Key result
Intraoperative blood pressure variability parameters, including Poincaré plot descriptors and coefficient of variation, performed poorly in predicting 30-day mortality and in-hospital renal failure, adding no significant value to conventional risk models.
Why the study?
Blood pressure variability is associated with postoperative outcomes after cardiac surgery, but its outcome prediction ability remains unclear as current models use static preoperative factors.
Does intraoperative blood pressure variability measured by Poincaré plots and coefficient of variation improve the prediction of 30-day mortality and renal failure in adult patients undergoing cardiac surgery compared to conventional preoperative risk models?
Observational (n=3,687)
No
Does intraoperative blood pressure variability measured by Poincaré plots and coefficient of variation improve the prediction of 30-day mortality and renal failure in adult patients undergoing cardiac surgery compared to conventional preoperative risk models?
Intraoperative blood pressure variability measured by Poincaré plots and coefficient of variation does not add significant predictive value for 30-day mortality or renal failure beyond standard preoperative risk indices in cardiac surgery patients.
BP variability metrics add no value to standard perioperative risk models; leaves open identification of useful intraoperative predictors.
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 BP variability.Methods In this retrospective, observational, cohort study, 3687 adult patients undergoing cardiac surgery from 2008 to 2013 were included. Poincaré plots from BP data and descriptors SD1, SD2 by ellipse fitting technique were computed. 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 (SD1, SD2 and CV) performed poorly in predicting postoperative 30-day mortality and renal failure. They did not add any significant value to the conventional prediction model.Conclusions We demonstrate the feasibility of applying Poincaré plots for BP variability analysis. Patient comorbid 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 an observational in Cardiac surgery requiring cardiopulmonary bypass (n=3,687). Intraoperative blood pressure variability (Poincaré plot descriptors and coefficient of variation) vs. Conventional preoperative risk indices (STS risk scores) was evaluated on 30-day mortality and in-hospital renal failure. Intraoperative blood pressure variability parameters, including Poincaré plot descriptors and coefficient of variation, performed poorly in predicting 30-day mortality and in-hospital renal failure, adding no significant value to conventional risk models.
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