title: Automated interpretation of home blood pressure assessment (Hy-Result software) versus physician's assessment: a validation study.
abstract: OBJECTIVE
  Hy-Result is the first software for self-interpretation of home blood pressure measurement results, taking into account both the recommended thresholds for normal values and patient characteristics. We compare the software-generated classification with the physician's evaluation.
  
  
  METHODS
  The primary assessment criterion was whether algorithm classification of the blood pressure (BP) status concurred with the physician's advice (blinded to the software's results) following a consultation (n=195 patients). Secondary assessment was the reliability of text messages.
  
  
  RESULTS
  In the 58 untreated patients, the agreement between classification of the BP status generated by the software and the physician's classification was 87.9%. In the 137 treated patients, the agreement was 91.9%. The κ-test applied for all the patients was 0.81 (95% confidence interval: 0.73-0.89). After correction of errors identified in the algorithm during the study, agreement increased to 95.4% [κ=0.9 (95% confidence interval: 0.84-0.97)]. For 100% of the patients with comorbidities (n=46), specific text messages were generated, indicating that a physician might recommend a target BP lower than 135/85 mmHg. Specific text messages were also generated for 100% of the patients for whom global cardiovascular risks markedly exceeded norms.
  
  
  CONCLUSIONS
  Classification by Hy-Result is at least as accurate as that of a specialist in current practice (http://www.hy-result.com).
authors.affiliation: aHypertension Unit, Assistance Publique-Hôpitaux de Paris, Hôpital Européen Georges Pompidou, F-75015 Paris, France bINSERM UMRS1138, Centre de Recherche des Cordeliers, E22, Université Paris Descartes, Université Pierre et Marie Curie, Paris, France cUnité de Recherche Clinique, Assistance Publique-Hôpitaux de Paris, Hôpital Européen Georges Pompidou.F-75015 Paris, France dUniversité Paris Descartes, Sorbonne Paris Cité, Faculté de Médecine, F-75006 Paris, France eThot e-santé, Paris fCHU de Quebec - Université Laval. Hôtel-Dieu de Québec. Quebec (QC) Canada G1R 2J6 gPole of Cardiovascular Research, Institut de Recherche Expérimentale et Clinique, Université Catholique de Louvain, Brussels, Belgium hDivision of Cardiology, Cliniques Universitaires Saint-Luc, Université Catholique de Louvain, Brussels, Belgium.
authors.forename: Nicolas
authors.initials: N
authors.lastname: Postel-Vinay
authors.forename: Guillaume
authors.initials: G
authors.lastname: Bobrie
authors.forename: Alan
authors.initials: A
authors.lastname: Ruelland
authors.forename: Majida
authors.initials: M
authors.lastname: Oufkir
authors.forename: Sebastien
authors.initials: S
authors.lastname: Savard
authors.forename: Alexandre
authors.initials: A
authors.lastname: Persu
authors.forename: Sandrine
authors.initials: S
authors.lastname: Katsahian
authors.forename: Pierre F
authors.initials: PF
authors.lastname: Plouin
mesh_terms: D000293:Adolescent; D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D000465:Algorithms; D001794:Blood Pressure; D018660:Blood Pressure Monitoring, Ambulatory / Q000379:methods*; D001330:Electronic Data Processing; D006801:Humans; D008875:Middle Aged; D012984:Software