BACKGROUND: Echocardiographic prediction of congestive heart failure (CHF) in dogs has not been prospectively evaluated. HYPOTHESIS: CHF can be predicted by Doppler echocardiographic (DE) variables of left ventricular (LV) filling in dogs with degenerative mitral valve disease (MVD) and dilated cardiomyopathy (DCM). ANIMALS: Sixty-three client-owned dogs. METHODS: Prospective clinical cohort study. Physical examination, thoracic radiography, analysis of natriuretic peptides, and transthoracic echocardiography were performed. Diagnosis of CHF was based upon clinical and radiographic findings. Presence or absence of CHF was predicted using receiver-operating characteristic (ROC) curve, multivariate logistic and stepwise regression, and best subsets analyses. RESULTS: Presence of CHF secondary to MVD or DCM could best be predicted by E:isovolumic relaxation time (IVRT) (area under the ROC curve [AUC]=0.97, P<.001), respiration rate (AUC=0.94, P<.001), Diastolic Functional Class (AUC=0.93, P<.001), and a combination of Diastolic Functional Class, IVRT, and respiration rate (R2=0.80, P<.001) or Diastolic Functional Class (AUC=1.00, P<.001), respiration rate (AUC=1.00, P<.001), and E:IVRT (AUC=0.99, P<.001), and a combination of Diastolic Functional Class and E:IVRT (R2=0.94, P<.001), respectively, whereas other variables including N-terminal pro-brain natriuretic peptide, E:Ea, and E:Vp were less useful. CONCLUSION AND CLINICAL IMPORTANCE: Various DE variables can be used to predict CHF in dogs with MVD and DCM. Determination of the clinical benefit of such variables in initiating, modulating, and assessing success of treatments for CHF needs further study.
BACKGROUND: Echocardiographic prediction of congestive heart failure (CHF) in dogs has not been prospectively evaluated. HYPOTHESIS: CHF can be predicted by Doppler echocardiographic (DE) variables of left ventricular (LV) filling in dogs with degenerative mitral valve disease (MVD) and dilated cardiomyopathy (DCM). ANIMALS: Sixty-three client-owned dogs. METHODS: Prospective clinical cohort study. Physical examination, thoracic radiography, analysis of natriuretic peptides, and transthoracic echocardiography were performed. Diagnosis of CHF was based upon clinical and radiographic findings. Presence or absence of CHF was predicted using receiver-operating characteristic (ROC) curve, multivariate logistic and stepwise regression, and best subsets analyses. RESULTS: Presence of CHF secondary to MVD or DCM could best be predicted by E:isovolumic relaxation time (IVRT) (area under the ROC curve [AUC]=0.97, P<.001), respiration rate (AUC=0.94, P<.001), Diastolic Functional Class (AUC=0.93, P<.001), and a combination of Diastolic Functional Class, IVRT, and respiration rate (R2=0.80, P<.001) or Diastolic Functional Class (AUC=1.00, P<.001), respiration rate (AUC=1.00, P<.001), and E:IVRT (AUC=0.99, P<.001), and a combination of Diastolic Functional Class and E:IVRT (R2=0.94, P<.001), respectively, whereas other variables including N-terminal pro-brain natriuretic peptide, E:Ea, and E:Vp were less useful. CONCLUSION AND CLINICAL IMPORTANCE: Various DE variables can be used to predict CHF in dogs with MVD and DCM. Determination of the clinical benefit of such variables in initiating, modulating, and assessing success of treatments for CHF needs further study.
Authors: Matthieu Lebastard; Kevin Le Boedec; Mark Howes; Stephen Joslyn; Jodi S Matheson; Robert T O'Brien Journal: J Vet Intern Med Date: 2021-04-03 Impact factor: 3.333
Authors: J López-Alvarez; J Elliott; D Pfeiffer; Y-M Chang; M Mattin; W Moonarmart; M J Hezzell; A Boswood Journal: J Vet Intern Med Date: 2015 Mar-Apr Impact factor: 3.333
Authors: M Borgarelli; J Abbott; L Braz-Ruivo; D Chiavegato; S Crosara; K Lamb; I Ljungvall; M Poggi; R A Santilli; J Haggstrom Journal: J Vet Intern Med Date: 2015 Mar-Apr Impact factor: 3.333
Authors: M Baron Toaldo; H Poser; G Menciotti; S Battaia; B Contiero; M Cipone; A Diana; E Mazzotta; C Guglielmini Journal: J Vet Intern Med Date: 2016-05 Impact factor: 3.333
Authors: M Baron Toaldo; G Romito; C Guglielmini; A Diana; N G Pelle; B Contiero; M Cipone Journal: J Vet Intern Med Date: 2017-04-28 Impact factor: 3.333
Authors: J L Pouchelon; C E Atkins; C Bussadori; M A Oyama; S L Vaden; J D Bonagura; V Chetboul; L D Cowgill; J Elliot; T Francey; G F Grauer; V Luis Fuentes; N Sydney Moise; D J Polzin; A M Van Dongen; N Van Israël Journal: J Small Anim Pract Date: 2015-09 Impact factor: 1.522
Authors: A-C Merveille; G Bolen; E Krafft; E Roels; S Gomart; A-L Etienne; C Clercx; K Mc Entee Journal: J Vet Intern Med Date: 2015-09-29 Impact factor: 3.333