title: Acoustic cardiography helps to identify heart failure and its phenotypes.
abstract: BACKGROUND
  The prevalence of heart failure (HF) is increasing as the population ages, but its rapid diagnosis and phenotype identification remain challenging. We sought to determine whether acoustic cardiography can accurately identify HF and its phenotypes.
  
  
  METHODS
  Three cohorts of patients were studied [94 with hypertension, 109 with HF and normal ejection fraction (HFNEF, EF ≥ 50%) and 89 with HF and reduced ejection fraction (HFREF, EF<50%)]. All participants received acoustic cardiography and echocardiography examinations. Acoustic cardiographic parameters included S3 score (probability that the third heart sound exists), electromechanical activation time (EMAT, interval from Q wave to the first heart sound; EMAT/RR is EMAT normalized by heart rate), and systolic dysfunction index (SDI, a combination of EMAT/RR, S3 score, QRS duration and QR interval). Receiver operative characteristic curves were used to determine diagnostic utility of acoustic cardiography.
  
  
  RESULTS
  EMAT/RR significantly differentiated HFNEF from hypertension (area under curve [AUC], 0.83; 95% confidence interval [CI], 0.77-0.89) with an EMAT/RR>11.54% yielded 55% sensitivity and 90% specificity. Similarly, an echo-measured E/e'>15 yielded 55% sensitivity, 90% specificity and 0.84 AUC in detecting HFNEF. Whereas SDI out-performed the other acoustic cardiographic parameters in differentiating HFREF from HFNEF (AUC, 0.81; 95% CI, 0.75-0.87), and an SDI>5.43 yielded 53% sensitivity and 91% specificity. The E/e' ratio had a similar diagnostic performance.
  
  
  CONCLUSIONS
  Our study demonstrates that this bedside technology may be helpful in identifying HF and its phenotypes, especially when echocardiography is not immediately available.
authors.affiliation: Division of cardiology, Department of Medicine and Therapeutics, Prince of Wales Hospital, Li Ka Shing Institute of Health and Sciences, Institute of Vascular Medicine, The Chinese University of Hong Kong, Hong Kong, China.
authors.forename: Shang
authors.initials: S
authors.lastname: Wang
authors.forename: Yat-Yin
authors.initials: YY
authors.lastname: Lam
authors.forename: Ming
authors.initials: M
authors.lastname: Liu
authors.forename: Fang
authors.initials: F
authors.lastname: Fang
authors.forename: Jing
authors.initials: J
authors.lastname: Wang
authors.forename: Qing
authors.initials: Q
authors.lastname: Shang
authors.forename: Jing-Ping
authors.initials: JP
authors.lastname: Sun
authors.forename: John E
authors.initials: JE
authors.lastname: Sanderson
authors.forename: Cheuk-Man
authors.initials: CM
authors.lastname: Yu
mesh_terms: D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D015331:Cohort Studies; D004452:Echocardiography; D005260:Female; D006326:Heart Auscultation / Q000379:methods; D006333:Heart Failure / Q000000981:diagnostic imaging* / Q000235:genetics / Q000503:physiopathology*; D006347:Heart Sounds / Q000502:physiology*; D006801:Humans; D008297:Male; D008875:Middle Aged; D010641:Phenotype