Moving prediction of exacerbation in chronic obstructive pulmonary disease for patients in telecare

J Telemed Telecare. 2012 Mar;18(2):99-103. doi: 10.1258/jtt.2011.110607. Epub 2012 Jan 20.

Abstract

We investigated whether physiological data can be used for predicting chronic obstructive pulmonary disease (COPD) exacerbations. Home measurements from 57 patients were analysed, during which 10 exacerbations occurred in nine patients. A total of 273 different features were evaluated for their discrimination abilities between periods with and without exacerbations. The analysis showed that if a sensitivity level of 70% is considered to be acceptable, then the specificity was 95% and the AUC was 0.73, i.e. it is possible to discriminate between periods of exacerbation and periods without. A system capable of predicting risk could provide support to COPD patients in their tele-rehabilitation.

Publication types

  • Randomized Controlled Trial
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Acute Disease
  • Aged
  • Disease Progression
  • Female
  • Forecasting / methods*
  • Hospitalization / economics
  • Hospitalization / statistics & numerical data
  • Humans
  • Male
  • Pulmonary Disease, Chronic Obstructive / complications*
  • Pulmonary Disease, Chronic Obstructive / diagnosis
  • Pulmonary Disease, Chronic Obstructive / therapy*
  • Telemedicine / methods*