena, and permit an easier appreciation of autonomic performance.
authors.affiliation: BIOMETRA Department, University of Milano, Milano, Italy.|Exercise Medicine Unit, Humanitas Clinical and Research Hospital, Rozzano, Italy.
authors.forename: Roberto
authors.initials: R
authors.lastname: Sala
authors.affiliation: BIOMETRA Department, University of Milano, Milano, Italy.|Exercise Medicine Unit, Humanitas Clinical and Research Hospital, Rozzano, Italy.
authors.forename: Mara
authors.initials: M
authors.lastname: Malacarne
authors.affiliation: Department of Statistics and Quantitative Methods, University of Milano Bicocca, Milano, Italy.
authors.forename: Nadia
authors.initials: N
authors.lastname: Solaro
authors.affiliation: BIOMETRA Department, University of Milano, Milano, Italy.
authors.forename: Massimo
authors.initials: M
authors.lastname: Pagani
authors.affiliation: BIOMETRA Department, University of Milano, Milano, Italy.|Exercise Medicine Unit, Humanitas Clinical and Research Hospital, Rozzano, Italy.
authors.forename: Daniela
authors.identifier: http://orcid.org/0000-0003-4845-8988
authors.initials: D
authors.lastname: Lucini
mesh_terms: D000328:Adult; D056352:Athletes; D001341:Autonomic Nervous System / Q000502:physiology*; D001794:Blood Pressure; D003324:Coronary Artery Disease / Q000503:physiopathology*; D003922:Diabetes Mellitus, Type 1 / Q000503:physiopathology*; D003924:Diabetes Mellitus, Type 2 / Q000503:physiopathology*; D005260:Female; D006339:Heart Rate / Q000502:physiology*; D006801:Humans; D008297:Male; D008875:Middle Aged; D012307:Risk Factors; D055815:Young Adult
keywords: Autonomic nervous system; BMI; cardiometabolic risk; hypertension; personal prevention; smoke