Intraoperative Prophylaxis with Palonosetron for Postoperative Nausea and/or Vomiting in Adults Undergoing Cardiothoracic Surgery Under General Anesthesia: A Single-Center Retrospective Study.

OBJECTIVE: This study assessed the efficacy of palonosetron, alone or with dexamethasone, in reducing postoperative nausea and/or vomiting (PONV) and its impact on hospitalization duration in patients who undergo adult cardiothoracic surgery (CTS) under general anesthesia. DESIGN: This retrospective analysis involved 540 adult patients who underwent CTS from a single-center cohort, spanning surgeries between September 2021 and March 2023. Sensitivity, logistic, and Cox regression analyses evaluated antiemetic effects, PONV risk factors, and outcomes. SETTING: At the Virginia Mason Medical Center (VMMC), Seattle, WA. PARTICIPANTS: Adults undergoing cardiothoracic surgery at VMMC during the specified period. INTERVENTIONS: Patients were categorized into the following 4 groups based on antiemetic treatment: dexamethasone, palonosetron, dexamethasone with palonosetron, and no antiemetic. MEASUREMENTS AND MAIN RESULTS: Primary outcomes encompassed PONV incidence within 96 hours postoperatively. Secondary outcomes included intensive care unit stay duration and postoperative opioid use. Palonosetron recipients showed a significantly lower PONV rate of 42% (v controls at 63%). The dexamethasone and palonosetron combined group also demonstrated a lower rate of 40%. Sensitivity analysis revealed a notably lower 0- to 12-hour PONV rate for palonosetron recipients (9% v control at 28%). Logistic regression found decreased PONV risk (palonosetron odds ratio [OR]: 0.24; dexamethasone and palonosetron OR: 0.26). Cox regression identified varying PONV hazard ratios related to female sex, PONV history, and lower body mass index. CONCLUSIONS: This single-center retrospective study underscored palonosetron's efficacy, alone or combined with dexamethasone, in managing PONV among adult patients who undergo CTS. These findings contribute to evolving antiemetic strategies in cardiothoracic surgery, potentially impacting patient outcomes and satisfaction positively.

Lessons from aviation safety: pilot monitoring, the sterile flight deck rule, and aviation-style computerised checklists in the operating room.

Commercial aviation practices including the role of the pilot monitoring, the sterile flight deck rule, and computerised checklists have direct applicability to anaesthesia care. The pilot monitoring performs specific tasks that complement the pilot flying who is directly controlling the aircraft flight path. The anaesthesia care team, with two providers, can be organised in a manner that is analogous to the two-pilot flight deck. However, solo providers, such as solo pilots, can emulate the pilot monitoring role by reading checklists aloud, and utilise non-anaesthesia providers to fulfil some of the functions of pilot monitoring. The sterile flight deck rule states that flight crew members should not engage in any non-essential or distracting activity during critical phases of flight. The application of the sterile flight deck rule in anaesthesia practice entails deliberately minimising distractions during critical phases of anaesthesia care. Checklists are commonly used in the operating room, especially the World Health Organization surgical safety checklist. However, the use of aviation-style computerised checklists offers additional benefits. Here we discuss how these commercial aviation practices may be applied in the operating room.

Evaluation of machine learning models as decision aids for anesthesiologists.

Machine Learning (ML) models have been developed to predict perioperative clinical parameters. The objective of this study was to determine if ML models can serve as decision aids to improve anesthesiologists' prediction of peak intraoperative glucose values and postoperative opioid requirements. A web-based tool was used to present actual surgical case and patient information to 10 practicing anesthesiologists. They were asked to predict peak glucose levels and post-operative opioid requirements for 100 surgical patients with and without presenting ML model estimations of peak glucose and opioid requirements. The accuracies of the anesthesiologists' estimates with and without ML estimates as reference were compared. A questionnaire was also sent to the participating anesthesiologists to obtain their feedback on ML decision support. The accuracy of peak glucose level estimates by the anesthesiologists increased from 79.0 ± 13.7% without ML assistance to 84.7 ± 11.5% (< 0.001) when ML estimates were provided as reference. The accuracy of opioid requirement estimates increased from 18% without ML assistance to 42% (p < 0.001) when ML estimates were provided as reference. When ML estimates were provided, predictions of peak glucose improved for 8 out of the 10 anesthesiologists, while predictions of opioid requirements improved for 7 of the 10 anesthesiologists. Feedback questionnaire responses revealed that the anesthesiologist primarily used the ML estimates as reference to modify their clinical judgement. ML models can improve anesthesiologists' estimation of clinical parameters. ML predictions primarily served as reference information that modified an anesthesiologist's clinical estimate.

Intraoperative prediction of postanaesthesia care unit hypotension.

BACKGROUND: Postoperative hypotension is associated with adverse outcomes, but intraoperative prediction of postanaesthesia care unit (PACU) hypotension is not routine in anaesthesiology workflow. Although machine learning models may support clinician prediction of PACU hypotension, clinician acceptance of prediction models is poorly understood. METHODS: We developed a clinically informed gradient boosting machine learning model using preoperative and intraoperative data from 88 446 surgical patients from 2015 to 2019. Nine anaesthesiologists each made 192 predictions of PACU hypotension using a web-based visualisation tool with and without input from the machine learning model. Questionnaires and interviews were analysed using thematic content analysis for model acceptance by anaesthesiologists. RESULTS: The model predicted PACU hypotension in 17 029 patients (area under the receiver operating characteristic [AUROC] 0.82 [95% confidence interval {CI}: 0.81-0.83] and average precision 0.40 [95% CI: 0.38-0.42]). On a random representative subset of 192 cases, anaesthesiologist performance improved from AUROC 0.67 (95% CI: 0.60-0.73) to AUROC 0.74 (95% CI: 0.68-0.79) with model predictions and information on risk factors. Anaesthesiologists perceived more value and expressed trust in the prediction model for prospective planning, informing PACU handoffs, and drawing attention to unexpected cases of PACU hypotension, but they doubted the model when predictions and associated features were not aligned with clinical judgement. Anaesthesiologists expressed interest in patient-specific thresholds for defining and treating postoperative hypotension. CONCLUSIONS: The ability of anaesthesiologists to predict PACU hypotension was improved by exposure to machine learning model predictions. Clinicians acknowledged value and trust in machine learning technology. Increasing familiarity with clinical use of model predictions is needed for effective integration into perioperative workflows.

Development of an aviation-style computerized checklist displayed on a tablet computer for improving handoff communication in the post-anesthesia care unit.

Critical patient care information is often omitted or misunderstood during handoffs, which can lead to inefficiencies, delays, and sometimes patient harm. We implemented an aviation-style post-anesthesia care unit (PACU) handoff checklist displayed on a tablet computer to improve PACU handoff communication. We developed an aviation-style computerized checklist system for use in procedural rooms and adapted it for tablet computers to facilitate the performance of PACU handoffs. We then compared the proportion of PACU handoff items communicated before and after the implementation of the PACU handoff checklist on a tablet computer. A trained observer recorded the proportion of PACU handoff information items communicated, any resistance during the performance of the checklist, the type of provider participating in the handoff, and the time required to perform the handoff. We also obtained these patient outcomes: PACU length of stay, respiratory events, post-operative nausea and vomiting, and pain. A total of 209 PACU handoffs were observed before and 210 after the implementation of the tablet-based PACU handoff checklist. The average proportion of PACU handoff items communicated increased from 49.3% (95% CI 47.7-51.0%) before checklist implementation to 72.0% (95% CI 69.2-74.9%) after checklist implementation (p < 0.001). A tablet-based aviation-style handoff checklist resulted in an increase in PACU handoff items communicated, but did not have an effect on patient outcomes.

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.

Counting train-of-four twitch response: comparison of palpation to mechanomyography, acceleromyography, and electromyography.

BACKGROUND: Train-of-four twitch monitoring can be performed using palpation of thumb movement, or by the use of a more objective quantitative monitor, such as mechanomyography, acceleromyography, or electromyography. The relative performance of palpation and quantitative monitoring for determination of the train-of-four ratio has been studied extensively, but the relative performance of palpation and quantitative monitors for counting train-of-four twitch responses has not been completely described. METHODS: We compared train-of-four counts by palpation to mechanomyography, acceleromyography (Stimpod™), and electromyography (TwitchView Monitor™) in anaesthetised patients using 1691 pairs of measurements obtained from 46 subjects. RESULTS: There was substantial agreement between palpation and electromyography (kappa = 0.80), mechanomyography (kappa = 0.67), or acceleromyography (kappa = 0.63). Electromyography with TwitchView and mechanomyography most closely resembled palpation, whereas acceleromyography with StimPod often underestimated train-of-four count. With palpation as the comparator, acceleromyography was more likely to measure a lower train-of-four count, with 36% of counts less than palpation, and 3% more than palpation. For mechanomyography, 31% of train-of-four counts were greater than palpation, and 9% were less. For electromyography, 15% of train-of-four counts were greater than palpation, and 12% were less. The agreement between acceleromyography and electromyography was fair (kappa = 0.38). For acceleromyography, 39% of train-of-four counts were less than electromyography, and 5% were more. CONCLUSIONS: Acceleromyography with the StimPod frequently underestimated train-of-four count in comparison with electromyography with TwitchView.

Aviation-Style Computerized Surgical Safety Checklist Displayed on a Large Screen and Operated by the Anesthesia Provider Improves Checklist Performance.

BACKGROUND: Many hospitals have implemented surgical safety checklists based on the World Health Organization surgical safety checklist, which was associated with improved outcomes. However, the execution of the checklists is frequently incomplete. We reasoned that aviation-style computerized checklist displayed onto large, centrally located screen and operated by the anesthesia provider would improve the performance of surgical safety checklist. METHODS: We performed a prospective before and after observational study to evaluate the effect of a computerized surgical safety checklist system on checklist performance. We created checklist software and translated our 4-part surgical safety checklist from wall poster into an aviation-style computerized format displayed onto a large, centrally located screen and operated by the anesthesia provider. Direct observers recorded performance of the first part of the surgical safety checklist that was initiated before anesthetic induction, including completion of each checklist item, provider participation and distraction level, resistance to use of the checklist, and the time required for checklist completion before and after checklist system implementation. We compared trends of the proportions of cases with 100% surgical safety checklist completion over time between pre- and postintervention periods and assessed for a jump at the start of intervention using segmented logistic regression model while controlling for potential confounding variables. RESULTS: A total of 671 cases were observed before and 547 cases were observed after implementation of the computerized surgical safety checklist system. The proportion of cases in which all of the items of the surgical safety checklist were completed significantly increased from 2.1% to 86.3% after the computerized checklist system implementation (P < .001). Before computerized checklist system implementation, 488 of 671 (72.7%) cases had <75% of checklist items completed, whereas after a computerized checklist system implementation, only 3 of 547 (0.5%) cases had <75% of checklist items completed. CONCLUSIONS: The implementation of a computerized surgical safety checklist system resulted in an improvement in checklist performance.

Forecasting a Crisis: Machine-Learning Models Predict Occurrence of Intraoperative Bradycardia Associated With Hypotension.

BACKGROUND: Predictive analytics systems may improve perioperative care by enhancing preparation for, recognition of, and response to high-risk clinical events. Bradycardia is a fairly common and unpredictable clinical event with many causes; it may be benign or become associated with hypotension requiring aggressive treatment. Our aim was to build models to predict the occurrence of clinically significant intraoperative bradycardia at 3 time points during an operative course by utilizing available preoperative electronic medical record and intraoperative anesthesia information management system data. METHODS: The analyzed data include 62,182 scheduled noncardiac procedures performed at the University of Washington Medical Center between 2012 and 2017. The clinical event was defined as severe bradycardia (heart rate <50 beats per minute) followed by hypotension (mean arterial pressure <55 mm Hg) within a 10-minute window. We developed models to predict the presence of at least 1 event following 3 time points: induction of anesthesia (TP1), start of the procedure (TP2), and 30 minutes after the start of the procedure (TP3). Predictor variables were based on data available before each time point and included preoperative patient and procedure data (TP1), followed by intraoperative minute-to-minute patient monitor, ventilator, intravenous fluid, infusion, and bolus medication data (TP2 and TP3). Machine-learning and logistic regression models were developed, and their predictive abilities were evaluated using the area under the ROC curve (AUC). The contribution of the input variables to the models were evaluated. RESULTS: The number of events was 3498 (5.6%) after TP1, 2404 (3.9%) after TP2, and 1066 (1.7%) after TP3. Heart rate was the strongest predictor for events after TP1. Occurrence of a previous event, mean heart rate, and mean pulse rates before TP2 were the strongest predictor for events after TP2. Occurrence of a previous event, mean heart rate, mean pulse rates before TP2 (and their interaction), and 15-minute slopes in heart rate and blood pressure before TP2 were the strongest predictors for events after TP3. The best performing machine-learning models including all cases produced an AUC of 0.81 (TP1), 0.87 (TP2), and 0.89 (TP3) with positive predictive values of 0.30, 0.29, and 0.15 at 95% specificity, respectively. CONCLUSIONS: We developed models to predict unstable bradycardia leveraging preoperative and real-time intraoperative data. Our study demonstrates how predictive models may be utilized to predict clinical events across multiple time intervals, with a future goal of developing real-time, intraoperative, decision support.

Succinylcholine Use and Dantrolene Availability for Malignant Hyperthermia Treatment: Database Analyses and Systematic Review.

BACKGROUND: Although dantrolene effectively treats malignant hyperthermia (MH), discrepant recommendations exist concerning dantrolene availability. Whereas Malignant Hyperthermia Association of the United States guidelines state dantrolene must be available within 10 min of the decision to treat MH wherever volatile anesthetics or succinylcholine are administered, a Society for Ambulatory Anesthesia protocol permits Class B ambulatory facilities to stock succinylcholine for airway rescue without dantrolene. The authors investigated (1) succinylcholine use rates, including for airway rescue, in anesthetizing/sedating locations; (2) whether succinylcholine without volatile anesthetics triggers MH warranting dantrolene; and (3) the relationship between dantrolene administration and MH morbidity/mortality. METHODS: The authors performed focused analyses of the Multicenter Perioperative Outcomes Group (2005 through 2016), North American MH Registry (2013 through 2016), and Anesthesia Closed Claims Project (1970 through 2014) databases, as well as a systematic literature review (1987 through 2017). The authors used difficult mask ventilation (grades III and IV) as a surrogate for airway rescue. MH experts judged dantrolene treatment. For MH morbidity/mortality analyses, the authors included U.S. and Canadian cases that were fulminant or scored 20 or higher on the clinical grading scale and in which volatile anesthetics or succinylcholine were given. RESULTS: Among 6,368,356 queried outcomes cases, 246,904 (3.9%) received succinylcholine without volatile agents. Succinylcholine was used in 46% (n = 710) of grade IV mask ventilation cases (median dose, 100 mg, 1.2 mg/kg). Succinylcholine without volatile anesthetics triggered 24 MH cases, 13 requiring dantrolene. Among 310 anesthetic-triggered MH cases, morbidity was 20 to 37%. Treatment delay increased complications every 10 min, reaching 100% with a 50-min delay. Overall mortality was 1 to 10%; 15 U.S. patients died, including 4 after anesthetics in freestanding facilities. CONCLUSIONS: Providers use succinylcholine commonly, including during difficult mask ventilation. Succinylcholine administered without volatile anesthetics may trigger MH events requiring dantrolene. Delayed dantrolene treatment increases the likelihood of MH complications. The data reported herein support stocking dantrolene wherever succinylcholine or volatile anesthetics may be used.

Process Optimization and Digital Quality Improvement to Enhance Timely Initiation of Epidural Infusions and Postoperative Pain Control.

BACKGROUND: Although intraoperative epidural analgesia improves postoperative pain control, a recent quality improvement project demonstrated that only 59% of epidural infusions are started in the operating room before patient arrival in the postanesthesia care unit. We evaluated the combined effect of process and digital quality improvement efforts on provider compliance with starting continuous epidural infusions during surgery. METHODS: In October 2014, we instituted 2 process improvement initiatives: (1) an electronic order queue to assist the operating room pharmacy with infusate preparation; and (2) a designated workspace for the storage of equipment related to epidural catheter placement and drug infusion delivery. In addition, we implemented a digital quality improvement initiative, an Anesthesia Information Management System-mediated clinical decision support, to prompt anesthesia providers to start and document epidural infusions in pertinent patients. We assessed anesthesia provider compliance with epidural infusion initiation in the operating room and postoperative pain-related outcomes before (PRE: October 1, 2012 to September 31, 2014) and after (POST: January 1, 2015 to December 31, 2016) implementation of the quality improvement initiatives. RESULTS: Compliance with starting intraoperative epidural infusions was 59% in the PRE group and 85% in the POST group. After adjustment for confounders and preintervention time trends, segmented regression analysis demonstrated a statistically significant increase in compliance with the intervention in the POST phase (odds ratio, 2.78; 95% confidence interval, 1.73-4.49; P < .001). In the PRE and POST groups, cumulative postoperative intravenous opioid use (geometric mean) was 62 and 34 mg oral morphine equivalents, respectively. A segmented regression analysis did not demonstrate a statistically significant difference (P = .38) after adjustment for preintervention time trends. CONCLUSIONS: Process workflow optimization along with Anesthesia Information Management System-mediated digital quality improvement efforts increased compliance to intraoperative epidural infusion initiation. Adjusted for preintervention time trends, these findings coincided with a statistically insignificant decrease in postoperative opioid use in the postanesthesia care unit during the POST phase.

Electronic Audit and Feedback With Positive Rewards Improve Anesthesia Provider Compliance With a Barcode-Based Drug Safety System.

BACKGROUND: We implemented a previously described barcode-based drug safety system in all of our anesthetizing locations. Providers were instructed to scan the barcode on syringes using our Anesthesia Information Management System before drug administration, but the rate of provider adherence was low. We studied an implementation intervention intended to increase the rate of scanning. METHODS: Using our Anesthesia Information Management System and Smart Anesthesia Manager software, we quantified syringe drug administrations by anesthesia providers with and without barcode scanning. We use an anesthesia team model in which an attending anesthesiologist is paired with a certified registered nurse anesthetist (CRNA) or a resident. Our system identified the pair of providers associated with a particular drug administration, but did not distinguish which providers actually administered the drug. Therefore, the rate of barcode scanning for a particular case was assigned to both providers equally. A baseline rate of scanning was established over a period of 17 months. An audit and feedback intervention was then performed that consisted of monthly performance reports sent by email to individual providers along with coffee gift card awards for top performers. The coffee gift cards were awarded in only the first 2 months of the intervention, while the email performance reports continued on a monthly basis. The coffee card awards were made public. The monthly emails reported the individual provider's rank order of performance relative to other providers, but was otherwise anonymous. The baseline rate of scanning was compared to the rate of scanning after the intervention for a period of 7 months. RESULTS: From November 2014 to March 2017, we accumulated 60,197 cases performed by 88 attending anesthesiologists, 65 CRNAs, and 148 residents. The total number of syringe drug administrations was 653,355. Average scanning performance improved from 8.7% of syringe barcodes scanned during the baseline period from November 2014 to February 2016 to 64.4% scanned during the period September 2016 to March 2017 (P < .001). Variation in performance among individuals was marked, ranging from 0% to 100% of syringes scanned. The performance of some individuals showed marked oscillation over time. There was greater variation in performance attributable to residents than in performance attributable to CRNAs. CONCLUSIONS: Feedback of individual provider performance data from the anesthesia information system to providers can be used in conjunction with other measures to improve performance. Despite improved average performance, there was marked variation in performance between individuals, and some individuals had marked oscillation of their performance over time.

Feasibility and indicator outcomes using computerized clinical decision support in pediatric traumatic brain injury anesthesia care.

BACKGROUND: Traumatic brain injury anesthesia care is complex. The use of clinical decision support to improve pediatric trauma care has not been examined. AIMS: The aim of this study was to examine feasibility, reliability, and key performance indicators for traumatic brain injury anesthesia care using clinical decision support. METHODS: Clinical decision support was activated for patients under 19 years undergoing craniotomy for suspected traumatic brain injury. Anesthesia providers were prompted to adhere to process measures via on-screen alerts and notified in real time of abnormal monitor data or laboratory results (unwanted key performance indicator events). Process measures pertained to arterial line placement and blood gas draws, neuromuscular blockade, hypotension, anemia, coagulopathy, hyperglycemia, and intracranial hypertension. Unwanted key performance indicators were: hypotension, hypoxia, hypocarbia, hypercarbia, hypothermia, hyperthermia, anesthetic agent overdose; hypoxemia, coagulopathy, anemia, and hyperglycemia. Anesthesia records, vital signs, and alert logs were reviewed for 39 anesthetic cases (19 without clinical decision support and 20 with clinical decision support). RESULTS: Data from 35 patients aged 11 months to 17 years and 77% males were examined. Clinical decision support reliably identified 39/46 eligible anesthetic cases, with 85% sensitivity and 100% specificity, and was highly sensitive, detecting 89% of monitor key performance indicator events and 100% of reported lab key performance indicator events. There were no false positive alerts. Median event duration was lower in the "with clinical decision support" group for 4/7 key performance indicators. Second insult duration was lower for duration of hypocarbia (by 44%), hypotension (29%), hypothermia (12%), and hyperthermia (15%). CONCLUSION: Use of clinical decision support in pediatric traumatic brain injury anesthesia care is feasible, reliable, and may have the potential to improve key performance indicator outcomes. This observational study suggests the possibility of clinical decision support as a strategy to reduce second insults and improve traumatic brain injury guideline adherence during pediatric anesthesia care.

Intraoperative Clinical Decision Support for Anesthesia: A Narrative Review of Available Systems.

With increasing adoption of anesthesia information management systems (AIMS), there is growing interest in utilizing AIMS data for intraoperative clinical decision support (CDS). CDS for anesthesia has the potential for improving quality of care, patient safety, billing, and compliance. Intraoperative CDS can range from passive and post hoc systems to active real-time systems that can detect ongoing clinical issues and deviations from best practice care. Real-time CDS holds the most promise because real-time alerts and guidance can drive provider behavior toward evidence-based standardized care during the ongoing case. In this review, we describe the different types of intraoperative CDS systems with specific emphasis on real-time systems. The technical considerations in developing and implementing real-time CDS are systematically covered. This includes the functional modules of a CDS system, development and execution of decision rules, and modalities to alert anesthesia providers concerning clinical issues. We also describe the regulatory aspects that affect development, implementation, and use of intraoperative CDS. Methods and measures to assess the effectiveness of intraoperative CDS are discussed. Last, we outline areas of future development of intraoperative CDS, particularly the possibility of providing predictive and prescriptive decision support.

Methylprednisolone Therapy in Acute Traumatic Spinal Cord Injury: Analysis of a Regional Spinal Cord Model Systems Database.

BACKGROUND: The objective of this study was to assess the relationship between exposure to methylprednisolone (MP) and improvements in motor function among patients with acute traumatic spinal cord injury (TSCI). MP therapy for patients with TSCI is controversial because of the current conflicting evidence documenting its benefits and risks. METHODS: We conducted a retrospective cohort study from September 2007 to November 2014 of 311 patients with acute TSCI who were enrolled into a model systems database of a regional, level I trauma center. We linked outcomes and covariate data from the model systems database with MP exposure data from the electronic medical record. The primary outcomes were rehabilitation discharge in American Spinal Injury Association (ASIA) motor scores (sum of 10 key muscles bilaterally as per International Standards for Neurological Classification of Spinal Cord Injury, range, 0-100) and Functional Independence Measure (FIM) motor scores (range, 13-91). Secondary outcomes measured infection risk and gastrointestinal (GI) complications among MP recipients. For the primary outcomes, multivariable linear regression was used. RESULTS: There were 160 MP recipients and 151 nonrecipients. Adjusting for age, sex, weight, race, respective baseline motor score, surgical intervention, injury level, ASIA Impairment Scale (AIS) grade, education, and insurance status, there was no association with improvement in discharge ASIA motor function or FIM motor score among MP recipients: -0.34 (95% CI, -2.8, 2.1) and 0.75 (95% CI, -2.8, 4.3), respectively. Adjusting for age, sex, race, weight, injury level, and receipt of surgery, no association with increased risk of infection or GI complications was observed. CONCLUSIONS: This retrospective cohort study involving patients with acute TSCI observed no short-term improvements in motor function among MP recipients compared with nonrecipients. Our findings support current recommendations that MP use in this population should be limited.

Preoperative Low-Dose Aspirin Exposure and Outcomes After Emergency Neurosurgery for Traumatic Intracranial Hemorrhage in Elderly Patients.

BACKGROUND: Antiplatelet medications are usually discontinued before elective neurosurgery, but this is not an option for emergent neurosurgery. We performed a retrospective cohort study to examine whether preoperative aspirin use was associated with worse outcomes after emergency neurosurgery in elderly patients. METHODS: We analyzed all cases of emergency neurosurgical procedures for traumatic intracranial hemorrhage from 2008 to 2012 at a level 1 trauma center. Demographics, comorbidities, and outcomes were compared for patients ≥65 years by preoperative aspirin exposure. Exclusion criteria were: (1) polytrauma, (2) concomitant use of other preoperative anticoagulants or antiplatelet agents, (3) surgical indication other than subdural, extradural, or intraparenchymal hemorrhage, and (4) repeat neurosurgical procedures within a single admission. Estimated intraoperative blood loss, postprocedural intracranial bleeding requiring reoperation, death in hospital, intensive care unit, and hospital lengths of stay and perioperative blood product transfusion from 48 hours before 48 hours after surgery were the study outcomes. We also examined whether platelet transfusion had an impact on outcomes for patients on aspirin. RESULTS: The cohort included 171 patients. Patients receiving preoperative aspirin (n = 87, 95% taking 81 mg/day) were the same age as patients not receiving aspirin (n = 84; 78.3 ± 7.8 vs 75.9 ± 7.9 years, P > .05), had slightly higher admission Glasgow Coma Scale scores (12.8 ± 3.4 vs 11.4 ± 4, P = .02) and tended to have more coronary artery disease (P< .05). Adjusted for Glasgow Coma Scale and coronary artery disease, patients receiving preoperative aspirin had a higher odds of perioperative platelet transfusion (adjusted odds ratio 9.89, 95% confidence interval, 4.24-26.25). There were no other differences in outcomes between the 2 groups. Preoperative or intraoperative platelet transfusion was not associated with better outcomes among aspirin patients. CONCLUSIONS: In patients age ≥65 years undergoing emergency neurosurgery for traumatic intracranial hemorrhage, preoperative low-dose aspirin treatment was not associated with increased perioperative bleeding, hospital lengths of stay, or in-hospital mortality.

Risks of Routinely Clamping External Ventricular Drains for Intrahospital Transport in Neurocritically Ill Cerebrovascular Patients.

BACKGROUND: Current guidelines recommend routine clamping of external ventricular drains (EVD) for intrahospital transport (IHT). The aim of this project was to describe intracranial hemodynamic complications associated with routine EVD clamping for IHT in neurocritically ill cerebrovascular patients. METHODS: We conducted a retrospective review of cerebrovascular adult patients with indwelling EVD admitted to the neurocritical care unit (NICU) during the months of September to December 2015 at a tertiary care center. All IHTs from the NICU of the included patients were examined. Main outcomes were incidence and risk factors for an alteration in intracranial pressure (ICP) and cerebral perfusion pressure after IHT. RESULTS: Nineteen cerebrovascular patients underwent 178 IHTs (79.8 % diagnostic and 20.2 % therapeutic) with clamped EVD. Twenty-one IHTs (11.8 %) were associated with post-IHT ICP ≥ 20 mmHg, and 33 IHTs (18.5 %) were associated with escalation of ICP category. Forty IHTs (26.7 %) in patients with open EVD status in the NICU prior to IHT were associated with IHT complications, whereas no IHT complications occurred in IHTs with clamped EVD status in the NICU. Risk factors for post-IHT ICP ≥ 20 mmHg were IHT for therapeutic procedures (adjusted relative risk [aRR] 5.82; 95 % CI, 1.76-19.19), pre-IHT ICP 15-19 mmHg (aRR 3.40; 95 % CI, 1.08-10.76), pre-IHT ICP ≥ 20 mmHg (aRR 12.94; 95 % CI, 4.08-41.01), and each 1 mL of hourly cerebrospinal fluid (CSF) drained prior to IHT (aRR 1.11; 95 % CI, 1.01-1.23). CONCLUSIONS: Routine clamping of EVD for IHT in cerebrovascular patients is associated with post-IHT ICP complications. Pre-IHT ICP ≥ 15 mmHg, increasing hourly CSF output, and IHT for therapeutic procedures are risk factors.

Continuous intraoperative epidural infusions affect recovery room length of stay and analgesic requirements: a single-center observational study.

PURPOSE: Continuous intraoperative epidural analgesia may improve post-operative pain control and decrease opioid requirements. We investigate the effect of epidural infusion initiation before or after arrival in the post-anesthesia care unit on recovery room duration and post-operative opioid use. METHODS: We performed a retrospective chart review of abdominal, thoracic and orthopedic surgeries where an epidural catheter was placed prior to surgery at the University of Washington Medical Center during a 24 month period. RESULTS: Patients whose epidural infusions were started prior to PACU arrival (Group 2: n = 540) exhibited a shorter PACU length of stay (p = .004) and were less likely to receive intravenous opioids in the recovery room (34 vs. 48%; p < .001) compared to patients whose infusions were started after surgery (Group 1: n = 374). Although the highest patient-reported pain scores were lower in Group 2 (5.3 vs. 6.0; p = .030), no differences in the pain scores prior to PACU discharge were observed. CONCLUSION: Intraoperative continuous epidural infusions decrease PACU LOS as discharge criteria for patient-reported NRS pain scores are met earlier.

The Effect of Intraoperative Blood Glucose Management on Postoperative Blood Glucose Levels in Noncardiac Surgery Patients.

BACKGROUND: Postoperative hyperglycemia has been associated with poor surgical outcome. The effect of intraoperative glucose management on postoperative glucose levels and the optimal glycemic threshold for initiating insulin are currently unknown. METHODS: We performed a retrospective cohort study of surgery patients who required intraoperative glucose management with data extracted from electronic medical records. In patients who required glucose management, intraoperative glucose levels and insulin therapy were compared against postoperative glucose levels during 3 periods: first postoperative level within 1 hour, within the first 12 hours, and 24 hours of the postoperative period. Logistic regression models that adjusted for patient and surgical factors were used to determine the association between intraoperative glucose management and postoperative glucose levels. RESULTS: In 2440 patients who required intraoperative glucose management, an increase in mean intraoperative glucose level by 10 mg/dL was associated with an increase in postoperative glucose levels by 4.7 mg/dL (confidence interval [CI], 4.1-5.3; P < 0.001) for the first postoperative glucose measurement, 2.6 mg/dL (CI, 2.1-3.1; P < 0.001) for the mean first 12-hour postoperative glucose, and 2.4 mg/dL (CI, 2.0-2.9; P < 0.001) for the mean first 24-hour postoperative glucose levels (univariate analysis). Multivariate analysis showed that these effects depended on (interacted with) body mass index and diabetes status of the patient. Both diabetes status (regression coefficient = 12.2; P < 0.001) and intraoperative steroid use (regression coefficient = 10.2; P < 0.001) had a positive effect on elevated postoperative glucose levels. Intraoperative hyperglycemia (>180 mg/dL) was associated with postoperative hyperglycemia during the first 12 hours and the first 24 hours. However, interaction with procedure duration meant that this association was stronger for shorter surgeries. When compared with starting insulin for an intraoperative glucose threshold of 140 mg/dL thus avoiding hyperglycemia, initiation of insulin for a hyperglycemia threshold of 180 mg/dL was associated with an increase in postoperative glucose level (7 mg/dL; P < 0.001) and postoperative hyperglycemia incidence (odds ratio = 1.53; P = 0.01). CONCLUSIONS: A higher intraoperative glucose level is associated with a higher postoperative glucose level. Intraoperative hyperglycemia increases the odds for postoperative hyperglycemia. Adequate intraoperative glucose management by initiating insulin infusion when glucose level exceeds 140 mg/dL to prevent hyperglycemia is associated with lower postoperative glucose levels and fewer incidences of postoperative hyperglycemia. However, patient- and procedure-specific variable interactions make the relationship between intraoperative and postoperative glucose levels complicated.