The microcirculation in perioperative medicine: a narrative review.

The microcirculation describes the network of the smallest vessels in our cardiovascular system. On a microcirculatory level, oxygen delivery is determined by the flow of oxygen-carrying red blood cells in a given single capillary (capillary red blood cell flow) and the density of the capillary network in a given tissue volume (capillary vessel density). Handheld vital videomicroscopy enables visualisation of the capillary bed on the surface of organs and tissues but currently is only used for research. Measurements are generally possible on all organ surfaces but are most often performed in the sublingual area. In patients presenting for elective surgery, the sublingual microcirculation is usually intact and functional. Induction of general anaesthesia slightly decreases capillary red blood cell flow and increases capillary vessel density. During elective, even major, noncardiac surgery, the sublingual microcirculation is preserved and remains functional, presumably because elective noncardiac surgery is scheduled trauma and haemodynamic alterations are immediately treated by anaesthesiologists, usually restoring the macrocirculation before the microcirculation is substantially impaired. Additionally, surgery is regional trauma and thus likely causes regional, rather than systemic, impairment of the microcirculation. Whether or not the sublingual microcirculation is impaired after noncardiac surgery remains a subject of ongoing research. Similarly, it remains unclear if cardiac surgery, especially with cardiopulmonary bypass, impairs the sublingual microcirculation. The effects of therapeutic interventions specifically targeting the microcirculation remain to be elucidated and tested. Future research should focus on further improving microcirculation monitoring methods and investigating how regional microcirculation monitoring can inform clinical decision-making and treatment.

The Urethral Perfusion Index During Off-Pump Coronary Artery Bypass Surgery: An Observational Study.

OBJECTIVES: The IKORUS system (Vygon, Écouen, France) allows continuous monitoring of the urethral perfusion index (uPI) using a photoplethysmographic sensor mounted near the base of the balloon of a dedicated urinary catheter. We aimed to test the hypothesis that the uPI decreases during off-pump coronary artery bypass (OPCAB) surgery and to investigate the relationship between the uPI and macrocirculatory variables. DESIGN: Prospective observational study. SETTING: University Medical Center Hamburg-Eppendorf, Hamburg, Germany. PARTICIPANTS: Twenty patients having OPCAB surgery. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: The primary endpoint was changes in the uPI during OPCAB surgery. We additionally investigated associations between the uPI and cardiac output, mean arterial pressure, heart rate, and point-of-care variables. Twenty patients with 24,137 uPI measurements were included. Overall, there was a high interindividual variability in the uPI. Compared with the preparation phase (during which the median [interquartile range] uPI was 7.7 [5.6-12.0]), the uPI decreased by 14% (95% CI 13%-15%) during the bypass grafting phase, by 35% (95% CI 34%-36%) during the cardiac positioning phase, and by 7% (95% CI 6%-9%) during hemostasis. There was no clinically important association between uPI and either cardiac output, mean arterial pressure, or heart rate. CONCLUSIONS: The uPI decreases during OPCAB surgery, specifically during the cardiac positioning phase. There was no clinically important association between uPI and either cardiac output, mean arterial pressure, or heart rate. It, therefore, remains to be determined whether intraoperative uPI decreases are clinically important, reflect alterations in intra-abdominal tissue perfusion that are not reflected by systemic macrohemodynamics, and can help clinicians guide therapeutic interventions.

Post-anesthesia care unit hypotension in low-risk patients recovering from non-cardiac surgery: a prospective observational study.

Intraoperative hypotension is common and associated with organ injury. Hypotension can not only occur during surgery, but also thereafter. After surgery, most patients are treated in post-anesthesia care units (PACU). The incidence of PACU hypotension is largely unknown - presumably in part because arterial pressure is usually monitored intermittently in PACU patients. We therefore aimed to evaluate the incidence, duration, and severity of PACU hypotension in low-risk patients recovering from non-cardiac surgery. In this observational study, we performed blinded continuous non-invasive arterial pressure monitoring with finger-cuffs (ClearSight system; Edwards Lifesciences, Irvine, CA, USA) in 100 patients recovering from non-cardiac surgery in the PACU. We defined PACU hypotension as a mean arterial pressure (MAP) < 65 mmHg. Patients had continuous finger-cuff monitoring for a median (25th percentile, 75th percentile) of 64 (44 to 91) minutes. Only three patients (3%) had PACU hypotension for at least one consecutive minute. These three patients had 4, 4, and 2 cumulative minutes of PACU hypotension; areas under a MAP of 65 mmHg of 17, 9, and 9 mmHg x minute; and time-weighted averages MAP less than 65 mmHg of 0.5, 0.3, and 0.2 mmHg. The median volume of crystalloid fluid patients were given during PACU treatment was 200 (100 to 400) ml. None was given colloids or a vasopressor during PACU treatment. In low-risk patients recovering from non-cardiac surgery, the incidence of PACU hypotension was very low and the few episodes of PACU hypotension were short and of modest severity.

Intraoperative haemodynamic monitoring and management of adults having non-cardiac surgery: Guidelines of the German Society of Anaesthesiology and Intensive Care Medicine in collaboration with the German Association of the Scientific Medical Societies.

Haemodynamic monitoring and management are cornerstones of perioperative care. The goal of haemodynamic management is to maintain organ function by ensuring adequate perfusion pressure, blood flow, and oxygen delivery. We here present guidelines on "Intraoperative haemodynamic monitoring and management of adults having non-cardiac surgery" that were prepared by 18 experts on behalf of the German Society of Anaesthesiology and Intensive Care Medicine (Deutsche Gesellschaft für Anästhesiologie und lntensivmedizin; DGAI).

Continuous Finger-cuff versus Intermittent Oscillometric Arterial Pressure Monitoring and Hypotension during Induction of Anesthesia and Noncardiac Surgery: The DETECT Randomized Trial.

BACKGROUND: Finger-cuff methods allow noninvasive continuous arterial pressure monitoring. This study aimed to determine whether continuous finger-cuff arterial pressure monitoring helps clinicians reduce hypotension within 15 min after starting induction of anesthesia and during noncardiac surgery. Specifically, this study tested the hypotheses that continuous finger-cuff-compared to intermittent oscillometric-arterial pressure monitoring helps clinicians reduce the area under a mean arterial pressure of 65 mmHg within 15 min after starting induction of anesthesia and the time-weighted average mean arterial pressure less than 65 mmHg during noncardiac surgery. METHODS: In this single-center trial, 242 noncardiac surgery patients were randomized to unblinded continuous finger-cuff arterial pressure monitoring or to intermittent oscillometric arterial pressure monitoring (with blinded continuous finger-cuff arterial pressure monitoring). The first of two hierarchical primary endpoints was the area under a mean arterial pressure of 65 mmHg within 15 min after starting induction of anesthesia; the second primary endpoint was the time-weighted average mean arterial pressure less than 65 mmHg during surgery. RESULTS: Within 15 min after starting induction of anesthesia, the median (interquartile range) area under a mean arterial pressure of 65 mmHg was 7 (0, 24) mmHg × min in 109 patients assigned to continuous finger-cuff monitoring versus 19 (0.3, 60) mmHg × min in 113 patients assigned to intermittent oscillometric monitoring (P = 0.004; estimated location shift: -6 [95% CI: -15 to -0.3] mmHg × min). During surgery, the median (interquartile range) time-weighted average mean arterial pressure less than 65 mmHg was 0.04 (0, 0.27) mmHg in 112 patients assigned to continuous finger-cuff monitoring and 0.40 (0.03, 1.74) mmHg in 115 patients assigned to intermittent oscillometric monitoring (P < 0.001; estimated location shift: -0.17 [95% CI: -0.41 to -0.05] mmHg). CONCLUSIONS: Continuous finger-cuff arterial pressure monitoring helps clinicians reduce hypotension within 15 min after starting induction of anesthesia and during noncardiac surgery compared to intermittent oscillometric arterial pressure monitoring.

Endotypes of intraoperative hypotension during major abdominal surgery: a retrospective machine learning analysis of an observational cohort study.

BACKGROUND: Intraoperative hypotension is associated with myocardial injury, acute kidney injury, and death. In routine practice, specific causes of intraoperative hypotension are often unclear. A more detailed understanding of underlying haemodynamic alterations of intraoperative hypotension may identify specific treatments. We thus aimed to use machine learning - specifically, hierarchical clustering - to identify underlying haemodynamic alterations causing intraoperative hypotension in major abdominal surgery patients. Specifically, we tested the hypothesis that there are distinct endotypes of intraoperative hypotension, which may help refine therapeutic interventions. METHODS: We conducted a secondary analysis of intraoperative haemodynamic measurements from a prospective observational study in 100 patients who had major abdominal surgery under general anaesthesia. We used stroke volume index, heart rate, cardiac index, systemic vascular resistance index, and pulse pressure variation measurements. Intraoperative hypotension was defined as any mean arterial pressure ≤65 mm Hg or a mean arterial pressure between 66 and 75 mm Hg requiring a norepinephrine infusion rate exceeding 0.1 µg kg-1 min-1. To identify endotypes of intraoperative hypotension, we used hierarchical clustering (Ward's method). RESULTS: A total of 615 episodes of intraoperative hypotension occurred in 82 patients (46 [56%] female; median age: 64 [57, 73] yr) who had surgery of a median duration of 270 (195, 335) min. Hierarchical clustering revealed six distinct intraoperative hypotension endotypes. Based on their clinical characteristics, we labelled these endotypes as (1) myocardial depression, (2) bradycardia, (3) vasodilation with cardiac index increase, (4) vasodilation without cardiac index increase, (5) hypovolaemia, and (6) mixed type. CONCLUSION: Hierarchical clustering identified six endotypes of intraoperative hypotension. If validated, considering these intraoperative hypotension endotypes may enable causal treatment of intraoperative hypotension.

Energy Expenditure Under General Anesthesia: An Observational Study Using Indirect Calorimetry in Patients Having Noncardiac Surgery.

BACKGROUND: Perioperative hemodynamic management aims to optimize organ perfusion pressure and blood flow-assuming this ensures that oxygen delivery meets cellular metabolic needs. Cellular metabolic needs are reflected by energy expenditure. A better understanding of energy expenditure under general anesthesia could help tailor perioperative hemodynamic management to actual demands. We thus sought to assess energy expenditure under general anesthesia. Our primary hypothesis was that energy expenditure under general anesthesia is lower than preoperative awake resting energy expenditure. METHODS: We conducted an observational study on patients having elective noncardiac surgery at the University Medical Center Hamburg-Eppendorf (Germany) between September 2019 and March 2020. We assessed preoperative awake resting energy expenditure, energy expenditure under general anesthesia, and energy expenditure after surgery using indirect calorimetry. We compared energy expenditure under general anesthesia at incision to preoperative awake resting energy expenditure using a Wilcoxon signed-rank test for paired measurements. RESULTS: We analyzed 60 patients. Median (95% confidence interval [CI]) preoperative awake resting energy expenditure was 953 (95% CI, 906-962) kcal d -1 m -2 . Median energy expenditure under general anesthesia was 680 (95% CI, 642-711) kcal d -1 m -2 -and thus 263 (95% CI, 223-307) kcal d -1 m -2 or 27% (95% CI, 23%-30%) lower than preoperative awake resting energy expenditure ( P < .001). CONCLUSIONS: Median energy expenditure under general anesthesia is about one-quarter lower than preoperative awake resting energy expenditure in patients having noncardiac surgery.

Agreement between cardiac output measurements by pulse wave analysis using the Pressure Recording Analytical Method and transthoracic echocardiography in patients with veno-venous extracorporeal membrane oxygenation therapy: An observational method comparison.

BACKGROUND: Measuring cardiac output (CO) is important in patients treated with veno-venous extracorporeal membrane oxygenation (vvECMO) because vvECMO flow and CO need to be balanced. Uncalibrated pulse wave analysis with the Pressure Recording Analytical Method (PRAM) may be suitable to measure CO in patients with vvECMO therapy. OBJECTIVE: To assess the agreement between CO measured by PRAM (PRAM-CO; test method) and CO measured by transthoracic echocardiography (TTE-CO; reference method). DESIGN: A prospective observational method comparison study. SETTING: The ICU of a German university hospital between March and December 2021. PATIENTS: Thirty one adult patients with respiratory failure requiring vvECMO therapy: 29 of the 31 patients (94%) were treated for COVID-19 related respiratory failure. MAIN OUTCOME MEASURES: PRAM-CO and TTE-CO were measured simultaneously at two time points in each patient with at least 20 min between measurements. A radial or femoral arterial catheter-derived blood pressure waveform was used for PRAM-CO measurements. TTE-CO measurements were conducted using the pulsed wave Doppler-derived velocity time integral of the left ventricular outflow tract (LVOT) and the corresponding LVOT diameter. PRAM-CO and TTE-CO were compared using Bland-Altman analysis and the percentage error (PE). We defined a PE of <30% as clinically acceptable. RESULTS: Mean ±â€ŠSD PRAM-CO was 6.86 ±â€Š1.49 l min -1 and mean TTE-CO was 6.94 ±â€Š1.58 l min -1 . The mean of the differences between PRAM-CO and TTE-CO was 0.09 ±â€Š0.73 l min -1 with a lower 95% limit of agreement of -1.34 l min -1 and an upper 95% limit of agreement of 1.51 l min -1 . The PE was 21%. CONCLUSIONS: The agreement between PRAM-CO and TTE-CO is clinically acceptable in adult patients with vvECMO therapy.

Microcirculatory alterations in critically ill COVID-19 patients analyzed using artificial intelligence.

BACKGROUND: The sublingual microcirculation presumably exhibits disease-specific changes in function and morphology. Algorithm-based quantification of functional microcirculatory hemodynamic variables in handheld vital microscopy (HVM) has recently allowed identification of hemodynamic alterations in the microcirculation associated with COVID-19. In the present study we hypothesized that supervised deep machine learning could be used to identify previously unknown microcirculatory alterations, and combination with algorithmically quantified functional variables increases the model's performance to differentiate critically ill COVID-19 patients from healthy volunteers. METHODS: Four international, multi-central cohorts of critically ill COVID-19 patients and healthy volunteers (n = 59/n = 40) were used for neuronal network training and internal validation, alongside quantification of functional microcirculatory hemodynamic variables. Independent verification of the models was performed in a second cohort (n = 25/n = 33). RESULTS: Six thousand ninety-two image sequences in 157 individuals were included. Bootstrapped internal validation yielded AUROC(CI) for detection of COVID-19 status of 0.75 (0.69-0.79), 0.74 (0.69-0.79) and 0.84 (0.80-0.89) for the algorithm-based, deep learning-based and combined models. Individual model performance in external validation was 0.73 (0.71-0.76) and 0.61 (0.58-0.63). Combined neuronal network and algorithm-based identification yielded the highest externally validated AUROC of 0.75 (0.73-0.78) (P < 0.0001 versus internal validation and individual models). CONCLUSIONS: We successfully trained a deep learning-based model to differentiate critically ill COVID-19 patients from heathy volunteers in sublingual HVM image sequences. Internally validated, deep learning was superior to the algorithmic approach. However, combining the deep learning method with an algorithm-based approach to quantify the functional state of the microcirculation markedly increased the sensitivity and specificity as compared to either approach alone, and enabled successful external validation of the identification of the presence of microcirculatory alterations associated with COVID-19 status.

Continuous intra-arterial versus intermittent oscillometric arterial pressure monitoring and hypotension during induction of anaesthesia: the AWAKE randomised trial.

BACKGROUND: Hypotension during induction of anaesthesia is associated with organ injury. Continuous arterial pressure monitoring might help reduce hypotension. We tested the hypothesis that continuous intra-arterial compared with intermittent oscillometric arterial pressure monitoring reduces hypotension during induction of anaesthesia in noncardiac surgery patients. METHODS: In this single-centre randomised trial, 242 noncardiac surgery patients in whom intra-arterial arterial pressure monitoring was planned were randomised to unblinded continuous intra-arterial or to intermittent oscillometric arterial pressure monitoring (with blinded intra-arterial arterial pressure monitoring) during induction of anaesthesia. The primary endpoint was the area under a mean arterial pressure (MAP) of 65 mm Hg within the first 15 min of induction of anaesthesia. Secondary endpoints included areas under MAP values of 60, 50, and 40 mm Hg and durations of MAP values <65, <60, <50, and <40 mm Hg. RESULTS: There were 224 subjects available for analysis. The median (25th-75th percentile) area under a MAP of 65 mm Hg was 15 (2-36) mm Hg • min in subjects assigned to continuous intra-arterial monitoring and 46 (7-111) mm Hg • min in subjects assigned to intermittent oscillometric monitoring (P<0.001). Subjects assigned to continuous intra-arterial monitoring had smaller areas under MAP values of 60, 50, and 40 mm Hg and shorter durations of MAP values <65, <60, <50, and <40 mm Hg than subjects assigned to intermittent oscillometric monitoring. CONCLUSION: Continuous intra-arterial arterial pressure monitoring reduces hypotension during induction of anaesthesia compared with intermittent oscillometric arterial pressure monitoring in noncardiac surgery patients. In patients for whom an arterial catheter is planned, clinicians might therefore consider inserting the arterial catheter before rather than after induction of anaesthesia. CLINICAL TRIALS REGISTRATION: NCT04894019.

The Relation Between Mean Arterial Pressure and Cardiac Index in Major Abdominal Surgery Patients: A Prospective Observational Cohort Study.

BACKGROUND: Cardiac output is an important hemodynamic variable and determines oxygen delivery. In contrast to blood pressure, cardiac output is rarely measured even in high-risk surgical patients, suggesting that clinicians consider blood pressure to be a reasonable indicator of systemic blood flow. However, the relationship depends on constant vascular tone and volume, both of which routinely vary during anesthesia and surgery. We therefore tested the hypothesis that there is no clinically meaningful correlation between mean arterial pressure and cardiac index in major abdominal surgery patients. METHODS: In this prospective observational study, we assessed the relationship between mean arterial pressure and cardiac index in 100 patients having major abdominal surgery under general anesthesia. RESULTS: The pooled within-patient correlation coefficient calculated using meta-analysis methods was r = 0.34 (95% confidence interval, 0.28-0.40). Linear regression using a linear mixed effects model of cardiac index on mean arterial pressure revealed that cardiac index increases by 0.014 L·min-1·m-2 for each 1 mm Hg increase in mean arterial pressure. The 95% Wald confidence interval of this slope was 0.011 to 0.018 L·min-1·m-2·mm Hg-1 and thus within predefined equivalence margins of -0.03 and 0.03 L·min-1·m-2·mm Hg-1, thereby demonstrating lack of clinically meaningful association between mean arterial pressure and cardiac index. CONCLUSIONS: There is no clinically meaningful correlation between mean arterial pressure and cardiac index in patients having major abdominal surgery. Intraoperative blood pressure is thus a poor surrogate for cardiac index.

A new noninvasive finger sensor (NICCI system) for continuous blood pressure and pulse pressure variation monitoring: A method comparison study in patients having neurosurgery.

BACKGROUND: The NICCI system (Getinge, Gothenburg, Sweden) is a new noninvasive haemodynamic monitoring system using a finger sensor. OBJECTIVES: We aimed to investigate the performance of the NICCI system to measure blood pressure and pulse pressure variation compared with intra-arterial measurements. DESIGN: A prospective method comparison study. SETTING: University Medical Center Hamburg-Eppendorf, Hamburg, Germany. PATIENTS: Forty-seven neurosurgery patients. MAIN OUTCOME MEASURES: We performed a method comparison study in 47 neurosurgery patients to compare NICCI blood pressure measurements (BP NICCI ) with intra-arterial blood pressure measurements (BP ART ) (Bland-Altman analysis, four-quadrant plot, error grid analysis) and NICCI pulse pressure variation measurements (PPV NICCI ) with pulse pressure variation calculated manually from the intra-arterial blood pressure waveform (PPV ART ) (Bland-Altman analysis, predictive agreement, Cohen's kappa). RESULTS: The mean of the differences ±â€Šstandard deviation (95% limits of agreement) between BP NICCI and BP ART was 11 ±â€Š10 mmHg (-8 to 30 mmHg) for mean blood pressure (MBP), 3 ±â€Š12 mmHg (-21 to 26 mmHg) for systolic blood pressure (SBP) and 12 ±â€Š10 mmHg (-8 to 31 mmHg) for diastolic blood pressure (DBP). In error grid analysis, 54% of BP NICCI and BP ART MBP measurement pairs were classified as 'no risk', 43% as 'low risk', 3% as 'moderate risk' and 0% as 'significant risk' or 'dangerous risk'. The mean of the differences between PPV NICCI and PPV ART was 1 ±â€Š3% (-4 to 6%). The predictive agreement between PPV NICCI and PPV ART was 80% and Cohen's kappa was 0.55. CONCLUSIONS: The absolute agreement between BP NICCI and BP ART was not clinically acceptable. We recommend not using the current version of the NICCI system for blood pressure monitoring during surgery. The absolute agreement between PPV NICCI and PPV ART was clinically acceptable with moderate predictive agreement regarding pulse pressure variation categories. The NICCI system needs to be further developed and re-evaluated when an improved version is available. TRIAL REGISTRATION: The study was registered in the German Clinical Trials Register (DRKS00023188) on 2 October 2020.

A new noninvasive finger sensor (NICCI system) for cardiac output monitoring: A method comparison study in patients after cardiac surgery.

BACKGROUND: The new noninvasive finger sensor system NICCI (Getinge; Gothenburg, Sweden) allows continuous cardiac output monitoring. We aimed to investigate its cardiac output measurement performance. OBJECTIVES: To investigate the NICCI system's cardiac output measurement performance. DESIGN: Prospective method comparison study. SETTING: University Medical Center Hamburg-Eppendorf, Hamburg, Germany. PATIENTS: Fifty-one patients after cardiac surgery. MAIN OUTCOME MEASURES: We performed a method comparison study in 51 patients after cardiac surgery to compare NICCI cardiac output (CO NICCI ) and NICCI cardiac output calibrated to pulmonary artery thermodilution cardiac output measurement (CO NICCI-CAL ) with pulmonary artery thermodilution cardiac output (CO PAT ). As a secondary analysis we also compared CNAP cardiac output (CO CNAP ) and externally calibrated CNAP cardiac output (CO CNAP-CAL ) with CO PAT . RESULTS: We analysed 299 cardiac output measurement pairs. The mean of the differences (95% limits of agreement) between CO NICCI and CO PAT was 0.6 (-1.8 to 3.1) l min -1 with a percentage error of 48%. The mean of the differences between CO NICCI-CAL and CO PAT was -0.4 (-1.9 to 1.1) l min -1 with a percentage error of 29%. The mean of the differences between CO CNAP and CO PAT was 1.0 (-1.8 to 3.8) l min -1 with a percentage error of 53%. The mean of the differences between CO CNAP-CAL and CO PAT was -0.2 (-2.0 to 1.6) l min -1 with a percentage error of 35%. CONCLUSION: The agreement between CO NICCI and CO PAT is not clinically acceptable. TRIAL REGISTRATION: The study was registered in the German Clinical Trial Register (DRKS00023189) after inclusion of the first patient on October 2, 2020.

Microcirculatory tissue perfusion during general anaesthesia and noncardiac surgery: An observational study using incident dark field imaging with automated video analysis.

BACKGROUND: Handheld vital microscopy allows direct observation of red blood cells within the sublingual microcirculation. Automated analysis allows quantifying microcirculatory tissue perfusion variables - including tissue red blood cell perfusion (tRBCp), a functional variable integrating microcirculatory convection and diffusion capacities. OBJECTIVE: We aimed to describe baseline microcirculatory tissue perfusion in patients presenting for elective noncardiac surgery and test that microcirculatory tissue perfusion is preserved during elective general anaesthesia for noncardiac surgery. DESIGN: Prospective observational study. SETTING: University Medical Center Hamburg-Eppendorf, Hamburg, Germany. PATIENTS: 120 elective noncardiac surgery patients (major abdominal, orthopaedic or trauma and minor urologic surgery) and 40 young healthy volunteers. MAIN OUTCOME MEASURES: We measured sublingual microcirculation using incident dark field imaging with automated analysis at baseline before induction of general anaesthesia, under general anaesthesia before surgical incision and every 30 min during surgery. We used incident the dark field imaging technology with a validated automated analysis software. RESULTS: A total of 3687 microcirculation video sequences were analysed. Microcirculatory tissue perfusion variables varied substantially between individuals - but ranges were similar between patients and volunteers. Under general anaesthesia before surgical incision, there were no important changes in tRBCp, functional capillary density and capillary haematocrit compared with preinduction baseline. However, total vessel density was higher and red blood cell velocity and the proportion of perfused vessels were lower under general anaesthesia. There were no important changes in any microcirculatory tissue perfusion variables during surgery. CONCLUSION: In patients presenting for elective noncardiac surgery, baseline microcirculatory tissue perfusion variables vary substantially between individuals - but ranges are similar to those in young healthy volunteers. Microcirculatory tissue perfusion is preserved during general anaesthesia and noncardiac surgery - when macrocirculatory haemodynamics are maintained.

What is new in microcirculation and tissue oxygenation monitoring?

Ensuring and maintaining adequate tissue oxygenation at the microcirculatory level might be considered the holy grail of optimal hemodynamic patient management. However, in clinical practice we usually focus on macro-hemodynamic variables such as blood pressure, heart rate, and sometimes cardiac output. Other macro-hemodynamic variables like pulse pressure or stroke volume variation are additionally used as markers of fluid responsiveness. In recent years, an increasing number of technological devices assessing tissue oxygenation or microcirculatory blood flow have been developed and validated, and some of them have already been incorporated into clinical practice. In this review, we will summarize recent research findings on this topic as published in the last 2 years in the Journal of Clinical Monitoring and Computing (JCMC). While some techniques are already currently used as routine monitoring (e.g. cerebral oxygenation using near-infrared spectroscopy (NIRS)), others still have to find their way into clinical practice. Therefore, further research is needed, particularly regarding outcome measures and cost-effectiveness, since introducing new technology is always expensive and should be balanced by downstream savings. The JCMC is glad to provide a platform for such research.

Right ventricular and pulmonary artery pulse pressure variation and systolic pressure variation for the prediction of fluid responsiveness: an interventional study in coronary artery bypass surgery patients.

PURPOSE: Predicting fluid responsiveness is essential when treating surgical or critically ill patients. When using a pulmonary artery catheter, pulse pressure variation and systolic pressure variation can be calculated from right ventricular and pulmonary artery pressure waveforms. METHODS: We conducted a prospective interventional study investigating the ability of right ventricular pulse pressure variation (PPVRV) and systolic pressure variation (SPVRV) as well as pulmonary artery pulse pressure variation (PPVPA) and systolic pressure variation (SPVPA) to predict fluid responsiveness in coronary artery bypass (CABG) surgery patients. Additionally, radial artery pulse pressure variation (PPVART) and systolic pressure variation (SPVART) were calculated. The area under the receiver operating characteristics (AUROC) curve with 95%-confidence interval (95%-CI) was used to assess the capability to predict fluid responsiveness (defined as an increase in cardiac index of > 15%) after a 500 mL crystalloid fluid challenge. RESULTS: Thirty-three patients were included in the final analysis. Thirteen patients (39%) were fluid-responders with a mean increase in cardiac index of 25.3%. The AUROC was 0.60 (95%-CI 0.38 to 0.81) for PPVRV, 0.63 (95%-CI 0.43 to 0.83) for SPVRV, 0.58 (95%-CI 0.38 to 0.78) for PPVPA, and 0.71 (95%-CI 0.52 to 0.89) for SPVPA. The AUROC for PPVART was 0.71 (95%-CI 0.53 to 0.89) and for SPVART 0.78 (95%-CI 0.62 to 0.94). The correlation between pulse pressure variation and systolic pressure variation measurements derived from the different waveforms was weak. CONCLUSIONS: Right ventricular and pulmonary artery pulse pressure variation and systolic pressure variation seem to be weak predictors of fluid responsiveness in CABG surgery patients.

Non-invasive measurement of pulse pressure variation using a finger-cuff method (CNAP system): a validation study in patients having neurosurgery.

The finger-cuff system CNAP (CNSystems Medizintechnik, Graz, Austria) allows non-invasive automated measurement of pulse pressure variation (PPVCNAP). We sought to validate the PPVCNAP-algorithm and investigate the agreement between PPVCNAP and arterial catheter-derived manually calculated pulse pressure variation (PPVINV). This was a prospective method comparison study in patients having neurosurgery. PPVINV was the reference method. We applied the PPVCNAP-algorithm to arterial catheter-derived blood pressure waveforms (PPVINV-CNAP) and to CNAP finger-cuff-derived blood pressure waveforms (PPVCNAP). To validate the PPVCNAP-algorithm, we compared PPVINV-CNAP to PPVINV. To investigate the clinical performance of PPVCNAP, we compared PPVCNAP to PPVINV. We used Bland-Altman analysis (absolute agreement), Deming regression, concordance, and Cohen's kappa (predictive agreement for three pulse pressure variation categories). We analyzed 360 measurements from 36 patients. The mean of the differences between PPVINV-CNAP and PPVINV was -0.1% (95% limits of agreement (95%-LoA) -2.5 to 2.3%). Deming regression showed a slope of 0.99 (95% confidence interval (95%-CI) 0.91 to 1.06) and intercept of -0.02 (95%-CI -0.52 to 0.47). The predictive agreement between PPVINV-CNAP and PPVINV was 92% and Cohen's kappa was 0.79. The mean of the differences between PPVCNAP and PPVINV was -1.0% (95%-LoA-6.3 to 4.3%). Deming regression showed a slope of 0.85 (95%-CI 0.78 to 0.91) and intercept of 0.10 (95%-CI -0.34 to 0.55). The predictive agreement between PPVCNAP and PPVINV was 82% and Cohen's kappa was 0.48. The PPVCNAP-algorithm reliably calculates pulse pressure variation compared to manual offline pulse pressure variation calculation when applied on the same arterial blood pressure waveform. The absolute and predictive agreement between PPVCNAP and PPVINV are moderate.

Postoperative blood pressure management in patients treated in the ICU after noncardiac surgery.

PURPOSE OF REVIEW: Blood pressure management is a cornerstone of hemodynamic management in patients treated in the ICU after noncardiac surgery. Postoperative blood pressure management is challenging, because blood pressure alterations after surgery can be profound and have numerous causes. RECENT FINDINGS: Postoperative blood pressure alterations are common in patients treated in ICUs after noncardiac surgery. There is increasing evidence that hypotension during the initial days after noncardiac surgery is associated with postoperative adverse outcomes including myocardial infarction and death, acute myocardial injury, acute kidney injury, major adverse cardiac or cerebrovascular events, and delirium. Thus, postoperative hypotension could be a modifiable risk factor for postoperative adverse outcomes. However, robust evidence for a causal relationship between postoperative blood pressure and postoperative adverse outcomes is still lacking. SUMMARY: Future research on postoperative blood pressure management in patients treated in the ICU after noncardiac surgery needs to assess whether the prevention or treatment of postoperative blood pressure alterations - especially postoperative hypotension - reduces the incidence of postoperative adverse outcomes.

Agreement between continuous and intermittent pulmonary artery thermodilution for cardiac output measurement in perioperative and intensive care medicine: a systematic review and meta-analysis.

BACKGROUND: Pulmonary artery thermodilution is the clinical reference method for cardiac output monitoring. Because both continuous and intermittent pulmonary artery thermodilution are used in clinical practice it is important to know whether cardiac output measurements by the two methods are clinically interchangeable. METHODS: We performed a systematic review and meta-analysis of clinical studies comparing cardiac output measurements assessed using continuous and intermittent pulmonary artery thermodilution in adult surgical and critically ill patients. 54 studies with 1522 patients were included in the analysis. RESULTS: The heterogeneity across the studies was high. The overall random effects model-derived pooled estimate of the mean of the differences was 0.08 (95%-confidence interval 0.01 to 0.16) L/min with pooled 95%-limits of agreement of - 1.68 to 1.85 L/min and a pooled percentage error of 29.7 (95%-confidence interval 20.5 to 38.9)%. CONCLUSION: The heterogeneity across clinical studies comparing continuous and intermittent pulmonary artery thermodilution in adult surgical and critically ill patients is high. The overall trueness/accuracy of continuous pulmonary artery thermodilution in comparison with intermittent pulmonary artery thermodilution is good (indicated by a pooled mean of the differences < 0.1 L/min). Pooled 95%-limits of agreement of - 1.68 to 1.85 L/min and a pooled percentage error of 29.7% suggest that continuous pulmonary artery thermodilution barely passes interchangeability criteria with intermittent pulmonary artery thermodilution. PROSPERO registration number CRD42020159730.

Relationship Between Intraoperative and Preoperative Ambulatory Nighttime Heart Rates: A Secondary Analysis of a Prospective Observational Study.

BACKGROUND: It remains unknown what constitutes physiologically relevant intraoperative bradycardia. Intraoperative bradycardia is usually defined using absolute heart rate thresholds, ignoring preoperative baseline heart rates. In contrast, we considered defining intraoperative bradycardia relative to preoperative ambulatory nighttime heart rate. Specifically, we hypothesized that the individual mean intraoperative heart rate is lower than the mean preoperative ambulatory nighttime heart rate. We, therefore, sought to investigate the relationship between the intraoperative and preoperative ambulatory nighttime heart rates in adults having noncardiac surgery with general anesthesia. Additionally, we sought to investigate the incidence of intraoperative bradycardia using relative versus absolute heart rate thresholds. METHODS: We conducted a secondary analysis of a database from a prospective study including preoperative ambulatory and intraoperative heart rates in 363 patients having noncardiac surgery with general anesthesia. RESULTS: The mean intraoperative heart rate was lower than the mean nighttime heart rate (mean difference, -9 bpm; 95% confidence interval [CI], -10 to -8 bpm; P < .001). The mean intraoperative heart rate was lower than the mean nighttime heart rate in 319 of 363 patients (88%; 95% CI, 84%-91%). The incidence of intraoperative bradycardia was 42% (95% CI, 38%-47%) when it was defined as intraoperative heart rate >30% lower than mean nighttime heart rate and 43% (95% CI, 38%-49%) when it was defined as intraoperative heart rate <45 bpm. CONCLUSIONS: The mean intraoperative heart rate is lower than the mean nighttime heart rate in about 9 of 10 patients. Intraoperative bradycardia might thus be physiologically and clinically important. Future research needs to investigate whether there is an association between intraoperative bradycardia and postoperative outcomes.