Search

Pediatric burns affect approximately 15-20 patients per 100 000 hospital admissions, but unfortunately there is a lack of evidence to guide optimal strategies for acute pain control. The aim of this study was to evaluate whether caudal analgesia with single injection of local anesthetics reduced pain medication consumption in pediatric patients who required surgical intervention for burn injuries. Retrospective data from patients

Background Postamputation phantom pain is notoriously persistent with few validated treatments. Cryoneurolysis involves the application of low temperatures to reversibly ablate peripheral nerves. The authors tested the hypothesis that a single cryoneurolysis treatment would decrease phantom pain 4 months later. Methods The authors enrolled patients with a lower-limb amputation and established phantom pain. Each received a single-injection femoral and sciatic nerve block with lidocaine and was subsequently randomized to receive either ultrasound-guided percutaneous cryoneurolysis or sham treatment at these same locations. The primary outcome was the change in average phantom pain intensity between baseline and 4 months as measured with a numeric rating scale (0 to 10), after which an optional crossover treatment was offered. Investigators, participants, and clinical staff were masked to treatment group assignment with the exception of the treating physician performing the cryoneurolysis, who had no subsequent participant interaction. Results Pretreatment phantom pain scores were similar in both groups, with a median [quartiles] of 5.0 [4.0, 6.0] for active treatment and 5.0 [4.0, 7.0] for sham. After 4 months, pain intensity decreased by 0.5 [–0.5, 3.0] in patients given cryoneurolysis (n = 71) versus 0 [0, 3] in patients given sham (n = 73), with an estimated difference (95% CI) of –0.1 (–1.0 to 0.7), P = 0.759. Following their statistical gatekeeping protocol, the authors did not make inferences or draw conclusions on secondary endpoints. One serious adverse event occurred after a protocol deviation in which a femoral nerve cryolesion was induced just below the inguinal ligament—instead of the sensory-only saphenous nerve—which resulted in quadriceps weakness, and possibly a fall and clavicle fracture. Conclusions Percutaneous cryoneurolysis did not decrease chronic lower extremity phantom limb pain 4 months after treatment. However, these results were based upon the authors’ specific study protocol, and since the optimal cryoneurolysis treatment parameters such as freeze duration and anatomic treatment location remain unknown, further research is warranted. Editor’s Perspective What We Already Know about This Topic What This Article Tells Us That Is New

Background Ultrasound-guided percutaneous cryoneurolysis is an analgesic technique in which a percutaneous probe is used to reversibly ablate a peripheral nerve(s) using exceptionally low temperature, and has yet to be evaluated with randomized, controlled trials. Pain after mastectomy can be difficult to treat, and the authors hypothesized that the severity of surgically related pain would be lower on postoperative day 2 with the addition of cryoanalgesia compared with patients receiving solely standard-of-care treatment. Methods Preoperatively, participants at one enrolling center received a single injection of ropivacaine, 0.5%, paravertebral nerve block at T3 or T4, and perineural catheter. Participants subsequently underwent an active or sham ultrasound–guided percutaneous cryoneurolysis procedure of the ipsilateral T2 to T5 intercostal nerves in a randomized, patient- and observer-masked fashion. Participants all received a continuous paravertebral block with ropivacaine, 0.2%, until the early morning of discharge (usually postoperative day 2). The primary endpoint was the average pain level measured using a 0 to 10 numeric rating scale the afternoon of postoperative day 2. Participants were followed for 1 yr. Results On postoperative day 2, participants who had received active cryoneurolysis (n = 31) had a median [interquartile range] pain score of 0 [0 to 1.4] versus 3.0 [2.0 to 5.0] in patients given sham (n = 29): difference –2.5 (97.5% CI, –3.5 to –1.5), P < 0.001. There was evidence of superior analgesia through month 12. During the first 3 weeks, cryoneurolysis lowered cumulative opioid use by 98%, with the active group using 1.5 [0 to 14] mg of oxycodone compared with 72 [20 to 120] mg in the sham group (P < 0.001). No oral analgesics were required by any patient between months 1 and 12. After 1 yr chronic pain had developed in 1 (3%) active compared with 5 (17%) sham participants (P < 0.001). Conclusions Percutaneous cryoneurolysis markedly improved analgesia without systemic side effects or complications after mastectomy. Editor’s Perspective What We Already Know about This Topic What This Article Tells Us That Is New

Methods that can automate, support, and streamline the preanesthesia evaluation process may improve resource utilization and efficiency. Natural language processing (NLP) involves the extraction of relevant information from unstructured text data. We describe the utilization of a clinical NLP pipeline intended to identify elements relevant to preoperative medical history by analyzing clinical notes. We hypothesize that the NLP pipeline would identify a significant portion of pertinent history captured by a perioperative provider.For each patient, we collected all pertinent notes from the institution's electronic medical record that were available no later than 1 day before their preoperative anesthesia clinic appointment. Pertinent notes included free-text notes consisting of history and physical, consultation, outpatient, inpatient progress, and previous preanesthetic evaluation notes. The free-text notes were processed by a Named Entity Recognition pipeline, an NLP machine learning model trained to recognize and label spans of text that corresponded to medical concepts. These medical concepts were then mapped to a list of medical conditions that were of interest for a preanesthesia evaluation. For each condition, we calculated the percentage of time across all patients in which (1) the NLP pipeline and the anesthesiologist both captured the condition; (2) the NLP pipeline captured the condition but the anesthesiologist did not; and (3) the NLP pipeline did not capture the condition but the anesthesiologist did.A total of 93 patients were included in the NLP pipeline input. Free-text notes were extracted from the electronic medical record of these patients for a total of 9765 notes. The NLP pipeline and anesthesiologist agreed in 81.24% of instances on the presence or absence of a specific condition. The NLP pipeline identified information that was not noted by the anesthesiologist in 16.57% of instances and did not identify a condition that was noted by the anesthesiologist's review in 2.19% of instances.In this proof-of-concept study, we demonstrated that utilization of NLP produced an output that identified medical conditions relevant to preanesthetic evaluation from unstructured free-text input. Automation of risk stratification tools may provide clinical decision support or recommend additional preoperative testing or evaluation. Future studies are needed to integrate these tools into clinical workflows and validate its efficacy.

Purpose: A major source of inefficiency in the operating room is the mismatch between scheduled versus actual surgical time. The purpose of this study was to demonstrate a proof-of-concept study for predicting case duration by applying natural language processing (NLP) and machine learning that interpret radiology reports for patients undergoing radius fracture repair. Methods: Logistic regression, random forest, and artificial neural networks (ANN) were tested without NLP and with bag-of-words. Another NLP method tested used ANN and Bidirectional Encoder Representations from Transformers specifically pre-trained on clinical notes (ClinicalBERT). A total of 201 cases were included. The data were split into 70% training and 30% test sets. The average root mean squared error (RMSE) (and 95% confidence interval [CI]) from 10-fold cross-validation on the training set were used to develop each model. Models were then compared to a baseline model, which used historic averages to predict surgical time. Results: The average RMSE was lowest using ANN with ClinicalBERT (25.6 minutes, 95% CI: 21.5 - 29.7), which was significantly (PConclusion: This proof-of-concept study demonstrated the successful application of NLP and machine leaning to extract features from unstructured clinical data resulting in improved prediction accuracy for surgical case duration.

Background The common technique using a basal infusion for an ambulatory continuous peripheral nerve blocks frequently results in exhaustion of the local anesthetic reservoir before resolution of surgical pain. This study was designed to improve and prolong analgesia by delaying initiation using an integrated timer and delivering a lower hourly volume of local anesthetic as automated boluses. The hypothesis was that compared with a traditional continuous infusion, ropivacaine administered with automated boluses at a lower dose and 5-h delay would (1) provide at least noninferior analgesia (difference in average pain no greater than 1.7 points) while both techniques were functioning (average pain score day after surgery) and (2) result in a longer duration (dual primary outcomes). Methods Participants (n = 70) undergoing foot or ankle surgery with a popliteal–sciatic catheter received an injection of ropivacaine 0.5% with epinephrine (20 ml) and then were randomized to receive ropivacaine (0.2%) either as continuous infusion (6 ml/h) initiated before discharge or as automated boluses (8 ml every 2 h) initiated 5 h after discharge using a timer. Both groups could self-deliver supplemental boluses (4 ml, lockout 30 min); participants and outcome assessors were blinded to randomization. All randomized participants were included in the data analysis. Results The day after surgery, participants with automated boluses had a median [interquartile range] pain score of 0.0 [0.0 to 3.0] versus 3.0 [1.8 to 4.8] for the continuous infusion group, with an odds ratio of 3.1 (95% CI, 1.23 to 7.84; P = 0.033) adjusting for body mass index. Reservoir exhaustion in the automated boluses group occurred after a median [interquartile range] of 119 h [109 to 125] versus 74 h [57 to 80] for the continuous infusion group (difference of 47 h; 95% CI, 38 to 55; P < 0.001 adjusting for body mass index). Conclusions For popliteal–sciatic catheters, replacing a continuous infusion initiated before discharge with automated boluses and a start-delay timer resulted in better analgesia and longer infusion duration. Editor’s Perspective What We Already Know about This Topic What This Article Tells Us That Is New

BackgroundThe objective of this study is to develop predictive models for persistent opioid use following lower extremity joint arthroplasty and determine if ensemble learning and an oversampling technique may improve model performance.MethodsWe compared various predictive models to identify at-risk patients for persistent postoperative opioid use using various preoperative, intraoperative, and postoperative data, including surgical procedure, patient demographics/characteristics, past surgical history, opioid use history, comorbidities, lifestyle habits, anesthesia details, and postoperative hospital course. Six classification models were evaluated: logistic regression, random forest classifier, simple-feedforward neural network, balanced random forest classifier, balanced bagging classifier, and support vector classifier. Performance with Synthetic Minority Oversampling Technique (SMOTE) was also evaluated. Repeated stratified k-fold cross-validation was implemented to calculate F1-scores and area under the receiver operating characteristics curve (AUC).ResultsThere were 1042 patients undergoing elective knee or hip arthroplasty in which 242 (23.2%) reported persistent opioid use. Without SMOTE, the logistic regression model has an F1 score of 0.47 and an AUC of 0.79. All ensemble methods performed better, with the balanced bagging classifier having an F1 score of 0.80 and an AUC of 0.94. SMOTE improved performance of all models based on F1 score. Specifically, performance of the balanced bagging classifier improved to an F1 score of 0.84 and an AUC of 0.96. The features with the highest importance in the balanced bagging model were postoperative day 1 opioid use, body mass index, age, preoperative opioid use, prescribed opioids at discharge, and hospital length of stay.ConclusionsEnsemble learning can dramatically improve predictive models for persistent opioid use. Accurate and early identification of high-risk patients can play a role in clinical decision making and early optimization with personalized interventions.

PURPOSE The post-anesthesia care unit (PACU) length of stay is an important perioperative efficiency metric. The aim of this study was to develop machine learning models to predict ambulatory surgery patients at risk for prolonged PACU length of stay - using only pre-operatively identified factors - and then to simulate the effectiveness in reducing the need for after-hours PACU staffing. METHODS Several machine learning classifier models were built to predict prolonged PACU length of stay (defined as PACU stay ≥ 3 hours) on a training set. A case resequencing exercise was then performed on the test set, in which historic cases were re-sequenced based on the predicted risk for prolonged PACU length of stay. The frequency of patients remaining in the PACU after-hours (≥ 7:00 pm) were compared between the simulated operating days versus actual operating room days. RESULTS There were 10,928 ambulatory surgical patients included in the analysis, of which 580 (5.31%) had a PACU length of stay ≥ 3 hours. XGBoost with SMOTE performed the best (AUC = 0.712). The case resequencing exercise utilizing the XGBoost model resulted in an over three-fold improvement in the number of days in which patients would be in the PACU past 7pm as compared with historic performance (41% versus 12%, PCONCLUSION Predictive models using preoperative patient characteristics may allow for optimized case sequencing, which may mitigate the effects of prolonged PACU lengths of stay on after-hours staffing utilization.

Background Estimating surgical case duration accurately is an important operating room efficiency metric. Current predictive techniques in spine surgery include less sophisticated approaches such as classical multivariable statistical models. Machine learning approaches have been used to predict outcomes such as length of stay and time returning to normal work, but have not been focused on case duration. Objective The primary objective of this 4-year, single-academic-center, retrospective study was to use an ensemble learning approach that may improve the accuracy of scheduled case duration for spine surgery. The primary outcome measure was case duration. Methods We compared machine learning models using surgical and patient features to our institutional method, which used historic averages and surgeon adjustments as needed. We implemented multivariable linear regression, random forest, bagging, and XGBoost (Extreme Gradient Boosting) and calculated the average R2, root-mean-square error (RMSE), explained variance, and mean absolute error (MAE) using k-fold cross-validation. We then used the SHAP (Shapley Additive Explanations) explainer model to determine feature importance. Results A total of 3189 patients who underwent spine surgery were included. The institution’s current method of predicting case times has a very poor coefficient of determination with actual times (R2=0.213). On k-fold cross-validation, the linear regression model had an explained variance score of 0.345, an R2 of 0.34, an RMSE of 162.84 minutes, and an MAE of 127.22 minutes. Among all models, the XGBoost regressor performed the best with an explained variance score of 0.778, an R2 of 0.770, an RMSE of 92.95 minutes, and an MAE of 44.31 minutes. Based on SHAP analysis of the XGBoost regression, body mass index, spinal fusions, surgical procedure, and number of spine levels involved were the features with the most impact on the model. Conclusions Using ensemble learning-based predictive models, specifically XGBoost regression, can improve the accuracy of the estimation of spine surgery times.

BACKGROUND: The primary objective of this study was to employ a national database to evaluate the association of hospital urbanicity, urban versus rural, on mortality and length of hospital stay in patients hospitalized with acute respiratory failure. METHODS: We used the 2014 National Inpatient Sample database to evaluate the association of hospital urbanicity with (1) mortality and (2) prolonged hospital stay, defined as ≥ 75th percentile of the study population. We conducted a mixed-effects logistic regression analysis adjusting for sociodemographic variables and medical comorbidities. The random effect was hospital identification number (a unique value assigned in the NIS database for a specific institution). The odds ratio (OR), 95% CI, and P values were reported for each independent variable. RESULTS: The odds of inpatient mortality were significantly higher among urban teaching (OR 1.39, 95% CI 1.39–1.66, P CONCLUSIONS: This study supports the current body of literature that there are significant differences in patient populations among hospital type. Differences in health outcomes among different types of hospitals should be considered when designing policies to address health equity as these are unique populations with specific needs.

Background Regional anesthesia (RA) has demonstrated distinct advantages over general anesthesia, including decreased infection risk, lower rates of complications, and improved patient satisfaction. As such, the rate of RA utilization has been increasing, particularly among outpatient orthopedic surgeries like total hip arthroplasty and total knee arthroplasty. However, no studies have examined utilization rates as a function of hospital region. Methods A national hospital database (Hospital Corporation of American, HCA) was queried for patients 18 years or older that received selected surgical procedure codes between January 2016 and June 2021. The included CPT codes were for total knee arthroplasty (TKA), total shoulder arthroplasty (TSA), anterior cruciate ligament reconstruction (ACLR), carpal tunnel release, total abdominal hysterectomy (TAH), open reduction and internal fixation (ORIF) of the ankle, and arteriovenous (AV) fistula creation. Regional anesthesia was defined as any form of neuraxial and/or peripheral nerve blocks. Basic summary statistics were utilized to calculate the rates of RA, and chi-squared analysis were calculated to determine significant differences in the rate of RA utilization. Results A total of 52068 patients were included, of which 2114 (4.06%) received RA. With respect to RA utilization by procedure, the greatest RA rates were for TSA (5.8%), TKA (4.5), and ACLR (3.6%), whereas the lowest RA rate was for TAH (1.1%). For the TKA cohort, the Midwest has a significantly greater utilization rate than the South or West (10.9% vs. 4.8% or 3.1%, p

The Surgical Care Improvement Project (SCIP) added the SCIP-Inf-10 measure to mandate that all surgical patients have perioperative temperature management to reduce surgical site infection. While the basis of this measure originated in colorectal surgery, we hypothesized that this would also apply to thoracic surgery patients.This was a retrospective single-center pilot study reviewing two years of thoracic surgery cases for the incidence and duration of hypothermia during the operation and surgical site infection occurring within 30 days. Hypothermia was defined as a core temperature of36° C. Results: A total of 317 patients were included in the study. Sixty-two percent of patients were identified as hypothermic. The average intraoperative temperature was 35.4°C ± 0.8°C in the hypothermic group and 36.4°C ± 0.3°C in the normothermic group. There were four surgical site infections in the study with three cases from the36°C group (p = 1). There was no difference in average post-anesthesia care unit length of stay between the groups. The average hospital length of stay was 5.5 ± 5.2 days for the hypothermic group and 8.6 ± 12.8 days for the normothermic group (p=0.0024).Perioperative hypothermia was common in thoracic surgery and did not have a negative impact on surgical site infection.

Caffeine is the world's most widely used psychoactive legal substance. The involvement of caffeine in pain management has gotten minimal attention in the past, but it is getting more attention now. This article provides a brief assessment of the literature to clarify the role of caffeine as a pain reliever and stimulate the interest of researchers. Caffeine affects adenosine receptors, which are involved in nociception, and plays a significant role in pain regulation. Caffeine's usage as an adjuvant therapy has been extensively documented in the literature, and it is now accessible in certain over-the-counter drugs. The mixture of coffee and morphine for pain reduction in individuals with terminal cancer has shown mixed outcomes in studies. Caffeine can be utilized for hypnic headaches and post-dural puncture headaches since it is crucial in pain regulation. Caffeine has the potential to help in pain management. Caffeine's usage for migraines and end-stage cancer disease is not well acknowledged. Further research is essential to focus on caffeine's potential role in various forms of pain, including dosage escalation and outcome assessment standardization.

The StimRouter® peripheral nerve stimulation system created by Bioness, Inc., (CA, USA) is US FDA-approved for the treatment of peripheral mononeuropathy refractory to conservative medical management. StimRouter is a minimally invasive system that utilizes a subcutaneously implanted lead with integrated anchor and electrodes, and an external pulse generator to produce peripheral neuromodulation and achieve pain relief. Multiple published clinical trials reviewed here have shown the StimRouter system to have a high margin of safety, differentiating it from other existing peripheral neuromodulation systems requiring open surgical electrode placement and implantable pulse generators. These studies have also shown the StimRouter system to be efficacious in the treatment of multiple peripheral mononeuropathies; improving patient pain, activity levels and quality of life. StimRouter represents a feasible option for management of chronic peripheral mononeuropathy.

Background: Same-day discharge, defined as discharge from the hospital within 24 h of surgery, has been shown to be safe for joint arthroplasty. We examined demographic and clinical factors associated with same-day discharge and unplanned readmission following shoulder arthroplasty in adult patients.Methods: Utilizing data from the American College of Surgeons National Surgical Quality Improvement Program database, we extracted information of all patients that underwent shoulder arthroplasty. The primary and secondary outcome of interest was same-day discharge and 30-day unplanned readmission, respectively. We utilized multivariable logistic regression to identify covariates associated with these outcomes. Results: There were 17,011 patients analyzed when identifying predictors for same-day discharge. There was an increase in same-day discharge from 2007 to 2016. The odds of same-day discharge were significantly better for males (P < 0.001). The odds of same-day discharge was significantly decreased for every 10-year increase in age and for patients with insulin dependent diabetes, poor functional status, chronic obstructive pulmonary disease, congestive heart failure, bleeding disorder, and comorbidity burden (all P < 0.001). There were 14,276 patients analyzed for hospital readmission. The odds of unplanned readmission were significantly higher for every 10-year increase in age and for patients with poor functional status, congestive heart failure, bleeding disorder, and higher comorbidity burden (all P < 0.001). Conclusions: The results of this study show that preoperative comorbidities and advanced age reduce the odds of same-day discharge. Risk stratification, preoperative optimization, and coordinated care after surgery may be helpful to optimize patients for same-day discharge.

Ultrasound-guided percutaneous peripheral nerve stimulation (PNS) may be used to treat acute postoperative pain for various types of surgeries. This modality avoids several limitations of traditional local anesthetic-based peripheral nerve blocks including avoidance of motor blockade and sensory deficits.In this review, we discuss the use of SPRINT (SPR Therapeutics, Cleveland, OH) neuromodulation system in the setting of acute postoperative pain management.PNS is a novel modality in regional anesthesia that has much promise in reducing overall opioid use after surgery. Placement of PNS is very similar to that of catheter-based regional anesthesia techniques. Ultrasound is used to guide the percutaneously placed introducer needle in proximity to the target nerve. There are several benefits of PNS over catheter-based approaches, including: 1) avoidance of motor or sensory blockade; 2) no medication bag required to be carried; and 3) electric leads may be kept

The authors provide a comprehensive summary of all randomized, controlled trials (n = 76) involving the clinical administration of liposomal bupivacaine (Exparel; Pacira Pharmaceuticals, USA) to control postoperative pain that are currently published. When infiltrated surgically and compared with unencapsulated bupivacaine or ropivacaine, only 11% of trials (4 of 36) reported a clinically relevant and statistically significant improvement in the primary outcome favoring liposomal bupivacaine. Ninety-two percent of trials (11 of 12) suggested a peripheral nerve block with unencapsulated bupivacaine provides superior analgesia to infiltrated liposomal bupivacaine. Results were mixed for the 16 trials comparing liposomal and unencapsulated bupivacaine, both within peripheral nerve blocks. Overall, of the trials deemed at high risk for bias, 84% (16 of 19) reported statistically significant differences for their primary outcome measure(s) compared with only 14% (4 of 28) of those with a low risk of bias. The preponderance of evidence fails to support the routine use of liposomal bupivacaine over standard local anesthetics.

Days before surgery, add-ons may be scheduled to fill unused surgical block time at an outpatient surgery center. At times, outpatient surgery centers have time limitations for end of block time and discharge from the postanesthesia care unit (PACU). The objective of our study was to develop machine learning models that predicted the following composite outcome: (1) surgery finished by end of operating room block time and (2) patient was discharged by end of recovery room nursing shift. We compared various machine learning models to logistic regression. By evaluating various performance metrics, including F1 scores, we hypothesized that models using ensemble learning will be superior to logistic regression.Data were collected from patients at an ambulatory surgery center. The primary outcome measurement was determined to have a value of 1 (versus 0) if they met both criteria: (1) surgery ends by 5 pm and (2) patient is discharged from the recovery room by 7 pm. We developed models to determine if a procedure would meet both criteria if it were scheduled at 1 pm, 2 pm, 3 pm, or 4 pm. We implemented regression, random forest, balanced random forest, balanced bagging, neural network, and support vector classifier, and included the following features: surgery, surgeon, service line, American Society of Anesthesiologists score, age, sex, weight, and scheduled case duration. We evaluated model performance with Synthetic Minority Oversampling Technique (SMOTE). We compared the following performance metrics: F1 score, area under the receiver operating characteristic curve (AUC), specificity, sensitivity, precision, recall, and Matthews correlation coefficient.Among 13,447 surgical procedures, the median total perioperative time (actual case duration and PACU length stay) was 165 minutes. When SMOTE was not used, when predicting whether surgery will end by 5 pm and patient will be discharged by 7 pm, the average F1 scores were best with random forest, balanced bagging, and balanced random forest classifiers. When SMOTE was used, these models had improved F1 scores compared to no SMOTE. The balanced bagging classifier performed best with F1 score of 0.78, 0.80, 0.82, and 0.82 when predicting our outcome if cases were to start at 1 pm, 2 pm, 3 pm, or 4 pm, respectively.We demonstrated improvement in predicting the outcome at a range of start times when using ensemble learning versus regression techniques. Machine learning may be adapted by operating room management to allow for a better determination whether an add-on case at an outpatient surgery center could be appropriately booked.

BACKGROUND Understanding the impact of key metrics on operating room (OR) efficiency is important to optimize utilization and reduce costs, particularly in freestanding ambulatory surgery centers. The aim of this study was to assess the association between commonly used efficiency metrics and scheduled end-time accuracy. METHODS Data from patients who underwent surgery from May 2018 to June 2019 at an academic freestanding ambulatory surgery center was extracted from the medical record. Unique operating room days (ORDs) were analyzed to determine (1) duration of first case delays, (2) turnover times (TOT), and (3) scheduled case duration accuracies. Spearman's correlation coefficients and mixed-effects multivariable linear regression were used to assess the association of each metric with scheduled end-time accuracy. RESULTS There were 1378 cases performed over 300 unique ORDs. There were 86 (28.7%) ORDs with a first case delay, mean (standard deviation [SD]) 11.2 minutes (15.1 minutes), range of 2-101 minutes; the overall mean (SD) TOT was 28.1 minutes (19.9 minutes), range of 6-83 minutes; there were 640 (46.4%) TOT >20 minutes; the overall mean (SD) case duration accuracy was -6.6 minutes (30.3 minutes), range of -114 to 176; and there were 389 (28.2%) case duration accuracies ≥30 minutes. The mean (SD) scheduled end-time accuracy was 6.9 minutes (68.3 minutes), range of -173 to 229 minutes; 48 (15.9%) ORDs ended ≥1 hour before scheduled end-time and 56 (18.6%) ORDs ended ≥1 hour after scheduled end-time. The total case duration accuracy was strongly correlated with the scheduled end-time accuracy (r = 0.87, 95% confidence interval [CI], 0.84-0.89, P < .0001), while the total first case delay minutes (r = 0.12, 95% CI, 0.01-0.21, P = .04) and total turnover time (r = -0.16, 95% CI, 0.21-0.05, P = .005) were less relevant. Case duration accuracy had the highest association with the dependent variable (0.95 minutes changed in the difference between actual and schedule end time per minute increase in case duration accuracy, 95% CI, 0.90-0.99, P < .0001), compared to turnover time (estimate = 0.87, 95% CI, 0.75-0.99, P < .0001) and first case delay time (estimate = 0.83, 95% CI, 0.56-1.11, P < .0001). CONCLUSIONS Standard efficiency metrics are similarly associated with scheduled end-time accuracy, and addressing problems in each is requisite to having an efficient ambulatory surgery center. Pursuing methods to narrow the gap between scheduled and actual case duration may result in a more productive enterprise.

BACKGROUND: A retrospective study was performed to evaluate factors associated with 30-d re-intubation following surgical aortic valve repair. We hypothesized a significant increase in the odds of re-intubation among patients with preoperative comorbidities. METHODS: The American College of Surgery National Surgical Quality Improvement Program database from 2007 to 2016 was used to evaluate demographic and clinical factors associated with 30-d re-intubation following surgical aortic valve repair. Multivariable logistic regression was used to report factors associated with 30-d re-intubation while controlling for various patient characteristics. RESULTS: The study population consisted of 5,766 adult subjects who underwent surgical aortic valve repair, of whom 258 (4.47%) were re-intubated within 30 d of surgery. The mean ± SD age was 69 ± 12.98 y, and 3,668 (63.6%) were male. The prevalence of diabetes mellitus, shortness of breath, poor functional status, COPD, congestive heart failure, hypertension, and bleeding disorder was higher among subjects who were re-intubated compared to those who were not (P < .05). Age, severe COPD, congestive heart failure, and bleeding disorder were associated with this outcome. CONCLUSIONS: Age, COPD, congestive heart failure, and bleeding disorder were associated with 30-d re-intubation in this surgical cohort. If surgical aortic valve repair is deemed non-emergent, patients should be optimized preoperatively and receive careful postoperative planning to reduce the risk of postoperative complications.

Limiting the spread of the disease is key to controlling the COVID-19 pandemic. This includes identifying people who have been exposed to COVID-19, minimizing patient contact, and enforcing strict hygiene measures. To prevent healthcare systems from becoming overburdened, elective and non-urgent medical procedures and treatments have been postponed, and primary health care has broadened to include virtual appointments via telemedicine. Although telemedicine precludes the physical examination of a patient, it allows collection of a range of information prior to a patient's admission, and may therefore be used in preoperative assessment. This new tool can be used to evaluate the severity and progression of the main disease, other comorbidities, and the urgency of the surgical treatment as well as preferencing anesthetic procedures. It can also be used for effective screening and triaging of patients with suspected or established COVID-19, thereby protecting other patients, clinicians and communities alike.

Background The basic perineural catheter design has changed minimally since inception, with the catheter introduced through or over a straight needle. The U.S. Food and Drug Administration recently cleared a novel perineural catheter design comprising a catheter attached to the back of a suture-shaped needle that is inserted, advanced along the arc of its curvature pulling the catheter past the target nerve, and then exited through the skin in a second location. The authors hypothesized that analgesia would be noninferior using the new versus traditional catheter design in the first two days after painful foot/ankle surgery with a primary outcome of average pain measured with the Numeric Rating Scale. Methods Subjects undergoing painful foot or ankle surgery with a continuous supraparaneural popliteal-sciatic nerve block 5 cm proximal to the bifurcation were randomized to either a suture-type or through-the-needle catheter and subsequent 3-day 0.2% ropivacaine infusion (basal 6 ml/h, bolus 4 ml, lockout 30 min). Subjects received daily follow-up for the first four days after surgery, including assessment for evidence of malfunction or dislodgement of the catheters. Results During the first two postoperative days the mean ± SD average pain scores were lower in subjects with the suture-catheter (n = 35) compared with the through-the-needle (n = 35) group (2.7 ± 2.4 vs. 3.4 ± 2.4) and found to be statistically noninferior (95% CI, −1.9 to 0.6; P < 0.001). No suture-style catheter was completely dislodged (0%), whereas the tips of three (9%) traditional catheters were found outside of the skin before purposeful removal on postoperative day 3 (P = 0.239). Conclusions Suture-type perineural catheters provided noninferior analgesia compared with traditional catheters for continuous popliteal-sciatic blocks after painful foot and ankle surgery. The new catheter design appears to be a viable alternative to traditional designs used for the past seven decades. Editor’s Perspective What We Already Know about This Topic What This Article Tells Us That Is New

AIM: Patients with synchronous colon cancer metastases have highly variable overall survival (OS), making accurate predictive models challenging to build. We aim to use machine learning to more accurately predict OS in these patients and to present this predictive model in the form of nomograms for patients and clinicians. METHODS: Using the National Cancer Database (2010-2014), we identified right colon (RC) and left colon (LC) cancer patients with synchronous metastases. Each primary site was split into training and testing datasets. Nomograms predicting 3-year overall survival were created for each site using Cox proportional hazard regression with lasso regression. Each model was evaluated by both calibration (comparison of predicted versus observed overall survival) and validation (degree of concordance as measured by c-index) methodologies. RESULTS: A total of 11,018 RC and 8,346 LC patients were used to construct and validate the nomograms. After stratifying each model into 5 risk groups, the predicted OS was within the 95% CI of the observed OS in 4 out of 5 risk groups for both the RC and LC models. Externally validated c-indexes at 3 years for RC and LC models were 0.794 and 0.761, respectively. CONCLUSIONS: Utilization of machine learning can result in more accurate predictive models for patients with metastatic colon cancer. Nomograms built from these models can assist clinicians and patients in the shared decision-making process of their cancer care.

Our primary objective is to provide the clinical informatics community with an introductory tutorial on calibration measurements and calibration models for predictive models using existing R packages and custom implemented code in R on real and simulated data. Clinical predictive model performance is commonly published based on discrimination measures, but use of models for individualized predictions requires adequate model calibration. This tutorial is intended for clinical researchers who want to evaluate predictive models in terms of their applicability to a particular population. It is also for informaticians and for software engineers who want to understand the role that calibration plays in the evaluation of a clinical predictive model, and to provide them with a solid starting point to consider incorporating calibration evaluation and calibration models in their work.Covered topics include (1) an introduction to the importance of calibration in the clinical setting, (2) an illustration of the distinct roles that discrimination and calibration play in the assessment of clinical predictive models, (3) a tutorial and demonstration of selected calibration measurements, (4) a tutorial and demonstration of selected calibration models, and (5) a brief discussion of limitations of these methods and practical suggestions on how to use them in practice.

BackgroundCryoneurolysis of peripheral nerves uses localised intense cold to induce a prolonged block over multiple weeks that has the promise of providing potent analgesia outlasting the duration of postoperative pain following surgery, as well as treat other acute and chronic pain states. However, it remains unclear whether persistent functional motor deficits remain following cryoneurolysis of mixed sensorimotor peripheral nerves, greatly limiting clinical application of this modality. To help inform future research, we used a rat peroneal nerve injury model to evaluate if cryoneurolysis results in persistent deficits in motor function.MethodsMale Lewis rats (n=30) had their common peroneal nerves exposed bilaterally at the proximal lateral margin of the knee and subsequently underwent cryoneurolysis on one limb and sham treatment on the contralateral limb. Outcomes were evaluated on days 3, 14, 30, 90 and 180. The primary end point was motor function, based on ankle dorsiflexion torque. In addition, sensory function was tested based on von Frey’s filament sensitivity to the peroneal sensory distribution. A subset of animals was sacrificed following functional testing at each time point, and general tissue morphology, connective tissue deposition, and axon counts were evaluated.ResultsMotor deficits in treated limbs were observed at 3 and 14 days but had resolved at time points beyond 1 month. Bilateral sensory deficits were also observed at 3 and 14 days, and also resolved within 1 month. Consistent with motor functional deficits, axon counts trended lower in treated nerves compared with contralateral controls at 3 days; however, axon counts were not significantly different at later time points.ConclusionsWhen applied to a mixed sensorimotor nerve, cryoneurolysis did not result in persistent motor deficits.

Objective Obesity is frequently debated as a factor associated with increased postoperative complications. Specifically, upper airway surgeries for obstructive sleep apnea (OSA), a common comorbidity among obese patients, may be complicated by obesity’s impact on intraoperative ventilation. The aim of this retrospective study was to analyze the association of various degrees of obesity with postoperative outcomes in patients undergoing surgery for OSA. Methods The American College of Surgeons National Surgical Quality Improvement database between 2015 and 2019 was used to create a sample of patients diagnosed with OSA who underwent uvulopalatopharyngoplasty, tracheotomy, and surgeries at the base of tongue, maxilla, palate, or nose/turbinate. Inverse probability-weighted logistic regression and unadjusted multivariable logistic regression were used to compare outcomes of non-obese and obesity class 1, class 2, and class 3 groups (World Health Organization classification). Primary outcome was a composite of 30-day readmissions, reoperations, and/or postoperative complications, and a secondary outcome was all-cause same-day hospital admission. Results There were 1929 airway surgeries identified. The inverse probability-weighted regression comparing class 1, class 2, and class 3 obesity groups to non-obese patients showed no association between obesity and composite outcome and no association between obesity and hospital admission (all p-values > 0.05). Conclusion These results do not provide evidence that obesity is associated with poorer outcomes or hospital admission surrounding upper airway surgery for OSA. While these data points towards the safety of upper airway surgery in obese patients with OSA, larger prospective studies will aid in elucidating the impact of obesity.

The rise in obesity in the United States, along with improvements in antiviral therapies, has led to an increase in the number of obese patients receiving liver transplants. Currently, obesity is a relative contraindication for liver transplant, although exact body mass index (BMI) limits continue to be debated. Studies conflict regarding outcomes in obese patients, while some argue that BMI should not be used as an exclusion criterion at all. Therefore, this retrospective study-utilizing a large national database-seeks to elucidate the association between recipient BMI and hospital length of stay and mortality following liver transplant.A retrospective study was conducted using the United Network for Organ Sharing Standard Transplant Analysis and Research database. Fine-Gray competing risk regressions were used to explore the association between BMI and rate of discharge, which varies inversely with length of stay. In our model, subdistribution hazard ratio (SHR) represented the relative change in discharge rate compared to normal BMI, with in-hospital death was considered as a competing event for live discharge. Cox proportional hazard models were built to assess the association of BMI category on all-cause mortality after liver transplantation. Cluster-robust standard errors were used in all analyses to construct confidence intervals.Within the final sample (n = 47,038), overweight (≥25 and30 kg/m2) patients comprised the largest BMI group (34.7%). The competing risk regression model showed an association for increased length of stay among underweight (SHR = 0.82, 95% confidence interval [CI], 0.77-0.89; P.001) and class 3 obesity patients (SHR = 0.88, 95% CI, 0.83-0.94; P.001), while overweight (SHR = 1.05, 95% CI, 1.03-1.08; P.001) and class 1 obesity (SHR = 1.04, 95% CI, 1.01-1.07; P = .01) were associated with decreased length of stay. When the sample excluded patients with low pretransplant functional status, however, length of stay was not significantly shorter for overweight and obesity class 1 patients. Cox proportional hazard models demonstrated increased survival among overweight, class 1 and class 2 obesity patients and decreased survival among underweight patients.Our results provide evidence that overweight and obesity class 1 are associated with decreased length of stay and mortality following liver transplant, while underweight and obesity class 3 are associated with prolonged length of stay. Pretransplant functional status may contribute to outcomes for overweight and class 1 obese patients, which necessitates continued investigation of the isolated impact of BMI in those who have had a liver transplant.

Background Expansion of clinical guidance tools is crucial to identify patients at risk of requiring an opioid refill after outpatient surgery. Objective The objective of this study was to develop machine learning algorithms incorporating pain and opioid features to predict the need for outpatient opioid refills following ambulatory surgery. Methods Neural networks, regression, random forest, and a support vector machine were used to evaluate the data set. For each model, oversampling and undersampling techniques were implemented to balance the data set. Hyperparameter tuning based on k-fold cross-validation was performed, and feature importance was ranked based on a Shapley Additive Explanations (SHAP) explainer model. To assess performance, we calculated the average area under the receiver operating characteristics curve (AUC), F1-score, sensitivity, and specificity for each model. Results There were 1333 patients, of whom 144 (10.8%) refilled their opioid prescription within 2 weeks after outpatient surgery. The average AUC calculated from k-fold cross-validation was 0.71 for the neural network model. When the model was validated on the test set, the AUC was 0.75. The features with the highest impact on model output were performance of a regional nerve block, postanesthesia care unit maximum pain score, postanesthesia care unit median pain score, active smoking history, and total perioperative opioid consumption. Conclusions Applying machine learning algorithms allows providers to better predict outcomes that require specialized health care resources such as transitional pain clinics. This model can aid as a clinical decision support for early identification of at-risk patients who may benefit from transitional pain clinic care perioperatively in ambulatory surgery.

Introduction: This study is a retrospective cohort analysis that describes key clinical outcomes in elderly individuals who undergo outpatient surgical procedures. In particular, we report same-day admission, 30-day mortality, 30-day complications, and 30-day readmission rates for three separate age groups undergoing frequent outpatient, general surgical procedures. Methods: Patients ≥18 years old who underwent the 10 most common outpatient surgical procedures in the National Surgical Quality Improvement Program database from 2017 to 2019 and who underwent general anesthesia were included in the study. The primary outcome of interest was hospital admission, defined as hospital length of stay >0 days. Secondary outcomes of interest included 30-day readmission, 30-day mortality, and 30-day postoperative complications. The primary exposure variable of interest was age, which was divided into

Background Racial and ethnic differences in the use of neuraxial anesthesia compared with general anesthesia are less studied, particularly in obstetrical anesthesia. Here, we aimed to provide an update on the association between race and ethnicity, and the use of neuraxial anesthesia for cesarean delivery in the United States (US). Methods We used the American College of Surgeons National Surgical Quality Improvement Program (ACS NSQIP) Participant Use Data File 2019. We extracted cases that had a primary surgery defined with Current Procedural Terminology (CPT) code for cesarean delivery (59510, 59514, and 59515) and cesarean after attempted vaginal delivery in parturients with a prior history of cesarean (59618, 59620, and 59622). Multivariable logistic regression was used to report the association of race and ethnicity with primary anesthetic technique. Results There were 12,876 parturients included in the study. Compared with White parturients, Black (adjusted odds ratio (aOR) = 0.71, 95% confidence interval (CI): 0.57-0.88, p = 0.001) and American Indian or Alaska Native (aOR = 0.22, 95% CI: 0.12-0.40, p < 0.001) parturients had lower odds of receiving neuraxial compared with general anesthesia. There were no significant differences in the odds of neuraxial anesthesia between non-Hispanic and Hispanic cohorts. Conclusions While we do observe racial differences in anesthetic technique, Hispanic patients did not have significantly lower odds of neuraxial anesthesia. This study highlights the importance of an update to prior studies, as the current study suggests a lack of disparity between non-Hispanic and Hispanic parturients. While the results here are encouraging, a multidisciplinary approach is necessary to further address racial disparities.

In 2019, a novel coronavirus called the severe acute respiratory syndrome coronavirus 2 led to the outbreak of the coronavirus disease 2019, which was deemed a pandemic by the World Health Organization in March 2020. Owing to the accelerated rate of mortality and utilization of hospital resources, health care systems had to adapt to these major changes. This affected patient care across all disciplines and specifically within the perioperative services. In this review, we discuss the strategies and pitfalls of how perioperative services in a large academic medical center responded to the initial onset of a pandemic, adjustments made to airway management and anesthesia specialty services - including critical care medicine, obstetric anesthesiology, and cardiac anesthesiology - and strategies for reopening surgical caseload during the pandemic.

BackgroundParavertebral and serratus plane blocks are both used to treat pain following breast surgery. However, it remains unknown if the newer serratus block provides comparable analgesia to the decades-old paravertebral technique.MethodsSubjects undergoing unilateral or bilateral non-mastectomy breast surgery were randomized to a single-injection serratus or paravertebral block in a subject-masked fashion (ropivacaine 0.5%; 20 mL unilateral; 16 mL/side bilateral). We hypothesized that (1) analgesia would be non-inferior in the recovery room with serratus blocks (measurement: Numeric Rating Scale), and (2) opioid consumption would be non-inferior with serratus blocks in the operating and recovery rooms. In order to claim that serratus blocks are non-inferior to paravertebral blocks, both hypotheses must be at least non-inferior.ResultsWithin the recovery room, pain scores for participants with serratus blocks (n=49) had a median (IQR) of 4.0 (0–5.5) vs 0 (0–3.0) for those with paravertebral blocks (n=51): 0.95% CI −3.00 to −0.00; p=0.001. However, the difference in morphine equivalents did not reach statistical significance for superiority with the serratus group consuming 14 mg (10–19) vs 10 mg (10–16) for the paravertebral group: 95% CI −4.50 to 0.00, p=0.123. Since the 95% CI lower limit of −4.5 was less than our prespecified margin of −2.0, we failed to conclude non-inferiority of the serratus block with regard to opioid consumption.ConclusionsSerratus blocks provided inferior analgesia compared with paravertebral blocks. Without a dramatic improvement in safety profile for serratus blocks, it appears that paravertebral blocks are superior to serratus blocks for postoperative analgesia after non-mastectomy breast surgery.Trial registration numberNCT03860974.

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has infected over 1.5 million individuals and led to over 91, 000 deaths in the United States (US) alone as of May 20th, 2020. Minority populations, however, continue to be a high-risk population to contract the SARS-CoV-2 infection. While socioeconomic inequality may help to explain why minority ethnic populations are contracting the SARS-CoV-2 in larger proportions, the reason for elevated mortality rates in African Americans is still unknown. African Americans are less likely than whites to utilize high-quality hospitals, ambulatory care services, and regular primary care providers; this is most likely a result of barriers to accessing high quality treatment, as African Americans have substantially higher uninsured rates. However, previous reports have shown that regardless of insurance status, African Americans are more likely to be directed toward lower quality treatment plans compared to their white counterparts, and that physicians carry implicit biases that negatively impact treatment regimens for these minority populations. While income, education, and access to healthcare should be revised in due time, in the short term physicians should do everything possible to learn about implicit biases that may exist in healthcare, as the first step to minimize implicit biases is to recognize that they exist.

Autologous skin grafting from the thigh is frequently required for treatment of burns and is associated with intense pain at the donor site. Local anesthetic–based (LA) nerve blocks of the lateral femoral cutaneous nerve (LFCN) have been demonstrated to provide analgesia when the graft is taken from the lateral thigh. However, the duration of these single injection blocks has been reported to average only 9 hours, whereas the pain from the procedure lasts days or weeks. Continuous LA nerve blocks can also be used to provide analgesia during serial debridement of burns, although this requires placement of a perineural catheter which may increase infection risk in a population with an increased susceptibility to infection. Cryoneurolysis of the LFCN can potentially provide analgesia of the lateral thigh for skin graft harvesting or serial burn debridement that lasts far longer than conventional LA nerve blocks. Here, we present a series of three patients who received a combination of a LA nerve block and cryoneurolysis nerve block of the LFCN for analgesia of the lateral thigh. Two of these patients had the blocks placed before harvesting a split thickness skin graft. The third received the blocks for outpatient wound care of a burn to the lateral thigh. In all cases, the resulting analgesia lasted more than 1 week. A single cryoneurolysis block of the LFCN successfully provided extended duration analgesia of the lateral thigh for autologous skin graft donor site or wound care of a burn in three patients.

Author(s): Finneran Iv, John J; Gabriel, Rodney A; Swisher, Matthew W; Berndtson, Allison E; Godat, Laura N; Costantini, Todd W; Ilfeld, Brian M | Abstract: BackgruondRib fractures are a common injury in trauma patients and account for significant morbidity and mortality within this population. Local anesthetic-based nerve blocks have been demonstrated to provide significant pain relief and reduce complications. However, the analgesia provided by these blocks is limited to hours for single injection blocks or days for continuous infusions, while the duration of this pain often lasts weeks.CaseThis case series describes five patients with rib fractures whose pain was successfully treated with cryoneurolysis.ConclusionsUltrasound-guided percutaneous cryoneurolysis is a modality that has the potential to provide analgesia matching the duration of pain following rib fractures.