Michael Ma's research while affiliated with University of California, Irvine and other places

Background Compared to traditional breathing circuits, low-volume anesthesia machines utilize a lower-volume breathing circuit paired with needle injection vaporizers that supply volatile agents into the circuit mainly during inspiration. We aimed to assess whether or not low-volume anesthesia machines, such as the Maquet Flow-i C20 anesthesia workstation (MQ), deliver volatile anesthetics more efficiently than traditional anesthesia machines, such as the GE Aisys CS² anesthesia machine (GE), and, secondarily, whether this was in a meaningful economic or environmentally conscious way. Methodology Participants enrolled in the study (Institutional Review Board Identifier: 2014-1248) met the following inclusion criteria: 18-65 years old, scheduled for surgery requiring general anesthesia at the University of California Irvine Health, and expected to receive sevoflurane for the duration of the procedure. Exclusion criteria included age <18 years old, a history of chronic obstructive pulmonary disorder, cardiovascular disease, sevoflurane sensitivity, body mass index >30 kg/m², American Society of Anesthesiologists >2, pregnancy, or surgery scheduled <120 minutes. We calculated the total amount of sevoflurane delivered and consumption rates during induction and maintenance periods and compared the groups using one-sided parametric testing (Student’s t-test). There was no suspicion that the low-volume circuit could use more sevoflurane and that the outcome did not answer our research question. One-sided testing allowed for more power to be more certain of smaller differences in our results. Results In total, 103 subjects (MQ: n = 52, GE: n = 51) were analyzed. Seven subjects were lost to attrition of different types. Overall, the MQ group consumed significantly less sevoflurane (95.5 ± 49.3 g) compared to the GE group (118.3 ± 62.4 g) (p = 0.043), corresponding to an approximately 20% efficiency improvement in overall agent delivery. When accounting for the fresh gas flow setting, agent concentration, and length of induction, the MQ delivered the volatile agent at a significantly lower rate compared to the GE (7.4 ± 3.2 L/minute vs. 9.1 ± 4.1 L/minute; p = 0.017). Based on these results, we estimate that the MQ can save an estimated average of $239,440 over the expected 10-year machine lifespan. This 20% decrease in CO2 equivalent emissions corresponds to 201 metric tons less greenhouse gas emissions over a decade compared to the GE, which is equivalent to 491,760 miles driven by an average passenger vehicle or 219,881 pounds of coal burned. Conclusions Overall, our results from this study suggest that the MQ delivers statistically significantly less (~20%) volatile agent during routine elective surgery using a standardized anesthetic protocol and inclusion/exclusion criteria designed to minimize any patient or provider heterogeneity effects on the results. The results demonstrate an opportunity for economic and environmental benefits.

Background Invasive arterial pressure monitoring is frequently used in operating room and intensive care unit patients to provide continuous assessment of hemodynamics. We have previously developed an algorithm trained to detect error of >10 mmHg in leveling of the arterial pressure transducer from only the features of the waveform itself. In the present study we used the detection algorithm in real-time during surgical cases where the primary team had placed an arterial line for hemodynamic monitoring and tested its ability to detected introduced transducer drop errors. Methods Patients having surgery at UCI Medical Center who were 18 years or older and were expected to have invasive arterial pressure monitoring as part of their anesthetic care were eligible for enrollment. The arterial pressure waveform was captured during surgery and at random times the transducer was dropped from its secured location. The ability of the previously trained algorithm to detect these drops from the waveform alone was assessed in real-time as well as false-positives. Results A total of 50 patients were ultimately included for over 80 hours of monitoring time. A total of 78 drop tests were performed in that time. Overall, the algorithm detected 69 of these drops (88%), however detection for errors of 10 mmHg or more was 98% and for >12 mmHg was 100%. The overall false positive rate was 0.65% and balanced accuracy was 0.99 for errors >10 mmHg. Conclusion The algorithm was highly sensitive for detection of transducer drops resulting in error of ≥10 mmHg in real-time, with a very low false-positive rate. This algorithm may be of value in applications utilizing the arterial line for input where safety is essential.

In critically ill and high-risk surgical room patients, an invasive arterial catheter is often inserted to continuously measure arterial pressure (AP). The arterial waveform pressure measurement, however, may be compromised by damping or inappropriate reference placement of the pressure transducer. Clinicians, decision support systems, or closed-loop applications that rely on such information would benefit from the ability to detect error from the waveform alone. In the present study we hypothesized that machine-learning trained algorithms could discriminate three types of transducer error from accurate monitoring with receiver operator characteristic (ROC) curve areas greater than 0.9. After obtaining written consent, patient arterial line waveform data was collected in the operating room in real-time during routine surgery requiring arterial pressure monitoring. Three deliberate error conditions were introduced during monitoring: Damping, Transducer High, and Transducer Low. The waveforms were split up into 10 s clips that were featurized. The data was also either calibrated against the patient’s own baseline or left uncalibrated. The data was then split into training and validation sets, and machine-learning algorithms were run in a Monte-Carlo fashion on the training data with variable sized training sets and hyperparameters. The algorithms with the highest balanced accuracy were pruned, then the highest performing algorithm in the training set for each error state (High, Low, Damped) for both calibrated and uncalibrated data was finally tested against the validation set and the ROC and precision-recall curve area-under the curve (AUC) calculated. 38 patients were enrolled in the study with a mean age of 52 ± 15 years. A total of 40 h of monitoring time was recorded with approximately 120,000 heart beats featurized. For all error states, ROC AUCs for algorithm performance on classification of the state were greater than 0.9; when using patient-specific calibrated data AUCs were 0.94, 0.95, and 0.99 for the transducer low, transducer high, and damped conditions respectively. Machine-learning trained algorithms were able to discriminate arterial line transducer error states from the waveform alone with a high degree of accuracy.

We have previously demonstrated in in-silico, pre-clinical animal models, and finally human clinical studies the ability of a novel closed-loop vasopressor titration system to manage norepinephrine infusion rates to keep mean arterial blood pressure in a very tight range, reduce hypotension time and severity, and reduce overtreatment. We hypothesized that the same controller could, with modification for pharmacologic differences, suitably titrate a lower-potency longer duration of action agent like phenylephrine. Using the same physiologic simulation model as was used previously for in-silico testing of our controller for norepinephrine, we first updated the model to include a new vasopressor agent modeled after phenylephrine. A series of simulation tests patterned after our previous norepinephrine study was then conducted, this time using phenylephrine for management, in order to both test the system with the new agent and allow for comparisons between the two. Hundreds of simulation trials were conducted across a range of patient and environmental variances. The controller performance was characterized based on time in target, time above and below target, coefficient of variation, and using Varvel’s criteria. The controller kept the simulated patients’ MAP in target for 94% of management time in the simple scenarios and more than 85% of time in the most challenging scenarios. Varvel criteria were all under 1% error for expected pharmacologic responses and were consistent with those established for norepinephrine in our previous studies. The controller was able to acceptably titrate phenylephrine in this simulated patient model consistent with performance previously seen for norepinephrine after adjusting for the anticipated differences between the two agents.

Background: Compared to traditional breathing circuits, low-flow anesthesia machines utilize a low-volume breathing circuit system by injecting volatile agent into the circuit mainly during inspiration. We aimed to assess whether Maquet Flow-i C20 anesthesia workstation delivers volatile anesthetic more efficiently than a GE Aisys CS² during elective general surgery. Methods: Eligible candidates enrolled in the study (2014-1248) met the following inclusion criteria: 18 – 65 years old, scheduled for surgery requiring general anesthesia at UC Irvine Health, and expected to receive sevoflurane for the duration of the procedure. Exclusion criteria: < 18 years old, history of COPD, cardiovascular disease, sevoflurane sensitivity, BMI > 30 kg/m², ASA > 2, pregnant, or surgery scheduled < 120 minutes. We calculated the total amount of sevoflurane delivered and consumption rates during induction/maintenance periods and compared the groups using parametric testing (Student’s t-Test). Results: In total, 103 subjects (Maquet: n=52, GE: n=51) were analyzed. Overall, the Flow-i C-20 group consumed significantly less sevoflurane (95.5 ± 49.3 g) compared to the Aisys² (118.2 ± 62.4 g) (p = 0.043 for group difference) corresponding to an approximately 20% efficiency improvement in overall agent delivery. When accounting for the fresh gas flow setting, agent concentration and length of induction, the Maquet machines delivered volatile agent at a significantly lower rate compared to the GE devices (7.4 ± 3.2 L/min vs. 9.2 ± 4.1 L/min; p = 0.017). Based on these results, we estimate that the Maquet Flow-i workstations can save an estimated average of $239,440 over the expected 10-year machine lifespan. This 20% decrease in CO2 equivalent emissions corresponds to 201 metric tons less greenhouse gas emissions over a decade compared to the GE Aisys; equivalent to 491,760 miles driven by an average passenger vehicle or 219,881 pounds of coal burned. Conclusions: Overall, our results from this pilot study suggest that the Maquet Flow-i delivers significantly less (~20%) volatile agent during routine elective surgery using a standardized anesthetic protocol compared to a traditional anesthesia system. The results demonstrate a strong opportunity for economic and environmental benefits if implemented across other medical institutions.

Background: The prognostic value of right ventricular systolic dysfunction in high-risk patients undergoing non-emergent open abdominal surgery is unknown. Here, we aim to evaluate whether presence of preexisting right ventricular systolic dysfunction in this surgical cohort is independently associated with higher incidence of postoperative major adverse cardiac events and all-cause in-hospital mortality. Methods: This is a single-centered retrospective study. Patients identified as American Society Anesthesiology Classification III and IV who had a preoperative echocardiogram within 1 year of undergoing non-emergent open abdominal surgery between January 2010 and May 2017 were included in the study. Incidence of postoperative major cardiac adverse events and all-cause in-hospital mortality were collected. Multivariable logistic regression was performed in a step-wise manner to identify independent association between preexisting right ventricular systolic dysfunction with outcomes of interest. Results: Preexisting right ventricular systolic dysfunction was not associated with postoperative major adverse cardiac events (P = 0.26). However, there was a strong association between preexisting right ventricular systolic dysfunction and all-cause in-hospital mortality (P = 0.00094). After multivariate analysis, preexisting right ventricular systolic dysfunction continued to be an independent risk factor for all-cause in-hospital mortality with an odds ratio of 18.9 (95' CI: 1.8-201.7; P = 0.015). Conclusion: In this retrospective study of high-risk patients undergoing non-emergent open abdominal surgery, preexisting right ventricular systolic dysfunction was found to have a strong association with all-cause in-hospital mortality.

Evaluation of cardiac function during periods of stress is of key importance for the perioperative setting. Non-invasive hemodynamic monitors provide markers of cardiac function. This pilot study sought to evaluate the ability of a non-invasive hemodynamic monitor to detect cardiac stress during formal stress echocardiography testing. The primary goal was to compare the change in hemodynamic values during the pre/during/post phases of stress echocardiography testing in patients who had results negative versus positive for myocardial ischemia. Adult patients scheduled for outpatient cardiac stress testing were screened. Only patients scheduled for stress-echocardiography testing were consented. Patients with history of arrhythmias were excluded. During the testing, patients wore a cuff-based hemodynamic sensor (Nexfin system, Edwards Lifesciences). Data from the hemodynamic sensor were compared to the findings of the stress study. A total of 37 patients were enrolled, with 31 patients included for analysis. Five patients had stress studies positive for coronary ischemia. Comparison of the hemodynamic variables between patients who had a positive stress study versus negative showed a significant reduction in the percentage change in dP/dt and stroke volume from baseline (p < 0.05). This pilot study indicates that patients who have abnormal stress echocardiograms also have significantly reduced values from a noninvasive hemodynamic monitor. Further evaluation of the clinical utility of this technology, to assist in the care of patients at risk for cardiac ischemia, should be carried out.

Introduction: Point-of-care ultrasound (POCUS) is a rapidly expanding discipline that has proven to be a valuable modality in the hospital setting. Recent evidence has demonstrated the utility of commercially available video conferencing technologies, namely, FaceTime (Apple Inc, Cupertino, CA, USA) and Google Glass (Google Inc, Mountain View, CA, USA), to allow an expert POCUS examiner to remotely guide a novice medical professional. However, few studies have evaluated the ability to use these teleultrasound technologies to guide a nonmedical novice to perform an acute care POCUS examination for cardiac, pulmonary, and abdominal assessments. Additionally, few studies have shown the ability of a POCUS-trained cardiac anesthesiologist to perform the role of an expert instructor. This study sought to evaluate the ability of a POCUS-trained anesthesiologist to remotely guide a nonmedically trained participant to perform an acute care POCUS examination. Methods: A total of 21 nonmedically trained undergraduate students who had no prior ultrasound experience were recruited to perform a three-part ultrasound examination on a standardized patient with the guidance of a remote expert who was a POCUS-trained cardiac anesthesiologist. The examination included the following acute care POCUS topics: (1) cardiac function via parasternal long/short axis views, (2) pneumothorax assessment via pleural sliding exam via anterior lung views, and (3) abdominal free fluid exam via right upper quadrant abdominal view. Each examiner was given a handout with static images of probe placement and actual ultrasound images for the three views. After a brief 8 min tutorial on the teleultrasound technologies, a connection was established with the expert, and they were guided through the acute care POCUS exam. Each view was deemed to be complete when the expert sonographer was satisfied with the obtained image or if the expert sonographer determined that the image could not be obtained after 5 min. Image quality was scored on a previously validated 0 to 4 grading scale. The entire session was recorded, and the image quality was scored during the exam by the remote expert instructor as well as by a separate POCUS-trained, blinded expert anesthesiologist. Results: A total of 21 subjects completed the study. The average total time for the exam was 8.5 min (standard deviation = 4.6). A comparison between the live expert examiner and the blinded postexam reviewer showed a 100% agreement between image interpretations. A review of the exams rated as three or higher demonstrated that 87% of abdominal, 90% of cardiac, and 95% of pulmonary exams achieved this level of image quality. A satisfaction survey of the novice users demonstrated higher ease of following commands for the cardiac and pulmonary exams compared to the abdominal exam. Conclusions: The results from this pilot study demonstrate that nonmedically trained individuals can be guided to complete a relevant ultrasound examination within a short period. Further evaluation of using telemedicine technologies to promote POCUS should be evaluated.

Initial feasibility of a novel closed-loop controller created by our group for closed-loop control of vasopressor infusions has been previously described. In clinical practice, vasopressor potency may be affected by a variety of factors including other pharmacologic agents, organ dysfunction, and vasoplegic states. The purpose of this study was therefore to evaluate the effectiveness of our controller in the face of large variations in drug potency, where ‘effective’ was defined as convergence on target pressure over time. We hypothesized that the controller would remain effective in the face up to a tenfold variability in drug response. To perform the robustness study, our physiologic simulator was used to create randomized simulated septic patients. 250 simulated patients were managed by the closed-loop in each of 7 norepinephrine responsiveness conditions: 0.1 ×, 0.2 ×, 0.5 ×, 1 ×, 2 ×, 5 ×, and 10 × expected population response to drug dose. Controller performance was evaluated for each level of norepinephrine response using Varvel’s criteria as well as time-out-of-target. Median performance error and median absolute performance error were less than 5% in all response levels. Wobble was below 3% and divergence remained negative (i.e. the controller tended to converge towards the target over time) in all norepinephrine response levels, but at the highest response level of 10 × the value approached zero, suggesting the controller may be approaching instability. Response levels of 0.1 × and 0.2 × exhibited significantly higher time-out-of-target in the lower ranges (p < 0.001) compared to the 1 × response level as the controller was slower to correct the initial hypotension. In this simulation study, the closed-loop vasopressor controller remained effective in simulated patients exhibiting 0.1 to 10 × the expected population drug response.

Objectives: To evaluate whether the presence of preexisting right ventricular (RV) dysfunction in high-risk patients undergoing nonemergent major vascular surgery is associated independently with higher incidents of postoperative cardiac complications and a longer length of hospital stay. Design: Retrospective chart review. Setting: Single-center university hospital setting. Participants: The patient population consisted of those identified as American Society of Anesthesiologists classification III and above who had a preoperative echocardiogram within 1 year of undergoing nonemergent major vascular surgery between January 2010 and May 2017. Measurements and main results: After multivariate analyses, RV dysfunction (RVD) is associated independently with a higher incidence of postoperative major cardiac complications with an odds ratio = 6.3 (95% confidence interval [CI], 1.0-38.5; p = 0.046). In addition, patients with RVD had a 50% longer length of stay than those without RVD (incident rate ratio [95% CI], 1.5 [1.2-1.8]; p < 0.001). Conclusion: In this retrospective study of high-risk patients undergoing major vascular surgery, RV dysfunction was associated independently with a higher incidence of postoperative major cardiovascular events and longer length of hospital stays. Based on current findings, the prognostic value of RVD extends beyond the cardiac surgical cohort. Knowledge in management of patients with RVD in the perioperative setting should be understood by all anesthesiologists. Of note, a future study with a larger sample size is needed to validate the current findings given the small sample size of this study.