Cardiac surgical outcome prediction by blood pressure variability indices Poincaré plot and coefficient of variation: a retrospective study

Abstract 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 explored...

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Main Authors: Senthil Packiasabapathy, Varesh Prasad, Valluvan Rangasamy, David Popok, Xinling Xu, Victor Novack, Balachundhar Subramaniam
Format: Article
Language:English
Published: BMC 2020-03-01
Series:BMC Anesthesiology
Subjects:
Online Access:http://link.springer.com/article/10.1186/s12871-020-00972-5
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spelling doaj-6d59871fc51b4f7e9e611e6d724407b42020-11-25T02:47:52ZengBMCBMC Anesthesiology1471-22532020-03-0120111210.1186/s12871-020-00972-5Cardiac surgical outcome prediction by blood pressure variability indices Poincaré plot and coefficient of variation: a retrospective studySenthil Packiasabapathy0Varesh Prasad1Valluvan Rangasamy2David Popok3Xinling Xu4Victor Novack5Balachundhar Subramaniam6Department of Anesthesia, Critical Care, and Pain Medicine, Beth Israel Deaconess Medical Center, Harvard Medical SchoolHarvard-Massachusetts Institute of Technology Program in Health Sciences and TechnologyDepartment of Anesthesia, Critical Care, and Pain Medicine, Beth Israel Deaconess Medical Center, Harvard Medical SchoolClinical Research Center, Soroka University Medical Center and Faculty of Health Sciences, Ben-Gurion University of the NegevDepartment of Anesthesia, Critical Care, and Pain Medicine, Beth Israel Deaconess Medical Center, Harvard Medical SchoolClinical Research Center, Soroka University Medical Center and Faculty of Health Sciences, Ben-Gurion University of the NegevDepartment of Anesthesia, Critical Care, and Pain Medicine, Beth Israel Deaconess Medical Center, Harvard Medical SchoolAbstract 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 explored the ability of Poincaré plots and coefficient of variation (CV) by measuring intraoperative BPV in predicting adverse outcomes. 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 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.http://link.springer.com/article/10.1186/s12871-020-00972-5BP variabilityPoincaré plotCoefficient of variationCardiac surgerySTS risk score
collection DOAJ
language English
format Article
sources DOAJ
author Senthil Packiasabapathy
Varesh Prasad
Valluvan Rangasamy
David Popok
Xinling Xu
Victor Novack
Balachundhar Subramaniam
spellingShingle Senthil Packiasabapathy
Varesh Prasad
Valluvan Rangasamy
David Popok
Xinling Xu
Victor Novack
Balachundhar Subramaniam
Cardiac surgical outcome prediction by blood pressure variability indices Poincaré plot and coefficient of variation: a retrospective study
BMC Anesthesiology
BP variability
Poincaré plot
Coefficient of variation
Cardiac surgery
STS risk score
author_facet Senthil Packiasabapathy
Varesh Prasad
Valluvan Rangasamy
David Popok
Xinling Xu
Victor Novack
Balachundhar Subramaniam
author_sort Senthil Packiasabapathy
title Cardiac surgical outcome prediction by blood pressure variability indices Poincaré plot and coefficient of variation: a retrospective study
title_short Cardiac surgical outcome prediction by blood pressure variability indices Poincaré plot and coefficient of variation: a retrospective study
title_full Cardiac surgical outcome prediction by blood pressure variability indices Poincaré plot and coefficient of variation: a retrospective study
title_fullStr Cardiac surgical outcome prediction by blood pressure variability indices Poincaré plot and coefficient of variation: a retrospective study
title_full_unstemmed Cardiac surgical outcome prediction by blood pressure variability indices Poincaré plot and coefficient of variation: a retrospective study
title_sort cardiac surgical outcome prediction by blood pressure variability indices poincaré plot and coefficient of variation: a retrospective study
publisher BMC
series BMC Anesthesiology
issn 1471-2253
publishDate 2020-03-01
description Abstract 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 explored the ability of Poincaré plots and coefficient of variation (CV) by measuring intraoperative BPV in predicting adverse outcomes. 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 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.
topic BP variability
Poincaré plot
Coefficient of variation
Cardiac surgery
STS risk score
url http://link.springer.com/article/10.1186/s12871-020-00972-5
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