A Mobile Post Anesthesia Care Unit Order Reminder System Improves Timely Order Entry.

Transition to the postanesthesia care unit (PACU) requires timely order placement by anesthesia providers. Computerized ordering enables automated order reminder systems, but their value is not fully understood. We performed a single-center, retrospective cohort study to estimate the association between automated PACU order reminders and primary outcomes (1) on-time order placement and (2) the degree of delay in placement. As a secondary post-hoc analysis, we studied the association between late order placement and PACU outcomes. We included patients with a qualifying postprocedure order from January 1, 2019, to May 31, 2023. We excluded cases transferred directly to the ICU, whose anesthesia provider was involved in the pilot testing of the reminder system, or those with missing covariate data. Order reminder system usage was defined by the primary attending anesthesiologist's receipt of a push notification reminder on the day of surgery. We estimated the association between reminder system usage and timely order placement using a logistic regression. For patients with late orders, we performed a survival analysis of order placement. The significance level was 0.05. Patient (e.g., age, race), procedural (e.g., anesthesia duration), and provider-based (e.g., ordering privileges) variables were used as covariates within the analyses. Reminders were associated with 51% increased odds of order placement prior to PACU admission (Odds Ratio: 1.51; 95% Confidence Interval: 1.43, 1.58; p ≤ 0.001), reducing the incidence of late PACU orders from 17.5% to 12.6% (p ≤ 0.001). In patients with late orders, the reminders were associated with 10% quicker placement (Hazard Ratio: 1.10; 95% CI 1.05, 1.15; p < 0.001). On-time order placement was associated with decreased PACU duration (p < 0.001), decreased odds of peak PACU pain score (p < 0.001), and decreased odds of multiple administration of antiemetics (p = 0.02). An order reminder system was associated with an increase in order placement prior to PACU arrival and a reduction in delay in order placement after arrival.

Determinants and Practice Variability of Oxygen Administration during Surgery in the United States: A Retrospective Cohort Study.

BACKGROUND: The best approaches to supplemental oxygen administration during surgery remain unclear, which may contribute to variation in practice. This study aimed to assess determinants of oxygen administration and its variability during surgery. METHODS: Using multivariable linear mixed-effects regression, the study measured the associations between intraoperative fraction of inspired oxygen and patient, procedure, medical center, anesthesiologist, and in-room anesthesia provider factors in surgical cases of 120 min or longer in adult patients who received general anesthesia with tracheal intubation and were admitted to the hospital after surgery between January 2016 and January 2019 at 42 medical centers across the United States participating in the Multicenter Perioperative Outcomes Group data registry. RESULTS: The sample included 367,841 cases (median [25th, 75th] age, 59 [47, 69] yr; 51.1% women; 26.1% treated with nitrous oxide) managed by 3,836 anesthesiologists and 15,381 in-room anesthesia providers. Median (25th, 75th) fraction of inspired oxygen was 0.55 (0.48, 0.61), with 6.9% of cases less than 0.40 and 8.7% greater than 0.90. Numerous patient and procedure factors were statistically associated with increased inspired oxygen, notably advanced American Society of Anesthesiologists classification, heart disease, emergency surgery, and cardiac surgery, but most factors had little clinical significance (less than 1% inspired oxygen change). Overall, patient factors only explained 3.5% (95% CI, 3.5 to 3.5%) of the variability in oxygen administration, and procedure factors 4.4% (95% CI, 4.2 to 4.6%). Anesthesiologist explained 7.7% (95% CI, 7.2 to 8.2%) of the variability in oxygen administration, in-room anesthesia provider 8.1% (95% CI, 7.8 to 8.4%), medical center 23.3% (95% CI, 22.4 to 24.2%), and 53.0% (95% CI, 52.4 to 53.6%) was unexplained. CONCLUSIONS: Among adults undergoing surgery with anesthesia and tracheal intubation, supplemental oxygen administration was variable and appeared arbitrary. Most patient and procedure factors had statistical but minor clinical associations with oxygen administration. Medical center and anesthesia provider explained significantly more variability in oxygen administration than patient or procedure factors.

Neuraxial clonidine is not associated with lower post-cesarean opioid consumption or pain scores in parturients on chronic buprenorphine therapy: a retrospective cohort study.

PURPOSE: Adequate post-cesarean delivery analgesia can be difficult to achieve for women diagnosed with opioid use disorder receiving buprenorphine. We sought to determine if neuraxial clonidine administration is associated with decreased opioid consumption and pain scores following cesarean delivery in women receiving chronic buprenorphine therapy. METHODS: This was a retrospective cohort study at a tertiary care teaching hospital of women undergoing cesarean delivery with or without neuraxial clonidine administration while receiving chronic buprenorphine. The primary outcome was opioid consumption (in morphine milligram equivalents) 0-6 h following cesarean delivery. Secondary outcomes included opioid consumption 0-24 h post-cesarean, median postoperative pain scores 0-24 h, and rates of intraoperative anesthetic supplementation. Multivariable analysis evaluating the adjusted effects of neuraxial clonidine on outcomes was conducted using linear regression, proportional odds model, and logistic regression separately. RESULTS: 196 women met inclusion criteria, of which 145 (74%) received neuraxial clonidine while 51 (26%) did not. In univariate analysis, there was no significant difference in opioid consumption 0-6 h post-cesarean delivery between the clonidine (8 [IQR 0, 15]) and control (1 [IQR 0, 8]) groups (P = 0.14). After adjusting for potential confounders, there remained no significant association with neuraxial clonidine administration 0-6 h (Difference in means 2.77, 95% CI [- 0.89 to 6.44], P = 0.14) or 0-24 h (Difference in means 8.56, 95% CI [- 16.99 to 34.11], P = 0.51). CONCLUSION: In parturients receiving chronic buprenorphine therapy at the time of cesarean delivery, neuraxial clonidine administration was not associated with decreased postoperative opioid consumption, median pain scores, or the need for intraoperative supplementation.

The impact of a medically directed student registered nurse anesthesia staffing model on Postprocedural patient outcomes.

STUDY OBJECTIVE: In 2018, the American Society of Anesthesiologists stated that student registered nurse anesthetists (SRNAs) "are not yet fully qualified anesthesia personnel." It remains unclear, however, whether postprocedural outcomes are affected by SRNAs providing anesthesia care under the medical direction of anesthesiologists, as compared with medically directed anesthesiology fellows or residents, or certified registered nurse anesthetists (CRNAs). We therefore aimed to examine whether medically directed SRNAs serving as in-room anesthesia providers impact surgical outcomes. DESIGN: Retrospective, matched-cohort analysis. SETTING: Adult patients (≥18 years old) undergoing inpatient surgery between 2000 and 2017 at a tertiary academic medical center. PATIENTS: 15,365 patients exclusively cared for by medically directed SRNAs were matched to 15,365 cared for by medically directed CRNAs, anesthesiology residents, and/or fellows. INTERVENTIONS: None. MEASUREMENTS: The primary composite outcome was postoperative occurrence of in-hospital mortality and six categories of major morbidities (infectious, bleeding, serious cardiac, gastrointestinal, respiratory, and urinary complications). In-hospital mortality was analyzed as the secondary outcome. MAIN RESULTS: In all, 30,730 cases were matched using propensity score matching to control for potential confounding. The primary outcome was identified in 2295 (7.5%) cases (7.5% with exclusive medically directed SRNAs vs 7.4% with medically directed CRNAs, residents and/or fellows; relative risk, 1.02; 95% CI, 0.94-1.11). Thus, our effort to determine noninferiority (10% difference in relative risk) with other providers was inconclusive (P = .07). However, the medically directed SRNA group (0.8% [118]) was found to be noninferior (P < .001) to the matched group (1.0% [156]) on in-hospital mortality (relative risk, 0.75; 95% CI, 0.59-0.96). CONCLUSIONS: Among 30,730 patients undergoing inpatient surgery at a single hospital, findings were inconclusive regarding whether exclusive medically directed SRNAs as in-room providers were noninferior to other providers. The use of medically directed SRNAs under this staffing model should be subject to further review. Clinical Trial and Registry URL: Not applicable.

Model-Guided Decision-Making for Thromboprophylaxis and Hospital-Acquired Thromboembolic Events Among Hospitalized Children and Adolescents: The CLOT Randomized Clinical Trial.

Importance: Rates of hospital-acquired venous thromboembolism (HA-VTE) are increasing among pediatric patients. Identifying at-risk patients for whom prophylactic interventions should be considered remains challenging. Objective: To determine whether use of a previously validated HA-VTE prognostic model, together with pediatric hematologist review, could reduce pediatric inpatient rates of HA-VTE. Design, Setting, and Participants: This pragmatic randomized clinical trial was performed from November 2, 2020, through January 31, 2022, at a single-center academic children's hospital (Monroe Carell Jr Children's Hospital at Vanderbilt). All pediatric hospital admissions (aged <22 years) under inpatient status were included and randomized. Intervention: All patients had an HA-VTE probability automatically calculated daily, which was visible to the hematology research team for patients in the intervention group. Patients with an elevated risk (predicted probability ≥2.5%) underwent additional medical record review by the research team to determine eligibility for thromboprophylaxis. Main Outcomes and Measures: The primary outcome was rate of HA-VTE. Secondary outcomes included rates of prophylactic anticoagulation and anticoagulation-associated bleeding events. Results: A total of 17 427 hospitalizations met eligibility criteria, were randomized, and were included in the primary analysis: patients had a median (IQR) age of 1.7 (0 to 11.1) years; there were 9143 (52.5%) female patients and 8284 (47.5%) male patients, and there were 445 (2.6%) Asian patients, 2739 (15.9%) Black patients, and 11 752 (67.4%) White patients. The 2 groups were evenly balanced in number (8717 in the intervention group and 8710 in the control group) and patient characteristics. A total of 58 patients (0.7%) in the control group and 77 (0.9%) in the intervention group developed HA-VTE (risk difference: 2.2 per 1000 patients; 95% CI, -0.4 to 4.8 per 1000 patients; P = .10). Recommendations to initiate thromboprophylaxis were accepted by primary clinical teams 25.8% of the time (74 of 287 hospitalizations). Minor bleeding events were rare among patients who received anticoagulation (3 of 74 [4.1%]), and no major bleeding events were observed during the study period. Among patients randomized to the control group, the model exhibited high discrimination accuracy (C statistic, 0.799, 95% CI, 0.725 to 0.856). Conclusions and Relevance: In this randomized clinical trial of the use of a HA-VTE prognostic model to reduce pediatric inpatient rates of HA-VTE, despite the use of an accurate and validated prognostic model for HA-VTE, there was substantial reluctance by primary clinical teams to initiate thromboprophylaxis as recommended. In this context, rates of HA-VTE between the control and intervention groups were not different. Future research is needed to identify improved strategies for prevention of HA-VTE and to overcome clinician concerns regarding thromboprophylaxis. Trial Registration: ClinicalTrials.gov Identifier: NCT04574895.

Blood Pressure Management After Endovascular Therapy for Acute Ischemic Stroke: The BEST-II Randomized Clinical Trial.

Importance: The effects of moderate systolic blood pressure (SBP) lowering after successful recanalization with endovascular therapy for acute ischemic stroke are uncertain. Objective: To determine the futility of lower SBP targets after endovascular therapy (<140 mm Hg or 160 mm Hg) compared with a higher target (≤180 mm Hg). Design, Setting, and Participants: Randomized, open-label, blinded end point, phase 2, futility clinical trial that enrolled 120 patients with acute ischemic stroke who had undergone successful endovascular therapy at 3 US comprehensive stroke centers from January 2020 to March 2022 (final follow-up, June 2022). Intervention: After undergoing endovascular therapy, participants were randomized to 1 of 3 SBP targets: 40 to less than 140 mm Hg, 40 to less than 160 mm Hg, and 40 to 180 mm Hg or less (guideline recommended) group, initiated within 60 minutes of recanalization and maintained for 24 hours. Main Outcomes and Measures: Prespecified multiple primary outcomes for the primary futility analysis were follow-up infarct volume measured at 36 (±12) hours and utility-weighted modified Rankin Scale (mRS) score (range, 0 [worst] to 1 [best]) at 90 (±14) days. Linear regression models were used to test the harm-futility boundaries of a 10-mL increase (slope of 0.5) in the follow-up infarct volume or a 0.10 decrease (slope of -0.005) in the utility-weighted mRS score with each 20-mm Hg SBP target reduction after endovascular therapy (1-sided α = .05). Additional prespecified futility criterion was a less than 25% predicted probability of success for a future 2-group, superiority trial comparing SBP targets of the low- and mid-thresholds with the high-threshold (maximum sample size, 1500 with respect to the utility-weighted mRS score outcome). Results: Among 120 patients randomized (mean [SD] age, 69.6 [14.5] years; 69 females [58%]), 113 (94.2%) completed the trial. The mean follow-up infarct volume was 32.4 mL (95% CI, 18.0 to 46.7 mL) for the less than 140-mm Hg group, 50.7 mL (95% CI, 33.7 to 67.7 mL), for the less than 160-mm Hg group, and 46.4 mL (95% CI, 24.5 to 68.2 mL) for the 180-mm Hg or less group. The mean utility-weighted mRS score was 0.51 (95% CI, 0.38 to 0.63) for the less than 140-mm Hg group, 0.47 (95% CI, 0.35 to 0.60) for the less than 160-mm Hg group, and 0.58 (95% CI, 0.46 to 0.71) for the high-target group. The slope of the follow-up infarct volume for each mm Hg decrease in the SBP target, adjusted for the baseline Alberta Stroke Program Early CT score, was -0.29 (95% CI, -0.81 to ∞; futility P = .99). The slope of the utility-weighted mRS score for each mm Hg decrease in the SBP target after endovascular therapy, adjusted for baseline utility-weighted mRS score, was -0.0019 (95% CI, -∞ to 0.0017; futility P = .93). Comparing the high-target SBP group with the lower-target groups, the predicted probability of success for a future trial was 25% for the less than 140-mm Hg group and 14% for the 160-mm Hg group. Conclusions and Relevance: Among patients with acute ischemic stroke, lower SBP targets less than either 140 mm Hg or 160 mm Hg after successful endovascular therapy did not meet prespecified criteria for futility compared with an SBP target of 180 mm Hg or less. However, the findings suggested a low probability of benefit from lower SBP targets after endovascular therapy if tested in a future larger trial. Trial Registration: ClinicalTrials.gov Identifier: NCT04116112.

Development of a machine learning model to predict intraoperative transfusion and guide type and screen ordering.

STUDY OBJECTIVE: To develop an algorithm to predict intraoperative Red Blood Cell (RBC) transfusion from preoperative variables contained in the electronic medical record of our institution, with the goal of guiding type and screen ordering. DESIGN: Machine Learning model development on retrospective single-center hospital data. SETTING: Preoperative period and operating room. PATIENTS: The study included patients ≥18 years old who underwent surgery during 2019-2022 and excluded those who refused transfusion, underwent emergency surgery, or surgery for organ donation after cardiac or brain death. INTERVENTION: Prediction of intraoperative transfusion vs. no intraoperative transfusion. MEASUREMENTS: The outcome variable was intraoperative transfusion of RBCs. Predictive variables were surgery, surgeon, anesthesiologist, age, sex, body mass index, race or ethnicity, preoperative hemoglobin (g/dL), partial thromboplastin time (s), platelet count x 109 per liter, and prothrombin time. We compared the performances of seven machine learning algorithms. After training and optimization on the 2019-2021 dataset, model thresholds were set to the current institutional performance level of sensitivity (93%). To qualify for comparison, models had to maintain clinically relevant sensitivity (>90%) when predicting on 2022 data; overall accuracy was the comparative metric. MAIN RESULTS: Out of 100,813 cases that met study criteria from 2019 to 2021, intraoperative transfusion occurred in 5488 (5.4%) of cases. The LightGBM model was the highest performing algorithm in external temporal validity experiments, with overall accuracy of (76.1%) [95% confidence interval (CI), 75.6-76.5], while maintaining clinically relevant sensitivity of (91.2%) [95% CI, 89.8-92.5]. If type and screens were ordered based upon the LightGBM model, the predicted type and screen to transfusion ratio would improve from 8.4 to 5.1. CONCLUSIONS: Machine learning approaches are feasible in predicting intraoperative transfusion from preoperative variables and may improve preoperative type and screen ordering practices when incorporated into the electronic health record.

PeRiOperative Glucose PRAgMatic (PROGRAM) trial protocol and statistical analysis plan for comparing automated intraoperative reminders to standardise insulin administration in surgical patients at high risk of hyperglycaemia.

INTRODUCTION: Studies finding perioperative hyperglycaemia is associated with adverse patient outcomes in surgical procedures spurred the development of blood glucose guidelines at many institutions. In this trial, we will assess the implementation of a clinical decision support tool that is integrated into the intraoperative portion of our electronic health record and provides real-time best practice recommendations for intraoperative insulin dosing in surgical patients at high risk for hyperglycaemia. METHODS AND DESIGN: We will assess this intervention using a sequential and repeated cross-over design at the institutional level with periods of time for wash-out, control and study intervention. The unit of analysis will be the surgical case. The primary outcome will be the frequency of hyperglycaemia (>180 mg/dL (10 mmol/L)) at first postoperative anaesthesia care unit measurement. There are several prespecified secondary analyses focused on perioperative glycaemic control. DISCUSSION: This protocol and statistical analysis plan describes the methodology, primary and secondary analyses. The PeRiOperative Glucose PRAgMatic (PROGRAM) trial was approved by the Vanderbilt University Institutional Review Board (IRB), Vanderbilt University Medical Center, Nashville, Tennessee, USA (IRB, 220991). The study results will be disseminated via publication in a peer-reviewed journal and presented at national scientific conferences. The results of PROGRAM trial will inform best practice for perioperative standardised insulin administration in surgical patients at high risk of hyperglycaemia. TRIAL REGISTRATION NUMBER: NCT05426096.

Using phenotypic data from the Electronic Health Record (EHR) to predict discharge.

BACKGROUND: Timely discharge to post-acute care (PAC) settings, such as skilled nursing facilities, requires early identification of eligible patients. We sought to develop and internally validate a model which predicts a patient's likelihood of requiring PAC based on information obtained in the first 24 h of hospitalization. METHODS: This was a retrospective observational cohort study. We collected clinical data and commonly used nursing assessments from the electronic health record (EHR) for all adult inpatient admissions at our academic tertiary care center from September 1, 2017 to August 1, 2018. We performed a multivariable logistic regression to develop the model from the derivation cohort of the available records. We then evaluated the capability of the model to predict discharge destination on an internal validation cohort. RESULTS: Age (adjusted odds ratio [AOR], 1.04 [per year]; 95% Confidence Interval [CI], 1.03 to 1.04), admission to the intensive care unit (AOR, 1.51; 95% CI, 1.27 to 1.79), admission from the emergency department (AOR, 1.53; 95% CI, 1.31 to 1.78), more home medication prescriptions (AOR, 1.06 [per medication count increase]; 95% CI 1.05 to 1.07), and higher Morse fall risk scores at admission (AOR, 1.03 [per unit increase]; 95% CI 1.02 to 1.03) were independently associated with higher likelihood of being discharged to PAC facility. The c-statistic of the model derived from the primary analysis was 0.875, and the model predicted the correct discharge destination in 81.2% of the validation cases. CONCLUSIONS: A model that utilizes baseline clinical factors and risk assessments has excellent model performance in predicting discharge to a PAC facility.

Preemptive Pharmacogenetic-Guided Metoprolol Management for Postoperative Atrial Fibrillation in Cardiac Surgery: The Preemptive Pharmacogenetic-Guided Metoprolol Management for Atrial Fibrillation in Cardiac Surgery Pilot Trial.

OBJECTIVES: To test the hypothesis that implementation of a cytochrome P-450 2D6 (CYP2D6) genotype-guided perioperative metoprolol administration will reduce the risk of postoperative atrial fibrillation (AF), the authors conducted the Preemptive Pharmacogenetic-Guided Metoprolol Management for Atrial Fibrillation in Cardiac Surgery pilot study. DESIGN: Clinical pilot trial. SETTING: Single academic center. PARTICIPANTS: Seventy-three cardiac surgery patients. MEASUREMENTS AND MAIN RESULTS: Patients were classified as normal, intermediate, poor, or ultrarapid metabolizers after testing for their CYP2D6 genotype. A clinical decision support tool in the electronic health record advised providers on CYP2D6 genotype-guided metoprolol dosing. Using historical data, the Bayesian method was used to compare the incidence of postoperative AF in patients with altered metabolizer status to the reference incidence. A logistic regression analysis was performed to study the association between the metabolizer status and postoperative AF while controlling for the Multicenter Study of Perioperative Ischemia AF Risk Index. Of the 73 patients, 30% (n = 22) developed postoperative AF; 89% (n = 65) were normal metabolizers; 11% (n = 8) were poor/intermediate metabolizers; and there were no ultrarapid metabolizer patients identified. The estimated rate of postoperative AF in patients with altered metabolizer status was 30% (95% CI 8%-60%), compared with the historical reference incidence (27%). In the risk-adjusted analysis, there was insufficient evidence to conclude that modifying metoprolol dosing based on poor/intermediate metabolizer status was associated significantly with the odds of postoperative AF (odds ratio 0.82, 95% CI 0.15-4.55, p = 0.82). CONCLUSIONS: A CYP2D6 genotype-guided metoprolol management was not associated with a reduction of postoperative AF after cardiac surgery.

The IMpact of PerioperAtive KeTamine on Enhanced Recovery after Abdominal Surgery (IMPAKT ERAS): protocol for a pragmatic, randomized, double-blinded, placebo-controlled trial.

BACKGROUND: Multimodal analgesic strategies that reduce perioperative opioid consumption are well-supported in Enhanced Recovery After Surgery (ERAS) literature. However, the optimal analgesic regimen has not been established, as the contributions of each individual agent to the overall analgesic efficacy with opioid reduction remains unknown. Perioperative ketamine infusions can decrease opioid consumption and opioid-related side effects. However, as opioid requirements are drastically minimized within ERAS models, the differential effects of ketamine within an ERAS pathway remain unknown. We aim to pragmatically investigate through a learning healthcare system infrastructure how the addition of a perioperative ketamine infusion to mature ERAS pathways affects functional recovery. METHODS: The IMPAKT ERAS trial (IMpact of PerioperAtive KeTamine on Enhanced Recovery after Abdominal Surgery) is a single center, pragmatic, randomized, blinded, placebo-controlled trial. 1544 patients undergoing major abdominal surgery will be randomly allocated to receive intraoperative and postoperative (up to 48 h) ketamine versus placebo infusions as part of a perioperative multimodal analgesic regimen. The primary outcome is length of stay, defined as surgical start time until hospital discharge. Secondary outcomes will include a variety of in-hospital clinical end points derived from the electronic health record. DISCUSSION: We aimed to launch a large-scale, pragmatic trial that would easily integrate into routine clinical workflow. Implementation of a modified consent process was critical to preserving our pragmatic design, permitting an efficient, low-cost model without reliance on external study personnel. Therefore, we partnered with leaders of our Investigational Review Board to develop a novel, modified consent process and shortened written consent form that would meet all standard elements of informed consent, yet also allow clinical providers the ability to recruit and enroll patients during their clinical workflow. Our trial design has created a platform for subsequent pragmatic studies at our institution. TRIAL REGISTRATION: NCT04625283, Pre-results.

Genetic predisposition may not improve prediction of cardiac surgery-associated acute kidney injury.

Background: The recent integration of genomic data with electronic health records has enabled large scale genomic studies on a variety of perioperative complications, yet genome-wide association studies on acute kidney injury have been limited in size or confounded by composite outcomes. Genome-wide association studies can be leveraged to create a polygenic risk score which can then be integrated with traditional clinical risk factors to better predict postoperative complications, like acute kidney injury. Methods: Using integrated genetic data from two academic biorepositories, we conduct a genome-wide association study on cardiac surgery-associated acute kidney injury. Next, we develop a polygenic risk score and test the predictive utility within regressions controlling for age, gender, principal components, preoperative serum creatinine, and a range of patient, clinical, and procedural risk factors. Finally, we estimate additive variant heritability using genetic mixed models. Results: Among 1,014 qualifying procedures at Vanderbilt University Medical Center and 478 at Michigan Medicine, 348 (34.3%) and 121 (25.3%) developed AKI, respectively. No variants exceeded genome-wide significance (p < 5 × 10-8) threshold, however, six previously unreported variants exceeded the suggestive threshold (p < 1 × 10-6). Notable variants detected include: 1) rs74637005, located in the exonic region of NFU1 and 2) rs17438465, located between EVX1 and HIBADH. We failed to replicate variants from prior unbiased studies of post-surgical acute kidney injury. Polygenic risk was not significantly associated with post-surgical acute kidney injury in any of the models, however, case duration (aOR = 1.002, 95% CI 1.000-1.003, p = 0.013), diabetes mellitus (aOR = 2.025, 95% CI 1.320-3.103, p = 0.001), and valvular disease (aOR = 0.558, 95% CI 0.372-0.835, p = 0.005) were significant in the full model. Conclusion: Polygenic risk score was not significantly associated with cardiac surgery-associated acute kidney injury and acute kidney injury may have a low heritability in this population. These results suggest that susceptibility is only minimally influenced by baseline genetic predisposition and that clinical risk factors, some of which are modifiable, may play a more influential role in predicting this complication. The overall impact of genetics in overall risk for cardiac surgery-associated acute kidney injury may be small compared to clinical risk factors.

Using AI-generated suggestions from ChatGPT to optimize clinical decision support.

OBJECTIVE: To determine if ChatGPT can generate useful suggestions for improving clinical decision support (CDS) logic and to assess noninferiority compared to human-generated suggestions. METHODS: We supplied summaries of CDS logic to ChatGPT, an artificial intelligence (AI) tool for question answering that uses a large language model, and asked it to generate suggestions. We asked human clinician reviewers to review the AI-generated suggestions as well as human-generated suggestions for improving the same CDS alerts, and rate the suggestions for their usefulness, acceptance, relevance, understanding, workflow, bias, inversion, and redundancy. RESULTS: Five clinicians analyzed 36 AI-generated suggestions and 29 human-generated suggestions for 7 alerts. Of the 20 suggestions that scored highest in the survey, 9 were generated by ChatGPT. The suggestions generated by AI were found to offer unique perspectives and were evaluated as highly understandable and relevant, with moderate usefulness, low acceptance, bias, inversion, redundancy. CONCLUSION: AI-generated suggestions could be an important complementary part of optimizing CDS alerts, can identify potential improvements to alert logic and support their implementation, and may even be able to assist experts in formulating their own suggestions for CDS improvement. ChatGPT shows great potential for using large language models and reinforcement learning from human feedback to improve CDS alert logic and potentially other medical areas involving complex, clinical logic, a key step in the development of an advanced learning health system.

The IMpact of PerioperAtive KeTamine on Enhanced Recovery after Abdominal Surgery (IMPAKT ERAS): protocol for a pragmatic, randomized, double-blinded, placebo-controlled trial.

BACKGROUND: Multimodal analgesic strategies that reduce perioperative opioid consumption are well-supported in Enhanced Recovery After Surgery (ERAS) literature. However, the optimal analgesic regimen has not been established, as the contributions of each individual agent to the overall analgesic efficacy with opioid reduction remains unknown. Perioperative ketamine infusions can decrease opioid consumption and opioid-related side effects. However, as opioid requirements are drastically minimized within ERAS models, the differential effects of ketamine within an ERAS pathway remain unknown. We aim to pragmatically investigate through a learning healthcare system infrastructure how the addition of a perioperative ketamine infusion to mature ERAS pathways affects functional recovery. METHODS: The IMPAKT ERAS trial (IMpact of PerioperAtive KeTamine on Enhanced Recovery after Abdominal Surgery) is a single center, pragmatic, randomized, blinded, placebo-controlled trial. 1544 patients undergoing major abdominal surgery will be randomly allocated to receive intraoperative and postoperative (up to 48 hours) ketamine versus placebo infusions as part of a perioperative multimodal analgesic regimen. The primary outcome is length of stay, defined as surgical start time until hospital discharge. Secondary outcomes will include a variety of in-hospital clinical end points derived from the electronic health record. DISCUSSION: We aimed to launch a large-scale, pragmatic trial that would easily integrate into routine clinical workflow. Implementation of a modified consent process was critical to preserving our pragmatic design, permitting an efficient, low-cost model without reliance on external study personnel. Therefore, we partnered with leaders of our Investigational Review Board to develop a novel, modified consent process and shortened written consent form that would meet all standard elements of informed consent, yet also allow clinical providers the ability to recruit and enroll patients during their clinical workflow. Our trial design has created a platform for subsequent pragmatic studies at our institution. TRIAL REGISTRATION NUMBER: NCT04625283, Pre-results Protocol Version 1.0, 2021.

Assessing the Value of ChatGPT for Clinical Decision Support Optimization.

Objective: To determine if ChatGPT can generate useful suggestions for improving clinical decision support (CDS) logic and to assess noninferiority compared to human-generated suggestions. Methods: We supplied summaries of CDS logic to ChatGPT, an artificial intelligence (AI) tool for question answering that uses a large language model, and asked it to generate suggestions. We asked human clinician reviewers to review the AI-generated suggestions as well as human-generated suggestions for improving the same CDS alerts, and rate the suggestions for their usefulness, acceptance, relevance, understanding, workflow, bias, inversion, and redundancy. Results: Five clinicians analyzed 36 AI-generated suggestions and 29 human-generated suggestions for 7 alerts. Of the 20 suggestions that scored highest in the survey, 9 were generated by ChatGPT. The suggestions generated by AI were found to offer unique perspectives and were evaluated as highly understandable and relevant, with moderate usefulness, low acceptance, bias, inversion, redundancy. Conclusion: AI-generated suggestions could be an important complementary part of optimizing CDS alerts, can identify potential improvements to alert logic and support their implementation, and may even be able to assist experts in formulating their own suggestions for CDS improvement. ChatGPT shows great potential for using large language models and reinforcement learning from human feedback to improve CDS alert logic and potentially other medical areas involving complex, clinical logic, a key step in the development of an advanced learning health system.

Automated feedback modestly improves perioperative treatment adherence of postoperative nausea and vomiting.

STUDY OBJECTIVE: Extensive evidence demonstrates that medical record modernization and a vast amount of available data have not overcome the gap between recommended and delivered care. This study aimed to evaluate the use of clinical decision support (CDS) in conjunction with feedback (post-hoc reporting) to improve PONV medication administration compliance and postoperative nausea and vomiting (PONV) outcomes. DESIGN: Single center, prospective observational study between January 1, 2015, and June 30, 2017. SETTING: Perioperative care at a university-affiliated tertiary care center. PATIENTS: 57,401 adult patients who received general anesthesia in a non-emergency setting. INTERVENTION: A multi-phased intervention that consisted of post-hoc reporting for individual providers by email about PONV occurrences in their patients, followed by directive CDS through preoperative daily case emails that provided therapeutic PONV prophylaxis recommendations based on patients' PONV risk scores. MEASUREMENT: Compliance with PONV medication recommendations, as well as hospital rates of PONV were measured. MAIN RESULT: Over the study period, there was a 5.5% (95% CI, 4.2% to 6.4%; p < 0.001) improvement in the compliance of PONV medication administration along with an 8.7% (95% CI, 7.1% to 10.2%, p < 0.001) reduction in PONV rescue medication administration in the PACU. However, there was no statistically or clinically significant reduction in the prevalence of PONV in the PACU. The prevalence of PONV rescue medication administration decreased during the Intervention Rollout Period (odds ratio 0.95 [per month]; 95% CI, 0.91 to 0.99; p = 0.017), and during the Feedback with CDS Recommendation Period (odds ratio, 0.96 [per month]; 95% CI, 0.94 to 0.99; p = 0.013). CONCLUSION: PONV medication administration compliance modestly improves with CDS in conjunction with post-hoc reporting; however, no improvement in PACU rates of PONV occurred.

Prolonged Opioid Use and Pain Outcome and Associated Factors after Surgery under General Anesthesia: A Prospective Cohort Association Multicenter Study.

BACKGROUND: There is insufficient prospective evidence regarding the relationship between surgical experience and prolonged opioid use and pain. The authors investigated the association of patient characteristics, surgical procedure, and perioperative anesthetic course with postoperative opioid consumption and pain 3 months postsurgery. The authors hypothesized that patient characteristics and intraoperative factors predict opioid consumption and pain 3 months postsurgery. METHODS: Eleven U.S. and one European institution enrolled patients scheduled for spine, open thoracic, knee, hip, or abdominal surgery, or mastectomy, in this multicenter, prospective observational study. Preoperative and postoperative data were collected using patient surveys and electronic medical records. Intraoperative data were collected from the Multicenter Perioperative Outcomes Group database. The association between postoperative opioid consumption and surgical site pain at 3 months, elicited from a telephone survey conducted at 3 months postoperatively, and demographics, psychosocial scores, pain scores, pain management, and case characteristics, was analyzed. RESULTS: Between September and October 2017, 3,505 surgical procedures met inclusion criteria. A total of 1,093 cases were included; 413 patients were lost to follow-up, leaving 680 (64%) for outcome analysis. Preoperatively, 135 (20%) patients were taking opioids. Three months postsurgery, 96 (14%) patients were taking opioids, including 23 patients (4%) who had not taken opioids preoperatively. A total of 177 patients (27%) reported surgical site pain, including 45 (13%) patients who had not reported pain preoperatively. The adjusted odds ratio for 3-month opioid use was 18.6 (credible interval, 10.3 to 34.5) for patients who had taken opioids preoperatively. The adjusted odds ratio for 3-month surgical site pain was 2.58 (1.45 to 4.4), 4.1 (1.73 to 8.9), and 2.75 (1.39 to 5.0) for patients who had site pain preoperatively, knee replacement, or spine surgery, respectively. CONCLUSIONS: Preoperative opioid use was the strongest predictor of opioid use 3 months postsurgery. None of the other variables showed clinically significant association with opioid use at 3 months after surgery.

Implementation of an Epidural Rounding Reminder in the Electronic Medical Record Improves Performance of Standardized Patient Assessments during Labor.

BACKGROUND: Poorly functioning labor epidural catheters lead to pain and dissatisfaction. Regular catheter assessment ensures timely identification of malfunction and may improve safety by facilitating rapid and successful conversion to general anesthesia for emergency cesarean. Informatics-based systems encourage standardization of care to identify epidural malfunctions earlier. OBJECTIVES: This article demonstrates that visual epidural rounding reminder display on an electronic patient board would alert clinicians to elapsed time and decrease mean time between assessments. METHODS: As a quality initiative, we implemented an epidural rounding reminder on our obstetric patient board. The reminder indicated the number of elapsed minutes since placement or last patient assessment. We retrospectively reviewed labor epidural charts 3 months prior to and 5 months following reminder implementation, with a 4-week washout period. The primary outcome was mean time between documented epidural assessments, with secondary outcomes including maximum time between assessments, total number of assessments during labor, catheter replacement rates, and patient satisfaction. Unadjusted comparisons between pre- and postimplementation groups were conducted using Wilcoxon's rank-sum and Pearson's chi-square tests, as appropriate. A test for equal variances was conducted for time between assessment outcomes. RESULTS: Following implementation, mean time between assessments decreased from a median of 173 (interquartile range [IQR]: 53, 314) to 100 (IQR: 74, 125) minutes (p <0.001), and maximum time between assessments decreased from median 330 (IQR: 60, 542) to 162 (IQR: 125, 212) minutes (p < 0.001). Total number of evaluations during labor increased from 3 (IQR: 2, 4) to 5 (IQR: 3, 7; p < 0.001). Decreased variance in mean and maximum time between assessments was noted following reminder implementation (p < 0.001). Epidural replacement rates decreased from 14 to 5% postimplementation (p < 0.001). Patient satisfaction was unchanged. CONCLUSION: Implementation of an informatics-based solution can promote standardization of care. A simple epidural rounding reminder prompted clinicians to perform more frequent labor epidural assessments. In the future, these process improvements must be linked to improvements in patient experiences and outcomes.

Pediatric CYP2D6 metabolizer status and post-tonsillectomy nausea and vomiting after ondansetron.

The goal of this study was to determine whether CYP2D6 metabolizer status within the ondansetron-treated pediatric tonsillectomy population is associated with risk of postoperative nausea and vomiting (PONV) in the post-anesthesia care unit. We conducted a retrospective cohort study of pediatric patients (<18 years) who underwent tonsillectomy and received ondansetron on the day of the procedure. Data were obtained from BioVU, an institutional biobank that links DNA to de-identified electronic health record data. Subjects were tested for 10 CYP2D6 allelic variants and copy number variation, and genotype data translated into CYP2D6 metabolizer status. The cohort included 652 individuals, 105 (16.1%) of whom had PONV. Rates of PONV were similar across groups: ultrarapid metabolizers (UMs), 1 of 9 (11.1%); normal metabolizers (NMs), 64 of 354 (18.1%); intermediate metabolizers (IMs), 33 of 234 (14.1%); poor metabolizers (PMs), 6 of 39 (15.4%); and ambiguous phenotypes, 1 of 16 (6.3%). In multivariable analysis adjusted for age, sex, and time under anesthesia, CYP2D6 metabolizer status was not associated with PONV, with an odds ratio of 1.37 (95% confidence interval 0.9, 2.1) when comparing PM/IM versus NM/UM. In this large pediatric population, no significant differences were detected for PONV based on CYP2D6 metabolizer status. Further investigation is needed to determine mechanisms for ondansetron inefficacy in children.