ABSTRACT
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.
ABSTRACT
STUDY OBJECTIVE: Processed electroencephalography (pEEG) may help clinicians optimize depth of general anesthesia. Avoiding excessive depth of anesthesia may reduce intraoperative hypotension and the need for vasopressors. We tested the hypothesis that pEEG-guided - compared to non-pEEG-guided - general anesthesia reduces the amount of norepinephrine needed to keep intraoperative mean arterial pressure above 65 mmHg in patients having vascular surgery. DESIGN: Randomized controlled clinical trial. SETTING: University Medical Center Hamburg-Eppendorf, Hamburg, Germany. PATIENTS: 110 patients having vascular surgery. INTERVENTIONS: pEEG-guided general anesthesia. MEASUREMENTS: Our primary endpoint was the average norepinephrine infusion rate from the beginning of induction of anesthesia until the end of surgery. MAIN RESULT: 96 patients were analyzed. The mean ± standard deviation average norepinephrine infusion rate was 0.08 ± 0.04 µg kg-1 min-1 in patients assigned to pEEG-guided and 0.12 ± 0.09 µg kg-1 min-1 in patients assigned to non-pEEG-guided general anesthesia (mean difference 0.04 µg kg-1 min-1, 95% confidence interval 0.01 to 0.07 µg kg-1 min-1, p = 0.004). Patients assigned to pEEG-guided versus non-pEEG-guided general anesthesia, had a median time-weighted minimum alveolar concentration of 0.7 (0.6, 0.8) versus 0.8 (0.7, 0.8) (p = 0.006) and a median percentage of time Patient State Index was <25 of 12 (1, 41) % versus 23 (3, 49) % (p = 0.279). CONCLUSION: pEEG-guided - compared to non-pEEG-guided - general anesthesia reduced the amount of norepinephrine needed to keep mean arterial pressure above 65 mmHg by about a third in patients having vascular surgery. Whether reduced intraoperative norepinephrine requirements resulting from pEEG-guided general anesthesia translate into improved patient-centered outcomes remains to be determined in larger trials.
Subject(s)
Anesthesia, General , Electroencephalography , Norepinephrine , Vascular Surgical Procedures , Vasoconstrictor Agents , Humans , Anesthesia, General/methods , Norepinephrine/administration & dosage , Male , Female , Middle Aged , Aged , Electroencephalography/drug effects , Vascular Surgical Procedures/adverse effects , Vasoconstrictor Agents/administration & dosage , Hypotension/prevention & control , Arterial Pressure/drug effects , Monitoring, Intraoperative/methodsABSTRACT
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.
Subject(s)
Basal Metabolism , Energy Metabolism , Humans , Calorimetry, Indirect , Anesthesia, General , GermanyABSTRACT
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.
Subject(s)
Cardiac Surgical Procedures , Thermodilution , Cardiac Output , Cardiac Surgical Procedures/methods , Humans , Monitoring, Physiologic/methods , Reproducibility of Results , Thermodilution/methodsABSTRACT
STUDY OBJECTIVE: Postinduction and intraoperative hypotension are associated with organ injury in non-cardiac surgery patients. Automated ambulatory blood pressure monitoring can identify chronic arterial hypertension and nocturnal blood pressure non-dipping. We tested the hypotheses that: a) chronic arterial hypertension and nocturnal non-dipping are independent risk factors for postinduction and intraoperative hypotension; and b) adding information on chronic arterial hypertension and nocturnal non-dipping improves hypotension prediction models based on readily available preoperative clinical information. DESIGN: Prediction model development based on a secondary analysis of a prospective observational study. SETTING: German university medical center. PATIENTS: 366 non-cardiac surgery patients who had preoperative automated ambulatory blood pressure monitoring. MEASUREMENTS: Multivariable analyses to identify risk factors for postinduction and intraoperative hypotension. Area under receiver operating characteristics curves (AUROC) and likelihood-ratio tests to test whether adding information on chronic arterial hypertension and nocturnal non-dipping improves hypotension prediction models based on readily available preoperative clinical information. MAIN RESULTS: Risk factors for postinduction hypotension were age in years (odds ratio: 1.06 (95% confidence interval: 1.03 to 1.10), P = 0.001), American Society of Anesthesiologists physical status class (1.85 (1.02 to 3.35), P = 0.043), preoperative use of angiotensin-converting enzyme inhibitors or angiotensin II receptor blockers (15.19 (1.76 to 131.46), P = 0.013), chronic arterial hypertension (2.54 (1.49 to 4.34), P = 0.001), and nocturnal non-dipping (3.61 (2.09 to 6.23), P < 0.001). The model's AUROC was 0.76 (95% confidence interval: 0.71 to 0.81) with and 0.67 (0.62 to 0.73) without information on chronic arterial hypertension and nocturnal non-dipping (P < 0.001). Risk factors for intraoperative hypotension were male sex (1.73 (1.07 to 2.80), P = 0.025), chronic arterial hypertension (4.35 (2.33 to 8.14), P < 0.001), and nocturnal non-dipping (3.56 (2.07 to 6.11), P < 0.001). The model's AUROC was 0.76 (0.70 to 0.81) with and 0.63 (0.57 to 0.69) without information on chronic arterial hypertension and nocturnal non-dipping (P < 0.001). CONCLUSIONS: Chronic arterial hypertension and nocturnal non-dipping are independent risk factors for postinduction and intraoperative hypotension in non-cardiac surgery patients. Adding information on chronic arterial hypertension and nocturnal non-dipping moderately improved hypotension prediction models based on preoperative clinical information.
Subject(s)
Hypertension , Hypotension , Blood Pressure/physiology , Blood Pressure Monitoring, Ambulatory , Female , Humans , Hypertension/epidemiology , Hypertension/etiology , Hypotension/diagnosis , Hypotension/epidemiology , Hypotension/etiology , Male , Prospective StudiesABSTRACT
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.
Subject(s)
Neurosurgery , Arterial Pressure/physiology , Blood Pressure , Blood Pressure Determination/methods , Humans , Prospective StudiesABSTRACT
It remains unclear whether reduced myocardial contractility, venous dilation with decreased venous return, or arterial dilation with reduced systemic vascular resistance contribute most to hypotension after induction of general anesthesia. We sought to assess the relative contribution of various hemodynamic mechanisms to hypotension after induction of general anesthesia with sufentanil, propofol, and rocuronium. In this prospective observational study, we continuously recorded hemodynamic variables during anesthetic induction using a finger-cuff method in 92 non-cardiac surgery patients. After sufentanil administration, there was no clinically important change in arterial pressure, but heart rate increased from baseline by 11 (99.89% confidence interval: 7 to 16) bpm (P < 0.001). After administration of propofol, mean arterial pressure decreased by 23 (17 to 28) mmHg and systemic vascular resistance index decreased by 565 (419 to 712) dyn*s*cm-5*m2 (P values < 0.001). Mean arterial pressure was < 65 mmHg in 27 patients (29%). After propofol administration, heart rate returned to baseline, and stroke volume index and cardiac index remained stable. After tracheal intubation, there were no clinically important differences compared to baseline in heart rate, stroke volume index, and cardiac index, but arterial pressure and systemic vascular resistance index remained markedly decreased. Anesthetic induction with sufentanil, propofol, and rocuronium reduced arterial pressure and systemic vascular resistance index. Heart rate, stroke volume index, and cardiac index remained stable. Post-induction hypotension therefore appears to result from arterial dilation with reduced systemic vascular resistance rather than venous dilation or reduced myocardial contractility.
Subject(s)
Anesthetics , Hypotension , Propofol , Anesthetics, Intravenous , Blood Pressure , Hemodynamics/physiology , Humans , Rocuronium/pharmacology , Sufentanil/pharmacologyABSTRACT
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.
Subject(s)
Abdomen/surgery , Arterial Pressure/physiology , Blood Flow Velocity/physiology , Cardiac Output/physiology , Monitoring, Intraoperative/methods , Aged , Cohort Studies , Female , Humans , Male , Middle Aged , Prospective StudiesABSTRACT
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.
Subject(s)
Bradycardia/epidemiology , Circadian Rhythm , Electrocardiography , Heart Rate , Hemodynamic Monitoring , Monitoring, Intraoperative , Surgical Procedures, Operative/adverse effects , Adult , Aged , Anesthesia, General/adverse effects , Bradycardia/diagnosis , Bradycardia/physiopathology , Databases, Factual , Female , Humans , Incidence , Male , Middle Aged , Predictive Value of Tests , Retrospective Studies , Risk Factors , Time FactorsABSTRACT
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.
Subject(s)
Cardiac Output/physiology , Pulmonary Artery/physiopathology , Thermodilution/instrumentation , Weights and Measures/instrumentation , Humans , Monitoring, Physiologic/instrumentation , Monitoring, Physiologic/methods , Reproducibility of Results , Thermodilution/methods , Weights and Measures/standardsABSTRACT
BACKGROUND: The effect of different methods for data sampling and data processing on the results of comparative statistical analyses in method comparison studies of continuous arterial blood pressure (AP) monitoring systems remains unknown. OBJECTIVE: We sought to investigate the effect of different methods for data sampling and data processing on the results of statistical analyses in method comparison studies of continuous AP monitoring systems. DESIGN: Prospective observational study. SETTING: University Medical Center Hamburg-Eppendorf, Hamburg, Germany, from April to October 2019. PATIENTS: 49 patients scheduled for neurosurgery with AP measurement using a radial artery catheter. MAIN OUTCOME MEASURES: We assessed the agreement between continuous noninvasive finger cuff-derived (CNAP Monitor 500; CNSystems Medizintechnik, Graz, Austria) and invasive AP measurements in a prospective method comparison study in patients having neurosurgery using all beat-to-beat AP measurements (Methodall), 10-s averages (Methodavg), one 30-min period of 10-s averages (Method30), Method30 with additional offset subtraction (Method30off), and 10 30-s periods without (Methodiso) or with (Methodiso-zero) application of the zero zone. The agreement was analysed using Bland-Altman and error grid analysis. RESULTS: For mean AP, the mean of the differences (95% limits of agreement) was 9.0 (-12.9 to 30.9) mmHg for Methodall, 9.2 (-12.5 to 30.9) mmHg for Methodavg, 6.5 (-9.3 to 22.2) mmHg for Method30, 0.5 (-9.5 to 10.5) mmHg for Method30off, 4.9 (-6.0 to 15.7) mmHg for Methodiso, and 3.4 (-5.9 to 12.7) mmHg for Methodiso-zero. Similar trends were found for systolic and diastolic AP. Results of error grid analysis were also influenced by using different methods for data sampling and data processing. CONCLUSION: Data sampling and data processing substantially impact the results of comparative statistics in method comparison studies of continuous AP monitoring systems. Depending on the method used for data sampling and data processing, the performance of an AP test method may be considered clinically acceptable or unacceptable.
Subject(s)
Arterial Pressure , Blood Pressure Determination , Austria , Blood Pressure , Germany , Humans , Prospective StudiesABSTRACT
Pulse pressure variation (PPV) and cardiac output (CO) can guide perioperative fluid management. Capstesia (Galenic App, Vitoria-Gasteiz, Spain) is a mobile application for snapshot pulse wave analysis (PWAsnap) and estimates PPV and CO using pulse wave analysis of a snapshot of the arterial blood pressure waveform displayed on any patient monitor. We evaluated the PPV and CO measurement performance of PWAsnap in adults having major abdominal surgery. In a prospective study, we simultaneously measured PPV and CO using PWAsnap installed on a tablet computer (PPVPWAsnap, COPWAsnap) and using invasive internally calibrated pulse wave analysis (ProAQT; Pulsion Medical Systems, Feldkirchen, Germany; PPVProAQT, COProAQT). We determined the diagnostic accuracy of PPVPWAsnap in comparison to PPVProAQT according to three predefined PPV categories and by computing Cohen's kappa coefficient. We compared COProAQT and COPWAsnap using Bland-Altman analysis, the percentage error, and four quadrant plot/concordance rate analysis to determine trending ability. We analyzed 190 paired PPV and CO measurements from 38 patients. The overall diagnostic agreement between PPVPWAsnap and PPVProAQT across the three predefined PPV categories was 64.7% with a Cohen's kappa coefficient of 0.45. The mean (± standard deviation) of the differences between COPWAsnap and COProAQT was 0.6 ± 1.3 L min- 1 (95% limits of agreement 3.1 to - 1.9 L min- 1) with a percentage error of 48.7% and a concordance rate of 45.1%. In adults having major abdominal surgery, PPVPWAsnap moderately agrees with PPVProAQT. The absolute and trending agreement between COPWAsnap with COProAQT is poor. Technical improvements are needed before PWAsnap can be recommended for hemodynamic monitoring.
Subject(s)
Mobile Applications , Adult , Blood Pressure , Cardiac Output , Humans , Prospective Studies , Pulse Wave Analysis , Reproducibility of Results , ThermodilutionABSTRACT
Pulse wave analysis (PWA) allows estimation of cardiac output (CO) based on continuous analysis of the arterial blood pressure (AP) waveform. We describe the physiology of the AP waveform, basic principles of PWA algorithms for CO estimation, and PWA technologies available for clinical practice. The AP waveform is a complex physiological signal that is determined by interplay of left ventricular stroke volume, systemic vascular resistance, and vascular compliance. Numerous PWA algorithms are available to estimate CO, including Windkessel models, long time interval or multi-beat analysis, pulse power analysis, or the pressure recording analytical method. Invasive, minimally-invasive, and noninvasive PWA monitoring systems can be classified according to the method they use to calibrate estimated CO values in externally calibrated systems, internally calibrated systems, and uncalibrated systems.
Subject(s)
Cardiac Output/physiology , Monitoring, Physiologic/methods , Pulse Wave Analysis/methods , Algorithms , Arterial Pressure/physiology , Blood Pressure Determination/methods , Humans , Reproducibility of ResultsABSTRACT
Pulse pressure variation (PPV) is a dynamic cardiac preload variable used to predict fluid responsiveness. PPV can be measured non-invasively using innovative finger-cuff systems allowing for continuous arterial pressure waveform recording, e.g., the Nexfin system [BMEYE B.V., Amsterdam, The Netherlands; now Clearsight (Edwards Lifesciences, Irvine, CA, USA)] (PPVFinger). However, the agreement between PPVFinger and PPV derived from an arterial catheter (PPVART) in obese patients having laparoscopic bariatric surgery is unknown. We compared PPVFinger and PPVART at 6 time points in 60 obese patients having laparoscopic bariatric surgery in a secondary analysis of a prospective method comparison study. We used Bland-Altman analysis to assess absolute agreement between PPVFinger and PPVART. The predictive agreement for fluid responsiveness between PPVFinger and PPVART was evaluated across three PPV categories (PPV < 9%, PPV 9-13%, PPV > 13%) as concordance rate of paired measurements and Cohen's kappa. The overall mean of the differences between PPVFinger and PPVART was 0.5 ± 4.6% (95%-LoA - 8.6 to 9.6%) and the overall predictive agreement was 72.4% with a Cohen's kappa of 0.53. The mean of the differences was - 0.7 ± 3.8% (95%-LoA - 8.1 to 6.7%) without pneumoperitoneum in horizontal position and 1.1 ± 4.8% (95%-LoA - 8.4 to 10.5%) during pneumoperitoneum in reverse-Trendelenburg position. The absolute agreement and predictive agreement between PPVFinger and PPVART are moderate in obese patients having laparoscopic bariatric surgery.
Subject(s)
Bariatric Surgery , Laparoscopy , Arterial Pressure , Blood Pressure , Humans , Obesity/surgeryABSTRACT
BACKGROUND: Finger cuff technologies allow continuous noninvasive arterial blood pressure (AP) and cardiac output/index (CO/CI) monitoring. METHODS: We performed a meta-analysis of studies comparing finger cuff-derived AP and CO/CI measurements with invasive measurements in surgical or critically ill patients. We calculated overall random effects model-derived pooled estimates of the mean of the differences and of the percentage error (PE; CO/CI studies) with 95%-confidence intervals (95%-CI), pooled 95%-limits of agreement (95%-LOA), Cochran's Q and I2 (for heterogeneity). RESULTS: The pooled mean of the differences (95%-CI) was 4.2 (2.8 to 5.62) mm Hg with pooled 95%-LOA of -14.0 to 22.5 mm Hg for mean AP (Q=230.4 [P<0.001], I2=91%). For mean AP, the mean of the differences between finger cuff technologies and the reference method was ≤5±8 mm Hg in 9/27 data sets (33%). The pooled mean of the differences (95%-CI) was -0.13 (-0.43 to 0.18) L min-1 with pooled 95%-LOA of -2.56 to 2.23 L min-1 for CO (Q=66.7 [P<0.001], I2=90%) and 0.07 (0.01 to 0.13) L min-1 m-2 with pooled 95%-LOA of -1.20 to 1.15 L min-1 m-2 for CI (Q=5.8 [P=0.326], I2=0%). The overall random effects model-derived pooled estimate of the PE (95%-CI) was 43 (37 to 49)% (Q=48.6 [P<0.001], I2=63%). In 4/19 data sets (21%) the PE was ≤30%, and in 10/19 data sets (53%) it was ≤45%. CONCLUSIONS: Study heterogeneity was high. Several studies showed interchangeability between AP and CO/CI measurements using finger cuff technologies and reference methods. However, the pooled results of this meta-analysis indicate that AP and CO/CI measurements using finger cuff technologies and reference methods are not interchangeable in surgical or critically ill patients. CLINICAL TRIAL NUMBER: PROSPERO registration number: CRD42019119266.
Subject(s)
Arterial Pressure/physiology , Blood Pressure Determination/methods , Cardiac Output/physiology , Critical Care/methods , Perioperative Care/methods , Pulse Wave Analysis/methods , Blood Pressure Determination/instrumentation , Fingers , HumansABSTRACT
Intraoperative hypotension (IOH) i.e., low arterial blood pressure (AP) during surgery is common in patients having non-cardiac surgery under general anaesthesia. It has a multifactorial aetiology, and is associated with major postoperative complications including acute kidney injury, myocardial injury and death. Therefore, IOH may be a modifiable risk factor for postoperative complications. However, there is no uniform definition for IOH. IOH not only occurs during surgery but also after the induction of general anaesthesia before surgical incision. However, the optimal therapeutic approach to IOH remains elusive. There is evidence from one small randomised controlled trial that individualising AP targets may reduce the risk of postoperative organ dysfunction compared with standard care. More research is needed to define individual AP harm thresholds, to develop therapeutic strategies to treat and avoid IOH, and to integrate new technologies for continuous AP monitoring.
ABSTRACT
Blood pressure is the main determinant of organ perfusion. Hypotension is common in patients having surgery and in critically ill patients. The severity and duration of hypotension are associated with hypoperfusion and organ dysfunction. Hypotension is mostly treated reactively after low blood pressure values have already occurred. However, prediction of hypotension before it becomes clinically apparent would allow the clinician to treat hypotension pre-emptively, thereby reducing the severity and duration of hypotension. Hypotension can now be predicted minutes before it actually occurs from the blood pressure waveform using machine-learning algorithms that can be trained to detect subtle changes in cardiovascular dynamics preceding clinically apparent hypotension. However, analyzing the complex cardiovascular system is a challenge because cardiovascular physiology is highly interdependent, works within complicated networks, and is influenced by compensatory mechanisms. Improved hemodynamic data collection and integration will be a key to improve current models and develop new hypotension prediction models.
Subject(s)
Blood Pressure Determination/methods , Critical Care/methods , Hypotension/diagnosis , Hypotension/physiopathology , Perioperative Care/methods , Blood Pressure Determination/trends , Critical Care/trends , Humans , Machine Learning/trends , Perioperative Care/trends , Predictive Value of TestsABSTRACT
Automated continuous noninvasive ward monitoring may enable subtle changes in vital signs to be recognized. There is already some evidence that automated ward monitoring can improve patient outcome. Before automated continuous noninvasive ward monitoring can be implemented in clinical routine, several challenges and problems need to be considered and resolved; these include the meticulous validation of the monitoring systems with regard to their measurement performance, minimization of artifacts and false alarms, integration and combined analysis of massive amounts of data including various vital signs, and technical problems regarding the connectivity of the systems.
Subject(s)
Electronic Data Processing/trends , Monitoring, Physiologic/trends , Patients' Rooms/trends , Delayed Diagnosis/prevention & control , Electronic Data Processing/methods , Humans , Monitoring, Physiologic/methods , Patients' Rooms/organization & administrationABSTRACT
Calsarcin-1 deficient mice develop dilated cardiomyopathy (DCM) phenotype in pure C57BL/6 genetic background (Cs1-ko) despite severe contractile dysfunction and robust activation of fetal gene program. Here we performed a microRNA microarray to identify the molecular causes of this cardiac phenotype that revealed the dysregulation of several microRNAs including miR-301a, which was highly downregulated in Cs1-ko mice compared to the wild-type littermates. Cofilin-2 (Cfl2) was identified as one of the potential targets of miR-301a using prediction databases, which we validated by luciferase assay and mutation of predicted binding sites. Furthermore, expression of miR-301a contrastingly regulated Cfl2 expression levels in neonatal rat ventricular cardiomyocytes (NRVCM). Along these lines, Cfl2 was significantly upregulated in Cs1-ko mice, indicating the physiological association between miR-301a and Cfl2 in vivo. Mechanistically, we found that Cfl2 activated serum response factor response element (SRF-RE) driven luciferase activity in neonatal rat cardiomyocytes and in C2C12 cells. Similarly, knockdown of miR301a activated, whereas, its overexpression inhibited the SRF-RE driven luciferase activity, further strengthening physiological interaction between miR-301a and Cfl2. Interestingly, the expression of SRF and its target genes was strikingly increased in Cs1-ko suggesting a possible in vivo correlation between expression levels of Cfl2/miR-301a and SRF activation, which needs to be independently validated. In summary, our data demonstrates that miR-301a regulates Cofilin-2 in vitro in NRVCM, and in vivo in Cs1-ko mice. Our findings provide an additional and important layer of Cfl2 regulation, which we believe has an extended role in cardiac signal transduction and dilated cardiomyopathy presumably due to the reported involvement of Cfl2 in these mechanisms.