Blood Pressure Coefficient of Variation and Its Association With Cardiac Surgical Outcomes

Hypertension, Blood Pressure Variability, and Acute Kidney Injury in Hospitalized Children

Background Although hypertensive blood pressure measurements are common in hospitalized children, the degree of inpatient hypertension and blood pressure variability (BPV) associated with end organ complications like acute kidney injury (AKI) is unknown. Methods and Results All analyses are based on a retrospective cohort of children aged 1 to 17 years with ≥2 creatinine measurements during admission from 2014 to 2018. We used time-updated Cox models to evaluate the association between BPV and hypertension with AKI. Time-varying BPV and hypertension were based on blood pressure in the preceding 72 hours. For the analysis of hypertension and AKI, we excluded patients on vasopressors to ensure comparison between hypertensive and normotensive patients. During 5425 pediatric encounters, 258 430 blood pressure measurements were recorded (median [interquartile range] 22 [11-47] readings per encounter). Among all measurements, 32.7% were ≥95th percentile and 18.9% were ≥99th percentile for age, sex, and height. AKI occurred in 389 (7.2%) encounters. We observed a U-shaped relationship between mean blood pressure and incident AKI. BPV was associated with AKI, with the largest effect sizes in the systolic and mean arterial pressure variability measures. Multiple hypertension thresholds were associated with AKI after controlling for confounders. In an additional multivariable model adjusted for BPV, the association between hypertension and AKI was attenuated but remained significant for hypertension defined as three stage 2 measurements in 1 day (hazard ratio, 1.43 [95% CI, 1.01-2.01]). Conclusions Hypertension and BPV are associated with AKI in hospitalized children. Future studies are needed to determine how pharmacologic and nonpharmacologic interventions modify AKI risk in pediatric inpatients with hypertension.

Association between intraoperative pulmonary artery pressure and cardiovascular complications after off-pump coronary artery bypass surgery: a single-center observational study

BACKGROUND

The impact of intraoperative pulmonary hemodynamics on prognosis after off-pump coronary artery bypass (OPCAB) surgery remains unknown. In this study, we examined the association between intraoperative vital signs and the development of major adverse cardiovascular events (MACE) during hospitalization or within 30 days postoperatively.

METHODS

This retrospective study analyzed data from a university hospital. The study cohort comprised consecutive patients who underwent isolated OPCAB surgery between November 2013 and July 2021. We calculated the mean and coefficient of variation of vital signs obtained from the intra-arterial catheter, pulmonary artery catheter, and pulse oximeter. The optimal cut-off was defined as the receiver operating characteristic curve (ROC) with the largest Youden index (Youden index = sensitivity + specificity - 1). Multivariate logistic regression analysis ROC curves were used to adjust all baseline characteristics that yielded P values of < 0.05.

RESULTS

In total, 508 patients who underwent OPCAB surgery were analyzed. The mean patient age was 70.0 ± 9.7 years, and 399 (79%) were male. There were no patients with confirmed or suspected preoperative pulmonary hypertension. Postoperative MACE occurred in 32 patients (heart failure in 16, ischemic stroke in 16). The mean pulmonary artery pressure (PAP) was significantly higher in patients with than without MACE (19.3 ± 3.0 vs. 16.7 ± 3.4 mmHg, respectively; absolute difference, 2.6 mmHg; 95% confidence interval, 1.5 to 3.8). The area under the ROC curve of PAP for the prediction of MACE was 0.726 (95% confidence interval, 0.645 to 0.808). The optimal mean PAP cut-off was 18.8 mmHg, with a specificity of 75.8% and sensitivity of 62.5% for predicting MACE. After multivariate adjustments, high PAP remained an independent risk factor for MACE.

CONCLUSIONS

Our findings provide the first evidence that intraoperative borderline pulmonary hypertension may affect the prognosis of patients undergoing OPCAB surgery. Future large-scale prospective studies are needed to verify the present findings.

Predictive Capacity of Beat-to-Beat Blood Pressure Variability for Cardioautonomic and Vascular Dysfunction in Early Metabolic Challenge

Diabetic patients present established cardiovascular disease at the onset of diagnostic metabolic symptoms. While premature autonomic and vascular deterioration considered risk factors for major cardiovascular complications of diabetes, present in initial stages of metabolic impairment, their early detection remains a significant challenge impeding timely intervention. In the present study, we examine the utility of beat-to-beat blood pressure variability (BPV) parameters in capturing subtle changes in cardiac autonomic and vascular control distinguishing between various risk categories, independent of the average BP. A rat model of mild hypercaloric (HC) intake was used to represent the insidious cardiovascular changes associated with early metabolic impairment. Invasive hemodynamics were used to collect beat-to-beat BP time series in rats of either sex with different durations of exposure to the HC diet. Linear (standard deviation and coefficient of variation) and nonlinear (approximate entropy, ApEn, and self-correlation of detrended fluctuation analysis, α) BPV parameters were calculated to assess the impact of early metabolic impairment across sexes and feeding durations. HC-fed male, but not female, rats developed increased fat:lean ratio as well as hyperinsulinemia. Unlike linear parameters, multivariate analysis showed that HC-fed rats possessed lower ApEn and higher α, consistent with early changes in heart rate variability and blunting of parasympathetic baroreceptor sensitivity, particularly in males. Moreover, logistic regression demonstrated the superiority of nonlinear parameters of diastolic BPV in predicting a prediabetic disease state. Our findings support the use of nonlinear beat-to-beat BPV for early detection of cardiovascular derangements in the initial stages of metabolic impairment.

Intraoperative Hypotension and Acute Kidney Injury, Stroke, and Mortality during and outside Cardiopulmonary Bypass: A Retrospective Observational Cohort Study

BACKGROUND

In cardiac surgery, the association between hypotension during specific intraoperative phases or vasopressor-inotropes with adverse outcomes remains unclear. This study's hypothesis was that intraoperative hypotension duration throughout the surgery or when separated into hypotension during and outside cardiopulmonary bypass may be associated with postoperative major adverse events.

METHODS

This retrospective observational cohort study included data for adults who had cardiac surgery between 2008 and 2016 in a tertiary hospital. Intraoperative hypotension was defined as mean arterial pressure of less than 65 mmHg. The total duration of hypotension was divided into three categories based on the fraction of overall hypotension duration that occurred during cardiopulmonary bypass (more than 80%, 80 to 60%, and less than 60%). The primary outcome was a composite of stroke, acute kidney injury, or mortality during the index hospitalization. The association with the composite outcome was evaluated for duration of hypotension during the entire surgery, outside cardiopulmonary bypass, and during cardiopulmonary bypass and the fraction of hypotension during cardiopulmonary bypass adjusting for vasopressor-inotrope dose, milrinone dose, patient, and surgical factors.

RESULTS

The composite outcome occurred in 256 (5.1%) of 4,984 included patient records; 66 (1.3%) patients suffered stroke, 125 (2.5%) had acute kidney injury, and 109 (2.2%) died. The primary outcome was associated with total duration of hypotension (adjusted odds ratio, 1.05; 95% CI, 1.02 to 1.08; P = 0.032), hypotension outside cardiopulmonary bypass (adjusted odds ratio, 1.06; 95% CI, 1.03 to 1.10; P = 0.001) per 10-min exposure to mean arterial pressure of less than 65 mmHg, and fraction of hypotension duration during cardiopulmonary bypass of less than 60% (reference greater than 80%; adjusted odds ratio, 1.67; 95% CI, 1.10 to 2.60; P = 0.019) but not with each 10-min period hypotension during cardiopulmonary bypass (adjusted odds ratio, 1.04; 95% CI, 0.99 to 1.09; P = 0.118), fraction of hypotension during cardiopulmonary bypass of 60 to 80% (adjusted odds ratio, 1.45; 95% CI, 0.97 to 2.23; P = 0.082), or total vasopressor-inotrope dose (adjusted odds ratio, 1.00; 95% CI, 1.00 to 1.00; P = 0.247).

CONCLUSIONS

This study confirms previous single-center findings that intraoperative hypotension throughout cardiac surgery is associated with an increased risk of acute kidney injury, mortality, or stroke.

EDITOR’S PERSPECTIVE

The Relationship Between Short-Term Mean Arterial Pressure Variability and Mortality in Critically Ill Patients

Background

Increased or decreased blood pressure variability may affect the perfusion of tissues and organs, leading to acute kidney injury and death. This study was conducted to explore the relationship between mean arterial pressure variability and short- and long-term mortality in critically ill patients.

Methods

We used patient data from the MIMIC-III database for cohort study. According to the recorded mean arterial pressure during the first 24 h in the intensive care unit, we calculated each patient’s two variability parameters –coefficient of variation and average real variability. The primary outcome was in-hospital mortality and the secondary outcomes were 28-day mortality and 1-year mortality. We conducted smooth spline models to examine the possible nonlinear associations between blood pressure variability and mortality. According to the smoothing curve, we further developed a two-piecewise linear regression model to find out the threshold effect. Multivariable logistic regression or Cox proportional hazards model was used to evaluate the relationship. Kaplan–Meier survival analysis for 28-day and 1-year mortality was performed. Subgroup analysis explored the factors modifying the relationship between them.

Results

A total of 12,867 patients were enrolled in the study, 1,320 in-hospital death, 1,399 28-day death, and 2,734 1-year death occurred. The smooth spline showed death risk was the lowest when average real variability was around 7.2 mmHg. After adjusting for covariates, logistic or Cox regression showed the highest MAP variability level was strongly associated with increased mortality in the hospital (odds ratio: 1.44; 95% CI, 1.21∼1.72), at 28 days (hazard ratio: 1.28; 95% CI, 1.1∼1.5), and at 1 year (hazard ratio: 1.27; 95% CI, 1.14∼1.42) compared with the second level of average real variability group. The survival curve plot showed patients with higher average real variability had a higher risk of 28-day and 1-year mortality. This relationship remained remarkable in patients with low or high Sequential Organ Failure Assessment scores in the sensitivity analysis. The two-piecewise linear regression model showed that lower ARV was a risk factor for 28-day (HR 0.72, 95% CI, 0.57∼0.91) and 1-year mortality (HR 0.81, 95% CI, 0.68∼0.96) when ARV was less than 7.2 mmHg, higher ARV was a risk factor for 28-day mortality (HR 1.1, 95% CI, 1.04∼1.17) and 1-year mortality (HR 1.07, 95% CI, 1.02∼1.12) when ARV was greater than 7.2 mmHg.

Conclusion

Blood pressure variability predicts mortality in critically ill patients. Individuals with higher or lower mean arterial pressure average real variability during the first day in ICU may have an increased risk of death.

The burden of perioperative hypertension/hypotension: A systematic review

Study objective

Our goal is to review the outcomes of acute hypertensive/hypotensive episodes from articles published in the past 10 years that assessed the short- and long-term impact of acute hypertensive/hypotensive episodes in the perioperative setting.

Methods

We conducted a systematic peer review based upon PROSPERO and Cochrane Handbook protocols. The following study characteristics were collected: study type, author, year, population, sample size, their definition of acute hypertension, hypotension or other measures, and outcomes (probabilities, odds ratio, hazard ratio, and relative risk) and the p-values; and they were classified according to the type of surgery (cardiac and non-cardiac).

Results

A total of 3,680 articles were identified, and 66 articles fulfilled the criteria for data extraction. For the perioperative setting, the number of articles varies by outcome: 20 mortality, 16 renal outcomes, 6 stroke, 7 delirium and 34 other outcomes. Hypotension was reported to be associated with mortality (OR 1.02–20.826) as well as changes from the patient’s baseline blood pressure (BP) (OR 1.02–1.36); hypotension also had a role in the development of acute kidney injury (AKI) (OR 1.03–14.11). Postsurgical delirium was found in relation with BP lability (OR 1.018–1.038) and intra- and postsurgical hypotension (OR 1.05–1.22), and hypertension (OR 1.44–2.34). Increased OR (37.67) of intracranial hemorrhage was associated to postsurgical systolic BP >130 mmHg. There was a wide range of additional diverse outcomes related to hypo-, hypertension and BP lability.

Conclusions

The perioperative management of BP influences short- and long-term effects of surgical procedures in cardiac and non-cardiac interventions; these findings support the burden of BP fluctuations in this setting.

Low Mean Arterial Pressure During Cardiopulmonary Bypass and the Risk of Acute Kidney Injury: A Propensity Score Matched Observational Study

INTRODUCTION

Low mean arterial pressure (MAP) periods occur frequently during cardiopulmonary bypass (CPB), and their management remains controversial. Our aim was to correlate MAP during CPB with the occurrence of post-operative acute kidney injury (AKI), considering two different parameters: consecutive and cumulative low MAP periods.

METHODS

Single-centre observational retrospective study including 250 patients submitted to non-emergent aortic valve replacement, with tepid to mild hypothermia (not below 32°C). The primary outcome was the occurrence of AKI. A propensity scored matching of 43 patients was used to adjust both populations (AKI and No AKI). MAP measures were automatically and continuously recorded during CPB. Low MAP periods were analysed employing two parameters: consecutive and the cumulative sum of time.

RESULTS

Patients who experienced at least 5 min with MAP <50 mmHg had an increased risk of post-operative AKI (OR infinity; 95% CI, 1.47 to infinity; P = .026). The risk is also significant with MAP <40 mmHg (OR 2.78; 95% CI 1.1-6.9; = .044) and <30 mmHg (OR 3.36; 95% CI 1.2-9.2; P = .029). Post-operative AKI was associated with cumulative and consecutive periods of low MAP. Patients with periods of low MAP had higher levels of post-operative creatinine and reduced glomerular filtration rate (GFR). Patients with AKI had prolonged endotracheal ventilation time, and ICU and ward lengths of stay.

CONCLUSION

Low MAP periods during CPB are associated with an increased occurrence of post-operative AKI, leading to 1) higher creatinine levels; 2) decreased GFR and 3) longer ICU and ward lengths of stay. Both consecutive and cumulative periods of low MAP are associated with an increased risk of AKI. MAP appears to be an important contributor to post-operative AKI and should be carefully managed during CPB. Further studies must address if MAP variations lead to definitive and long-term consequences.

Assessment of Myocardial Function During Blood Pressure Manipulations Using Feature Tracking Cardiovascular Magnetic Resonance

Background: Coronary autoregulation is a feedback system, which maintains near-constant myocardial blood flow over a range of mean arterial pressure (MAP). Yet in emergency or peri-operative situations, hypotensive or hypertensive episodes may quickly arise. It is not yet established how rapid blood pressure changes outside of the autoregulation zone (ARZ) impact left (LV) and right ventricular (RV) function. Using cardiovascular magnetic resonance (CMR) imaging, measurements of myocardial tissue oxygenation and ventricular systolic and diastolic function can comprehensively assess the heart throughout a range of changing blood pressures.

Design and methods: In 10 anesthetized swine, MAP was varied in steps of 10–15 mmHg from 29 to 196 mmHg using phenylephrine and urapidil inside a 3-Tesla MRI scanner. At each MAP level, oxygenation-sensitive (OS) cine images along with arterial and coronary sinus blood gas samples were obtained and blood flow was measured from a surgically implanted flow probe on the left anterior descending coronary artery. Using CMR feature tracking-software, LV and RV circumferential systolic and diastolic strain parameters were measured from the myocardial oxygenation cines.

Results: LV and RV peak strain are compromised both below the lower limit (LV: Δ1.2 ± 0.4%, RV: Δ4.4 ± 1.2%, p < 0.001) and above the upper limit (LV: Δ2.1 ± 0.4, RV: Δ5.4 ± 1.4, p < 0.001) of the ARZ in comparison to a baseline of 70 mmHg. LV strain demonstrates a non-linear relationship with invasive and non-invasive measures of oxygenation. Specifically for the LV at hypotensive levels below the ARZ, systolic dysfunction is related to myocardial deoxygenation (β = −0.216, p = 0.036) in OS-CMR and both systolic and diastolic dysfunction are linked to reduced coronary blood flow (peak strain: β = −0.028, p = 0.047, early diastolic strain rate: β = 0.026, p = 0.002). These relationships were not observed at hypertensive levels.

Conclusion: In an animal model, biventricular function is compromised outside the coronary autoregulatory zone. Dysfunction at pressures below the lower limit is likely caused by insufficient blood flow and tissue deoxygenation. Conversely, hypertension-induced systolic and diastolic dysfunction points to high afterload as a cause. These findings from an experimental model are translatable to the clinical peri-operative environment in which myocardial deformation may have the potential to guide blood pressure management, in particular at varying individual autoregulation thresholds.

Explainable machine-learning predictions for complications after pediatric congenital heart surgery

The quality of treatment and prognosis after pediatric congenital heart surgery remains unsatisfactory. A reliable prediction model for postoperative complications of congenital heart surgery patients is essential to enable prompt initiation of therapy and improve the quality of prognosis. Here, we develop an interpretable machine-learning-based model that integrates patient demographics, surgery-specific features and intraoperative blood pressure data for accurately predicting complications after pediatric congenital heart surgery. We used blood pressure variability and the k-means algorithm combined with a smoothed formulation of dynamic time wrapping to extract features from time-series data. In addition, SHAP framework was used to provide explanations of the prediction. Our model achieved the best performance both in binary and multi-label classification compared with other consensus-based risk models. In addition, this explainable model explains why a prediction was made to help improve the clinical understanding of complication risk and generate actionable knowledge in practice. The combination of model performance and interpretability is easy for clinicians to trust and provide insight into how they should respond before the condition worsens after pediatric congenital heart surgery.

The association of blood pressure variability with adverse outcomes in a primary care chronic kidney disease cohort

BACKGROUND

Hypertension is common in individuals with chronic kidney disease and both conditions are associated with adverse outcomes including cardiovascular morbidity. Therefore, it is clinically important to identify methods of risk prediction in individuals with chronic kidney disease. Blood pressure variability has recently emerged as a predictor of cardiovascular events and mortality in the general population, with growing evidence indicating that it may play a similar role in individuals with chronic kidney disease. However, there have been no large studies assessing blood pressure variability in individuals with chronic kidney disease in primary care, where the majority of these patients are managed.

METHOD

Using a retrospective observational study design, we analyzed routinely collected blood pressure readings from 16 999 individuals in The Leicester and County Chronic Kidney Disease cohort. Standard deviation, coefficient of variation and average real variability of SBP were used to calculate blood pressure variability.

RESULTS

During a median follow-up of 5.0 (IQR 3.3--5.0) years, 2053 (12.1%) patients had cardiovascular events, death occurred in 5021 (29.6%) individuals and 156 (0.9%) individuals had endstage kidney disease events. In adjusted models, standard deviation and coefficient of variation were associated with cardiovascular events, all-cause mortality and endstage kidney disease. Average real variability was associated with all-cause mortality and cardiovascular events, but not endstage kidney disease.

CONCLUSION

Blood pressure variability may be an accessible, routinely collected, noninvasive measure for stratifying the risk of adverse events in individuals with chronic kidney disease in a primary care setting.

Intraoperative Data Enhance the Detection of High-Risk Acute Kidney Injury Patients When Added to a Baseline Prediction Model

BACKGROUND

Aspects of intraoperative management (eg, hypotension) are associated with acute kidney injury (AKI) in noncardiac surgery patients. However, it is unclear if and how the addition of intraoperative data affects a baseline risk prediction model for postoperative AKI.

METHODS

With institutional review board (IRB) approval, an institutional cohort (2005-2015) of inpatient intra-abdominal surgery patients without preoperative AKI was identified. Data from the American College of Surgeons National Surgical Quality Improvement Program (preoperative and procedure data), Anesthesia Information Management System (intraoperative data), and electronic health record (postoperative laboratory data) were linked. The sample was split into derivation/validation (70%/30%) cohorts. AKI was defined as an increase in serum creatinine ≥0.3 mg/dL within 48 hours or >50% within 7 days of surgery. Forward logistic regression fit a baseline model incorporating preoperative variables and surgical procedure. Forward logistic regression fit a second model incorporating the previously selected baseline variables, as well as additional intraoperative variables. Intraoperative variables reflected the following aspects of intraoperative management: anesthetics, beta-blockers, blood pressure, diuretics, fluids, operative time, opioids, and vasopressors. The baseline and intraoperative models were evaluated based on statistical significance and discriminative ability (c-statistic). The risk threshold equalizing sensitivity and specificity in the intraoperative model was identified.

RESULTS

Of 2691 patients in the derivation cohort, 234 (8.7%) developed AKI. The baseline model had c-statistic 0.77 (95% confidence interval [CI], 0.74-0.80). The additional variables added to the intraoperative model were significantly associated with AKI (P < .0001) and the intraoperative model had c-statistic 0.81 (95% CI, 0.78-0.83). Sensitivity and specificity were equalized at a risk threshold of 9.0% in the intraoperative model. At this threshold, the baseline model had sensitivity and specificity of 71% (95% CI, 65-76) and 69% (95% CI, 67-70), respectively, and the intraoperative model had sensitivity and specificity of 74% (95% CI, 69-80) and 74% (95% CI, 73-76), respectively. The high-risk group had an AKI risk of 18% (95% CI, 15-20) in the baseline model and 22% (95% CI, 19-25) in the intraoperative model.

CONCLUSIONS

Intraoperative data, when added to a baseline risk prediction model for postoperative AKI in intra-abdominal surgery patients, improves the performance of the model.

Beat-to-beat blood pressure variability: an early predictor of disease and cardiovascular risk

Blood pressure (BP) varies on the long, short and very-short term. Owing to the hidden physiological and pathological information present in BP time-series, increasing interest has been given to the study of continuous, beat-to-beat BP variability (BPV) using invasive and noninvasive methods. Different linear and nonlinear parameters of variability are employed in the characterization of BP signals in health and disease. Although linear parameters of beat-to-beat BPV are mainly measures of dispersion, such as standard deviation (SD), nonlinear parameters of BPV quantify the degree of complexity/irregularity- using measures of entropy or self-similarity/correlation. In this review, we summarize the value of linear and nonlinear parameters in reflecting different information about the pathophysiology of changes in beat-to-beat BPV independent of or superior to mean BP. We then provide a comparison of the relative power of linear and nonlinear parameters of beat-to-beat BPV in detecting early and subtle differences in various states. The practical advantage and utility of beat-to-beat BPV monitoring support its incorporation into routine clinical practices.

Relationship between blood pressure stability and mortality in cardiac surgery patients: retrospective cohort study

Performance measurement variables can be applied in clinical practice to evaluate hemodynamic instability. This study aimed to evaluate the relationship between the performance measurement of mean arterial pressure during cardiac surgery using cardiopulmonary bypass and postoperative mortality. A retrospective cohort study of patients who underwent cardiac surgery requiring cardiopulmonary bypass between 2013 and 2016 was conducted. The median performance error (MDPE) and median absolute performance error (MDAPE) were calculated using the preoperative mean arterial pressure as a reference, and intraoperative mean arterial pressures as measured values. Multivariable logistic regression analyses were performed using performance measurement variables to predict 30-day mortality. Overall survival according to performance measurement variables was evaluated using Cox proportional hazard models and Kaplan-Meier survival curves were generated to compare survival probability. Among 1203 patients, 110 (9.1%) died after surgery, and the 30-day mortality rate was 2.3% (28/1203). After adjusting for confounders, MDPE and MDAPE were significant mean arterial pressure derived predictors of 30-day mortality and overall survival. Intraoperative hypotension measured by performance measurement variables was independently associated with 30-day and overall mortality after cardiac surgery requiring cardiopulmonary bypass. Kaplan-Meier survival curves showed lower survival probability in patients with higher MDAPE during the pre- and post- cardiopulmonary bypass periods (P < 0.001 by log-rank test). Intraoperative hypotension measured by performance measurement variables was independently associated with 30-day and overall mortality after cardiac surgery requiring CPB. We propose that performance measurement variables are useful for quantifying the degree of intraoperative hypotension and predicting survival following cardiac surgery.Trial registration: ClinicalTrials.gov, identifier: NCT03785132.

Automated closed-loop versus manually controlled norepinephrine infusion in patients undergoing intermediate- to high-risk abdominal surgery: a randomised controlled trial

BACKGROUND

Hypotension occurs frequently during surgery and may be associated with adverse complications. Vasopressor titration is frequently used to correct hypotension, but requires considerable time and attention, potentially reducing the time available for other clinical duties. To overcome this issue, we have developed a closed-loop vasopressor (CLV) controller to help correct hypotension more efficiently. The aim of this randomised controlled study was to evaluate whether the CLV controller was superior to traditional vasopressor management at minimising hypotension in patients undergoing abdominal surgery.

METHODS

Thirty patients scheduled for elective intermediate-to high-risk abdominal surgery were randomised into two groups. In the CLV group, hypotension was corrected automatically via the CLV controller system, which adjusted the rate of a norepinephrine infusion according to MAP values recorded using an advanced haemodynamic device. In the control group, management of hypotension consisted of standard, manual adjustment of the norepinephrine infusion. The primary outcome was the percentage of time that a patient was hypotensive, defined as MAP <90% of their baseline value, during surgery.

RESULTS

The percentage of time patients were hypotensive during surgery was 10 times less in the CVL group than in the control group (1.6 [0.9-2.3]% vs 15.4 [9.9-24.3]%; difference: 13 [95% confidence interval: 9-19]; P<0.0001). The CVL group also spent much less time with MAP <65 mm Hg (0.2 [0.0-0.4]% vs 4.5 [1.1-7.9]%; P<0.0001).

CONCLUSIONS

In patients undergoing intermediate- to high-risk surgery under general anaesthesia, computer-assisted adjustment of norepinephrine infusion significantly decreases the incidence of hypotension compared with manual control.

CLINICAL TRIAL REGISTRATION

NCT04089644.

Automated Blood Pressure Control

Arterial pressure management is a crucial task in the operating room and intensive care unit. In high-risk surgical and in critically ill patients, sustained hypotension is managed with continuous infusion of vasopressor agents, which most commonly have direct α agonist activity like phenylephrine or norepinephrine. The current standard of care to guide vasopressor infusion is manual titration to an arterial pressure target range. This approach may be improved by using automated systems that titrate vasopressor infusions to maintain a target pressure. In this article, we review the evidence behind blood pressure management in the operating room and intensive care unit and discuss current and potential future applications of automated blood pressure control.

Machine Learning Models with Preoperative Risk Factors and Intraoperative Hypotension Parameters Predict Mortality After Cardiac Surgery

OBJECTIVES

Machine learning models used to predict postoperative mortality rarely include intraoperative factors. Several intraoperative factors like hypotension (IOH), vasopressor-inotropes, and cardiopulmonary bypass (CPB) time are significantly associated with postoperative outcomes. The authors explored the ability of machine learning models incorporating intraoperative risk factors to predict mortality after cardiac surgery.

DESIGN

Retrospective study.

SETTING

Tertiary hospital.

PARTICIPANTS

A total of 5,015 adults who underwent cardiac surgery from 2008 to 2016.

INTERVENTION

None.

MEASUREMENTS AND MAIN RESULTS

The intraoperative phase was divided into the following: (1) CPB, (2) outside CPB, and (3) total surgery for quantifying IOH only. Phase-specific IOH parameters (area under the curve for mean arterial pressure <65 mmHg), vasopressor-inotropes (norepinephrine equivalents), duration, and cross-clamp time, along with preoperative risk factors ,were incorporated into the models. The primary outcome was mortality. The following 5 models were applied to 3 intraoperative phases separately: (1) logistic regression, (2) random forests, (3) neural networks, (4) support vector machines, and (5) extreme gradient boosting (XGB). Mortality was predicted using area under the receiver operating characteristic curve. Of 5,015 patients included, 112 (2.2%) died. XGB model from the outside-CPB phase predicted mortality better with area under the receiver operating characteristic curve, 95% confidence interval (CI): 0.88(0.83-0.94); positive predictive value, 0.10(0.06-0.15); specificity 0.85 (0.83-0.87) and sensitivity 0.75 (0.57-0.90).

CONCLUSION

XGB machine learning model from IOH outside the CPB phase seemed to offer a better discrimination, sensitivity, specificity, and positive predictive value compared with other models. Machine learning models incorporating intraoperative adverse factors might offer better predictive ability for risk stratification and triaging of patients after cardiac surgery.

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

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.

Intraoperative Blood Pressure Variability Predicts Postoperative Mortality in Non-Cardiac Surgery-A Prospective Observational Cohort Study

Little is known about the clinical importance of blood pressure variability (BPV) during anesthesia in non-cardiac surgery. We sought to investigate the impact of intraoperative BPV on postoperative mortality in non-cardiac surgery subjects, taking into account patient- and procedure-related variables. This prospective observational study covered 835 randomly selected patients who underwent gastrointestinal (n = 221), gynecological (n = 368) and neurosurgical (n = 246) procedures. Patient’s and procedure’s risks were assessed according to the validated tools and guidelines. Blood pressure (systolic, SBP, and diastolic, DBP) was recorded in five-minute intervals during anesthesia. Mean arterial pressure (MAP) was assessed. Individual coefficients of variation (Cv) were calculated. Postoperative 30-day mortality was considered the outcome. Median SBP_Cv was 11.2% (IQR 8.4–14.6), DBP_Cv was 12.7% (IQR 9.8–16.3) and MAP_Cv was 10.96% (IQR 8.26–13.86). Mortality was 2%. High SBP_Cv (i.e., ≥11.9%) was associated with increased mortality by 4.5 times (OR = 4.55; 95% CI 1.48–13.93; p = 0.008). High DBP_Cv (i.e., ≥22.4%) was associated with increased mortality by nearly 10 times (OR = 9.73; 95% CI 3.26–28.99; p < 0.001). High MAP_Cv (i.e., ≥13.6%) was associated with increased mortality by 3.5 times (OR = 3.44; 95% CI 1.34–8.83; p = 0.01). In logistic regression, it was confirmed that the outcome was dependent on both SBPV and DBPV, after adjustment for perioperative variables, with AUCSBP_Cv = 0.884 (95% CI 0.859–0.906; p < 0.001) and AUCDBP_Cv = 0.897 (95% CI 0.873–0.918; p < 0.001). Therefore, intraoperative BPV may be considered a prognostic factor for the postoperative mortality in non-cardiac surgery, and DBPV seems more accurate in outcome prediction than SBPV.

Closed-loop hemodynamic management

As the operating room and intensive care settings become increasingly complex, the required vigilance practitioners must dedicate to a wide array of clinical systems has increased concordantly. The resulting shortage of available attention to these various clinical tasks creates a vacuum for the introduction of systems that can administer well-established goal-directed therapies without significant provider feedback. Recently, there has been an explosion of academic exploration into creating such automated systems, with a strong specific focus on hemodynamic control. Within this field, the largest focus has been on goal-directed fluid therapy as systems automating vasopressor administration have only recently become viable options. Our goal in this review article is to summarize the validity of the relevant goal-directed hemodynamic systems and explore the expanding role of automation within these systems.

Peripheral nerve block combined with general anesthesia for lower extremity amputation in hemodialysis patients: case series

Background

Anesthetic management of lower extremity amputation in chronic hemodialysis (HD) patients can be challenging because of their poor cardiovascular status. As previously reported, peripheral nerve block (PNB) may be beneficial in these complicated cases. We report the effects of PNB combined with general anesthesia on hemodynamic stability in HD patients undergoing elective lower extremity amputation.

Methods

We retrospectively analyzed 13 HD patients who underwent lower extremity amputation. Patients received general anesthesia (GA group, n = 7) or general anesthesia combined with PNB (GA with PNB group, n = 6), as decided by the anesthesiologists. Mean blood pressure (MBP), systolic blood pressure (SBP), lowest BP, heart rate (HR), blood loss, fluid and blood infusion volumes, and doses of vasopressors required were compared for hemodynamic assessment. The coefficient of variation (\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$ \mathrm{CV}=\upsigma /\overline{\mathcal{X}} $$\end{document}CV=σ/X¯) of MBP (CV_MBP) and SBP (CV_SBP) was calculated to compare hemodynamic stability. Intraoperative opioid use and postoperative pain scores at rest using a numerical rating scale (NRS) on postoperative days 0 and 1 were compared for pain assessment. We also assessed 30-day mortality.

Results

CV_MBP in the GA group was significantly higher than that in the GA with PNB group (0.15 ± 0.05 and 0.08 ± 0.04, respectively, p = 0.03). The CV_SBP in the GA group was also significantly higher than that in the GA with PNB group (0.16 ± 0.02 and 0.09 ± 0.01, respectively, p = 0.03). No significant differences in other hemodynamic parameters were observed. Intraoperative fentanyl doses were significantly lower in the GA with PNB group (GA 210.7 ± 99.9 μg vs. GA with PNB 113.0 ± 75.6 μg, p = 0.04). There were no significant differences in other pain parameters and 30-day mortality between the groups.

Conclusion

Our results suggest that PNB combined with general anesthesia contributes to intraoperative hemodynamic stability through better pain control in HD patients undergoing lower extremity amputation.