Evaluation of relationships between results of electrocardiography and echocardiography in 341 chimpanzees (Pan troglodytes) - Drane, Aimee L.; Atencia, Rebeca; Cooper, Stephen-Mark; Feltrer, Yedra; Calvi, Thalita; Strike, Tai; Palmer, Christopher; Simcox, Sarah; Rodriguez, Pablo; Sanchez, Carlos; van Bolhuis, Hester; Peck, Bruce; et al. (American Journal of Veterinary Research, 2020)
To examine potential relationships between ECG characteristics and echocardiographic measures of cardiac structure in chimpanzees ( ). 341 chimpanzees (175 males and 166 females) from 5 sanctuaries and 2 zoological collections. Chimpanzees were anesthetized for routine health examinations between May 2011 and July 2017 as part of the International Primate Heart Project and, during the same anesthetic events, underwent 12-lead ECG and transthoracic echocardiographic assessments. Relationships between results for ECG and those for echocardiographic measures of atrial areas, left ventricular internal diameter in diastole (LVIDd), and mean left ventricular wall thicknesses (MLVWT) were assessed with correlational analysis, then multiple linear regression analyses were used to create hierarchical models to predict cardiac structure from ECG findings. Findings indicated correlations ( = -0.231 to 0.310) between results for ECG variables and echocardiographic measures. The duration and amplitude of P waves in lead II had the strongest correlations with atrial areas. The Sokolow-Lyon criteria, QRS-complex duration, and R-wave amplitude in leads V and II had the strongest correlations with MLVWT, whereas the Sokolow-Lyon criteria, QRS-complex duration, and S-wave amplitude in leads V and V had the strongest correlations with LVIDd. However, the ECG predictive models that were generated only accounted for 17%, 7%, 11%, and 8% of the variance in the right atrial end-systolic area, left atrial end-systolic area, MLVWT, and LVIDd, respectively. Results indicated that relationships existed between ECG findings and cardiac morphology in the chimpanzees of the present study; however, further research is required to examine whether the predictive models generated can be modified to improve their clinical utility.