Opioid Dose Variation in Cardiac Surgery: A Multicenter Study of Practice.

BACKGROUND: Although high-opioid anesthesia was long the standard for cardiac surgery, some anesthesiologists now favor multimodal analgesia and low-opioid anesthetic techniques. The typical cardiac surgery opioid dose is unclear, and the degree to which patients, anesthesiologists, and institutions influence this opioid dose is unknown. METHODS: We reviewed data from nonemergency adult cardiac surgeries requiring cardiopulmonary bypass performed at 30 academic and community hospitals within the Multicenter Perioperative Outcomes Group registry from 2014 through 2021. Intraoperative opioid administration was measured in fentanyl equivalents. We used hierarchical linear modeling to attribute opioid dose variation to the institution where each surgery took place, the primary attending anesthesiologist, and the specifics of the surgical patient and case. RESULTS: Across 30 hospitals, 794 anesthesiologists, and 59,463 cardiac cases, patients received a mean of 1139 (95% confidence interval [CI], 1132-1146) fentanyl mcg equivalents of opioid, and doses varied widely (standard deviation [SD], 872 µg). The most frequently used opioids were fentanyl (86% of cases), sufentanil (16% of cases), hydromorphone (12% of cases), and morphine (3% of cases). 0.6% of cases were opioid-free. 60% of dose variation was explainable by institution and anesthesiologist. The median difference in opioid dose between 2 randomly selected anesthesiologists across all institutions was 600 µg of fentanyl (interquartile range [IQR], 283-1023 µg). An anesthesiologist's intraoperative opioid dose was strongly correlated with their frequency of using a sufentanil infusion (r = 0.81), but largely uncorrelated with their use of nonopioid analgesic techniques (|r| < 0.3). CONCLUSIONS: High-dose opioids predominate in cardiac surgery, with substantial dose variation from case to case. Much of this variation is attributable to practice variability rather than patient or surgical differences. This suggests an opportunity to optimize opioid use in cardiac surgery.

Variation in Intraoperative Opioid Administration by Patient, Clinician, and Hospital Contribution.

Importance: The opioid crisis has led to scrutiny of opioid exposures before and after surgical procedures. However, the extent of intraoperative opioid variation and the sources and contributing factors associated with it are unclear. Objective: To analyze attributable variance of intraoperative opioid administration for patient-, clinician-, and hospital-level factors across surgical and analgesic categories. Design, Setting, and Participants: This cohort study was conducted using electronic health record data collected from a national quality collaborative database. The cohort consisted of 1 011 268 surgical procedures at 46 hospitals across the US involving 2911 anesthesiologists, 2291 surgeons, and 8 surgical and 4 analgesic categories. Patients without ambulatory opioid prescriptions or use history undergoing an elective surgical procedure between January 1, 2014, and September 11, 2020, were included. Data were analyzed from January 2022 to July 2023. Main Outcomes and Measures: The rate of intraoperative opioid administration as a continuous measure of oral morphine equivalents (OMEs) normalized to patient weight and case duration was assessed. Attributable variance was estimated in a hierarchical structure using patient, clinician, and hospital levels and adjusted intraclass correlations (ICCs). Results: Among 1 011 268 surgical procedures (mean [SD] age of patients, 55.9 [16.2] years; 604 057 surgical procedures among females [59.7%]), the mean (SD) rate of intraoperative opioid administration was 0.3 [0.2] OME/kg/h. Together, clinician and hospital levels contributed to 20% or more of variability in intraoperative opioid administration across all analgesic and surgical categories (adjusting for surgical or analgesic category, ICCs ranged from 0.57-0.79 for the patient, 0.04-0.22 for the anesthesiologist, and 0.09-0.26 for the hospital, with the lowest ICC combination 0.21 for anesthesiologist and hosptial [0.12 for the anesthesiologist and 0.09 for the hospital for opioid only]). Comparing the 95th and fifth percentiles of opioid administration, variation was 3.3-fold among anesthesiologists (surgical category range, 2.7-fold to 7.7-fold), 4.3-fold among surgeons (surgical category range, 3.4-fold to 8.0-fold), and 2.2-fold among hospitals (surgical category range, 2.2-fold to 4.3-fold). When adjusted for patient and surgical characteristics, mean (square error mean) administration was highest for cardiac surgical procedures (0.54 [0.56-0.52 OME/kg/h]) and lowest for orthopedic knee surgical procedures (0.19 [0.17-0.21 OME/kg/h]). Peripheral and neuraxial analgesic techniques were associated with reduced administration in orthopedic hip (51.6% [95% CI, 51.4%-51.8%] and 60.7% [95% CI, 60.5%-60.9%] reductions, respectively) and knee (48.3% [95% CI, 48.0%-48.5%] and 60.9% [95% CI, 60.7%-61.1%] reductions, respectively) surgical procedures, but reduction was less substantial in other surgical categories (mean [SD] reduction, 13.3% [8.8%] for peripheral and 17.6% [9.9%] for neuraxial techniques). Conclusions and Relevance: In this cohort study, clinician-, hospital-, and patient-level factors had important contributions to substantial variation of opioid administrations during surgical procedures. These findings suggest the need for a broadened focus across multiple factors when developing and implementing opioid-reducing strategies in collaborative quality-improvement programs.

Development and Testing of a Data Capture Device for Use With Clinical Incentive Spirometers: Testing and Usability Study.

BACKGROUND: The incentive spirometer is a basic and common medical device from which electronic health care data cannot be directly collected. As a result, despite numerous studies investigating clinical use, there remains little consensus on optimal device use and sparse evidence supporting its intended benefits such as prevention of postoperative respiratory complications. OBJECTIVE: The aim of the study is to develop and test an add-on hardware device for data capture of the incentive spirometer. METHODS: An add-on device was designed, built, and tested using reflective optical sensors to identify the real-time location of the volume piston and flow bobbin of a common incentive spirometer. Investigators manually tested sensor level accuracies and triggering range calibrations using a digital flowmeter. A valid breath classification algorithm was created and tested to determine valid from invalid breath attempts. To assess real-time use, a video game was developed using the incentive spirometer and add-on device as a controller using the Apple iPad. RESULTS: In user testing, sensor locations were captured at an accuracy of 99% (SD 1.4%) for volume and 100% accuracy for flow. Median and average volumes were within 7.5% (SD 6%) of target volume sensor levels, and maximum sensor triggering values seldom exceeded intended sensor levels, showing a good correlation to placement on 2 similar but distinct incentive spirometer designs. The breath classification algorithm displayed a 100% sensitivity and a 99% specificity on user testing, and the device operated as a video game controller in real time without noticeable interference or delay. CONCLUSIONS: An effective and reusable add-on device for the incentive spirometer was created to allow the collection of previously inaccessible incentive spirometer data and demonstrate Internet-of-Things use on a common hospital device. This design showed high sensor accuracies and the ability to use data in real-time applications, showing promise in the ability to capture currently inaccessible clinical data. Further use of this device could facilitate improved research into the incentive spirometer to improve adoption, incentivize adherence, and investigate the clinical effectiveness to help guide clinical care.

Association of Anesthesiologist Staffing Ratio With Surgical Patient Morbidity and Mortality.

Importance: Recent studies have investigated the effect of overlapping surgeon responsibilities or nurse to patient staffing ratios on patient outcomes, but the association of overlapping anesthesiologist responsibilities with patient outcomes remains unexplored to our knowledge. Objective: To examine the association between different levels of anesthesiologist staffing ratios and surgical patient morbidity and mortality. Design, Setting, and Participants: A retrospective, matched cohort study consisting of major noncardiac inpatient surgical procedures performed from January 1, 2010, to October 31, 2017, was conducted in 23 US academic and private hospitals. A total of 866 453 adult patients (aged ≥18 years) undergoing major inpatient surgery within the Multicenter Perioperative Outcomes Group electronic health record registry were included. Anesthesiologist sign-in and sign-out times were used to calculate a continuous time-weighted average staffing ratio variable for each operation. Propensity score-matching methods were applied to create balanced sample groups with respect to patient-, operative-, and hospital-level confounders and resulted in 4 groups based on anesthesiologist staffing ratio. Groups consisted of patients receiving care from an anesthesiologist covering 1 operation (group 1), more than 1 to no more than 2 overlapping operations (group 1-2), more than 2 to no more than 3 overlapping operations (group 2-3), and more than 3 to no more than 4 overlapping operations (group 3-4). Data analysis was performed from October 2019 to October 2021. Exposure: Undergoing a major inpatient surgical operation that involved an anesthesiologist providing care for up to 4 overlapping operations. Main Outcomes and Measures: The primary composite outcome was 30-day mortality and 6 major surgical morbidities (cardiac, respiratory, gastrointestinal, urinary, bleeding, and infectious complications) derived from International Classification of Diseases, Ninth Revision and International Statistical Classification of Diseases and Related Health Problems, Tenth Revision discharge diagnosis codes. Results: In all, 578 815 adult patients (mean [SD] age, 55.7 [16.2] years; 55.1% female) were analyzed. After matching operations according to anesthesiologist staffing ratio, 48 555 patients were in group 1; 247 057, group 1-2; 216 193, group 2-3; and 67 010, group 3-4. Increasing anesthesiologist coverage responsibilities was associated with an increase in risk-adjusted surgical patient morbidity and mortality. Compared with patients in group 1-2, those in group 2-3 had a 4% relative increase in risk-adjusted mortality and morbidity (5.06% vs 5.25%; adjusted odds ratio [AOR], 1.04; 95% CI, 1.01-1.08; P = .02) and those in group 3-4 had a 14% increase in risk-adjusted mortality and morbidity (5.06% vs 5.75%; AOR, 1.15; 95% CI, 1.09-1.21; P < .001). Conclusions and Relevance: This study's findings suggest that increasing overlapping coverage by anesthesiologists is associated with increased surgical patient morbidity and mortality. Therefore, the potential effects of staffing ratios in perioperative team models should be considered in clinical coverage efforts.

Re-evaluating expanding intravenous catheters in medical practice.

BACKGROUND: Intravenous catheters are common and essential devices within medical practice. Their placement can be difficult, leading to application of several technologies to improve success. Functionally expanding catheters were once an exciting technology, derailed clinically by hypersensitivity reactions. The exact cause of reactions, attributed to Aquavene catheter materials, remains unknown. AIMS: To reinvestigate functionally expanding intravenous catheters. MATERIALS AND METHODS: The history of the functionally expanding intravenous catheter is presented here along with its utility in current medical practice, potential for further investigation, and possible redesign of these once promising devices. RESULTS: This review demonstrates clinical utility and a lack of definitive cause for failure of the previous functionally expanding intravenous catheter design. As Aquavene materials themselves are commonly considered the cause of hypersensitivity reactions which removed expanding intravenous catheters from the market, this review found several possible substitutes for this material for use in any redesign. DISCUSSION AND CONCLUSION: The functionally expanding intravenous catheter failed due to hypersensitivity reactions in patients. Alternative materials exist for a possible redesign on this once promising clinical product.

Swellable catheters based on a dynamic expanding inner diameter.

Intravenous (IV) fluid administration is critical for all patients undergoing care in a hospital setting. In-patient hospital practice, surgeries, and emergency care require functional IVs for fluid replacement and medication administration. Proper placement of IVs is vital to providing medical services. The ease of placement of an IV catheter, however, depends not only on the size of the catheter but also on provider experience and patient demographics such as age, body mass index, hydration status, and medical comorbidities present challenges to successful IV placement. Smaller diameter IV placement can improve success and there are instances where multiple small diameter catheters are placed for patient care when larger bore access is unattainable. Smaller inner-diameter catheters for anesthesia have functional constraints. Ideally, there would be a smaller catheter for placement that could function as a larger catheter for patient care. One solution is the idea of functionally responsive catheters. Here, we evaluated tubular-shaped hydrogels as potential functional catheters that can increase in inner diameter through fluid swelling using cross-linked homopolymers of polyacrylamide, PAM (10-40% w/w), and their copolymers with 0-8% w/w Poly-(Ethylene Glycol)-Diacrylate, PEGDA. For the PAM gels, the water transport mechanism was shown to be concentration-dependent Fickian diffusion, with the less concentrated gels exhibiting increasingly anomalous modes. Increasing the PEGDA content in the network yielded an initial high rate of water uptake, characterized by Case II transport. The swelling kinetics depended strongly on the sample geometry and boundary conditions. Initially, in a submerged swelling, the annulus expands symmetrically in both outward and inward directions (it thickens), reducing the internal diameter by up to 70%. After 1 h, however, the inner diameter increases steadily so that at equilibrium, there is a net (>100%) increase in all the dimensions of the tube. The amount of linear swelling at equilibrium depended only on the polymer volume fraction as made, while the rate of inner diameter expansion depended on the hydrophilicity of the matrix and the kinetics of sorption. This study serves as proof of concept to identify key parameters for the successful design of hydrogel-based catheter devices with expanding inner-diameters for applications in medical care.

Considerations for Integration of Perioperative Electronic Health Records Across Institutions for Research and Quality Improvement: The Approach Taken by the Multicenter Perioperative Outcomes Group.

Use of the electronic health record (EHR) has become a routine part of perioperative care in the United States. Secondary use of EHR data includes research, quality, and educational initiatives. Fundamental to secondary use is a framework to ensure fidelity, transparency, and completeness of the source data. In developing this framework, competing priorities must be considered as to which data sources are used and how data are organized and incorporated into a useable format. In assembling perioperative data from diverse institutions across the United States and Europe, the Multicenter Perioperative Outcomes Group (MPOG) has developed methods to support such a framework. This special article outlines how MPOG has approached considerations of data structure, validation, and accessibility to support multicenter integration of perioperative EHRs. In this multicenter practice registry, MPOG has developed processes to extract data from the perioperative EHR; transform data into a standardized format; and validate, deidentify, and transfer data to a secure central Coordinating Center database. Participating institutions may obtain access to this central database, governed by quality and research committees, to inform clinical practice and contribute to the scientific and clinical communities. Through a rigorous and standardized approach to ensure data integrity, MPOG enables data to be usable for quality improvement and advancing scientific knowledge. As of March 2019, our collaboration of 46 hospitals has accrued 10.7 million anesthesia records with associated perioperative EHR data across heterogeneous vendors. Facilitated by MPOG, each site retains access to a local repository containing all site-specific perioperative data, distinct from source EHRs and readily available for local research, quality, and educational initiatives. Through committee approval processes, investigators at participating sites may additionally access multicenter data for similar initiatives. Emerging from this work are 4 considerations that our group has prioritized to improve data quality: (1) data should be available at the local level before Coordinating Center transfer; (2) data should be rigorously validated against standardized metrics before use; (3) data should be curated into computable phenotypes that are easily accessible; and (4) data should be collected for both research and quality improvement purposes because these complementary goals bolster the strength of each endeavor.

Early Detection of Heart Failure With Reduced Ejection Fraction Using Perioperative Data Among Noncardiac Surgical Patients: A Machine-Learning Approach.

BACKGROUND: Heart failure with reduced ejection fraction (HFrEF) is a condition imposing significant health care burden. Given its syndromic nature and often insidious onset, the diagnosis may not be made until clinical manifestations prompt further evaluation. Detecting HFrEF in precursor stages could allow for early initiation of treatments to modify disease progression. Granular data collected during the perioperative period may represent an underutilized method for improving the diagnosis of HFrEF. We hypothesized that patients ultimately diagnosed with HFrEF following surgery can be identified via machine-learning approaches using pre- and intraoperative data. METHODS: Perioperative data were reviewed from adult patients undergoing general anesthesia for major surgical procedures at an academic quaternary care center between 2010 and 2016. Patients with known HFrEF, heart failure with preserved ejection fraction, preoperative critical illness, or undergoing cardiac, cardiology, or electrophysiologic procedures were excluded. Patients were classified as healthy controls or undiagnosed HFrEF. Undiagnosed HFrEF was defined as lacking a HFrEF diagnosis preoperatively but establishing a diagnosis within 730 days postoperatively. Undiagnosed HFrEF patients were adjudicated by expert clinician review, excluding cases for which HFrEF was secondary to a perioperative triggering event, or any event not associated with HFrEF natural disease progression. Machine-learning models, including L1 regularized logistic regression, random forest, and extreme gradient boosting were developed to detect undiagnosed HFrEF, using perioperative data including 628 preoperative and 1195 intraoperative features. Training/validation and test datasets were used with parameter tuning. Test set model performance was evaluated using area under the receiver operating characteristic curve (AUROC), positive predictive value, and other standard metrics. RESULTS: Among 67,697 cases analyzed, 279 (0.41%) patients had undiagnosed HFrEF. The AUROC for the logistic regression model was 0.869 (95% confidence interval, 0.829-0.911), 0.872 (0.836-0.909) for the random forest model, and 0.873 (0.833-0.913) for the extreme gradient boosting model. The corresponding positive predictive values were 1.69% (1.06%-2.32%), 1.42% (0.85%-1.98%), and 1.78% (1.15%-2.40%), respectively. CONCLUSIONS: Machine-learning models leveraging perioperative data can detect undiagnosed HFrEF with good performance. However, the low prevalence of the disease results in a low positive predictive value, and for clinically meaningful sensitivity thresholds to be actionable, confirmatory testing with high specificity (eg, echocardiography or cardiac biomarkers) would be required following model detection. Future studies are necessary to externally validate algorithm performance at additional centers and explore the feasibility of embedding algorithms into the perioperative electronic health record for clinician use in real time.

Classification of Current Procedural Terminology Codes from Electronic Health Record Data Using Machine Learning.

BACKGROUND: Accurate anesthesiology procedure code data are essential to quality improvement, research, and reimbursement tasks within anesthesiology practices. Advanced data science techniques, including machine learning and natural language processing, offer opportunities to develop classification tools for Current Procedural Terminology codes across anesthesia procedures. METHODS: Models were created using a Train/Test dataset including 1,164,343 procedures from 16 academic and private hospitals. Five supervised machine learning models were created to classify anesthesiology Current Procedural Terminology codes, with accuracy defined as first choice classification matching the institutional-assigned code existing in the perioperative database. The two best performing models were further refined and tested on a Holdout dataset from a single institution distinct from Train/Test. A tunable confidence parameter was created to identify cases for which models were highly accurate, with the goal of at least 95% accuracy, above the reported 2018 Centers for Medicare and Medicaid Services (Baltimore, Maryland) fee-for-service accuracy. Actual submitted claim data from billing specialists were used as a reference standard. RESULTS: Support vector machine and neural network label-embedding attentive models were the best performing models, respectively, demonstrating overall accuracies of 87.9% and 84.2% (single best code), and 96.8% and 94.0% (within top three). Classification accuracy was 96.4% in 47.0% of cases using support vector machine and 94.4% in 62.2% of cases using label-embedding attentive model within the Train/Test dataset. In the Holdout dataset, respective classification accuracies were 93.1% in 58.0% of cases and 95.0% among 62.0%. The most important feature in model training was procedure text. CONCLUSIONS: Through application of machine learning and natural language processing techniques, highly accurate real-time models were created for anesthesiology Current Procedural Terminology code classification. The increased processing speed and a priori targeted accuracy of this classification approach may provide performance optimization and cost reduction for quality improvement, research, and reimbursement tasks reliant on anesthesiology procedure codes.

Preoperative Risk and the Association between Hypotension and Postoperative Acute Kidney Injury.

BACKGROUND: Despite the significant healthcare impact of acute kidney injury, little is known regarding prevention. Single-center data have implicated hypotension in developing postoperative acute kidney injury. The generalizability of this finding and the interaction between hypotension and baseline patient disease burden remain unknown. The authors sought to determine whether the association between intraoperative hypotension and acute kidney injury varies by preoperative risk. METHODS: Major noncardiac surgical procedures performed on adult patients across eight hospitals between 2008 and 2015 were reviewed. Derivation and validation cohorts were used, and cases were stratified into preoperative risk quartiles based upon comorbidities and surgical procedure. After preoperative risk stratification, associations between intraoperative hypotension and acute kidney injury were analyzed. Hypotension was defined as the lowest mean arterial pressure range achieved for more than 10 min; ranges were defined as absolute (mmHg) or relative (percentage of decrease from baseline). RESULTS: Among 138,021 cases reviewed, 12,431 (9.0%) developed postoperative acute kidney injury. Major risk factors included anemia, estimated glomerular filtration rate, surgery type, American Society of Anesthesiologists Physical Status, and expected anesthesia duration. Using such factors and others for risk stratification, patients with low baseline risk demonstrated no associations between intraoperative hypotension and acute kidney injury. Patients with medium risk demonstrated associations between severe-range intraoperative hypotension (mean arterial pressure less than 50 mmHg) and acute kidney injury (adjusted odds ratio, 2.62; 95% CI, 1.65 to 4.16 in validation cohort). In patients with the highest risk, mild hypotension ranges (mean arterial pressure 55 to 59 mmHg) were associated with acute kidney injury (adjusted odds ratio, 1.34; 95% CI, 1.16 to 1.56). Compared with absolute hypotension, relative hypotension demonstrated weak associations with acute kidney injury not replicable in the validation cohort. CONCLUSIONS: Adult patients undergoing noncardiac surgery demonstrate varying associations with distinct levels of hypotension when stratified by preoperative risk factors. Specific levels of absolute hypotension, but not relative hypotension, are an important independent risk factor for acute kidney injury.

Pro-region engineering for improved yeast display and secretion of brain derived neurotrophic factor.

Brain derived neurotrophic factor (BDNF) is a promising therapeutic candidate for a variety of neurological diseases. However, it is difficult to produce as a recombinant protein. In its native mammalian context, BDNF is first produced as a pro-protein with subsequent proteolytic removal of the pro-region to yield mature BDNF protein. Therefore, in an attempt to improve yeast as a host for heterologous BDNF production, the BDNF pro-region was first evaluated for its effects on BDNF surface display and secretion. Addition of the wild-type pro-region to yeast BDNF production constructs improved BDNF folding both as a surface-displayed and secreted protein in terms of binding its natural receptors TrkB and p75, but titers remained low. Looking to further enhance the chaperone-like functions provided by the pro-region, two rounds of directed evolution were performed, yielding mutated pro-regions that further improved the display and secretion properties of BDNF. Subsequent optimization of the protease recognition site was used to control whether the produced protein was in pro- or mature BDNF forms. Taken together, we have demonstrated an effective strategy for improving BDNF compatibility with yeast protein engineering and secretion platforms.

Directed evolution of brain-derived neurotrophic factor for improved folding and expression in Saccharomyces cerevisiae.

Brain-derived neurotrophic factor (BDNF) plays an important role in nervous system function and has therapeutic potential. Microbial production of BDNF has resulted in a low-fidelity protein product, often in the form of large, insoluble aggregates incapable of binding to cognate TrkB or p75 receptors. In this study, employing Saccharomyces cerevisiae display and secretion systems, it was found that BDNF was poorly expressed and partially inactive on the yeast surface and that BDNF was secreted at low levels in the form of disulfide-bonded aggregates. Thus, for the purpose of increasing the compatibility of yeast as an expression host for BDNF, directed-evolution approaches were employed to improve BDNF folding and expression levels. Yeast surface display was combined with two rounds of directed evolution employing random mutagenesis and shuffling to identify BDNF mutants that had 5-fold improvements in expression, 4-fold increases in specific TrkB binding activity, and restored p75 binding activity, both as displayed proteins and as secreted proteins. Secreted BDNF mutants were found largely in the form of soluble homodimers that could stimulate TrkB phosphorylation in transfected PC12 cells. Site-directed mutagenesis studies indicated that a particularly important mutational class involved the introduction of cysteines proximal to the native cysteines that participate in the BDNF cysteine knot architecture. Taken together, these findings show that yeast is now a viable alternative for both the production and the engineering of BDNF.