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. 2020 Nov;17(11):1431–1439. doi: 10.1513/AnnalsATS.201910-767OC

Table 3.

Association between strain and echocardiographic measures of RV function by time period

Dependent Variable Predictor Estimate (95% CI); P Value*
All Data Pre-Op After Repair Immediate Post-Op Recovery
GLS TAPSEZ −0.88 (−1.19 to −0.58); <0.0001 −0.89 (−1.46 to 0.31); 0.0033 −0.58 (−0.99 to −0.17); 0.006 −0.29 (−1.60 to 1.02); 0.64 −0.70 (−1.14 to −0.26); 0.0024
RV FAC, % −0.48 (−0.51 to −0.45); <0.0001 −0.53 (−0.57 to −0.49); <0.0001 −0.42 (−0.47 to −0.37); <0.0001 −0.52 (−0.63 to −0.40); <0.0001 −0.39 (−0.45 to −0.34); <0.0001
RV s’, m/s −0.85 (−1.19 to −0.51); <0.0001 −0.38 (−1.04 to −0.27); 0.24 −0.58 (−1.09 to −0.08); 0.026 0.20 (−2.65 to 3.04); 0.89 −0.79 (−1.30 to −0.28); 0.0036
Pulmonary hypertension 4.71 (3.37 to 6.04); <0.0001 2.30 (−3.38 to 7.99); 0.32 3.45 (1.90 to 5.00); 0.0001 −4.08 (−10.05 to 1.89); 0.17 3.47 (1.85 to 5.08); 0.0003
FWS TAPSEZ −0.94 (−1.27 to −0.61); <0.0001 −1.01 (−1.60 to −0.42); 0.0013 −0.46 (−0.92 to −0.01); 0.046 −0.21 (−1.43 to 1.02); 0.72 −0.56 (−1.08 to −0.05); 0.03
RV FAC, % −0.48 (−0.52 to −0.45); <0.0001 −0.52 (−0.57 to −0.48); <0.0001 −0.40 (−0.46 to −0.34); <0.0001 −0.48 (−0.60 to −0.36); <0.0001 −0.38 (−0.45 to −0.30); <0.0001
RV s’, m/s −0.85 (−1.20 to −0.49); <0.0001 −0.76 (−1.40 to −0.13); 0.021 −0.08 (−0.66 to −0.50); 0.78 0.09 (−2.69 to 2.88); 0.94 −0.16 (−0.78 to 0.46); 0.61
Pulmonary hypertension 5.05 (3.64 to 6.46); <0.0001 2.43 (−3.37 to 8.23); 0.31 3.10 (1.41 to 4.80); 0.0009 −3.86 (−9.12 to 2.41); 0.24 3.07 (1.24 to 4.91); 0.0026

Definition of abbreviations: 95% CI = 95% confidence interval; FAC = fractional area change; FWS = free-wall strain; GLS = global longitudinal strain; post-op = postoperative; pre-op = preoperative; RV = right ventricle; s’ = tricuspid annular peak systolic velocity; TAPSEZ = tricuspid annular plane systolic excursion z-score.

*

All P values are for comparisons among pre-op, immediate post-op, and recovery periods.

Includes both immediate post-op and recovery data.