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

2020 ◽  
Vol 20 (1) ◽  
Author(s):  
Senthil Packiasabapathy ◽  
Varesh Prasad ◽  
Valluvan Rangasamy ◽  
David Popok ◽  
Xinling Xu ◽  
...  
Keyword(s):  
Blood Pressure ◽  
Retrospective Study ◽  
Coefficient Of Variation ◽  
Surgical Outcome ◽  
Blood Pressure Variability ◽  
Outcome Prediction ◽  
Poincaré Plot

scholarly journals Cardiac Surgical Outcome Prediction by Blood Pressure Variability Indices Poincaré plot and Coefficient of Variation: an Observational Study

2019 ◽  
Author(s):  
Senthil Packiasabapathy K ◽  
Varesh Prasad ◽  
Valluvan Rangasamy ◽  
David Popok ◽  
Xinling Xu ◽  
...  
Keyword(s):  
Blood Pressure ◽  
Renal Failure ◽  
Logistic Regression ◽  
Cardiac Surgery ◽  
Coefficient Of Variation ◽  
Blood Pressure Variability ◽  
Regression Models ◽  
Outcome Prediction ◽  
Prediction Ability ◽  
Logistic Regression Models

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 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.

scholarly journals Cardiac Surgical Outcome Prediction by Blood Pressure Variability Indices Poincaré plot and Coefficient of Variation: an Observational Study

2020 ◽  
Author(s):  
Senthil Packiasabapathy K ◽  
Varesh Prasad ◽  
Valluvan Rangasamy ◽  
David Popok ◽  
Xinling Xu ◽  
...  
Keyword(s):  
Blood Pressure ◽  
Renal Failure ◽  
Logistic Regression ◽  
Cardiac Surgery ◽  
Coefficient Of Variation ◽  
Blood Pressure Variability ◽  
Regression Models ◽  
Outcome Prediction ◽  
Logistic Regression Models ◽  
C Statistic

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.

scholarly journals Cardiac Surgical Outcome Prediction by Blood Pressure Variability Indices Poincaré plot and Coefficient of Variation: an Observational Study

2020 ◽  
Author(s):  
Senthil Packiasabapathy K ◽  
Varesh Prasad ◽  
Valluvan Rangasamy ◽  
David Popok ◽  
Xinling Xu ◽  
...  
Keyword(s):  
Blood Pressure ◽  
Renal Failure ◽  
Logistic Regression ◽  
Cardiac Surgery ◽  
Coefficient Of Variation ◽  
Blood Pressure Variability ◽  
Regression Models ◽  
Outcome Prediction ◽  
Logistic Regression Models ◽  
C Statistic

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.

scholarly journals Cardiac Surgical Outcome Prediction by Blood Pressure Variability Indices Poincaré plot and Coefficient of Variation: a Retrospective Study

2019 ◽  
Author(s):  
Senthil Packiasabapathy K ◽  
Varesh Prasad ◽  
Valluvan Rangasamy ◽  
David Popok ◽  
Xinling Xu ◽  
...  
Keyword(s):  
Blood Pressure ◽  
Renal Failure ◽  
Logistic Regression ◽  
Cardiac Surgery ◽  
Coefficient Of Variation ◽  
Blood Pressure Variability ◽  
Regression Models ◽  
Outcome Prediction ◽  
Logistic Regression Models ◽  
C Statistic

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 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.

Dose-Response Relationship Between Long-Term Blood Pressure Variability and Cognitive Decline

Stroke ◽  
2021 ◽  
Author(s):  
Chenglong Li ◽  
Yanjun Ma ◽  
Rong Hua ◽  
Zhenchun Yang ◽  
Baoliang Zhong ◽  
...  
Keyword(s):  
Blood Pressure ◽  
Cognitive Decline ◽  
Dose Response ◽  
Coefficient Of Variation ◽  
Blood Pressure Variability ◽  
Turning Point ◽  
Linear Mixed Model ◽  
Response Relationship ◽  
Dose Response Relationship

Background and Purpose: We aimed to test whether higher long-term blood pressure variability was associated with accelerated rate of cognitive decline and evaluate potential dose-response relationship. Methods: Original survey data from the Health and Retirement Study and the English Longitudinal Study of Ageing were used. Standardized Z score of cognitive function was the main outcome measure. Visit-to-visit blood pressure SD, coefficient of variation, and variation independent of mean were used. Linear mixed model and restricted spline were applied to assess association and explore dose-response pattern. Segmented regression was used to analyze dose-response relationship and estimate turning point. Meta-analysis using random-effects model was conducted to pool results, with I 2 used to test heterogeneity. Results: A total of 12 298 dementia-free participants were included (mean age: 64.6±8.6 years). Significant association was observed between blood pressure variability and cognitive decline. Each 10% increment in coefficient of variation of systolic and diastolic blood pressure was associated with accelerated global cognitive decline of 0.026 SD/y (95% CI, 0.016–0.036, P< 0.001) and 0.022 SD/y (95% CI, 0.017–0.027, P< 0.001), respectively. Nonlinear dose-response relationship was found ( P< 0.001 for nonlinearity), with clear turning point observed ( P< 0.001 for change in slopes). Conclusions: Higher long-term blood pressure variability was associated with accelerated cognitive decline among general adults aged ≥50 years, with nonlinear dose-response relationship. Further randomized controlled trials are warranted to evaluate potential benefits of blood pressure variability-lowering strategies from a cognitive health perspective.

scholarly journals Age and sex distribution of beat-to-beat blood pressure variability after transient ischemic attack and minor stroke: A population-based study

2020 ◽  
pp. 174749302097190
Author(s):  
Alastair JS Webb ◽  
Amy Lawson ◽  
Sara Mazzucco ◽  
Linxin Li ◽  
Peter M Rothwell
Keyword(s):  
Risk Factors ◽  
Blood Pressure ◽  
Ischemic Stroke ◽  
Coefficient Of Variation ◽  
Blood Pressure Variability ◽  
Population Based ◽  
Elevated Blood Pressure ◽  
Minor Stroke ◽  
Elevated Blood ◽  
Sex Distribution

Background Beat-to-beat blood pressure variability is associated with increased stroke risk but its importance at different ages is unclear. Aims To determine the age-sex distribution of blood pressure variability in patients with transient ischemic stroke or minor stroke. Methods In consecutive patients within six weeks of transient ischemic stroke or non-disabling stroke (Oxford Vascular Study), non-invasive blood pressure was measured beat-to-beat over five minutes (Finometer). The age-sex distribution of blood pressure variability (residual coefficient of variation) was determined for systolic blood pressure and diastolic blood pressure. The risk of top-decile blood pressure variability was estimated (logistic regression), unadjusted, and adjusted for age, sex, and cardiovascular risk factors. Results In 908 of 1013 patients, excluding 54 in atrial fibrillation and 51 with low quality recordings, residual coefficient of variation was positively skewed with a median systolic residual coefficient of variation of 4.2% (IQR 3.2–5.5) and diastolic residual coefficient of variation of 3.9% (3.0–5.5), with 90th centile thresholds of 7.2 and 7.3%. Median systolic residual coefficient of variation was higher in patients under 50 years (4.5 and 3.0–5.3) compared to 60–70 years (4.1 and 3.2–5.2), but rose to 4.5% (3.5–6.9) above 80 years, with an increasingly positive skew. The proportion of patients with markedly elevated blood pressure variability in the top-decile increased significantly per decade (OR 1.72, p < 0.001), after adjustment for sex and risk factors. Conclusions Median beat-to-beat blood pressure variability fell in midlife, reflecting loss of physiological, organized blood pressure variability. However, rates of markedly elevated blood pressure variability significantly increased with greater age, suggesting that blood pressure variability may be particularly important in older patients.

Within-Visit Blood Pressure Variability in an Unselected Adult Population

2021 ◽  
Vol 34 (10) ◽  
pp. 1125-1126
Author(s):  
Xin Chen ◽  
Shao-kun Xu ◽  
Yan Li ◽  
Zhe Hu ◽  
Hong-yu Wang ◽  
...  
Keyword(s):  
Blood Pressure ◽  
Standard Deviation ◽  
Systolic Blood Pressure ◽  
Diastolic Blood Pressure ◽  
Coefficient Of Variation ◽  
Blood Pressure Variability ◽  
Adult Population ◽  
Linear Regression Analysis ◽  
Multiple Linear Regression Analysis ◽  
Pressure Measurements

Abstract Background To investigate blood pressure variability among 3 successive blood pressure measurements in an unselected nationwide population in China. Methods A total of 77,549 participants were included from measurements in May 2017 in China. Blood pressure was measured 3 times consecutively with a half minute interval. Blood pressure variability was estimated with the standard deviation and coefficient of variation of the systolic and diastolic blood pressure. Results Not all participants showed a decreasing trend with increasing number of measurements. In fact, 14% of the participants showed at least 5 mm Hg increase in systolic blood pressure. The coefficient of variation of systolic and diastolic blood pressure in women was higher than in men [(4.2 ± 3.3)% vs. (4.1 ± 3.3)%, (4.7 ± 4.0)% vs. (4.6 ± 4.1)%; P &lt; 0.05]. The differences were significant (P &lt; 0.01) among different groups of age and blood pressure levels. Multiple linear regression analysis showed that the systolic blood pressure variability indexes were inversely associated with age but positively associated with the level of the first systolic blood pressure reading (P &lt; 0.01). The systolic blood pressure standard deviation and coefficient of variation in females were higher than in males (P &lt; 0.01). Conclusions Not all subjects demonstrate a decreasing trend with increasing number of blood pressure measurements. Within-visit blood pressure variability varies with age, gender, and blood pressure.

scholarly journals Blood Pressure Variability and Prognosis in Hemodialysis Patients: A Systematic Review and Meta-Analysis

2020 ◽  
pp. 1-14
Author(s):  
Yuliang Zhao ◽  
Letian Yang ◽  
Shaobin Yu ◽  
Stephen Salerno ◽  
Yi Li ◽  
...  
Keyword(s):  
Blood Pressure ◽  
Systolic Blood Pressure ◽  
Cardiovascular Mortality ◽  
Coefficient Of Variation ◽  
Blood Pressure Variability ◽  
Meta Analysis ◽  
Cochrane Library ◽  
All Cause Mortality ◽  
The Cochrane Library ◽  
Stratified Analysis

<b><i>Background:</i></b> The prognostic value of blood pressure variability (BPV) in patients receiving hemodialysis is inconclusive. In this study, we aimed to assess the association between BPV and clinical outcomes in the hemodialysis population. <b><i>Methods:</i></b> Pubmed/Medline, EMBASE, Ovid, the Cochrane Library, and the Web of Science databases were searched for relevant articles published until April 1, 2020. Studies on the association between BPV and prognosis in patients receiving hemodialysis were included. <b><i>Results:</i></b> A total of 14 studies (37,976 patients) were included in the analysis. In patients receiving hemodialysis, systolic BPV was associated with higher all-cause (hazard ratio [HR]: 1.13; 95% confidence interval [CI]: 1.07–1.19; <i>p</i> &#x3c; 0.001) and cardiovascular (HR: 1.16; 95% CI: 1.10–1.22; <i>p</i> &#x3c; 0.001) mortality. In the stratified analysis of systolic BPV, interdialytic systolic BPV, rather than 44-h ambulatory systolic BPV or intradialytic systolic BPV, was identified to be related to both all-cause (HR: 1.11; 95% CI: 1.05–1.17; <i>p</i> = 0.001) and cardiovascular (HR: 1.14; 95% CI: 1.06–1.22; <i>p</i> &#x3c; 0.001) mortality. Among the different BPV metrics, the coefficient of variation of systolic blood pressure was a predictor of both all-cause (<i>p</i> = 0.01) and cardiovascular (<i>p</i> = 0.002) mortality. Although diastolic BPV was associated with all-cause mortality (HR: 1.09; 95% CI: 1.01–1.17; <i>p</i> = 0.02) in patients receiving hemodialysis, it failed to predict cardiovascular mortality (HR: 0.86; 95% CI: 0.52–1.42; <i>p</i> = 0.56). <b><i>Conclusions:</i></b> This meta-analysis revealed that, in patients receiving hemodialysis, interdialytic systolic BPV was associated with both increased all-cause and cardiovascular mortality. Furthermore, the coefficient of variation of systolic blood pressure was identified as a potentially promising metric of BPV in predicting all-cause and cardiovascular mortality. The use of 44-h ambulatory systolic BPV, intradialytic systolic BPV, and metrics of diastolic BPV in the prognosis of the hemodialysis population require further investigation (PROSPERO registry number: CRD42019139215).

scholarly journals Blood Pressure Variability in Acute Ischemic Stroke: The Role of Early Recanalization

2018 ◽  
Vol 80 (1-2) ◽  
pp. 63-67 ◽  
Author(s):  
Ana Inês Martins ◽  
João Sargento-Freitas ◽  
Joana Jesus-Ribeiro ◽  
Inês Correia ◽  
Leila Cardoso ◽  
...  
Keyword(s):  
Blood Pressure ◽  
Ischemic Stroke ◽  
Retrospective Study ◽  
Clinical Outcome ◽  
Functional Outcome ◽  
Blood Pressure Variability ◽  
Multivariate Analyses ◽  
Modified Rankin Scale ◽  
Arterial Recanalization

We performed a retrospective study with the aim of investigating the association between blood pressure (BP) variability in the first 24 h after ischemic stroke and functional outcome, regarding arterial recanalization status. A total of 674 patients diagnosed with acute stroke and treated with revascularization therapies were enrolled. Systolic and diastolic BP values of the first 24 h after stroke were collected and their variation quantified through standard deviation. Recanalization state was evaluated at 6 h and clinical outcome at 3 months was assessed by modified Rankin Scale. In multivariate analyses systolic BP variability in the first 24 h post-stroke showed an association with 3 months clinical outcome in the whole population and non-recanalyzed patients. In recanalyzed patients, BP variability did not show a significant association with functional outcome.

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