title: Development and validation of an integrated diagnostic algorithm derived from parameters monitored in implantable devices for identifying patients at risk for heart failure hospitalization in an ambulatory setting.
abstract: BACKGROUND
  We developed and validated a heart failure (HF) risk score combining daily measurements of multiple device-derived parameters.
  
  
  METHODS
  Heart failure patients from clinical studies with implantable devices were used to form two separate data sets. Daily HF scores were estimated by combining changes in intra-thoracic impedance, atrial fibrillation (AF) burden, rapid rate during AF, %CRT pacing, ventricular tachycardia, night heart rate, heart rate variability, and activity using a Bayesian model. Simulated monthly follow-ups consisted of looking back at the maximum daily HF risk score in the preceding 30 days, categorizing the evaluation as high, medium, or low risk, and evaluating the occurrence of HF hospitalizations in the next 30 days. We used an Anderson-Gill model to compare survival free from HF events in the next 30 days based on risk groups.
  
  
  RESULTS
  The development data set consisted of 921 patients with 9790 patient-months of data and 91 months with HF hospitalizations. The validation data set consisted of 1310 patients with 10 655 patient-months of data and 163 months with HF hospitalizations. In the validation data set, 10% of monthly evaluations in 34% of the patients were in the high-risk group. Monthly diagnostic evaluations in the high-risk group were 10 times (adjusted HR: 10.0; 95% CI: 6.4-15.7, P < 0.001) more likely to have an HF hospitalization (event rate of 6.8%) in the next 30 days compared with monthly evaluations in the low-risk group (event rate of 0.6%).
  
  
  CONCLUSIONS
  An HF score based on implantable device diagnostics can identify increased risk for HF hospitalization in the next 30 days.
authors.affiliation: National Heart and Lung Institute, Imperial College, London, UK. m.cowie@imperial.ac.uk
authors.forename: Martin R
authors.initials: MR
authors.lastname: Cowie
authors.forename: Shantanu
authors.initials: S
authors.lastname: Sarkar
authors.forename: Jodi
authors.initials: J
authors.lastname: Koehler
authors.forename: David J
authors.initials: DJ
authors.lastname: Whellan
authors.forename: George H
authors.initials: GH
authors.lastname: Crossley
authors.forename: Wai Hong Wilson
authors.initials: WH
authors.lastname: Tang
authors.forename: William T
authors.initials: WT
authors.lastname: Abraham
authors.forename: Vinod
authors.initials: V
authors.lastname: Sharma
authors.forename: Massimo
authors.initials: M
authors.lastname: Santini
mesh_terms: D000368:Aged; D000465:Algorithms; D017147:Defibrillators, Implantable; D005260:Female; D006333:Heart Failure / Q000517:prevention & control*; D006760:Hospitalization; D006801:Humans; D053208:Kaplan-Meier Estimate; D008297:Male; D018670:Monitoring, Ambulatory; D012372:ROC Curve; D018570:Risk Assessment; D013997:Time Factors
keywords: Ambulatory monitoring; Heart failure; Hospitalization; Implantable device diagnostics; Risk