Key result
Intraoperative blood pressure variability computed from Poincaré plots and coefficient of variation performed poorly in predicting 30-day mortality and renal failure (C-statistic ~0.5) and did not improve the standard STS risk score.
Why the study?
Blood pressure variability is associated with postoperative outcomes after cardiac surgery, but its ability to predict outcomes beyond static preoperative factors remains unclear.
Does intraoperative blood pressure variability computed by Poincaré plots and coefficient of variation predict 30-day mortality and renal failure in adult patients undergoing cardiac surgery?
Cohort (n=3,687)
No
Does intraoperative blood pressure variability computed by Poincaré plots and coefficient of variation predict 30-day mortality and renal failure in adult patients undergoing cardiac surgery?
Intraoperative blood pressure variability measured by Poincaré plots and coefficient of variation does not improve the prediction of 30-day mortality or renal failure beyond standard preoperative risk scores in cardiac surgery patients.
These metrics add no value to STS-based prediction; leaves open whether alternative variability indices warrant prospective testing.
Background Recent literature suggests a significant association between blood pressure variability (BPV) and postoperative outcomes after cardiac surgery. However, its outcome prediction ability remains unclear. Current prediction models use static preoperative patient factors. We aimed to test the performance of Poincaré plots and coefficient of variation (CV) independently by measuring intraoperative blood pressure variability. Methods In this retrospective, observational, cohort study, 3687 adult patients (> 18 years) undergoing cardiac surgery requiring cardio-pulmonary bypass from 2008 to 2014 were included. Blood pressure variability was computed by Poincare plots and CV. Standard descriptors (SD) SD1, SD2 were measured with Poincare plots by ellipse fitting technique. The outcomes analyzed were the 30-day mortality and postoperative renal failure. Logistic regression models adjusted for preoperative and surgical factors were constructed to evaluate the association between BPV parameters and outcomes. C-statistics were used to analyse the predictive ability. Results Analysis found that, 99 (2.7%) patients died within 30 days and 105 (2.8%) patients suffered from in-hospital renal failure. Logistic regression models including BPV parameters (standard descriptors from Poincare plots and CV) performed poorly in predicting postoperative 30-day mortality and renal failure [Concordance(C)-Statistic around 0.5]. They did not add any significant value to the standard STS risk score [C-statistic: STS alone 0.7, STS + BPV parmeters 0.7]. Conclusions In conclusion, BP variability computed from Poincare plots and CV were not predictive of mortality and renal failure in cardiac surgical patients. Patient co-morbid conditions and other preoperative factors are still the gold standard for outcome prediction. Future directions include analysis of dynamic parameters such as complexity of physiological signals in identifying high risk patients and tailoring management accordingly.
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Packiasabapathy et al. (2019) conducted a cohort in Cardiac surgery requiring cardio-pulmonary bypass (n=3,687). Intraoperative blood pressure variability (Poincaré plot descriptors and coefficient of variation) vs. Standard STS risk score was evaluated on 30-day mortality and in-hospital renal failure (C-statistic ~0.5). Intraoperative blood pressure variability computed from Poincaré plots and coefficient of variation performed poorly in predicting 30-day mortality and renal failure (C-statistic ~0.5) and did not improve the standard STS risk score.
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