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 obesitys 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.

Background Severe cases of carpal tunnel syndrome (CTS) are treated with surgical decompression, for which regional nerve blocks are often administered. There is little data about complications associated with these regional techniques for this surgery. The primary objective was to assess the association of ultrasound-guided regional anesthesia nerve blocks in patients undergoing carpal tunnel release with symptom resolution. Methods This single-institution, retrospective study analyzed all patients undergoing open carpal tunnel release from March 2018 to November 2020. Primary exposure was either regional anesthesia (median and ulnar nerve blocks) or non-regional anesthesia (general anesthesia or local infiltration by surgeon). The primary outcome measurement was symptom resolution at postoperative follow-up at 30-60 days. Secondary outcomes were postoperative surgical site infection, time in operating room (minutes), and post-anesthesia care unit (PACU) length of stay (min). The primary outcome was analyzed using multivariable logistic regression. Results A total of 417 patients were included in this study. Of these, 269 (64.5%) subjects received regional anesthesia as their primary anesthetic. When adjusting for confounders, the use of regional anesthesia was not associated with symptoms not improving at postoperative visit (OR 0.52, 95% CI 0.22 - 1.26, P = 0.15), postoperative surgical site infection (OR 1.47, 95% CI 0.44 - 4.85, p = 0.53), or operating room time duration (p = 0.09). However, the use of regional anesthesia was associated with an approximately 15-minute decrease in PACU length of stay (p < 0.001). Conclusions Regional anesthesia is a safe, effective, and time-efficient method for anesthesia in patients undergoing open carpal tunnel release.

Background and objective A high rate of preoperative anemia has been observed in patients undergoing knee and hip arthroplasty. The type of anesthesia that patients receive may play a role in preventing or minimizing adverse outcomes in these patients. In this study, we aimed to examine the complication rates in patients with severe anemia undergoing this surgery. In addition, we explore whether neuraxial anesthesia is associated with better outcomes compared to general anesthesia. Methods The American College of Surgeons National Surgical Quality Improvement Program (ACS NSQIP) registry was used to extract data related to patients who underwent total hip or knee arthroplasty from 2014 to 2016. Only those patients with a hematocrit level <30% were included, and they were classified into two groups based on primary anesthesia type received: neuraxial versus general anesthesia. The primary outcome of interest was postoperative transfusion. Secondary outcomes included 30-day hospital readmission and postoperative complications. Multivariable logistic regression was used to model primary anesthesia type to outcomes while controlling for various confounders. The odds ratio (OR) and their 95% confidence intervals (CI) were reported. Results There were 1,723 patients with severe anemia included in our analysis, of which 41.2% received neuraxial anesthesia. Among patients that received neuraxial versus general anesthesia, 170 (31.08%) and 486 (41.33%), respectively, received a postoperative blood transfusion (p<0.001). On multivariable regression analysis, neuraxial anesthesia was associated with 40% decreased odds of postoperative transfusion (OR: 0.63, 95% CI: 0.51-0.79, p<0.0001), but it was not associated with any other outcomes. Conclusion Neuraxial anesthesia can reduce the risk of postoperative transfusion in severely anemic patients undergoing total joint arthroplasty (TJA), ultimately leading to reduced discomfort, hospital expenditure, and adverse outcomes.

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.

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.