Compensatory reserve was measured in baboons (n = 13) during hemorrhage (Hem) and lower-body negative pressure (LBNP) using a machine-learning algorithm developed to estimate compensatory reserve by detecting reductions in central blood volume during LBNP. The algorithm calculates compensatory reserve index (CRI) from normovolemia (CRI = 1) to cardiovascular decompensation (CRI = 0). The hypothesis was that Hem and LBNP will elicit similar CRI values and that CRI would have higher specificity than stroke volume (SV) in predicting decompensation. Blood was removed in four steps: 6.25%, 12.5%, 18.75%, and 25% of total blood volume. Four weeks after Hem, the same animals were subjected to four levels of LBNP that was matched on the basis of their central venous pressure. Data (mean ± 95% confidence interval) indicate that CRI decreased (P < 0.001) from baseline during Hem (0.69 ± 0.10, 0.57 ± 0.09, 0.36 ± 0.10, 0.16 ± 0.08, and 0.08 ± 0.03) and LBNP (0.76 ± 0.05, 0.66 ± 0.08, 0.36 ± 0.13, 0.23 ± 0.11, and 0.14 ± 0.09). CRI was not different between Hem and LBNP (P = 0.20). Linear regression analysis between Hem CRI and LBNP CRI revealed a slope of 1.03 and a correlation coefficient of 0.96. CRI exhibited greater specificity than SV in both Hem (92.3 vs. 82.1) and LBNP (94.8 vs. 83.1) and greater ROC AUC in Hem (0.94 vs. 0.84) and LBNP (0.94 vs. 0.92). These data support the hypothesis that Hem and LBNP elicited the same CRI response, suggesting that measurement of compensatory reserve is superior to SV as a predictor of cardiovascular decompensation.
Keywords: blood loss; blood pressure; central hypovolemia; compensatory mechanisms; stroke volume.