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ABSTRACT: Hemodynamic monitoring and management has greatly improved during the past decade. Technologies have evolved from very invasive to non-invasive, and the philosophy has shifted from a static approach to a functional approach. However, despite these major changes, the critical care community still has potential to improve its ability to adopt the most modern standards of research methodology in order to more effectively evaluate new monitoring systems and their impact on patient outcome. Today, despite the huge enthusiasm raised by new hemodynamic monitoring systems, there is still a big gap between clinical research studies evaluating these monitors and clinical practice. A few studies, especially in the perioperative period, have shown that hemodynamic monitoring systems coupled with treatment protocols can improve patient outcome. These trials are small and, overall, the corpus of science related to this topic does not yet fit the standard of clinical research methodology encountered in other specialties such as cardiology and oncology. Larger randomized trials or quality improvement processes will probably answer questions related to the real impact of these systems.
Critical care (London, England) 03/2013; 17(2):208. · 4.61 Impact Factor
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ABSTRACT: Blood pressure monitoring has come a long way from the initial observations made by Reverend Hales in the 18th century. There are none that deny the importance of monitoring perioperative blood pressure; however, the limited ability of the current prevalent technology (oscillometric blood pressure monitoring) to offer continuous blood pressure measurements leaves room for improvement. Invasive monitoring is able to detect beat-to-beat blood pressure measurement, but the risks inherent to the procedure make it unsuitable for routine use except when this risk is outweighed by the benefits. This review focuses on the discoveries which have led up to the current blood pressure monitoring technologies, and especially the creation of those offering non-invasive but continuous blood pressure monitoring capabilities, including their methods of measurement and limitations.
Frontiers of medicine. 01/2013;
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International Journal of Clinical Monitoring and Computing 11/2012;
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ABSTRACT: BACKGROUND:: Cardiac output (CO) is rarely monitored during surgery, and arterial pressure remains the only hemodynamic parameter for assessing the effects of volume expansion (VE). However, whether VE-induced changes in arterial pressure accurately reflect changes in CO has not been demonstrated. The authors studied the ability of VE-induced changes in arterial pressure and in pulse pressure variation to detect changes in CO induced by VE in the perioperative period. METHODS:: The authors studied 402 patients in four centers. Hemodynamic variables were recorded before and after VE. Response to VE was defined as more than 15% increase in CO. The ability of VE-induced changes in arterial pressure to detect changes in CO was assessed using a gray zone approach. RESULTS:: VE increased CO of more than 15% in 205 patients (51%). Areas under the receiver operating characteristic curves for VE-induced changes in systolic, diastolic, means, and pulse pressure ranged between 0.64 and 0.70, and sensitivity and specificity ranged between 52 and 79%. For these four arterial pressure-derived parameters, large gray zones were found, and more than 60% of the patients lay within this inconclusive zone. A VE-induced decrease in pulse pressure variation of 3% or more allowed detecting a fluid-induced increase in CO of more than 15% with a sensitivity of 90% and a specificity of 77% and a gray zone between 2.2 and 4.7% decrease in pulse pressure variation including 14% of the patients. CONCLUSION:: Only changes in pulse pressure variation accurately detect VE-induced changes in CO and have a potential clinical applicability.
Anesthesiology 11/2012; · 5.36 Impact Factor
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Anesthesiology 10/2012; 117(5):937-9. · 5.36 Impact Factor
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ABSTRACT: The authors compared the performance of a group of anesthesia providers to closed-loop (Learning Intravenous Resuscitator [LIR]) management in a simulated hemorrhage scenario using cardiac output monitoring.
A prospective cohort study.
In silico simulation.
University hospital anesthesiologists and the LIR closed-loop fluid administration system.
Using a patient simulator, a 90-minute simulated hemorrhage protocol was run, which included a 1,200-mL blood loss over 30 minutes. Twenty practicing anesthesiology providers were asked to manage this scenario by providing fluids and vasopressor medication at their discretion. The simulation program was also run 20 times with the LIR closed-loop algorithm managing fluids and an additional 20 times with no intervention.
Simulated patient weight, height, heart rate, mean arterial pressure, and cardiac output (CO) were similar at baseline. The mean stroke volume, the mean arterial pressure, CO, and the final CO were higher in the closed-loop group than in the practitioners group, and the coefficient of variance was lower. The closed-loop group received slightly more fluid (2.1 v 1.9 L, p < 0.05) than the anesthesiologist group.
Despite the roughly similar volumes of fluid given, the closed-loop maintained more stable hemodynamics than the practitioners primarily because the fluid was given earlier in the protocol and CO optimized before the hemorrhage began, whereas practitioners tended to resuscitate well but only after significant hemodynamic change indicated the need. Overall, these data support the potential usefulness of this closed-loop algorithm in clinical settings in which dynamic predictors are not available or applicable.
Journal of cardiothoracic and vascular anesthesia 07/2012; 26(5):933-9. · 1.06 Impact Factor
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ABSTRACT: To evaluate the validity of cardiac output (CO) measurements obtained using the Nexfin device in comparison to those obtained with the esophageal Doppler in steady-state conditions and after phenylephrine administration.
Prospective observational study.
Operating room of a North American academic medical center.
25 ASA physical status 1, 2, and 3 patients referred for abdominal or orthopedic surgeries.
After endotracheal intubation, patients who presented with a 20% or greater decrease in mean arterial pressure (MAP) received an intravenous (IV) bolus of 100 μg of phenylephrine. If MAP was still 20% lower than the patient's baseline level at least 10 minutes after the first vasopressor treatment, a second bolus of 100 μg of phenylephrine was given.
CO was measured simultaneously by esophageal Doppler (CO(ED)) and Nexfin (CO(NXF)) at baseline and when blood pressure peaked after an IV 100 μg phenylephrine bolus. Comparisons were then made between the two devices to evaluate the ability of the Nexfin device to track changes in CO.
66 pairs of data were obtained. Mean CO(ED) and CO(NXF) were 4.7 ± 1.8 L/min and 5.6 ± 2.0 L/min, respectively. There was a significant relationship between CO(ED) and CO(NXF) (r(2) = 0.82; P < 0.001). The agreement between CO(ED) and CO(NXF) was 0.88 ± 0.86 L/min (Bland Altman). The mean percent error (Critchley and Critchley) of CO(NXF) versus CO(ED) was 37%. Trending analysis found a 94% concordance between changes in CO(ED) and CO(NXF) after phenylephrine administration.
Intraoperative CO measurement using the Nexfin device has a strong correlation with CO measured by esophageal Doppler.
Journal of clinical anesthesia 06/2012; 24(4):275-83. · 1.32 Impact Factor
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ABSTRACT: phenylephrine is used daily during anesthesia for treating hypotension. However, the effects of phenylephrine on cardiac output (CO) are not clear. We hypothesized that the impact of phenylephrine on cardiac output is related to preload dependency.
eight pigs were studied at a preload independent stage (after CO augmentation) and at a preload dependent stage (after a 21 ml/kg hemorrhage). At each stage, phenylephrine boluses (0.5, 1.0, 2.0, and 4.0 μg/kg) were given randomly while mean arterial pressure (MAP), CO, inferior vena cava flow (IVCf) (both measured using ultrasonic flow probes), and pulse pressure variation were measured.
at the preload independent stage, phenylephrine boluses induced significant increases in MAP (from 72 ± 6 to 100 ± 6 mmHg; P < 0.05) and decreases in CO and IVCf (from 7.0 ± 0.8 to 6.0 ± 1.1 l/min and from 4.6 ± 0.5 to 3.8 ± 0.6 l/min, respectively). At the preload-dependent stage, phenylephrine boluses induced significant increases in MAP (from 40 ± 7 to 65 ± 9 mmHg), CO (from 4.1 ± 0.6 to 4.9 ± 0.7 l/min), and IVCf (from 3.0 ± 0.4 to 3.5 ± 0.6 l/min; all data presented are for 4 μg/kg). Incremental doses of phenylephrine induced incremental changes in cardiac output. A pulse pressure variation >16.4% before phenylephrine predicted an increase in stroke volume with a 93% sensitivity and a 100% specificity.
impact of phenylephrine on cardiac output is related to preload dependency. When the heart is preload independent, phenylephrine boluses induce on average a decrease in cardiac output. When the heart is preload dependent, phenylephrine boluses induce on average an increase in cardiac output.
Journal of Applied Physiology 05/2012; 113(2):281-9. · 3.75 Impact Factor
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Journal of cardiothoracic and vascular anesthesia 04/2012; 26(4):711-20. · 1.06 Impact Factor
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ABSTRACT: Pulse pressure variation (PPV) can be monitored several ways, but according to recent survey data it is most often visually estimated ("eyeballed") by practitioners. It is not known how accurate visual estimation of PPV is, or whether eyeballing of PPV in goal-directed fluid therapy studies may limit the ability to blind the control group to PPV value. The goal of this study was to test the accuracy of visual estimation of PPV. Using a simulator program designed by the authors that runs on a PC, 20 residents and 19 attendings were shown five arterial pressure waveforms each with different PPV values (range 1-30 %) moving at one of three sweep speeds (6.25, 12.5, or 25 mm/s) and asked to determine the PPV. There was a weak but significant relationship between true PPV and eyeball PPV (r (2) = 0.22; p < 0.01). The agreement between true PPV and eyeball PPV was 3.3 ± 8.7 %. The mean percent error was 122 %. The rate of correct response group classification was 65 %. Mean percent error was higher the faster the waveform sweep speed (130 % at 25 mm/s vs. 117 % at 6.25 mm/s), and correct responsiveness classification lower (58 % at 25 mm/s vs. 69 % at 6.25 mm/s). The results from this study show that eyeballing the arterial pressure waveform in order to evaluate pulse pressure variation is not accurate.
International Journal of Clinical Monitoring and Computing 04/2012; 26(3):191-6.
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Anesthesiology 03/2012; 116(3):741-3. · 5.36 Impact Factor
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ABSTRACT: The Nexfin device allows for non-invasive beat-to-beat blood pressure monitoring (BP(NXF)). Perioperative hypotension and hypertension have been shown to be associated with poor clinical outcomes. The goal of the present study was to assess the ability of this device to decrease the duration of significant intraoperative hypo- or hypertension compared to standard BP monitoring by cuff (BP(CUFF)). We studied25 patients (ASA I-III) undergoing either abdominal or orthopedic surgery. BP(CUFF) was monitored every 5 min from the introduction of anesthesia, while BP(NXF) was monitored continuously on the opposite arm. When systolic BP(NXF) (SBP(NXF)) decreased or increased more than 20% relative to baseline SBP(NXF), a standard BP(CUFF) measurement was taken to compare values. In addition, the time interval between the 20% change in SBP(NXF) and the next scheduled standard SBP(CUFF) measurement was recorded for each event. The mean length of surgery was 3.0 ± 0.3 h. Patients presented with 11 ± 4 episodes of hypotension and 12 ± 4 episodes of hypertension during the surgery. If BP(CUFF) had been used, this would have resulted in 21 ± 7 min of hypotension and 20 ± 10 min of hypertension. If hemodynamic changes seen by SBP(NXF) were appropriately treated, an average of 7 ± 1 min/h of hypotension time, 7 ± 2 min/h of hypertension time and 14 ± 3 min per hour of hypo- or hypertension time may have been identified. The Nexfin BP has the potential to decrease the time of hypotension and hypertension compared to conventional intermittent BP(CUFF) monitoring. Therefore, this device has the potential to positively impact clinical outcomes.
International Journal of Clinical Monitoring and Computing 03/2012; 26(2):133-40.
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ABSTRACT: During anesthesia, maneuvers which cause the least disturbance of cerebral oxygenation with the greatest decrease in intracranial pressure would be most beneficial to patients with intracranial hypertension. Both head-up tilt (HUT) and hyperventilation are used to decrease brain bulk, and both may be associated with decreases in cerebral oxygenation. In this observational study, our null hypothesis was that the impact of HUT and hyperventilation on cerebral tissue oxygen saturation (SctO2) and cerebral blood volume (CBV) are comparable.
Surgical patients without neurological disease were anesthetized with propofol-remifentanil. Before the start of surgery, frequency-domain near-infrared spectroscopy was used to measure SctO2 and CBV at the supine position, at the 30° head-up and head-down positions, as well as during hypoventilation and hyperventilation.
Thirty-three patients were studied. Both HUT and hyperventilation induced small decreases in SctO2 [3.5 (2.6)%; P < 0.001 and 3.0 (1.8)%; P < 0.001, respectively] and in CBV [0.05 (0.07) mL x 100 g(-1); P < 0.001 and 0.06 (0.05) mL x 100 g(-1); P < 0.001, respectively]. There were no differences between HUT to 30° and hyperventilation to an end-tidal carbon dioxide (ETCO2) of 25 mmHg (from 45 mmHg) in both SctO2 (P = 0.3) and CBV (P = 0.4).
The small but statistically significant decreases in both SctO2 and CBV caused by HUT and hyperventilation are comparable. There was no correlation between the decreases in SctO2 and CBV and the decreases in blood pressure and cardiac output during head-up and head-down tilts. However, the decreases in both SctO2 and CBV correlate with the decreases in ETCO2 during ventilation adjustment.
Canadian Anaesthetists? Society Journal 01/2012; 59(4):357-65. · 2.31 Impact Factor
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ABSTRACT: Dynamic predictors of fluid responsiveness have made automated management of fluid resuscitation more practical. We present initial simulation data for a novel closed-loop fluid-management algorithm (LIR, Learning Intravenous Resuscitator).
The performance of the closed-loop algorithm was tested in three phases by using a patient simulator including a pulse-pressure variation output. In the first phase, LIR was tested in three different hemorrhage scenarios and compared with no management. In the second phase, we compared LIR with 20 practicing anesthesiologists for the management of a simulated hemorrhage scenario. In the third phase, LIR was tested under conditions of noise and artifact in the dynamic predictor.
In the first phase, we observed a significant difference between the unmanaged and the LIR groups in moderate to large hemorrhages in heart rate (76 ± 8 versus 141 ± 29 beats/min), mean arterial pressure (91 ± 6 versus 59 ± 26 mm Hg), and cardiac output (CO; (6.4 ± 0.9 versus 3.2 ± 1.8 L/min) (P < 0.005 for all comparisons). In the second phase, LIR intervened significantly earlier than the practitioners (16.0 ± 1.3 minutes versus 21.5 ± 5.6 minutes; P < 0.05) and gave more total fluid (2,675 ± 244 ml versus 1,968 ± 644 ml; P < 0.05). The mean CO was higher in the LIR group than in the practitioner group (5.9 ± 0.2 versus 5.2 ± 0.6 L/min; P < 0.05). Finally, in the third phase, despite the addition of noise to the pulse-pressure variation value, no significant difference was found across conditions in mean, final, or minimum CO.
These data demonstrate that LIR is an effective volumetric resuscitator in simulated hemorrhage scenarios and improved physician management of the simulated hemorrhages.
Critical care (London, England) 11/2011; 15(6):R278. · 4.61 Impact Factor
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Critical care (London, England) 10/2011; 15(5):445. · 4.61 Impact Factor
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ABSTRACT: Closed-loop (automated) controllers are encountered in all aspects of modern life in applications ranging from air-conditioning to spaceflight. Although these systems are virtually ubiquitous, they are infrequently used in anesthesiology because of the complexity of physiologic systems and the difficulty in obtaining reliable and valid feedback data from the patient. Despite these challenges, closed-loop systems are being increasingly studied and improved for medical use. Two recent developments have made fluid administration a candidate for closed-loop control. First, the further description and development of dynamic predictors of fluid responsiveness provides a strong parameter for use as a control variable to guide fluid administration. Second, rapid advances in noninvasive monitoring of cardiac output and other hemodynamic variables make goal-directed therapy applicable for a wide range of patients in a variety of clinical care settings. In this article, we review the history of closed-loop controllers in clinical care, discuss the current understanding and limitations of the dynamic predictors of fluid responsiveness, and examine how these variables might be incorporated into a closed-loop fluid administration system.
Anesthesia and analgesia 09/2011; 114(1):130-43. · 3.08 Impact Factor
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ABSTRACT: Tissue oxygen saturation (StO(2)) assessed using Near Infrared Spectroscopy and its derived parameters during a vascular occlusion test (VOT) can detect microvascular changes in septic shock patients. General anesthesia (GA) impacts microcirculation. Our aim was to study the effects of general anesthesia on StO(2) and StO(2) derived parameters obtained during VOT in patients referred for cardiac surgery.
We studied 15 patients referred for cardiac surgery before and after induction of GA. Before GA induction, we also studied 15 healthy volunteers (non patients) in order to compare baseline physiological data between patients and healthy subjects. Hemodynamic and microcirculatory (StO(2), ischemic slope, reperfusion slope, and hyperemic response) data were recorded at each step. We used the Inspectra StO(2) system (Hutchinson Inc, MN, USA) with a sensor placed on the thenar eminence. StO(2) values were obtained at baseline and during a VOT. A sphyngomanometer was placed on the forearm above the StO(2) probe and the cuff was then rapidly inflated 30 mmHg above systolic pressure and was maintained inflated until the StO(2) value reached 40%. It was then rapidly deflated.
Healthy volunteers had significantly higher reperfusion slope than patients (348 [251-393] vs. 261 [185-279] %/min; P < 0.05). GA induction induced no significant change in StO(2) value compared to baseline (79 [75-85] vs. 80 [76-86]%; P = 0.57). We observed a significant decrease in ischemic slope (from -12 [-16--8] to -8 [-10--6] %/min; P = 0.004) and in reperfusion slope (from 261 [185-279] %/min to 164 [151-222] %/min; P = 0.008) suggesting a decrease in local metabolic rate and a negative impact on reperfusion reserve induced by anesthesia.
StO(2) derived parameters during a VOT are impacted by GA induction. These parameters may have potential for microcirculation assessment in patients undergoing surgery.
International Journal of Clinical Monitoring and Computing 09/2011; 25(4):237-44.
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ABSTRACT: To investigate the ability of a new stroke volume variation algorithm to predict fluid responsiveness during general anesthesia and mechanical ventilation in animals with multiple extrasystoles.
Prospective laboratory animal experiment.
Investigational laboratory.
Eight instrumented pigs.
Eight anesthetized and mechanically ventilated pigs were monitored with an arterial line and a pulmonary artery catheter. Multiple extrasystoles were induced by right ventricular pacing (25% of heart beats). Arterial pressure waveforms were recorded and stroke volume variation was computed from the new and from the standard algorithm. The new stroke volume variation algorithm is designed to restore the respiratory component of the arterial pressure waveform despite multiple ectopic heart beats. Cardiac output was measured before and after 56 fluid boluses (7 mL/kg of 6% hydroxy ethyl starch) performed at different volemic states.
A positive response to fluid boluses (>15% increase in cardiac output) was observed in 21 of 56 boluses. The new stroke volume variation was higher in responders than in nonresponders (19% ± 5% vs. 12% ± 3%, p < .05), whereas the standard stroke volume variation was similar in the two groups (29% ± 8% vs. 26% ± 11%, p = .4). Receiver operating characteristic curve analysis showed that the new stroke volume variation was an accurate predictor of fluid responsiveness (sensitivity = 86%, specificity = 85%, best cutoff value = 14%, area under the curve = 0.892 ±, whereas the standard stroke volume variation was not (area under the curve = 0.596 ± 0.077).
In contrast to the standard stroke volume variation, the new stroke volume variation algorithm was able to predict fluid responsiveness in animals with multiple ventricular extrasystoles.
Critical care medicine 09/2011; 40(1):193-8. · 6.37 Impact Factor
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ABSTRACT: Predicting the effects of volume expansion on cardiac output and oxygen delivery is of major importance in different clinical scenarios. Functional hemodynamic parameters based on pulse waveform analysis, which are relying on the effects of mechanical ventilation on stroke volume and its surrogates, have been shown to be reliable predictors of fluid responsiveness during anesthesia and intensive care unit treatment, as demonstrated by several clinical studies and meta-analyses. However, different limitations of these parameters have to be considered when they are used in clinical practice. Today, they can be continuously and automatically monitored by a variety of commercially available devices. These parameters have been introduced into the concept of perioperative fluid management and hemodynamic optimization - an approach that may positively impact postoperative patients' outcomes. In this article, technical aspects of the assessment of the functional hemodynamic parameters derived from pulse waveform analysis are summarized, emphasizing their advantages, limitations and potential applications, primarily in a perioperative setting in order to improve patient outcome.
Expert Review of Medical Devices 09/2011; 8(5):635-46. · 2.63 Impact Factor
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ABSTRACT: Cardiac output (CO) monitoring based on pulse contour analysis (Vigileo-FloTrac) has the potential to be used for goal-directed fluid therapy in the perioperative setting. However, factors such as vasopressor usage may impact Vigileo-FloTrac's reliability in tracking CO changes. We tested third-generation Vigileo-FloTrac system's ability to accurately measure the changes in CO induced by vasopressor administration and increased preload in comparison with esophageal Doppler measurements.
In 33 anesthetized patients, CO was monitored simultaneously by the third-generation Vigileo-FloTrac and esophageal Doppler. Hemodynamic challenges included phenylephrine (to increase vasomotor tone), ephedrine (to increase myocardial contractility and heart rate), and whole-body tilting (to increase preload). Measurements were performed before and after each intervention.
Overall, 176 pairs of CO measurements were obtained. The difference between paired pulse contour and Doppler measurements of CO was 0.14 ± 2.13 L/min (mean ± SD), and the percentage error (2 SD of the difference divided by the mean CO of the reference method) was 66%. The trending ability of pulse contour versus Doppler was 23% (concordance, the percentage of the total number of data points that are in 1 of the 2 quadrants of agreement) after phenylephrine treatment, 69% (concordance) after ephedrine treatment, and 96% (concordance) after whole-body tilting.
The pulse contour method of measuring CO, as implemented in the third-generation Vigileo-FloTrac device, accurately tracks changes in CO when preload changes. However, the pulse contour method does not accurately track changes in CO induced with phenylephrine and ephedrine.
Anesthesia and analgesia 08/2011; 113(4):751-7. · 3.08 Impact Factor
