title: Evaluation of a Computer-aided Lung Auscultation System for Diagnosis of Bovine Respiratory Disease in Feedlot Cattle.
abstract: BACKGROUND
  A computer-aided lung auscultation (CALA) system was recently developed to diagnose bovine respiratory disease (BRD) in feedlot cattle.
  
  
  OBJECTIVE
  To determine, in a case-control study, the level of agreement between CALA and veterinary lung auscultation and to evaluate the sensitivity (Se) and specificity (Sp) of CALA to diagnose BRD in feedlot cattle.
  
  
  METHODS
  A total of 561 Angus cross-steers (initial body weight = 246 ± 45 kg) were observed during the first 50 day after entry to a feedlot.
  
  
  METHODS
  Case-control study. Steers with visual signs of BRD identified by pen checkers were examined by a veterinarian, including lung auscultation using a conventional stethoscope and CALA that produced a lung score from 1 (normal) to 5 (chronic). For each steer examined for BRD, 1 apparently healthy steer was selected as control and similarly examined. Agreement between CALA and veterinary auscultation was assessed by kappa statistic. CALA's Se and Sp were estimated using Bayesian latent class analysis.
  
  
  RESULTS
  Of the 561 steers, 35 were identified with visual signs of BRD and 35 were selected as controls. Comparison of veterinary auscultation and CALA (using a CALA score ≥2 as a cut off) revealed a substantial agreement (kappa = 0.77). Using latent class analysis, CALA had a relatively high Se (92.9%; 95% credible interval [CI] = 0.71-0.99) and Sp (89.6%; 95% CI = 0.64-0.99) for diagnosing BRD compared with pen checking.
  
  
  CONCLUSIONS
  CALA had good diagnostic accuracy (albeit with a relatively wide CI). Its use in feedlots could increase the proportion of cattle accurately diagnosed with BRD.
authors.affiliation: Department of Production Animal Health, Faculty of Veterinary Medicine, University of Calgary, Calgary, AB, Canada.
authors.forename: A V
authors.initials: AV
authors.lastname: Mang
authors.affiliation: Department of Clinical Science, Faculté de Médecine Vétérinaire, Université de Montréal, St-Hyacinthe, QC, Canada.
authors.forename: S
authors.initials: S
authors.lastname: Buczinski
authors.affiliation: Feedlot Health Management Services, Okotoks, AB, Canada.
authors.forename: C W
authors.initials: CW
authors.lastname: Booker
authors.affiliation: Department of Production Animal Health, Faculty of Veterinary Medicine, University of Calgary, Calgary, AB, Canada.|Feedlot Health Management Services, Okotoks, AB, Canada.
authors.forename: E
authors.initials: E
authors.lastname: Timsit
mesh_terms: D000818:Animals; D001314:Auscultation / Q000295:instrumentation / Q000379:methods / Q000662:veterinary*; D048090:Bovine Respiratory Disease Complex / Q000175:diagnosis* / Q000503:physiopathology; D016022:Case-Control Studies; D002417:Cattle; D003936:Diagnosis, Computer-Assisted / Q000379:methods / Q000662:veterinary*; D006242:Haptoglobins / Q000032:analysis; D008168:Lung / Q000503:physiopathology*; D008297:Male; D012680:Sensitivity and Specificity
chemical_list: D006242:Haptoglobins
keywords: Bayesian latent class analysis; Electronic stethoscope; Whisper®