Marcel E. Durieux

Five billion people, from disproportionately low and middle-income countries, are unable to access safe, timely, and affordable surgical and anesthesia care [1]. Patients in Africa are twice as likely to die after surgery when compared with the global average for postoperative deaths [2]. Given most of this mortality happens after surgery, perioperative mortality rate (POMR) has been identified by the World Health Organization as a global measure of the quality of surgical procedures. Perioperative data collected during surgery can predict adverse surgical outcomes. Access to such data is essential for decreasing mortality rates and improving medical treatment. In many low and middle-income countries, data is often manually recorded on paper flowsheets, restricting the ability to discover medical trends and inhibiting easy and efficient data aggregation and analysis. Thus, systems put in place to digitize these flowsheets are key in utilizing data to improve overall healthcare. By streamlining the digitization of intraoperative flowsheets, more data will be collected while minimizing the time while optimizing the quality. In order to optimize the digitization process, the research team has made several improvements to the current system, including a complete redesign of the digital upload process in the form of a mobile app that integrates scanner functionality and upload capability into one convenient and efficient step, thereby reducing devices and platforms required to upload. This redesign also provides increased user feedback and corrects issues in which flowsheet uploads failed. In addition, improvements were made to the SARA (Scanning Apparatus for Remote Access). SARA is a wooden box designed to standardized the distance, lighting, and background for each scan, improving readability. Possible replacement power supplies and lighting sources are being examined for durability, ease of repair, and functionality. Additionally, usability testing and evaluation was completed to measure increases in successful task completion and decreases in time and steps required. The goal of this project is to design a system to digitize the information contained in surgical flowsheets at the University Teaching Hospital of Kigali in Rwanda in the most efficient and effective manner. To accomplish this goal, the research team reduced the time and devices needed to upload a surgical sheet by 78% and 50%, respectively. Hardware and software malfunctions were fixed, and the longevity of the system was improved as procedural checklists to upkeep and correctly utilize the system were implemented.

Perioperative data are essential to investigating the causes of adverse surgical outcomes. In some low to middle income countries, these data are computationally inaccessible due to a lack of digitization of surgical flowsheets. In this paper, we present a deep image segmentation approach using a U-Net architecture that can detect hand-drawn symbols on a flowsheet graph. The segmentation mask outputs are post-processed with techniques unique to each symbol to convert into numeric values. The U-Net method can detect, at the appropriate time intervals, the symbols for heart rate and blood pressure with over 99 percent accuracy. Over 95 percent of the predictions fall within an absolute error of five when compared to the actual value. The deep learning model outperformed template matching even with a small size of annotated images available for the training set.

BACKGROUND: Chronic opioid use is a significant public health concern. Surgery is a risk factor for developing chronic opioid use. Patients undergoing major spine surgery frequently are prescribed opioids preoperatively and may be at risk for chronic opioid use postoperatively. The aim of this study was to investigate the incidence of and perioperative risk factors associated with chronic opioid use after major spine surgery. METHODS: The records of patients who underwent elective major spine surgery at the University of Virginia between March 2011 and February 2016 were retrospectively reviewed. The primary outcome was chronic opioid use through 12 months postoperatively. Demographic data, medical comorbidities, preoperative pain scores, and medication use including daily morphine-equivalent (ME) dose, intraoperative use of lidocaine and ketamine, estimated blood loss, postoperative pain scores and medication use, and postoperative opioid use were collected. Logistic regression models were used to examine factors associated with chronic opioid use. RESULTS: Of 1477 patient records reviewed, 412 patients (27.9%) were opioid naive and 1065 patients (72.3%) used opioids before surgery. Opioid data were available for 1325 patients, while 152 patients were lost to 12-month follow-up and were excluded. Of 958 preoperative opioid users, 498 (52.0%) remained chronic users through 12 months. There was a decrease in opioid dosage (mg ME) from preoperative to 12 months postoperatively with a mean difference of −14.7 mg ME (standard deviation, 1.57; 95% confidence interval [CI], −17.8 to −11.7). Among 367 previously opioid-naive patients, 67 (18.3%) became chronic opioid users. Factors associated with chronic opioid use were examined using logistic regression models. Preoperative opioid users were nearly 4 times more likely to be chronic opioid users through 12 months than were opioid-naive patients (odds ratio, 3.95; 95% CI, 2.51–6.33; P < .001). Mean postoperative pain score (0–10) was associated with increased odds of chronic opioid use (odds ratio for a 1 unit increase in pain score 1.25, 95% CI, 1.13–1.38; P < .001). Use of intravenous ketamine or lidocaine was not associated with chronic opioid use through 12 months. CONCLUSIONS: Greater than 70% of patients presenting for major spine surgery used opioids preoperatively. Preoperative opioid use and higher postoperative pain scores were associated with chronic opioid use through 12 months. Use of ketamine and lidocaine did not decrease the risk for chronic opioid use. Surveillance of patients for these factors may identify those at highest risk for chronic opioid use and target them for intervention and reduction strategies.

Perioperative lung-protective ventilation (LPV) can reduce perioperative pulmonary morbidity. We hypothesized that modifying default anesthesia machine ventilator settings would increase the use of intraoperative LPV. Default tidal volume settings on our anesthesia machines were decreased from 600 to 400 mL, and default positive end-expiratory pressure was increased from 0 to 5 cm H₂O. This modification increased mean positive end-expiratory pressure from 3.1 to 5.0 cm H₂O and decreased mean tidal volume from 8.2 to 6.7 mL/kg predicted body weight. Notably, increased adherence to LPV from 1.6% to 23.0% occurred quickly with the rate of increase more than doubling from 1.8% to 3.9% per year.

Objective: To investigate the incidence of perioperative adverse events in patients receiving intravenous methadone for major spine surgery.Design: Retrospective review of perioperative records from March 2011 and February 2016.Setting: University of Virginia Healthsystem.Patients: Adult patients undergoing elective spinal fusion of two or more levels. Main Outcome Measures: Incidence of respiratory depression, time to extubation, hypotension, hypoxemia, reintubation, cardiac complications, and death.Results: Reviewed 1,478 patient records. Mean intraoperative methadone dose was 0.14 ± 0.07 mg/kg. A total of 1,142 patients (77.4 percent) were extubated in the operating room, 543 (36.8 percent) experienced respiratory depression, 1,180 (79.8 percent) hypoxemia, and 22 (1.5 percent) required reintubation. Cardiac complications included arrhythmias (289 patients, 29.9 percent), QTc prolongation (568 patients, 58.8 percent), and myocardial infarction (16 patients, 1.1 percent). Two in hospital deaths occurred (0.14 percent).Conclusions: Mild-moderate respiratory depression is observed following a onetime dose of intraoperative methadone, and monitoring in an appropriate postoperative setting is recommended.

BACKGROUND: Lung-protective ventilation (LPV) has been demonstrated to improve clinical outcomes in surgical patients. There are very limited data on the current use of LPV for patients undergoing 1-lung ventilation (1LV) despite evidence that 1LV may be a particularly important setting for its use. In this multicenter study, we report trends in ventilation practice for patients undergoing 1LV. METHODS: The Multicenter Perioperative Outcomes Group database was used to identify patients undergoing 1LV. We retrieved and calculated median initial and overall tidal volume (V _T) for the cohort and for high-risk subgroups (female sex, obesity [body mass index >30 kg/m²], and short stature), percentage of patients receiving positive end-expiratory pressure (PEEP) ≥5 cm H₂O, LPV during 1LV (V _T ≤ 6 mL/kg predicted body weight [PBW] and PEEP ≥5 cm H₂O), and ventilator driving pressure (ΔP; plateau airway pressure − PEEP). RESULTS: Data from 5609 patients across 4 institutions were included in the analysis. Median V _T was calculated for each case and since the data were normally distributed, the mean is reported for the entire cohort and subgroups. Mean of median V _T during 1LV for the cohort was 6.49 ± 1.82 mL/kg PBW. V _T (mL/kg PBW) for high-risk subgroups was significantly higher; 6.86 ± 1.97 for body mass index ≥30 kg/m², 7.05 ± 1.92 for female patients, and 7.33 ± 2.01 for short stature patients. Mean of the median V _T declined significantly over the study period (from 6.88 to 5.72; P < .001), and the proportion of patients receiving LPV increased significantly over the study period (from 9.1% to 54.6%; P < .001). These changes coincided with a significant decrease in ΔP during the study period, from 19.4 cm H₂O during period 1 to 17.3 cm H₂O in period 12 (P = .003). CONCLUSIONS: Despite a growing awareness of the importance of protective ventilation, a large proportion of patients undergoing 1LV continue to receive V _T PEEP levels outside of recommended thresholds. Moreover, V _T remains higher and LPV less common in high-risk subgroups, potentially placing them at elevated risk for iatrogenic lung injury.

Functional neurosurgery has undergone rapid growth over the last few years fueled by advances in imaging technology and novel treatment modalities. These advances have led to new surgical treatments using minimally invasive and precise techniques for conditions such as Parkinson’s disease, essential tremor, epilepsy, and psychiatric disorders. Understanding the goals and technological issues of these procedures is imperative for the anesthesiologist to ensure safe management of patients presenting for functional neurosurgical procedures. In this review, we discuss the advances in neurosurgical techniques for deep brain stimulation, focused ultrasound and minimally invasive laser-based treatment of refractory epilepsy and provide a guideline for anesthesiologists caring for patients undergoing these procedures.