Maxime Cannesson

University of California, Irvine, Irvine, California, United States

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Publications (142)294.01 Total impact

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    ABSTRACT: Several studies have demonstrated that perioperative hemodynamic optimization (or “goal directed therapy”) using minimally invasive hemodynamic monitoring technologies has the ability to improve postoperative patients’ outcome with lower complication rates, shorter hospital lengths of stay, and lower cost of surgery. This specific concept of goal-directed therapy (GDT) uses perioperative cardiac output monitoring and manipulation of physiologic parameters (dynamic parameters of fluid responsiveness) to guide intravenous fluids and inotropic therapy with the goal of ensuring adequate tissue perfusion. Recently, the evidence related to the implementation of GDT strategies has been considered strong enough to allow for the creation of national recommendations in the UK, in France, and by the European Society of Anaesthesiology. The aims of the programs are to apply best practices to high-risk surgical patients and requires the participation of all clinicians involved in patients’ care. Considering the potential clinical and economic benefits of GDT protocols and the positive recommendations from influential scientific societies, more and more hospitals around the world have become interested in implementing hemodynamic optimization in their departments. This review provides the information about the evolution of hemodynamic monitoring from invasive to the more recent noninvasive devices, and how these devices can be used in the operating rooms through well-defined algorithms of GDT.
    Current Anesthesiology Reports. 12/2014;
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    ABSTRACT: To expose residents to two methods of education for point-of-care ultrasound, a traditional didactic lecture and a model/simulation-based lecture, which focus on concepts of cardiopulmonary function, volume status, and evaluation of severe thoracic/abdominal injuries; and to assess which method is more effective.
    Journal of clinical anesthesia. 09/2014;
  • Guo Chen, Yunxia Zuo, Lei Yang, Elena Chung, Maxime Cannesson
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    ABSTRACT: Hemodynamic monitoring and optimization improve postoperative outcome during high-risk surgery. However, hemodynamic management practices among Chinese anesthesiologists are largely unknown. This study sought to evaluate the current intraoperative hemodynamic management practices for high-risk surgery patients in China. From September 2010 to November 2011, we surveyed anesthesiologists working in the operating rooms of 265 hospitals representing 28 Chinese provinces. All questionnaires were distributed to department chairs of anesthesiology or practicing anesthesiologists. Once completed, the 29-item questionnaires were collected and analyzed. Two hundred and 10 questionnaires from 265 hospitals in China were collected. We found that 91.4% of anesthesiologists monitored invasive arterial pressure, 82.9% monitored central venous pressure (CVP), 13.3% monitored cardiac output (CO), 10.5% monitored mixed venous saturation, and less than 2% monitored pulse pressure variation (PPV) or systolic pressure variation (SPV) during high-risk surgery. The majority (88%) of anesthesiologists relied on clinical experience as an indicator for volume expansion and more than 80% relied on blood pressure, CVP and urine output. Anesthesiologists in China do not own enough attention on hemodynamic parameters such as PPV, SPV and CO during fluid management in high-risk surgical patients. The lack of CO monitoring may be attributed largely to the limited access to technologies, the cost of the devices and the lack of education on how to use them. There is a need for improving access to these technologies as well as an opportunity to create guidelines and education for hemodynamic optimization in China.
    Journal of biomedical research. 09/2014; 28(5):376-82.
  • M Cannesson, F Ani, M M Mythen, Z Kain
    BJA British Journal of Anaesthesia 08/2014; · 4.24 Impact Factor
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    ABSTRACT: Noninvasive hemoglobin (Hb) monitoring devices are available in the clinical setting, but their accuracy and precision against central laboratory Hb measurements have not been evaluated in a systematic review and meta-analysis.
    Anesthesia and analgesia. 06/2014;
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    ABSTRACT: The perioperative setting in the United States is noted for variable and fragmented care that increases the chance for errors and adverse outcomes as well as the overall cost of perioperative care. Recently, the American Society of Anesthesiologists put forward the Perioperative Surgical Home (PSH) concept as a potential solution to this problem. Although the PSH concept has been described previously, "real-life" implementation of this new model has not been reported. Members of the Departments of Anesthesiology and Perioperative Care and Orthopedic Surgery, in addition to perioperative hospital services, developed and implemented a series of clinical care pathways defining and standardizing preoperative, intraoperative, postoperative, and postdischarge management for patients undergoing elective primary hip (n = 51) and knee (n = 95) arthroplasty. We report on the impact of the Total Joint Replacement PSH on length of hospital stay (LOS), incidence of perioperative blood transfusions, postoperative complications, 30-day readmission rates, emergency department visits, mortality, and patient satisfaction. The incidence of major complication was 0.0 (0.0-7.0)% and of perioperative blood transfusion was 6.2 (2.9-11.4)%. In-hospital mortality was 0.0 (0.0-7.0)% and 30-day readmission was 0.7 (0.0-3.8)%. All Surgical Care Improvements Project measures were at 100.0 (93.0-100.0)%. The median LOS for total knee arthroplasty and total hip arthroplasty, respectively, was (median (95% confidence interval [interquartile range]) 3 (2-3) [2-3] and 3 (2-3) [2-3] days. Approximately half of the patients were discharged to a location other than their customary residence (70 to skilled nursing facility, 1 to rehabilitation, 39 to home with organization health services, and 36 to home). We believe that our experience with the Total Joint Replacement PSH program provides solid evidence of the feasibility of this practice model to improve patient outcomes and achieve high patient satisfaction. In the future, the impact of LOS on cost will have to be better quantified. Specifically, future studies comparing PSH to traditional care will have to include consideration of postdischarge care, which are drivers of the perioperative costs.
    Anesthesia and analgesia 05/2014; 118(5):1081-1089. · 3.08 Impact Factor
  • Anesthesia and analgesia 05/2014; 118(5):1126-1130. · 3.08 Impact Factor
  • Maxime Cannesson, Zeev Kain
    Anesthesia and analgesia 05/2014; 118(5):901-902. · 3.08 Impact Factor
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    ABSTRACT: Continuous noninvasive arterial pressure monitoring devices are available for bedside use, but the accuracy and precision of these devices have not been evaluated in a systematic review and meta-analysis. The authors performed a systematic review and meta-analysis of studies comparing continuous noninvasive arterial pressure monitoring with invasive arterial pressure monitoring. Random-effects pooled bias and SD of bias for systolic arterial pressure, diastolic arterial pressure, and mean arterial pressure were calculated. Continuous noninvasive arterial pressure monitoring was considered acceptable if pooled estimates of bias and SD were not greater than 5 and 8 mmHg, respectively, as recommended by the Association for the Advancement of Medical Instrumentation. Twenty-eight studies (919 patients) were included. The overall random-effect pooled bias and SD were -1.6 ± 12.2 mmHg (95% limits of agreement -25.5 to 22.2 mmHg) for systolic arterial pressure, 5.3 ± 8.3 mmHg (-11.0 to 21.6 mmHg) for diastolic arterial pressure, and 3.2 ± 8.4 mmHg (-13.4 to 19.7 mmHg) for mean arterial pressure. In 14 studies focusing on currently commercially available devices, bias and SD were -1.8 ± 12.4 mmHg (-26.2 to 22.5 mmHg) for systolic arterial pressure, 6.0 ± 8.6 mmHg (-10.9 to 22.9 mmHg) for diastolic arterial pressure, and 3.9 ± 8.7 mmHg (-13.1 to 21.0 mmHg) for mean arterial pressure. The results from this meta-analysis found that inaccuracy and imprecision of continuous noninvasive arterial pressure monitoring devices are larger than what was defined as acceptable. This may have implications for clinical situations where continuous noninvasive arterial pressure is being used for patient care decisions.
    Anesthesiology 03/2014; · 5.16 Impact Factor
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    ABSTRACT: The numbers of people requiring total arthroplasty is expected to increase substantially over the next two decades. However, increasing costs and new payment models in the USA have created a sustainability gap. Ad hoc interventions have reported marginal cost reduction, but it has become clear that sustainability lies only in complete restructuring of care delivery. The Perioperative Surgical Home (PSH) model, a patient-centered and physician-led multidisciplinary system of coordinated care, was implemented at UC Irvine Health in 2012 for patients undergoing primary elective total knee arthroplasty (TKA) or total hip arthroplasty (THA). This observational study examines the costs associated with this initiative.
    Perioperative medicine (London, England). 01/2014; 3:6.
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    ABSTRACT: Intraoperative haemodynamic optimization based on fluid management and stroke volume optimization (Goal Directed Fluid Therapy [GDFT]) can improve patients' postoperative outcome. We have described a closed-loop fluid management system based on stroke volume variation and stroke volume monitoring. The goal of this system is to apply GDFT protocols automatically. After conducting simulation, engineering, and animal studies the present report describes the first use of this system in the clinical setting. Prospective pilot study. Patients undergoing major surgery. Twelve patients at two institutions had intraoperative GDFT delivered by closed-loop controller under the direction of an anaesthesiologist. Compliance with GDFT management was defined as acceptable when a patient spent more than 85% of the surgery time in a preload independent state (defined as stroke volume variation<13%), or when average cardiac index during the case was superior or equal to 2.5l/min/m(2). Closed-loop GDFT was completed in 12 patients. Median surgery time was 447 [309-483] min and blood loss was 200 [100-1000] ml. Average cardiac index was 3.2±0.8l/min/m(2) and on average patients spent 91% (76 to 100%) of the surgery time in a preload independent state. Twelve of 12 patients met the criteria for compliance with intraoperative GDFT management. Intraoperative GDFT delivered by closed-loop system under anaesthesiologist guidance allowed to obtain targeted objectives in 91% of surgery time. This approach may provide a way to ensure consistent high-quality delivery of fluid administration and compliance with perioperative goal directed therapy.
    Annales francaises d'anesthesie et de reanimation 12/2013; · 0.77 Impact Factor
  • Source
    Maxime Cannesson, Joseph Rinehart
    International Journal of Clinical Monitoring and Computing 12/2013;
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    ABSTRACT: Administration of fluid to improve cardiac output is the mainstay of hemodynamic resuscitation. Not all patients respond to fluid therapy, and excessive fluid administration is harmful. Predicting fluid responsiveness can be challenging, particularly in children. Numerous hemodynamic variables have been proposed as predictors of fluid responsiveness. Dynamic variables based on the heart-lung interaction appear to be excellent predictors of fluid responsiveness in adults, but there is no consensus on their usefulness in children. We systematically reviewed the current evidence for predictors of fluid responsiveness in children. A systematic search was performed using PubMed (1947-2013) and EMBASE (1974-2013). Search terms included fluid, volume, response, respond, challenge, bolus, load, predict, and guide. Results were limited to studies involving pediatric subjects (infant, child, and adolescent). Extraction of data was performed independently by 2 authors using predefined data fields, including study quality indicators. Any variable with an area under the receiver operating characteristic curve that was significantly above 0.5 was considered predictive. Twelve studies involving 501 fluid boluses in 438 pediatric patients (age range 1 day to 17.8 years) were included. Twenty-four variables were investigated. The only variable shown in multiple studies to be predictive was respiratory variation in aortic blood flow peak velocity (5 studies). Stroke volume index, stroke distance variation, and change in cardiac index (and stroke volume) induced by passive leg raising were found to be predictive in single studies only. Static variables based on heart rate, systolic arterial blood pressure, preload (central venous pressure, pulmonary artery occlusion pressure), thermodilution (global end diastolic volume index), ultrasound dilution (active circulation volume, central blood volume, total end diastolic volume, total ejection fraction), echocardiography (left ventricular end diastolic area), and Doppler (stroke volume index, corrected flow time) did not predict fluid responsiveness in children. Dynamic variables based on arterial blood pressure (systolic pressure variation, pulse pressure variation and stroke volume variation, difference between maximal or minimal systolic arterial blood pressure and systolic pressure at end-expiratory pause) and plethysmography (pulse oximeter plethysmograph amplitude variation) were also not predictive. There were contradicting results for plethymograph variation index and inferior vena cava diameter variation. Respiratory variation in aortic blood flow peak velocity was the only variable shown to predict fluid responsiveness in children. Static variables did not predict fluid responsiveness in children, which was consistent with evidence in adults. Dynamic variables based on arterial blood pressure did not predict fluid responsiveness in children, but the evidence for dynamic variables based on plethysmography was inconclusive.
    Anesthesia and analgesia 12/2013; 117(6):1380-1392. · 3.08 Impact Factor
  • M Cannesson
    Annales francaises d'anesthesie et de reanimation 10/2013; · 0.77 Impact Factor
  • Article: In reply.
    Anesthesiology 09/2013; 119(3):726-7. · 5.16 Impact Factor
  • Maxime Cannesson, Michael Earing
    Anesthesiology 08/2013; · 5.16 Impact Factor
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    ABSTRACT: BACKGROUND:Surgical patients present with a wide variety of body sizes and blood volumes, have large differences in baseline volume status, and may exhibit significant differences in cardiac function. Any closed-loop fluid administration system must be robust against these differences. In the current study, we tested the stability and robustness of the closed-loop fluid administration system against the confounders of body size, starting volume status, and cardiac contractility using control engineering methodology.METHODS:Using an independently developed previously published hemodynamic simulation model that includes blood volumes and cardiac contractility, we ran a Monte-Carlo simulation series with variation in starting blood volume and body weight (phase 1, weight 35-100 kg), and starting blood volume and cardiac contractility (phase 2, contractility from 1500 [severe heart failure] to 6000 [hyperdynamic]). The performance of the controller in resuscitating to the target set point was evaluated in terms of milliliters of blood volume error from optimal, with <250 mL of error defined as "successful."RESULTS:One thousand simulations were run for each of the 2 phases of the study. The phase 1 mean blood volume error ± SD from optimal was 25 ± 59 mL. The phase 2 mean blood volume error from optimal was -60 ± 89 mL. The lower 95% Clopper-Pearson binomial confidence interval for resuscitation to within 250 mL of optimal blood volume for phase 1 and 2 was 99.6% and 97.1%, respectively.CONCLUSION:The results indicate that the controller is highly effective in targeting optimal blood and stroke volumes, regardless of weight, contractility or starting blood volume.
    Anesthesia and analgesia 07/2013; · 3.08 Impact Factor
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    ABSTRACT: BACKGROUND:Closed-loop systems have been designed to assist practitioners in maintaining stability of various physiologic variables in the clinical setting. In this context, we recently performed in silico testing of a novel closed-loop fluid management system that is designed for cardiac output and pulse pressure variation monitoring and optimization. The goal of the present study was to assess the effectiveness of this newly developed system in optimizing hemodynamic variables in an in vivo surgical setting.METHODS:Sixteen Yorkshire pigs underwent a 2-phase hemorrhage protocol and were resuscitated by either the Learning Intravenous Resuscitator closed-loop system or an anesthesiologist. Median hemodynamic values and variation of hemodynamics were compared between groups.RESULTS:Cardiac index (in liters per minute per square meter) and stroke volume index (in milliliters per square meter) were higher in the closed-loop group compared with the anesthesiologist group over the protocol (3.7 [3.4-4.1] vs 3.5 [3.2-3.9]; 95% Wald confidence interval, -0.5 to -0.23; P < 0.0005 and 40 [34-45] vs 36 [31-38]; 95% Wald confidence interval, -5.9 to -3.1; P < 0.0005, respectively). There was no significant difference in total fluid administration between the closed-loop and anesthesiologist groups (3685 [3230-4418] vs 3253 [2735-3926] mL; 95% confidence interval, -1651 to 431; P = 0.28). Closed-loop group animals also had lower coefficients of variance of cardiac index and stroke volume index during the protocol (11% [10%-16%] vs 22% [18%-23%]; confidence interval, 0.8%-12.3%; P = 0.02 and 11% [8%-16%] vs 17% [13%-21%]; confidence interval, 0.2%-11.4%; P = 0.04, respectively).CONCLUSION:This in vivo study building on previous simulation work demonstrates that the closed-loop fluid management system used in this experiment can perform fluid resuscitation during mild and severe hemorrhages and is able to maintain high cardiac output and stroke volume while reducing hemodynamic variability.
    Anesthesia and analgesia 07/2013; · 3.08 Impact Factor
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    ABSTRACT: Hemodynamic optimization improves postoperative outcomes in high-risk surgery patients. The monitoring of cardiac output (CO) and dynamic parameters of fluid responsiveness can guide hemodynamic optimization. We conducted a survey to assess the current hemodynamic monitoring and management practices of Korean anesthesiologists during high-risk surgery. E-mails containing a link to our survey, which consisted of 33 questions relating to hemodynamic monitoring during high-risk surgery, were sent to 3,943 members of the Korean Society of Anesthesiologists (KSA). The survey web page was open from December 30, 2011 to March 31, 2012. A total of 139 anesthesiologists responded during the survey period. Invasive arterial pressure (97.2%) and central venous pressure (93.4%) were routinely monitored. CO was monitored in 58.5% of patients; stroke volume variations were monitored in 50.9% of patients. However, CO was consistently optimized by < 20% of anesthesiologists. An arterial pressure waveform-derived CO monitor was the most frequently used device to monitor CO (79.0%). Blood pressure, urine output, central venous pressure, and clinical experience were considered to be the best indicators of volume expansion than CO or dynamic parameters of fluid responsiveness. The survey revealed that KSA members frequently monitor CO and dynamic parameters of fluid responsiveness during high-risk surgery. However, static indices were used more often to judge volume expansion. The current study reveals that CO is not frequently optimized despite the relatively high incidence of CO monitoring during high-risk surgery in Korea.
    Korean journal of anesthesiology 07/2013; 65(1):19-32.
  • Article: In reply.
    Maxime Cannesson, Yannick Le Manach
    Anesthesiology 06/2013; 118(6):1481. · 5.16 Impact Factor

Publication Stats

2k Citations
294.01 Total Impact Points

Institutions

  • 2009–2014
    • University of California, Irvine
      • • Department of Anesthesiology and Perioperative Care
      • • Department of Medicine
      Irvine, California, United States
  • 2013
    • Soonchunhyang University
      • College of Medicine
      Onyang, South Chungcheong, South Korea
  • 2012
    • Sichuan University
      • Department of Anesthesiology
      Chengdu, Sichuan Sheng, China
    • Hôpital La Pitié Salpêtrière (Groupe Hospitalier "La Pitié Salpêtrière - Charles Foix")
      Lutetia Parisorum, Île-de-France, France
  • 2011
    • Triemli City Hospital
      Zürich, Zurich, Switzerland
    • Centre Hospitalier Universitaire de Lyon
      • Service d'Anesthésie-Réanimation
      Lyon, Rhone-Alpes, France
    • St. George's School
      Middletown, Rhode Island, United States
  • 2010–2011
    • CSU Mentor
      Long Beach, California, United States
    • Mayo Foundation for Medical Education and Research
      • Department of Anesthesiology
      Scottsdale, AZ, United States
    • King Abdulaziz University
      Djidda, Makkah, Saudi Arabia
  • 2007–2011
    • CHU de Lyon - Hôpital Cardio-vasculaire et Pneumologique Louis Pradel
      Lyons, Rhône-Alpes, France
    • Claude Bernard University Lyon 1
      Villeurbanne, Rhône-Alpes, France
  • 2006–2011
    • Hospices Civils de Lyon
      Lyons, Rhône-Alpes, France
  • 2006–2009
    • Hôpital Louis Pradel
      Lyons, Rhône-Alpes, France
  • 2006–2007
    • University of Pittsburgh
      Pittsburgh, Pennsylvania, United States
  • 2005
    • Centre Hospitalier Lyon Sud
      Lyons, Rhône-Alpes, France