Preoperative Prediction of Postoperative Infections Using Machine Learning and Electronic Health Record Data.

OBJECTIVE: To estimate preoperative risk of postoperative infections using structured electronic health record (EHR) data. BACKGROUND: Surveillance and reporting of postoperative infections is primarily done through costly, labor-intensive manual chart reviews on a small sample of patients. Automated methods using statistical models applied to postoperative EHR data have shown promise to augment manual review as they can cover all operations in a timely manner. However, there are no specific models for risk-adjusting infectious complication rates using EHR data. METHODS: Preoperative EHR data from 30,639 patients (2013-2019) were linked to the American College of Surgeons National Surgical Quality Improvement Program preoperative data and postoperative infection outcomes data from 5 hospitals in the University of Colorado Health System. EHR data included diagnoses, procedures, operative variables, patient characteristics, and medications. Lasso and the knockoff filter were used to perform controlled variable selection. Outcomes included surgical site infection, urinary tract infection, sepsis/septic shock, and pneumonia up to 30 days postoperatively. RESULTS: Among >15,000 candidate predictors, 7 were chosen for the surgical site infection model and 6 for each of the urinary tract infection, sepsis, and pneumonia models. Important variables included preoperative presence of the specific outcome, wound classification, comorbidities, and American Society of Anesthesiologists physical status classification. The area under the receiver operating characteristic curve for each model ranged from 0.73 to 0.89. CONCLUSIONS: Parsimonious preoperative models for predicting postoperative infection risk using EHR data were developed and showed comparable performance to existing American College of Surgeons National Surgical Quality Improvement Program risk models that use manual chart review. These models can be used to estimate risk-adjusted postoperative infection rates applied to large volumes of EHR data in a timely manner.

Esophagram should be performed to diagnose esophageal perforation before inter-hospital transfer.

Background: Early recognition of esophageal perforation may prevent morbidity and mortality, and accurate diagnostic imaging facilitates triage. Stable patients with suspected perforation may be transferred to higher levels of care before appropriate work-up and diagnosis confirmation. We reviewed patients transferred for esophageal perforation to critically analyze the diagnostic workflow. Methods: We performed a retrospective review of patients transferred to our tertiary care institution from 2015-2021 for suspected esophageal perforation. Demographics, referring site characteristics, diagnostic studies, and management were analyzed. Bivariate comparisons were performed using Wilcoxon-Mann-Whitney tests for continuous variables and chi-squared or Fisher's exact tests for categorical variables. Results: Sixty-five patients were included. Etiology of suspected perforation was spontaneous in 53.8% and iatrogenic in 33.8%. Most patients were transferred within 24 hours from time of suspected perforation (66.2%). Transferring sites included seven states and were 101-300 miles (32.3%) or >300 miles (26.2%) away. CT imaging was obtained in 96.9% before transfer, most commonly demonstrating pneumomediastinum (46.2%). Only 21.5% of patients had an esophagram before transfer. Following transfer, 36.9% (n=24) were ultimately not found to have esophageal perforation, demonstrated by negative arrival esophagram in 79.1%. In patients with confirmed perforation (n=41), 58.5% had surgery, 26.8% endoscopic intervention, and 14.6% supportive care. Conclusions: After transfer a proportion of patients were ultimately found to not have esophageal perforation, typically demonstrated by negative esophagram upon arrival. We conclude that a recommendation of performing esophagram at the presenting site, when possible, may prevent unnecessary transfers, and will likely reduce costs, conserve resources, and decrease management delays.

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.

Prospective Evaluation of a Universally Applied Laparoscopic Gastric Ischemic Preconditioning Protocol Prior to Esophagectomy with Comparison with Historical Controls.

BACKGROUND: Anastomotic leak after esophagectomy is associated with significant morbidity and mortality. Our institution began performing laparoscopic gastric ischemic preconditioning (LGIP) with ligation of the left gastric and short gastric vessels prior to esophagectomy in all patients presenting with resectable esophageal cancer. We hypothesized that LGIP may decrease the incidence and severity of anastomotic leak. METHODS: Patients were prospectively evaluated following the universal application of LGIP prior to esophagectomy protocol in January 2021 until August 2022. Outcomes were compared with patients who underwent esophagectomy without LGIP from a prospectively maintained database from 2010 to 2020. RESULTS: We compared 42 patients who underwent LGIP followed by esophagectomy with 222 who underwent esophagectomy without LGIP. Age, sex, comorbidities, and clinical stage were similar between groups. Outpatient LGIP was generally well tolerated, with one patient experiencing prolonged gastroparesis. Median time from LGIP to esophagectomy was 31 days. Mean operative time and blood loss were not significantly different between groups. Patients who underwent LGIP were significantly less likely to develop an anastomotic leak following esophagectomy (7.1% vs. 20.7%, p = 0.038). This finding persisted on multivariate analysis [odds ratio (OR) 0.17, 95% confidence interval (CI) 0.03-0.42, p = 0.029]. The occurrence of any post-esophagectomy complication was similar between groups (40.5% vs. 46.0%, p = 0.514), but patients who underwent LGIP had shorter length of stay [10 (9-11) vs. 12 (9-15), p = 0.020]. CONCLUSIONS: LGIP prior to esophagectomy is associated with a decreased risk of anastomotic leak and length of hospital stay. Further, multi-institutional studies are warranted to confirm these findings.

Food Deserts Increase Readmission After Esophagectomy for Cancer: A Multi-institutional Study.

BACKGROUND: Food deserts are low-income census tracts with poor access to supermarkets and are associated with worse outcomes in breast, colon, and a small number of esophageal cancer patients. This study investigated residency in food deserts on readmission rates in a multi-institutional cohort of esophageal cancer patients undergoing trimodality therapy. METHODS: A retrospective review of patients who underwent trimodality therapy at 6 high-volume institutions from January 2015 to July 2019 was performed. Food desert status was defined by the United States Department of Agriculture by patient ZIP Code. The primary outcome was 30-day readmission after esophagectomy. Multilevel, multivariable logistic regression was used to model readmission on food desert status adjusted for diabetes, insurance type, length of stay, and any complication, treating the institution as a random factor. RESULTS: Of the 453 records evaluated, 425 were included in the analysis. Seventy-three patients (17.4%) resided in a food desert. Univariate analysis demonstrated food desert patients had significantly increased 30-day readmission. No differences were seen in length of stay, complications, or 30-day mortality. In the adjusted logistic regression model, residing in a food desert remained a significant risk factor for readmission (odds ratio, 2.11; 95% CI, 1.07-4.15). There were no differences in 30-day, 90-day, or 1-year mortality based on food desert status, although readmission was associated with worse 90-day and 1-year mortality. CONCLUSIONS: Food desert residence was associated with 30-day readmission after esophagectomy in patients undergoing trimodality treatment for esophageal cancer in this multi-institutional population. Identification of patients residing in a food desert may allow surgeons to focus preventative interventions during treatment and postoperatively to improve outcomes.

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.

Lessons learned by thoracic surgeons during the COVID-19 pandemic.

Background: The scale of the coronavirus disease 2019 (COVID-19) pandemic has necessitated healthcare systems to adapt and evolve, altering physician roles and expectations. Thoracic surgeons have seen practice changes from new COVID-19 consults to necessary delay and triage of elective care. The goal of this study was to understand the impact of COVID-19 on thoracic surgeon experiences in order to anticipate roles and changes in practice in future such circumstances. Methods: Semi-structured, qualitative individual telephone interviews were conducted with thoracic surgeons. Interviews were structured to understand how surgeons were impacted by the COVID-19 pandemic and to record lessons learned. Interviews were conducted until thematic saturation was achieved. Data were analyzed using matrix analysis. Results: Eleven board-certified general thoracic surgeons from nine institutions were interviewed. Thoracic surgeon roles in COVID-19 care included critical care delivery, performing tracheostomies and establishing related protocols, and interventions for long-term airway complications. Attention was called to the impact of the pandemic on thoracic cancer: patients avoided hospitals because of concern over COVID-19, delaying care. Conclusions: Thoracic surgeons played a critical role in the COVID-19 pandemic response in both technical patient care and administrative capacities. Primary care responsibilities included the development, administration and delivery of tracheostomy protocols, and the care of down-stream airway complications. Thoracic surgeons were critical in triage decisions to minimize the impact of COVID-19 on thoracic cancer care. Lessons learned during the COVID-19 pandemic may provide insight into opportunities to promote collaboration in thoracic surgery and facilitate improved care delivery in future settings of resource limitation.

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.

Cannabis use and post-operative complications in patients undergoing pancreatic resection.

BACKGROUND: Many states have legalized medical cannabis with various reported therapeutic benefits. However, there is little data assessing the effects of cannabis on surgical outcomes. We sought to compare post-operative pancreatic resection complications between cannabis users and non-users. METHODS: This is a single-center, retrospective review of patients who underwent Whipple or distal pancreatectomy from 1/2017-12/2020. The primary outcome was any in-hospital complication, using Clavien-Dindo. Multivariable regression analysis was performed. RESULTS: There were 486 patients who underwent Whipple (n=346, 71.2%) or distal pancreatectomy (n=140, 28.8%). Overall, 21.4% (n=104) reported cannabis use, of whom 80.8% were current users. Cannabis users were younger (60 vs. 66 years, p < 0.001), and more likely to have smoked tobacco (p=0.04), but otherwise had similar demographics as non-users. There were 288 (59.3%) patients who developed an in-hospital complication (grade 1-2, 75.3%; grade 3-5, 24.7%). A trend towards increased complications was observed with tobacco smoking (OR 1.33, 95% CI 0.91-1.94, p=0.14), but no association of cannabis use with complications was observed (OR 0.93, 95% CI 0.58-1.47, p=0.74). DISCUSSION: A significant proportion of patients undergoing pancreatic resection report cannabis use. These results suggest that there was no association between cannabis use and post-operative complications, future prospective evaluation is warranted.

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.

Barriers and Facilitators in Implementation of an Esophagectomy Care Pathway: a Qualitative Analysis.

INTRODUCTION: A new postoperative esophagectomy care pathway was recently implemented at our institution. Practice pattern change among provider teams can prove challenging; therefore, we sought to study the barriers and facilitators toward pathway implementation at the provider level. METHODS: This qualitative study was guided by the Theoretical Domains Framework (TDF) to study the adoption and implementation of a post-esophagectomy care pathway. Sixteen in-depth interviews were conducted with providers involved with the pathway. Matrix analysis was used to analyze the data. RESULTS: Providers included attending surgeons (n = 6), advanced practice providers (n = 8), registered dietitian (n = 1), and clinic staff (n = 1). TDF domains that were salient across our findings included knowledge, beliefs about consequences, social influences, and environmental context and resources. Identified facilitators included were electronic health record tools, such as note templates including pathway components and a pathway-specific order set, patient satisfaction, and preliminary data indicating clinical benefits such as a reduced anastomotic leak rate. The major barrier reported was a hesitance to abandon previous practice patterns, most prevalent at the attending surgeon level. CONCLUSION: The TDF enabled us to identify and understand the individuals' perceived barriers and facilitators toward adoption and implementation of a postoperative esophagectomy pathway. This analysis can help guide and improve adoption of surgical patient care pathways among providers.

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.

Informational Needs of Surgical Oncology Patients: A Cross-Sectional Patient Survey.

INTRODUCTION: Patients newly diagnosed with cancer often seek information prior to being seen by a specialist. Little is known about the type of information desired and the sources used. We asked how patients find information about their new cancer diagnoses to improve information provision. METHODS: An anonymous seven-question survey was provided to new patients in the surgical and medical oncology clinics at a comprehensive cancer center from February 2021 to June 2021. RESULTS: Of 503 consecutive patients, 405 (81%) returned surveys; 49% female, 57% aged 51-75 y, and 71% Caucasian. Many (74%) sought information before their visit. Most (57%) relied on prior medical providers and 77% reported them as a trusted source. Nearly 80% of patients used at least one nonvalidated resource; 21% friends and relatives, 20% nongovernment or hospital resources, and 12% social media. Importantly, 23% found conflicting information. Respondents desired information on cancer treatment (58%), alternative therapies (35%), and nutrition and supplements (31%). CONCLUSIONS: Patients with cancer trust information from medical providers but seek information from a variety of sources that can provide conflicting information. These data support encouraging patients to use validated sources, providing robust organization-based resources, and engaging patients on topics such as alternative therapies and nutrition.

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.

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.

Making a Painless Drain: Proof of Concept.

Chest tubes account for a large proportion of postoperative pain after cardiothoracic operations. The objective of this study was to develop a novel, cost-effective, easy-to-use, lidocaine-eluting coating to reduce pain associated with postoperative chest tubes. A lidocaine-eluting hydrogel was developed by dispersing lidocaine-loaded nanoparticles in an aqueous solution containing gelatin (5%). Glutaraldehyde (1%) was added to crosslink the gelatin into a hydrogel. The hydrogel was dehydrated, resulting in a thin, stable polymer. Sterile lidocaine hydrogel-coated silicone discs and control discs were prepared and surgically implanted in the subcutaneous space of C57B6 mice. Using von Frey filaments, mice underwent preoperative baseline pain testing, followed by pain testing on post-procedure day 1 and 3. On post-procedure day 1, mice implanted with control discs demonstrated no change in pain tolerance compared to baseline, while mice implanted with 20 mg and 80 mg lidocaine-loaded discs demonstrated a 2.4-fold (P = 0.36) and 4.7-fold (P = 0.01) increase in pain tolerance, respectively. On post-procedure day 3, mice implanted with control discs demonstrated a 0.7-fold decrease in pain tolerance compared to baseline, while mice implanted with 20 mg and 80 mg lidocaine-loaded discs demonstrated a 1.8-fold (P = 0.88) and 8.4-fold (P = 0.02) increase in pain tolerance, respectively. Our results demonstrate successful development of a lidocaine-eluting chest tube with hydrogel coating, leading to improved pain tolerance in vivo. The concept of a drug-eluting drain coating has significant importance due to its potential universal application in a variety of drain types and insertion locations.

Development and validation of a model for surveillance of postoperative bleeding complications using structured electronic health records data.

BACKGROUND: Postoperative bleeding complications surveillance is done primarily through manual chart review. The purpose of this study was to develop and validate a detection model for postoperative bleeding complications using structured electronic health records data. METHODS: Patients who underwent operations at 1 of 5 hospitals within our local health system between 2013 and 2019 and whose complications were reported by the American College of Surgeons National Surgical Quality Improvement Program were included. Electronic health records data were linked to American College of Surgeons National Surgical Quality Improvement Program data using personal health identifiers. Electronic health records predictors included diagnosis codes mapped to PheCodes, procedure names, and medications within 30 days after surgery. We defined bleeding events as the transfusion of red blood cell components within 30 days after surgery. The knockoff filter and the lasso were used to develop a model in a training set of operations from January 2013 to March 2017. Performance of each model was tested in a held-out data set of patients who underwent operations from March 2017 to October 2019. RESULTS: A total of 30,639 patients were included; 1,112 patients (3.6%) had a bleeding event. Eight predictor variables were selected by the knockoff filter. When applied to the test set, specificity was 94%, sensitivity was 94%, area under the curve was 0.97, and accuracy was 93%. Calibration was consistent in lower predicted risk patients, whereas the model slightly overpredicted risk in high-risk patients. CONCLUSION: We created a parsimonious, accurate model for identifying patients with bleeding complications. This model can be used to augment manual chart review for surveillance and reporting of perioperative bleeding complications, enabling inclusion of all surgeries in quality improvement efforts.

Associations Between Preoperative Risk, Postoperative Complications, and 30-Day Mortality.

BACKGROUND: Comorbidities and postoperative complications increase mortality, making early recognition and management critical. It is useful to understand how they are associated with one another. This study assesses associations between comorbidities, complications, and mortality. METHODS: We calculated associations between comorbidities, complications, and 30-day mortality using the 2012-2018 ACS-NSQIP database. We examined the association between mortality and number of complications which complications were most associated with mortality. RESULTS: 5,777,108 patients were included. 30-day mortality was 0.95%. For most comorbidities or postoperative complications, patients with these had higher mortality than patients without. Having ≥ 1 complication increased mortality risk by 32.5-fold (6.5% vs. 0.2%). Mortality rate significantly increased with increasing number of complications, particularly after two or more complications. Bleeding and sepsis were associated with the most deaths. CONCLUSION: The 30-day mortality rate was < 1% but was 32-fold higher in patients with complications and increased rapidly for patients with ≥ 2 complications. Bleeding and sepsis were the most prominent complications associated with mortality.