The deimplementation of laboratory testing in low-risk patients as recommended by the American society of anesthesiologists: An ACS-NSQIP longitudinal analysis.

BACKGROUND: In 2012, the American Society of Anesthesiologists (ASA) published guidelines recommending against routine preoperative laboratory testing for low-risk patients to reduce unnecessary medical expenditures. The aim of this study was to assess the change in routine preoperative laboratory testing in low-risk versus higher-risk patients before and after release of these guidelines. METHODS: The ACS-NSQIP database, 2005-2018, was separated into low-risk versus higher-risk patients based upon a previously published stratification. The guideline implementation date was defined as January 2013. Changes in preoperative laboratory testing over time were compared between low- and higher-risk patients. A difference-in-differences model was applied. The primary outcome included any laboratory test obtained ≤90 days prior to surgery. RESULTS: Of 7,507,991 patients, 972,431 (13.0%) were defined as low-risk and 6,535,560 (87.0%) higher-risk. Use of any preoperative laboratory test declined in low-risk patients from 66.5% before to 59.6% after guidelines, a 6.9 percentage point reduction, versus 93.0%-91.9% in higher-risk patients, a 1.1 percentage point reduction (p < 0.0001, comparing percentage point reductions). After risk-adjustment, the adjusted odds ratio for having any preoperative laboratory test after versus before the guidelines was 0.77 (95% CI 0.76-0.78) in low-risk versus 0.93 (0.92-0.94) in higher-risk patients. In low-risk patients, lack of any preoperative testing was not associated with worse outcomes. CONCLUSIONS: While a majority of low-risk patients continue to receive preoperative laboratory testing not recommended by the ASA, there has been a decline after implementation of guidelines. Continued effort should be directed at the deimplementation of routine preoperative laboratory testing for low-risk patients.

Anatomic Lung Resection Outcomes After Implementation of a Universal Thoracic ERAS Protocol Across a Diverse Health Care System.

OBJECTIVE: We sought to evaluate how implementing a thoracic enhanced recovery after surgery (ERAS) protocol impacted surgical outcomes after elective anatomic lung resection. BACKGROUND: The effect of implementing the ERAS Society/European Society of Thoracic Surgery thoracic ERAS protocol on postoperative outcomes throughout an entire health care system has not yet been reported. METHODS: This was a prospective cohort study within one health care system (January 2019-March, 2023). A thoracic ERAS protocol was implemented on May 1, 2021 for elective anatomic lung resections, and postoperative outcomes were tracked using the electronic health record and Vizient data. The primary outcome was overall morbidity; secondary outcomes included individual complications, length of stay, opioid use, chest tube duration, and total cost. Patients were grouped into pre-ERAS and post-ERAS cohorts. Bivariable comparisons were performed using independent t -test, χ 2 , or Fisher exact tests, and multivariable logistic regression was performed to control for confounders. RESULTS: There were 1007 patients in the cohort; 450 (44.7%) were in the post-ERAS group. Mean age was 66.2 years; most patients were female (65.1%), white (83.8%), had a body mass index between 18.5 and 29.9 (69.7%), and were ASA class 3 (80.6%). Patients in the postimplementation group had lower risk-adjusted rates of any morbidity, respiratory complication, pneumonia, surgical site infection, arrhythmias, infections, opioid usage, ICU use, and shorter postoperative length of stay (all P <0.05). CONCLUSIONS: Postoperative outcomes were improved after the implementation of an evidence-based thoracic ERAS protocol throughout the health care system. This study validates the ERAS Society/European Society of Thoracic Surgery guidelines and demonstrates that simultaneous multihospital implementation can be feasible and effective.

The Effect of Social Vulnerability on Initial Stage and Treatment for Non-Small Cell Lung Cancer.

OBJECTIVE: The Social Vulnerability Index (SVI) is a composite metric for social determinants of health. The objective of this study was to determine if SVI influences stage at presentation for non-small cell lung cancer (NSCLC) patients and subsequent therapies. MATERIALS AND METHODS: NSCLC patients from our local contribution to the National Cancer Database (2011-2021) were grouped into low SVI (<75 %ile) and high SVI (>75 %ile) cohorts. Demographics, cancer-related variables, and treatment modalities were compared. Multivariable logistic regression was performed to control for the impact of demographics on cancer presentation and for the impact of oncologic variables on treatment outcomes. RESULTS: Of 1,662 NSCLC patients, 435 (26 %) were defined as high SVI. Compared to the 1,227 (74 %) low SVI patients, highly vulnerable patients were more likely to be male (53.3 % vs 46.0 %, p = 0.009), non-White (17.2 % vs 9.7 %, p < 0.0001), have comorbidities (29.4 % vs 23.1 %, p = 0.009) and present at a higher AJCC clinical T, M and overall stage (all p < 0.05). These findings persisted on multivariable analysis, with highly vulnerable patients having 1.5x the odds (95 %CI: 1.23-1.86, p < 0.001) of presenting at more advanced stage. Patients with high SVI were less likely to be recommended for and receive surgery (40.9 % vs 53.2 %, p < 0.001), and this finding persisted after controlling for stage at presentation (OR 1.37, 95 %CI 1.04-1.80). CONCLUSIONS: Highly vulnerable patients present at a more advanced clinical stage and are less likely to be recommended and receive surgery, even after controlling for stage at presentation. Further investigation into these findings is warranted to achieve more equitable oncologic care.

Social vulnerability is associated with higher risk-adjusted rates of postoperative complications in a broad surgical population.

OBJECTIVE: The purpose of this study was to determine if an association between Social Vulnerability Index (SVI) and risk-adjusted complications exists in a broad spectrum of surgical patients. SUMMARY BACKGROUND DATA: Growing evidence supports the impact of social circumstances on surgical outcomes. SVI is a neighborhood-based measure accounting for sociodemographic factors putting communities at risk. METHODS: This was a multi-hospital, retrospective cohort study including a sample of patients within one healthcare system (2012-2017). Patient addresses were geocoded to determine census tract of residence and estimate SVI. Patients were grouped into low SVI (score<75) and high SVI (score≥75) cohorts. Perioperative variables and postoperative outcomes were tracked and compared using local ACS-NSQIP data. Multivariable logistic regression was performed to generate risk-adjusted odds ratios of postoperative complications in the high SVI cohort. RESULTS: Overall, 31,224 patients from five hospitals were included. Patients with high SVI were more likely to be racial minorities, have 12/18 medical comorbidities, have high ASA class, be functionally dependent, be treated at academic hospitals, and undergo emergency operations (all p â€‹< â€‹0.05). Patients with high SVI had significantly higher rates of 30-day mortality, overall morbidity, respiratory, cardiac and infectious complications, urinary tract infections, postoperative bleeding, non-home discharge, and unplanned readmissions (all p â€‹< â€‹0.05). After risk-adjustment, only the associations between high SVI and mortality and unplanned readmission became non-significant. CONCLUSIONS: High SVI was associated with multiple adverse outcomes even after risk adjustment for preoperative clinical factors. Targeted preventative interventions to mitigate risk of these specific complications should be considered in this high-risk population.

The United States experience with diagnosing and treating esophageal cancer during the SARS-CoV-2 pandemic: A retrospective cohort study.

The downstream effects on healthcare delivery during the initial wave of the COVID-19 pandemic remain unclear. The purpose of this study was to determine how the healthcare environment surrounding the pandemic affected the oncologic care of patients diagnosed with esophageal cancer. This was a retrospective cohort study evaluating patients in the National Cancer Database (2019-2020). Patients with esophageal cancer diagnoses were divided into pre-pandemic (2019) and pandemic (2020) groups. Patient demographics, cancer-related variables, and treatment modalities were compared. Among 26,231 esophageal cancer patients, 14,024 patients (53.5%) were in the pre-pandemic cohort and 12,207 (46.5%) were in the pandemic cohort. After controlling for demographics, patients diagnosed during the pandemic were more likely to have poorly differentiated tumors (odds ratio [OR] 1.24, 95% confidence interval [CI] 1.08-1.42), pathologic T3 disease compared to T1 (OR 1.25, 95% CI 1.02-1.53), positive lymph nodes on pathology (OR 1.36, 95% CI 1.14-1.64), and to be pathologic stage IV (OR 1.51, 95% CI 1.29-1.76). After controlling for oncologic characteristics, patients diagnosed during the pandemic were more likely to require at least two courses of systemic therapy (OR 1.78, 95% CI 1.48-2.14) and to be offered palliative care (OR 1.13, 95% CI 1.04-1.22). While these patients were offered curative therapy at lower rates, this became non-significant after risk-adjustment (p = .15). The pandemic healthcare environment was associated with significantly increased risk-adjusted rates of patients presenting with advanced esophageal cancer. While this led to significant differences in treatment, most of these differences became non-significant after controlling for oncologic factors.

National trends in technique use for esophagectomy: Does primary surgeon specialty matter?

BACKGROUND: Cardiothoracic surgeons and general surgeons (including surgical oncologists) perform most esophagectomies. The purpose of this study was to explore whether specialty-driven differences in surgical techniques and the use of minimally invasive surgical approaches exist and are associated with postoperative outcomes after esophagectomy. METHODS: This was a retrospective review of the American College of Surgeons National Surgical Quality Improvement Program esophagectomy-targeted participant user file (2016-2018). Patients who underwent esophagectomy were sorted into cardiothoracic and general surgeon cohorts based on surgeon specialty. Perioperative characteristics and postoperative outcomes were compared using the χ2 analysis or independent t test. Multivariable logistic regression controlling for perioperative variables was performed to generate risk-adjusted rates of postoperative outcomes compared by surgical specialty. RESULTS: Of 3,247 patients included, 1,792 (55.2%) underwent esophagectomy by cardiothoracic surgeons and 1,455 (44.5%) by general surgeons as the primary surgeon. Cardiothoracic surgeons were more likely to use traditional minimally invasive surgical (P = .0004) or open approaches (P < .0001) and less likely to use robotic (P = .04) or a hybrid robotic and traditional approaches (P < .0001). Cardiothoracic surgeons performed more Ivor Lewis esophagectomies and fewer transhiatal and McKeown esophagectomies (P < .0001). After risk adjustment, there were no differences in rates of postesophagectomy complications, such as anastomotic leaks or positive margins, between cardiothoracic surgeons and general surgeons (all P > .05). However, cardiothoracic surgeons were more likely than general surgeons to treat anastomotic leaks with surgery rather than procedural interventions (odds ratio = 1.76; 95% confidence interval, 1.24-2.52). CONCLUSION: Cardiothoracic surgeons and general surgeons use minimally invasive surgical subtypes differently when performing esophagectomy. However, there were no risk-adjusted differences in postoperative complications when compared by surgical subspecialty. Esophagectomy is being performed safely by surgeons with different specialties and training pathways.

Analyzing the impact of the Coronavirus disease 2019 pandemic on initial oncologic presentation and treatment of non-small cell lung cancer in the United States.

BACKGROUND: A significantly lower rate of non-small cell lung cancer (NSCLC) screening, greater healthcare avoidance, and changes to oncologic recommendations were some consequences of the Coronavirus disease 2019 (COVID-19) pandemic affecting the medical environment. We sought to determine how the healthcare environment during the COVID-19 pandemic affected the oncologic treatment of patients diagnosed with non-small cell lung cancer (NSCLC). METHODS: This was a retrospective cohort study evaluating patients with NSCLC in the National Cancer Database (2019-2020). Patients were divided into prepandemic (2019) and pandemic (2020) cohorts, and patient, oncologic, and treatment variables were compared. Multivariable logistic regression was performed to control for the impact of demographic characteristics on oncologic variables and the impact of oncologic variables on treatment variables. RESULTS: The study population comprised 250,791 patients, including 114,533 patients (45.7%) in the pandemic cohort. There were 15% fewer new NSCLC diagnoses during the pandemic compared with prepandemic. Patients diagnosed during the pandemic had more advanced clinical TNM stage on presentation (P < .0001) and were more likely to have tumors in overlapping lobes or in a main bronchus (P = .0002). They were less likely to receive cancer treatment (P < .0001) and to undergo primary resection (P < .0001) and more likely to receive adjuvant systemic therapy (P = .004) and a combination of palliative treatment regimens (P < .0001). After risk adjustment, all these differences remained statistically significant (P < .05). CONCLUSIONS: The COVID-19 pandemic was associated with increased clinical stage at presentation for patients with NSCLC, which impacted subsequent treatment strategies. However, treatment differed minimally when controlling for cancer stage. Future studies will examine the impact of these differences on overall survival and cancer-free survival.

Perioperative hypothermia in robotic-assisted thoracic surgery: Incidence, risk factors, and associations with postoperative outcomes.

OBJECTIVE: Inadvertent perioperative hypothermia has been associated with poor surgical outcomes. The purpose of this study was to evaluate the incidence and associated postoperative complications of inadvertent perioperative hypothermia in patients undergoing robotic-assisted thoracic surgery lung resections. METHODS: This was a single-center, retrospective cohort study evaluating all consecutive patients who underwent robotic-assisted thoracic surgery lung resection between January 1, 2021, and November 30, 2022. Temperatures were measured at 5 time points: preprocedure unit, anesthesia induction, 30 minutes postinduction, extubation, and recovery room arrival. Temperature changes were calculated at each interval. Adjusted and unadjusted comparison was performed between those who experienced varying levels of inadvertent perioperative hypothermia (Hypothermia I: <36 °C, Hypothermia II: <35.5 °C, and Hypothermia III: <35 °C) and those who did not. RESULTS: A total of 313 patients were included, and 201 (64.2%) lobectomies, 50 (16.0%) segmentectomies, and 62 (19.8%) wedge resections were performed. Across all patients, 291 (93.0%) had a temperature less than 36 °C, 195 (62.3%) had a temperature less than 35.5 °C, and 100 (31.9%) had a temperature less than 35.0 °C. Patients experienced significant temperature change at all intervals (P < .001), with the greatest loss occurring during the preprocedure interval (between leaving preprocedure unit and anesthesia induction). On adjusted analysis, patients who experienced inadvertent perioperative hypothermia less than 35.5 °C were older (odds ratio, 1.03; 95% CI, 1.01-1.05), had lower body mass index (odds ratio, 0.95; 95% CI, 0.87-0.98), and had increasing operative time (odds ratio, 1.00; 95% CI, 1.00-1.01). Patients who experienced inadvertent perioperative hypothermia had higher risk-adjusted rates of overall morbidity and infectious postoperative complications. CONCLUSIONS: The majority of patients undergoing robotic-assisted thoracic surgery lung resections experience some degree of inadvertent perioperative hypothermia and have associated increased rates of 30-day morbidity. Structured and interval-specific interventions should be implemented to decrease rates of inadvertent perioperative hypothermia and subsequent complications.

Emergency thoracic surgery patients have worse risk-adjusted outcomes than non-emergency patients.

BACKGROUND: Outcomes for patients undergoing emergency thoracic operations have not been well described. This study was designed to compare postoperative outcomes among patients undergoing emergency versus nonemergency thoracic operations. METHODS: We retrospectively analyzed the American College of Surgeons National Surgical Quality Improvement Program database (2005-2018). We identified patients who underwent emergency thoracic operations using current procedural technology codes. Patients were then sorted into 1 of 4 cohorts: lung and chest wall, hiatal hernia, esophagus, and pericardium. Emergency versus nonemergency outcomes were compared. Univariate logistic regression was performed with "emergency status" as the independent variable and 30-day postoperative outcomes as the dependent variables. Multiple logistic regression models were performed to control for preoperative factors. RESULTS: Of 90,398 thoracic operations analyzed, 4,044 (4.5%) were emergency. Common emergency operations were pericardial window (n = 580, 10.2%), laparoscopic hiatal hernia repair (n = 366, 8.9%), thoracoscopic partial lung decortication (n = 334, 8.1%), thoracoscopic wedge resection (n = 301, 7.3%), thoracoscopic total lung decortication (n = 256, 6.2%), and open repair of hiatal hernia without mesh (n = 254, 6.2%). In all 4 cohorts, 30-day postoperative complications occurred more frequently after emergency surgery. After controlling for patient characteristics, 8 complications were more frequent after emergency lung and chest wall surgery, 5 complications were more frequent after emergency hiatal hernia surgery, and 3 complications were more frequent after emergency pericardium surgery. Risk-adjusted complications were not different after emergency esophageal surgery. CONCLUSION: Patients undergoing emergency thoracic operations have worse risk-adjusted outcomes than those undergoing nonemergency thoracic operations. Subset analysis is needed to determine what factors contribute to increased adverse outcomes in specific patient populations.

Preoperative risk factors and postoperative complications associated with mortality after outpatient surgery in a broad surgical population: an analysis of 2.8 million ACS-NSQIP patients.

BACKGROUND: Thirty-day mortality after outpatient surgery is unexpected and undesired. We investigated preoperative risk factors, operative variables, and postoperative complications associated with 30-day death after outpatient surgery. METHODS: Using the 2005 to 2018 American College of Surgeons National Surgical Quality Improvement Program database, we evaluated 30-day mortality rate trends over time after outpatient operations. We analyzed associations between 37 preoperative variables, operation time, hospital length of stay, and 9 postoperative complications with mortality rate using χ2 analyses for categorical data and tests for continuous data. We used forward selection logistic regression models to determine the best predictors of mortality preoperatively and postoperatively. We also separately analyzed mortality by age group. RESULTS: A total of 2,822,789 patients were included. The 30-day mortality rate did not change significantly over time (P = .34, Cochran-Armitage trend test), remaining steady at around 0.06%. The most significant preoperative predictors of mortality included the patient having disseminated cancer, decreased functional health status, increased American Society of Anesthesiology Physical Status classification, increased age, and ascites, accounting for 95.8% (0.837/0.874) of the full model c-index. The most significant postoperative complications associated with increased risk of mortality included having cardiac (26.95% yes vs 0.04% no), pulmonary (10.25% vs 0.04%), stroke (9.22% vs 0.06%), and renal (9.33% vs 0.06%) complications. Postoperative complications conferred a greater risk for mortality than preoperative variables. Mortality risk increased incrementally with age, particularly past age 80. CONCLUSION: The operative mortality rate after outpatient surgery has not changed over time. Patients over 80 years with disseminated cancer, decreased functional health status, or increased ASA class should generally be considered for inpatient surgery. However, there might be some circumstances where outpatient surgery could be considered.

Development and validation of a multivariable preoperative prediction model for postoperative length of stay in a broad inpatient surgical population.

BACKGROUND: Postoperative length of stay is a meaningful patient-centered outcome and an important determinant of healthcare costs. The Surgical Risk Preoperative Assessment System preoperatively predicts 12 postoperative adverse events using 8 preoperative variables, but its ability to predict postoperative length of stay has not been assessed. We aimed to determine whether the Surgical Risk Preoperative Assessment System variables could accurately predict postoperative length of stay up to 30 days in a broad inpatient surgical population. METHODS: This was a retrospective analysis of the American College of Surgeons' National Surgical Quality Improvement Program adult database from 2012 to 2018. A model using the Surgical Risk Preoperative Assessment System variables and a 28-variable "full" model, incorporating all available American College of Surgeons' National Surgical Quality Improvement Program preoperative nonlaboratory variables, were fit to the analytical cohort (2012-2018) using multiple linear regression and compared using model performance metrics. Internal chronological validation of the Surgical Risk Preoperative Assessment System model was conducted using training (2012-2017) and test (2018) datasets. RESULTS: We analyzed 3,295,028 procedures. The adjusted R2 for the Surgical Risk Preoperative Assessment System model fit to this cohort was 93.3% of that for the full model (0.347 vs 0.372). In the internal chronological validation of the Surgical Risk Preoperative Assessment System model, the adjusted R2 for the test dataset was 97.1% of that for the training dataset (0.3389 vs 0.3489). CONCLUSION: The parsimonious Surgical Risk Preoperative Assessment System model can preoperatively predict postoperative length of stay up to 30 days for inpatient surgical procedures almost as accurately as a model using all 28 American College of Surgeons' National Surgical Quality Improvement Program preoperative nonlaboratory variables and has shown acceptable internal chronological validation.

A comparison of the National Surgical Quality Improvement Program and the Society of Thoracic Surgery Cardiac Surgery preoperative risk models: a cohort study.

BACKGROUND: Cardiac surgery prediction models and outcomes from the American College of Surgeons National Surgical Quality Improvement Program (ACS-NSQIP) have not been reported. The authors sought to develop preoperative prediction models and estimates of postoperative outcomes for cardiac surgery using the ACS-NSQIP and compare these to the Society of Thoracic Surgeons Adult Cardiac Surgery Database (STS-ACSD). METHODS: In a retrospective analysis of the ACS-NSQIP data (2007-2018), cardiac operations were identified using cardiac surgeon primary specialty and sorted into cohorts of coronary artery bypass grafting (CABG) only, valve surgery only, and valve+CABG operations using CPT codes. Prediction models were created using backward selection of the 28 non-laboratory preoperative variables in ACS-NSQIP. Rates of nine postoperative outcomes and performance statistics of these models were compared to published STS 2018 data. RESULTS: Of 28 912 cardiac surgery patients, 18 139 (62.8%) were CABG only, 7872 (27.2%) were valve only, and 2901 (10.0%) were valve+CABG. Most outcome rates were similar between the ACS-NSQIP and STS-ACSD, except for lower rates of prolonged ventilation and composite morbidity and higher reoperation rates in ACS-NSQIP (all P <0.0001). For all 27 comparisons (9 outcomes × 3 operation groups), the c-indices for the ACS-NSQIP models were lower by an average of ~0.05 than the reported STS models. CONCLUSIONS: The ACS-NSQIP preoperative risk models for cardiac surgery were almost as accurate as the STS-ACSD models. Slight differences in c-indexes could be due to more predictor variables in STS-ACSD models or the use of more disease- and operation-specific risk variables in the STS-ACSD models.

The association between obesity and postoperative outcomes in a broad surgical population: A 7-year American College of Surgeons National Surgical Quality Improvement analysis.

BACKGROUND: The number of obese surgical patients continues to grow, and yet obesity's association with surgical outcomes is not totally clear. This study examined the association between obesity and surgical outcomes across a broad surgical population using a very large sample size. METHODS: This was an analysis of the 2012 to 2018 American College of Surgeons National Surgical Quality Improvement database, including all patients from 9 surgical specialties (general, gynecology, neurosurgery, orthopedics, otolaryngology, plastics, thoracic, urology, and vascular). Preoperative characteristics and postoperative outcomes were compared by body mass index class (normal weight 18.5-24.9 kg/m2, overweight 25.0-29.9, obese class I 30.0-34.9, obese II 35.0-39.9, obese III ≥40). Adjusted odds ratios were computed for adverse outcomes by body mass index class. RESULTS: A total of 5,572,019 patients were included; 44.6% were obese. Median operative times were marginally higher for obese patients (89 vs 83 minutes, P < .001). Compared to normal weight patients, overweight and obese patients in classes I, II, and III all had higher adjusted odds of developing infection, venous thromboembolism, and renal complications, but they did not exhibit elevated odds of other postoperative complications (mortality, overall morbidity, pulmonary, urinary tract infection, cardiac, bleeding, stroke, unplanned readmission, or discharge not home (except for class III patients). CONCLUSION: Obesity was associated with increased odds of postoperative infection, venous thromboembolism, and renal but not the other American College of Surgeons National Surgical Quality Improvement complications. Obese patients need to be carefully managed for these complications.

Does Work Relative Value Unit Measure Surgical Complexity for Risk Adjustment of Surgical Outcomes?

INTRODUCTION: The purpose of this study was to determine whether the work relative value unit (workRVU) of a patient's operation can be useful as a measure of surgical complexity for the risk adjustment of surgical outcomes. METHODS: We retrospectively analyzed the American College of Surgeon's National Surgical Quality Improvement Program database (2005-2018). We examined the associations of workRVU of the patient's primary operation with preoperative patient characteristics and associations with postoperative complications. We performed forward selection multiple logistic regression analysis to determine the predictive importance of workRVU. We then generated prediction models using patient characteristics with and without workRVU and compared c-indexes to assess workRVU's additive predictive value. RESULTS: 7,507,991 operations were included. Patients who were underweight, functionally dependent, transferred from an acute care hospital, had higher American Society of Anesthesiologists class or who had medical comorbidities had operations with higher workRVU (all P < 0.0001). The subspecialties with the highest workRVU were neurosurgery (mean = 22.2), thoracic surgery (mean = 21.1), and vascular surgery (mean = 18.8) (P < 0.0001). For all postoperative complications, mean workRVU was higher for patients with the complication than those without (all P < 0.0001). For eight of 12 postoperative complications, workRVU entered the logistic regression models as a predictor variable in the 1st to 4th steps. Addition of workRVU as a preoperative predictive variable improved the c-index of the prediction models. CONCLUSIONS: WorkRVU was associated with sicker patients and patients experiencing postoperative complications and was an important predictor of postoperative complications. When added to a prediction model including patient characteristics, it only marginally improved prediction. This is possibly because workRVU is associated with patient characteristics.

Preoperative Prediction of Unplanned Reoperation in a Broad Surgical Population.

INTRODUCTION: Unplanned reoperation is an undesirable outcome with considerable risks and an increasingly assessed quality of care metric. There are no preoperative prediction models for reoperation after an index surgery in a broad surgical population in the literature. The Surgical Risk Preoperative Assessment System (SURPAS) preoperatively predicts 12 postoperative adverse events using 8 preoperative variables, but its ability to predict unplanned reoperation has not been assessed. This study's objective was to determine whether the SURPAS model could accurately predict unplanned reoperation. METHODS: This was a retrospective analysis of the American College of Surgeons' National Surgical Quality Improvement Program adult database, 2012-2018. An unplanned reoperation was defined as any unintended operation within 30 d of an initial scheduled operation. The 8-variable SURPAS model and a 29-variable "full" model, incorporating all available American College of Surgeons' National Surgical Quality Improvement Program nonlaboratory preoperative variables, were developed using multiple logistic regression and compared using discrimination and calibration metrics: C-indices (C), Hosmer-Lemeshow observed-to-expected plots, and Brier scores (BSs). The internal chronological validation of the SURPAS model was conducted using "training" (2012-2017) and "test" (2018) datasets. RESULTS: Of 5,777,108 patients, 162,387 (2.81%) underwent an unplanned reoperation. The SURPAS model's C-index of 0.748 was 99.20% of that for the full model (C = 0.754). Hosmer-Lemeshow plots showed good calibration for both models and BSs were similar (BS = 0.0264, full; BS = 0.0265, SURPAS). Internal chronological validation results were similar for the training (C = 0.749, BS = 0.0268) and test (C = 0.748, BS = 0.0250) datasets. CONCLUSIONS: The SURPAS model accurately predicted unplanned reoperation and was internally validated. Unplanned reoperation can be integrated into the SURPAS tool to provide preoperative risk assessment of this outcome, which could aid patient risk education.

Mucosal Ulceration in Gastrointestinal Stromal Tumor is an Independent Predictor of Progression-Free Survival.

INTRODUCTION: Gastrointestinal stromal tumors (GISTs) are the most common mesenchymal tumors of the gastrointestinal (GI) tract. Known prognostic features of GISTs include tumor mitotic rate, size, and location, yet one common feature of primary GISTs for which prognostic significance is unknown, is mucosal ulceration. This study aims to investigate the significance of mucosal ulceration in GISTs. MATERIALS AND METHODS: A retrospective study was conducted of 513 patients at a tertiary referral center with a suspected or documented diagnosis of primary GIST between the years of 2000 and 2020. Ulceration was confirmed by definitive documentation in the endoscopic or histopathologic report. The significance of ulceration in GIST was compared to other prognostic factors. RESULTS: Of the 513 patients reviewed, 310 primary GIST patients with known ulceration and disease status were identified. Of those, 27.4% (n = 85) demonstrated mucosal ulceration. Mucosal ulceration in GISTs is associated with GI bleeding, mitotic rate, tumor size, and exon 11 mutations. After a median follow-up of 35.4 (interquartile range = 17.1-62.2) mo, patients with ulcerated GISTs experienced higher rates of tumor progression (40.0% versus 14.2%, P < 0.0001). In multivariate analysis, ulceration of GISTs was highly associated with disease progression (P < 0.0001) and progression-free survival (hazard ratio = 2.4 [1.2-4.7], P = 0.01). CONCLUSIONS: Mucosal ulceration in GISTs is associated with GI bleeding, mitotic rate, tumor size, and exon 11 mutations. Overall, ulceration in GISTs is associated with elevated risk of tumor progression and is an independent prognostic factor. In multivariate analysis, ulceration in GIST remains an independent risk factor for disease progression.

Effect of Present at Time of Surgery on Unadjusted and Risk-Adjusted Postoperative Complication Rate.

BACKGROUND: Present at the time of surgery (PATOS) is an important measure to collect in postoperative complication surveillance systems because it may affect a patient's risk of a subsequent complication and the estimation of postoperative complication rates attributed to the healthcare system. The American College of Surgeons (ACS) NSQIP started collecting PATOS data for 8 postoperative complications in 2011, but no one has used these data to quantify how this may affect unadjusted and risk-adjusted postoperative complication rates. STUDY DESIGN: This study was a retrospective observational study of the ACS NSQIP database from 2012 to 2018. PATOS data were analyzed for the 8 postoperative complications of superficial, deep, and organ space surgical site infection; pneumonia; urinary tract infection; ventilator dependence; sepsis; and septic shock. Unadjusted postoperative complication rates were compared ignoring PATOS vs taking PATOS into account. Observed to expected ratios over time were also compared by calculating expected values using multiple logistic regression analyses with complication as the dependent variable and the 28 nonlaboratory preoperative variables in the ACS NSQIP database as the independent variables. RESULTS: In 5,777,108 patients, observed event rates for each outcome were reduced by between 6.1% (superficial surgical site infection) and 52.5% (sepsis) when PATOS was taken into account. The observed to expected ratios were similar each year for all outcomes, except for sepsis and septic shock in the early years. CONCLUSIONS: Taking PATOS into account is important for reporting unadjusted event rates. The effect varied by type of complication-lowest for superficial surgical site infection and highest for sepsis and septic shock. Taking PATOS into account was less important for risk-adjusted outcomes (observed to expected ratios), except for sepsis and septic shock.

Minimally invasive surgery is associated with decreased postoperative complications after esophagectomy.

BACKGROUND: Although some studies have compared esophagectomy outcomes by technique or approach, there is opportunity to strengthen our knowledge surrounding these outcomes. We aimed to perform a comprehensive comparison of esophagectomy postoperative complications. METHODS: We retrospectively reviewed the American College of Surgeons National Surgical Quality Improvement Program database (2007-2018). Esophagectomies were identified using Current Procedural Terminology codes and grouped by operative technique (Ivor Lewis, transhiatal, McKeown) and surgical approach (minimally invasive vs open esophagectomy). Twelve postoperative complications were compared. Significant complications underwent risk adjustment using multivariate logistic regression. RESULTS: Analysis was performed on 13,457 esophagectomies: 11,202 (83.2%) open and 2255 (16.8%) minimally invasive. There were 7611 (56.6%) Ivor Lewis, 3348 (24.9%) transhiatal, and 2498 (18.6%) McKeown procedures. There were significant differences among the surgical techniques in 6 of 12 risk-adjusted complications. When comparing the outcomes of minimally invasive techniques, there were only significant differences in 2 of 12 complications: overall morbidity (minimally invasive Ivor Lewis 30.5%, minimally invasive transhiatal 43.4%, minimally invasive McKeown 40.3%, P = .0009) and infections (minimally invasive Ivor Lewis 15.4%, minimally invasive transhiatal 26.0%, minimally invasive McKeown 25.3%, P = .0003). Patients who underwent minimally invasive surgery were less likely to have overall morbidity (odds ratio, 0.68; 95% confidence interval, 0.62-0.75), respiratory complications (odds ratio, 0.77; 95% confidence interval, 0.68-0.87), urinary tract infection (odds ratio, 0.61; 95% confidence interval, 0.43-0.88), renal complications (odds ratio, 0.52; 95% confidence interval, 0.34-0.81), bleeding complications (odds ratio, 0.36; 95% confidence interval, 0.30-0.43), and nonhome discharge (odds ratio, 0.54; 95% confidence interval, 0.45-0.64), and had shorter length of stay (9.7 vs 13.2 days, P < .0001). CONCLUSIONS: Patients undergoing minimally invasive esophagectomy have lower rates of postoperative complications regardless of esophagectomy techniques. The minimally invasive approach was associated with reduced complication variance among 3 common esophagectomy techniques.

Inpatient Versus Outpatient Surgery: A Comparison of Postoperative Mortality and Morbidity in Elective Operations.

BACKGROUND: Operations performed outpatient offer several benefits. The prevalence of outpatient operations is growing. Consequently, the proportion of patients with multiple comorbidities undergoing outpatient surgery is increasing. We compared 30-day mortality and overall morbidity between outpatient and inpatient elective operations. METHODS: Using the 2005-2018 ACS-NSQIP database, we evaluated trends in percent of hospital outpatient operations performed over time, and the percent of operations done outpatient versus inpatient by CPT code. Patient characteristics were compared for outpatient versus inpatient operations. We compared unadjusted and risk-adjusted 30-day mortality and morbidity for inpatient and outpatient operations. RESULTS: A total of 6,494,298 patients were included. The proportion of outpatient operations increased over time, from 37.8% in 2005 to 48.2% in 2018. We analyzed the 50 most frequent operations performed outpatient versus inpatient 25-75% of the time (n = 1,743,097). Patients having outpatient operations were younger (51.6 vs 54.6 years), female (70.3% vs 67.3%), had fewer comorbidities, and lower ASA class (I-II, 69.3% vs. 59.9%). On both unadjusted and risk-adjusted analysis, 30-day mortality and overall morbidity were less likely in outpatient versus inpatient operations. CONCLUSION: In this large multi-specialty analysis, we found that patients undergoing outpatient surgery had lower risk of 30-day morbidity and mortality than those undergoing the same inpatient operation. Patients having outpatient surgery were generally healthier, suggesting careful patient selection occurred even with increasing outpatient operation frequency. Patients and providers can feel reassured that outpatient operations are a safe, reasonable option for selected patients.

Development and validation of models for detection of postoperative infections using structured electronic health records data and machine learning.

BACKGROUND: Postoperative infections constitute more than half of all postoperative complications. Surveillance of these complications is primarily done through manual chart review, which is time consuming, expensive, and typically only covers 10% to 15% of all operations. Automated surveillance would permit the timely evaluation of and reporting of all operations. METHODS: The goal of this study was to develop and validate parsimonious, interpretable models for conducting surveillance of postoperative infections using structured electronic health records data. This was a retrospective study using 30,639 unique operations from 5 major hospitals between 2013 and 2019. Structured electronic health records data were linked to postoperative outcomes data from the American College of Surgeons National Surgical Quality Improvement Program. Predictors from the electronic health records included diagnoses, procedures, and medications. Infectious complications included surgical site infection, urinary tract infection, sepsis, and pneumonia within 30 days of surgery. The knockoff filter, a penalized regression technique that controls type I error, was applied for variable selection. Models were validated in a chronological held-out dataset. RESULTS: Seven percent of patients experienced at least one type of postoperative infection. Models selected contained between 4 and 8 variables and achieved >0.91 area under the receiver operating characteristic curve, >81% specificity, >87% sensitivity, >99% negative predictive value, and 10% to 15% positive predictive value in a held-out test dataset. CONCLUSION: Surveillance and reporting of postoperative infection rates can be implemented for all operations with high accuracy using electronic health records data and simple linear regression models.