Nationwide, County-Level Analysis of the Patterns, Trends, and System-Level Predictors of Opioid Prescribing in Surgery in the US: Social Determinants and Access to Mental Health Services Matter.

BACKGROUND: The diversion of unused opioid prescription pills to the community at large contributes to the opioid epidemic in the US. In this county-level population-based study, we aimed to examine the US surgeons' opioid prescription patterns, trends, and system-level predictors in the peak years of the opioid epidemic. STUDY DESIGN: Using the Medicare Part D database (2013 to 2017), the mean number of opioid prescriptions per beneficiary (OPBs) was determined for each US county. Opioid-prescribing patterns were compared across counties. Multivariable linear regression was performed to determine relationships between county-level social determinants of health (demographic, eg median age and education level; socioeconomic, eg median income; population health status, eg percentage of current smokers; healthcare quality, eg rate of preventable hospital stays; and healthcare access, eg healthcare costs) and OPBs. RESULTS: Opioid prescription data were available for 1,969 of 3,006 (65.5%) US counties, and opioid-related deaths were recorded in 1,384 of 3,006 counties (46%). Nationwide, the mean OPBs decreased from 1.08 ± 0.61 in 2013 to 0.87 ± 0.55 in 2017; 81.6% of the counties showed the decreasing trend. County-level multivariable analyses showed that lower median population age, higher percentages of bachelor's degree holders, higher percentages of adults reporting insufficient sleep, higher healthcare costs, fewer mental health providers, and higher percentages of uninsured adults are associated with higher OPBs. CONCLUSIONS: Opioid prescribing by surgeons decreased between 2013 and 2017. A county's suboptimal access to healthcare in general and mental health services in specific may be associated with more opioid prescribing after surgery.

The use of POTTER (Predictive Optimal Trees in Emergency Surgery Risk) calculator to predict mortality and complications in patients submitted to Emergency Surgery.

INTRODUCTION: the ability of the care team to reliably predict postoperative risk is essential for improvements in surgical decision-making, patient and family counseling, and resource allocation in hospitals. The Artificial Intelligence (AI)-powered POTTER (Predictive Optimal Trees in Emergency Surgery Risk) calculator represents a user-friendly interface and has since been downloaded in its iPhone and Android format by thousands of surgeons worldwide. It was originally developed to be used in non-traumatic emergency surgery patients. However, Potter has not been validated outside the US yet. In this study, we aimed to validate the POTTER calculator in a Brazilian academic hospital. METHODS: mortality and morbidity were analyzed using the POTTER calculator in both trauma and non-trauma emergency surgery patients submitted to surgical treatment between November 2020 and July 2021. A total of 194 patients were prospectively included in this analysis. RESULTS: regarding the presence of comorbidities, about 20% of the population were diabetics and 30% were smokers. A total of 47.4% of the patients had hypertensive prednisone. After the analysis of the results, we identified an adequate capability to predict 30-day mortality and morbidity for this group of patients. CONCLUSION: the POTTER calculator presented excellent performance in predicting both morbidity and mortality in the studied population, representing an important tool for surgical teams to define risks, benefits, and outcomes for the emergency surgery population.

Use of artificial intelligence for nonlinear benchmarking of surgical care.

BACKGROUND: Existent methodologies for benchmarking the quality of surgical care are linear and fail to capture the complex interactions of preoperative variables. We sought to leverage novel nonlinear artificial intelligence methodologies to benchmark emergency surgical care. METHODS: Using a nonlinear but interpretable artificial intelligence methodology called optimal classification trees, first, the overall observed mortality rate at the index hospital's emergency surgery population (index cohort) was compared to the risk-adjusted expected mortality rate calculated by the optimal classification trees from the American College of Surgeons National Surgical Quality Improvement Program database (benchmark cohort). Second, the artificial intelligence optimal classification trees created different "nodes" of care representing specific patient phenotypes defined by the artificial intelligence optimal classification trees without human interference to optimize prediction. These nodes capture multiple iterative risk-adjusted comparisons, permitting the identification of specific areas of excellence and areas for improvement. RESULTS: The index and benchmark cohorts included 1,600 and 637,086 patients, respectively. The observed and risk-adjusted expected mortality rates of the index cohort calculated by optimal classification trees were similar (8.06% [95% confidence interval: 6.8-9.5] vs 7.53%, respectively, P = .42). Two areas of excellence and 4 for improvement were identified. For example, the index cohort had lower-than-expected mortality when patients were older than 75 and in respiratory failure and septic shock preoperatively but higher-than-expected mortality when patients had respiratory failure preoperatively and were thrombocytopenic, with an international normalized ratio ≤1.7. CONCLUSION: We used artificial intelligence methodology to benchmark the quality of emergency surgical care. Such nonlinear and interpretable methods promise a more comprehensive evaluation and a deeper dive into areas of excellence versus suboptimal care.

Development of a Machine Learning-Based Prescriptive Tool to Address Racial Disparities in Access to Care After Penetrating Trauma.

Importance: The use of artificial intelligence (AI) in clinical medicine risks perpetuating existing bias in care, such as disparities in access to postinjury rehabilitation services. Objective: To leverage a novel, interpretable AI-based technology to uncover racial disparities in access to postinjury rehabilitation care and create an AI-based prescriptive tool to address these disparities. Design, Setting, and Participants: This cohort study used data from the 2010-2016 American College of Surgeons Trauma Quality Improvement Program database for Black and White patients with a penetrating mechanism of injury. An interpretable AI methodology called optimal classification trees (OCTs) was applied in an 80:20 derivation/validation split to predict discharge disposition (home vs postacute care [PAC]). The interpretable nature of OCTs allowed for examination of the AI logic to identify racial disparities. A prescriptive mixed-integer optimization model using age, injury, and gender data was allowed to "fairness-flip" the recommended discharge destination for a subset of patients while minimizing the ratio of imbalance between Black and White patients. Three OCTs were developed to predict discharge disposition: the first 2 trees used unadjusted data (one without and one with the race variable), and the third tree used fairness-adjusted data. Main Outcomes and Measures: Disparities and the discriminative performance (C statistic) were compared among fairness-adjusted and unadjusted OCTs. Results: A total of 52 468 patients were included; the median (IQR) age was 29 (22-40) years, 46 189 patients (88.0%) were male, 31 470 (60.0%) were Black, and 20 998 (40.0%) were White. A total of 3800 Black patients (12.1%) were discharged to PAC, compared with 4504 White patients (21.5%; P < .001). Examining the AI logic uncovered significant disparities in PAC discharge destination access, with race playing the second most important role. The prescriptive fairness adjustment recommended flipping the discharge destination of 4.5% of the patients, with the performance of the adjusted model increasing from a C statistic of 0.79 to 0.87. After fairness adjustment, disparities disappeared, and a similar percentage of Black and White patients (15.8% vs 15.8%; P = .87) had a recommended discharge to PAC. Conclusions and Relevance: In this study, we developed an accurate, machine learning-based, fairness-adjusted model that can identify barriers to discharge to postacute care. Instead of accidentally encoding bias, interpretable AI methodologies are powerful tools to diagnose and remedy system-related bias in care, such as disparities in access to postinjury rehabilitation care.

Timing of regional analgesia in elderly patients with blunt chest-wall injury.

BACKGROUND: Rib fractures represent a typical injury pattern in older people and are associated with respiratory morbidity and mortality. Regional analgesia modalities are adjuncts for pain management, but the optimal timing for their initiation remains understudied. We hypothesized that early regional analgesia would have similar outcomes to late regional analgesia. METHODS: We retrospectively reviewed the American College of Surgeons Trauma Quality Improvement Program database from 2017 to 2019. We included patients ≥65 years old admitted with blunt chest wall trauma who received regional analgesia. We divided patients into 2 groups: (1) early regional analgesia (within 24 hours of admission) and (2) late regional analgesia (>24 hours). The outcomes evaluated were ventilator-associated pneumonia, mortality, unplanned intensive care unit admission, unplanned intubation, discharge to home, and duration of stay. Univariable analysis and multivariable logistic regression adjusting for patient and injury characteristics, trauma center level, and respiratory interventions were performed. RESULTS: In the study, 2,248 patients were included. The mean (standard deviation) age was 75.3 (6.9), and 52.7% were male. The median injury severity score (interquartile range) was 13 (9-17). The early regional analgesia group had a decreased incidence of unplanned intubation (2.7% vs 5.3%, P = .002), unplanned intensive care unit admission (4.9% vs 8.4%, P < .001), and shorter mean duration of stay (5.5 vs 6.5 days, P = .002). In multivariable analysis, early regional analgesia was associated with decreased odds of unplanned intubation (odds ratio, 0.58; 95% confidence interval, 0.36-0.94; P = .026), unplanned intensive care unit admission (odds ratio, 0.60; 95% confidence interval, 0.041-0.86; P = .006), and increased odds of discharge to home (odds ratio, 1.27; 95% confidence interval, 1.04-1.55; P = .019). After multivariable adjustment, no significant difference was found for ventilator-associated pneumonia or mortality (odds ratio, 0.60; 95% confidence interval, 0.34-1.04; P = .070). CONCLUSION: Early regional analgesia initiation is associated with improved outcomes in older people with blunt chest wall injuries. Geriatric trauma care bundles targeting early initiation of regional analgesia can potentially decrease complications and resource use.

Artificial intelligence versus surgeon gestalt in predicting risk of emergency general surgery.

BACKGROUND: Artificial intelligence (AI) risk prediction algorithms such as the smartphone-available Predictive OpTimal Trees in Emergency Surgery Risk (POTTER) for emergency general surgery (EGS) are superior to traditional risk calculators because they account for complex nonlinear interactions between variables, but how they compare to surgeons' gestalt remains unknown. Herein, we sought to: (1) compare POTTER to surgeons' surgical risk estimation and (2) assess how POTTER influences surgeons' risk estimation. STUDY DESIGN: A total of 150 patients who underwent EGS at a large quaternary care center between May 2018 and May 2019 were prospectively followed up for 30-day postoperative outcomes (mortality, septic shock, ventilator dependence, bleeding requiring transfusion, pneumonia), and clinical cases were systematically created representing their initial presentation. POTTER's outcome predictions for each case were also recorded. Thirty acute care surgeons with diverse practice settings and levels of experience were then randomized into two groups: 15 surgeons (SURG) were asked to predict the outcomes without access to POTTER's predictions while the remaining 15 (SURG-POTTER) were asked to predict the same outcomes after interacting with POTTER. Comparing to actual patient outcomes, the area under the curve (AUC) methodology was used to assess the predictive performance of (1) POTTER versus SURG, and (2) SURG versus SURG-POTTER. RESULTS: POTTER outperformed SURG in predicting all outcomes (mortality-AUC: 0.880 vs. 0.841; ventilator dependence-AUC: 0.928 vs. 0.833; bleeding-AUC: 0.832 vs. 0.735; pneumonia-AUC: 0.837 vs. 0.753) except septic shock (AUC: 0.816 vs. 0.820). SURG-POTTER outperformed SURG in predicting mortality (AUC: 0.870 vs. 0.841), bleeding (AUC: 0.811 vs. 0.735), pneumonia (AUC: 0.803 vs. 0.753) but not septic shock (AUC: 0.712 vs. 0.820) or ventilator dependence (AUC: 0.834 vs. 0.833). CONCLUSION: The AI risk calculator POTTER outperformed surgeons' gestalt in predicting the postoperative mortality and outcomes of EGS patients, and when used, improved the individual surgeons' risk prediction. Artificial intelligence algorithms, such as POTTER, could prove useful as a bedside adjunct to surgeons when preoperatively counseling patients. LEVEL OF EVIDENCE: Prognostic and Epidemiological; Level II.

Open Abdomen in Elderly Patients With Surgical Sepsis: Predictors of Mortality.

INTRODUCTION: Elderly patients are frequently presenting with emergency surgical conditions. The open abdomen technique is widely used in abdominal emergencies needing rapid control of intrabdominal contamination. However, specific predictors of mortality identifying candidates for comfort care are understudied. METHODS: The 2013-2017 the American College of Surgeons-National Surgical Quality Improvement Program database was queried for emergent laparotomies performed in geriatric patients with sepsis or septic shock in whom fascial closure was delayed. Patients with acute mesenteric ischemia were excluded. The primary outcome was 30-d mortality. Univariable analysis, followed by multivariable logistic regression, was performed. Mortality was computed for combinations of the five predictors with the highest odds ratios (OR). RESULTS: A total of 1399 patients were identified. The median age was 73 (69-79) y, and 54.7% were female. 30-d mortality was 50.6%. In the multivariable analysis, the most important predictors were as follows: American Society of Anesthesiologists status 5 (OR = 4.80, 95% confidence interval [CI], 1.85-12.49 P = 0.002), dialysis dependence (OR = 2.65, 95% CI 1.54-4.57, P < 0.001), congestive hearth failure (OR = 2.53, 95% CI 1.52-4.21, P < 0.001), disseminated cancer (OR = 2.61, 95% CI 1.55-4.38, P < 0.001), and preoperative platelet count of <100,000 cells/µL (OR = 1.87, 95% CI 1.15-3.04, P = 0.011). The presence of two or more of these factors resulted in over 80% mortality. The absence of all these risk factors results in a survival rate of 62.1%. CONCLUSIONS: In elderly patients, surgical sepsis or septic shock requiring an open abdomen for surgical management is highly lethal. The presence of several combinations of preoperative comorbidities is associated with a poor prognosis and can identify patients who can benefit from timely initiation of palliative care.

Is perioperative COVID-19 really associated with worse surgical outcomes? A nationwide COVIDSurg propensity-matched analysis.

BACKGROUND: Patients undergoing surgery with perioperative COVID-19 are suggested to have worse outcomes, but whether this is COVID-related or due to selection bias remains unclear. We aimed to compare the postoperative outcomes of patients with and without perioperative COVID-19. METHODS: Patients with perioperative COVID-19 diagnosed within 7 days before or 30 days after surgery between February and July 2020 from 68 US hospitals in COVIDSurg, an international multicenter database, were 1:1 propensity score matched to patients without COVID-19 undergoing similar procedures in the 2012 American College of Surgeons National Surgical Quality Improvement Program database. The matching criteria included demographics (e.g., age, sex), comorbidities (e.g., diabetes, chronic obstructive pulmonary disease, chronic kidney disease), and operation characteristics (e.g., type, urgency, complexity). The primary outcome was 30-day hospital mortality. Secondary outcomes included hospital length of stay and 13 postoperative complications (e.g., pneumonia, renal failure, surgical site infection). RESULTS: A total of 97,936 patients were included, 1,054 with and 96,882 without COVID-19. Prematching, COVID-19 patients more often underwent emergency surgery (76.1% vs. 10.3%, p < 0.001). A total of 843 COVID-19 and 843 non-COVID-19 patients were successfully matched based on demographics, comorbidities, and operative characteristics. Postmatching, COVID-19 patients had a higher mortality (12.0% vs. 8.1%, p = 0.007), longer length of stay (6 [2-15] vs. 5 [1-12] days), and higher rates of acute renal failure (19.3% vs. 3.0%, p < 0.001), sepsis (13.5% vs. 9.0%, p = 0.003), and septic shock (11.8% vs. 6.0%, p < 0.001). They also had higher rates of thromboembolic complications such as deep vein thrombosis (4.4% vs. 1.5%, p < 0.001) and pulmonary embolism (2.5% vs. 0.4%, p < 0.001) but lower rates of bleeding (11.6% vs. 26.1%, p < 0.001). CONCLUSION: Patients undergoing surgery with perioperative COVID-19 have higher rates of 30-day mortality and postoperative complications, especially thromboembolic, compared with similar patients without COVID-19 undergoing similar surgeries. Such information is crucial for the complex surgical decision making and counseling of these patients. LEVEL OF EVIDENCE: Prognostic and Epidemiologic; Level IV.

Surgical Implications of Coronavirus Disease-19.

As the coronavirus disease-19 (COVID-19) pandemic continues to evolve in 2022 with the surge of novel viral variants, it is important for physicians to understand and appreciate the surgical implications of the pandemic. This review provides an overview of the implications of the ongoing COVID-19 pandemic on surgical care and provides recommendations for perioperative management. Most observational studies suggest a higher risk for patients undergoing surgery with COVID-19 compared with risk-adjusted non-COVID-19 patients.

A Surgical Perspective of Gastrointestinal Manifestations and Complications of COVID-19 Infection.

The coronavirus disease 2019 (COVID-19), caused by the severe acute respiratory syndrome coronavirus 2, has quickly spread over the world since December 2019. COVID-19 is a systemic disease that can affect various organs throughout the body. Gastrointestinal (GI) symptoms have been reported in 16% to 33% of all patients with COVID-19 and in 75% of critically ill patients. This chapter reviews the GI manifestations of COVID-19 as well as their diagnostic and treatment modalities.

Association of Comorbidities and Functional Level With Mortality in Geriatric Bowel Perforation.

INTRODUCTION: Spontaneous bowel perforation is associated with high morbidity and mortality. This entity remains understudied in the geriatric patient. We sought to use a national surgical sample to uncover independent predictors of mortality in elderly patients undergoing emergent operation for perforated bowel. METHODS: Using the American College of Surgeons National Surgical Quality Improvement database, years 2007 to 2017, all geriatric patients (age ≥65 y) who underwent emergency surgery and who had a postoperative diagnosis of bowel perforation were included. Univariate and multivariable analyses were used to identify independent predictors of 30-d mortality. RESULTS: A total of 8981 patients were included. The median (interquartile range) age was 75 y (69, 82), and 59.0% were female. Twenty-one percent of patients were partially or totally dependent, and 25.2% were admitted from sources other than home. Overall, 30-d mortality rate was 22.1%. Independent predictors of mortality included the following: age 70-79 y (odds ratio [OR]: 1.59, P < 0.001), age ≥80 y (OR: 3.23, P < 0.001), American Society of Anesthesiologists ≥3 (OR: 4.74, P < 0.001), admission from chronic care facility (OR: 1.61, P < 0.001), being partially or totally dependent (OR: 1.50, P < 0.001), chronic steroid use (OR: 1.36, P < 0.001), and preoperative septic shock (OR: 3.74, P < 0.001). Having immediate fascial closure was protective against mortality (immediate fascial closure only, OR: 0.55, P < 0.001; -immediate closure of all surgical site layers, OR: 0.44, P < 0.001). CONCLUSIONS: In geriatric patients, functional status and chronic steroid therapy play an important role in determining survival following surgery for bowel perforation. These factors should be considered during preoperative counseling and decision-making.

Factors that Predict Survival From Mesenteric Ischemia in the Geriatric Patient: Not a Death Sentence.

BACKGROUND: The mortality rate from mesenteric ischemia is reported to be as high as 80%. The goal of our study was to identify demographic and clinical predictors of post-operative mortality and discharge disposition among elderly patients with mesenteric ischemia. METHODS: All patients 65 years and older who underwent emergency surgery (ES) for the management of mesenteric ischemia in the American College of Surgeons-National Surgical Quality Improvement Program database from 2007 to 2017 were included. Univariate analyses and logistic regressions were used to identify independent predictors of mortality and discharge disposition. RESULTS: A total of 2438 patients met inclusion criteria, with a median age of 77 years and 60.8% being female. The 30-day mortality of the overall cohort was 31.5% and the 30-day morbidity was 65.3%. The following were the major predictors of 30-day mortality: pre-operative diagnosis of septic shock [OR: 2.46, (95% CI: 1.94-3.13)], dialysis dependence [OR: 2.05, (95% CI: 1.45-2.90)], recent weight loss [OR: 1.80, (95% CI: 1.16-2.79)], age ≥80 years [OR: 1.67, (95% CI: 1.25-2.23)], and ventilator dependence [OR: 1.65, (95% CI: 1.23-2.23)]. In the absence of these predictors, survival rate was 84%. The major predictors of discharge to post-acute care (PAC) included age ≥80 years [OR: 3.70, (95% CI: 2.50-5.47)] and pre-operative septic shock [OR: 2.20, (95% CI: 1.42-3.41)]. CONCLUSION: In the geriatric patient, a diagnosis of mesenteric ischemia does not equate to an automatic death sentence. The presence of certain pre-operative risk factors confers a high risk of mortality, whereas their absence is associated with a high chance of survival.

Underuse and Variability in Substance Use Screening Among Adult Trauma Patients in the U.S.: A Nationwide Retrospective Cohort Study.

OBJECTIVE: To characterize the rates and variability in substance screening among adult trauma patients in the U.S. SUMMARY BACKGROUND DATA: Emergency Department trauma visits provide a unique opportunity to identify patients with substance use disorders. Despite the existence of screening guidelines, underscreening and variability in screening practices remain. METHODS: Retrospective cohort study including adult trauma patients (18- 64-year-old) from the ACS-TQIP 2017-18 database. Multivariable logistic regressions were performed to adjust for demographics, clinical, and facility factors, and marginal probabilities were calculated using these multivariable models. The primary outcomes were substance screening and positivity, which were defined relative to the observation-weighted grand mean (mean). RESULTS: 2,048,176 patients were contained in the TQIP dataset, 809,878 (39.5%) were screened for alcohol (20.8% positive), and 617,129 (30.1%) were screened for drugs (37.3% positive). After all exclusion criteria were applied, 765,897 patients were included in the analysis, 394,391 (52.9%) were screened for alcohol (22.1% tested positive), and 279,531 (36.5%) were screened for drugs (44.3% tested positive). Among the patients included in our study, significant variability in screening rates existed with respect to demo-graphic, trauma mechanism, injury severity, and facility factors. Furthermore, in several cases, patient subpopulations who were less likely to be screened were in fact more likely to screen positive or vice versa. CONCLUSIONS: Effective substance-screening guidelines should be predicated on achieving universal screening. Current lapses in screening, along with the observed variability, likely affect different patient populations in disparate manners and lead to both under-detection as well as waste of valuable resources.

Complicated Abdominal Wall Hernias in the Elderly: Time Is Life and Comorbidities Matter.

BACKGROUND: Abdominal wall hernias represent a common problem that can present as surgical emergencies with increased morbidity and mortality. The data examining outcomes in elderly patients with hernia emergencies is scant. METHODS: The 2007-2017 ACS-NSQIP database was queried. Patients ≥65 years old with a diagnosis of acute complicated abdominal wall hernia were included. Univariable and multivariable analyses were used to identify independent predictors of 30-day mortality and surgical site infection (SSI). RESULTS: Main predictors of 30-day mortality were admission from nursing home or chronic care facility (OR = 1.62, 95% CI: 1.10-2.38, P = .014), transfer from outside ED (OR = 1.81, 95% CI: 1.31-2.51, P < .001), days from admission to operation (OR = 1.05, 95% CI: 1.02-1.08, P = .002), recent significant weight loss (OR = 1.95, 95% CI: 1.12-3.37, P = .018), pre-operative septic shock (OR = 4.13, 95% CI: 2.44-6.99, P < .001), ventilator dependence (OR = 2.50, 95% CI: 1.29-4.81, P = .006), and ASA status. When compared to open repair, laparoscopic repair emerged as protective against SSI (OR = .34, 95% CI: .17-.66, P = .001). Bowel resection (OR = 2.15, 95% CI: 1.63-2.84, P < .001) and increasing wound class were risk factors for SSI. CONCLUSION: In the elderly patient presenting with an acute complicated abdominal wall hernia, time to surgery is crucial for survival, and comorbidities influence outcome. Laparoscopy is an option in management due to its decreased risk of surgical site infection without increased mortality, whenever patient factors are favorable for this approach.

Revisiting abdominal closure in mesenteric ischemia: is there an association with outcome?

PURPOSE: Current guidelines advocate liberal use of delayed abdominal closure in patients with acute mesenteric ischemia (AMI) undergoing laparotomy. Few studies have systematically examined this practice. The goal of this study was to evaluate the effect of delayed abdominal closure on postoperative morbidity and mortality in patients with AMI. METHODS: We performed a retrospective cohort study of the ACS-NSQIP 2013-2017 registry. We included patients with a diagnosis of AMI undergoing emergency laparotomy. Patients were divided into two groups based on the type of abdominal closure: (1) delayed fascial closure (DFC) when no layers of the abdominal wall were closed and (2) immediate fascial closure (IFC) if deep layers or all layers of the abdominal wall were closed. Propensity score matching was performed based on comorbidities, pre-operative, and operative characteristics. Univariable analysis was performed on the matched sample. RESULTS: The propensity-matched cohort consisted of 1520 patients equally divided into the DFC and IFC groups. The median (IQR) age was 68 (59-77), and 836 (55.0%) were female. Compared to IFC, the DFC group showed increased in-hospital mortality (38.9% vs. 31.6%, p = 0.002), 30-day mortality (42.4% vs. 36.3%, p = 0.012), and increased risk of respiratory failure (59.5% vs. 31.2%, p < 0.001). CONCLUSIONS: The delayed fascial closure technique was associated with increased mortality compared to immediate fascial closure. These findings do not support the blanket incorporation of delayed closure in mesenteric ischemia care or its previously advocated liberal use.

Balanced blood component resuscitation in trauma: Does it matter equally at different transfusion volumes?

BACKGROUND: It remains unclear whether the association between balanced blood component transfusion and lower mortality is generalizable to trauma patients receiving varying transfusion volumes. We sought to study the role red blood cell transfusion volume plays in the relationships between red blood cell:platelet and red blood cell:fresh frozen plasma ratios and 4-hour mortality. METHODS: Adult patients in the 2013 to 2018 American College of Surgeons Trauma Quality Improvement Program database receiving ≥6 red blood cell, ≥1 platelet, and ≥1 fresh frozen plasma within 4 hours were included. The following 4 cohorts were defined based on 4-hour red blood cell transfusion volume: (1) 6 to 10 units, (2) 11 to 15 units, (3) 16 to 20 units, and (4) >20 units. The association between red blood cell:fresh frozen plasma, red blood cell:platelet, and 4-hour mortality was evaluated discretely for each red blood cell transfusion volume category, statistically adjusting for confounders. RESULTS: A total of 14,549 patients were included. In patients receiving 6 to 10 units of red blood cells, red blood cell:platelet ratios were not associated with 4-hour mortality, and only red blood cell:fresh frozen plasma ≥4:1 were associated with significantly higher odds of 4-hour mortality compared to 1:1. For patients receiving >10 red blood cell units, increasing red blood cell:platelet and red blood cell:fresh frozen plasma ratios were consistently associated with increased odds of 4-hour mortality. For example, in red blood cell volumes of 11 to 15, 16 to 20, and >20 units, risk-adjusted 4-hour mortality odds ratios for red blood cell:platelet ≥4:1 were 2.27 (1.47-3.51), 3.32 (2.26-4.90), and 3.01 (2.33-3.88), respectively. CONCLUSION: The association between balanced blood component transfusion and 4-hour mortality is not homogenous in trauma patients requiring different transfusion volumes and is specifically less evident in patients receiving lower volumes. Such findings should be considered in the current and future blood shortage crises across the nation.

Timing and choice of systemic anticoagulation in the setting of extremity arterial injury repair.

PURPOSE: The role of perioperative anticoagulation in the setting of peripheral arterial injury remains unclear. We hypothesized that early initiation of anticoagulation is associated with a reduced amputation rate without increasing bleeding complications. METHODS: Using the 2016-2019 ACS-TQIP database, adult patients with upper and lower extremity vascular injuries who underwent open arterial repair and received anticoagulation were included. Patients were divided into two groups: (1) early venous thromboembolism prophylaxis (≤ 24 h) and (2) late prophylaxis (> 24 h) following arterial repair. The primary outcomes were the rates of limb amputation and bleeding complications. Multivariable logistic regression was used to estimate the impact of timing and type of anticoagulation on the rates of limb amputation and bleeding complications. RESULTS: 4379 patients were included, and 83.9% were males. 68.1% of patients received early anticoagulation, whereas 31.9% received late thromboprophylaxis. Low-molecular-weight heparin (LMWH) was used in 62.0% of patients, and unfractionated heparin (UFH) was administered in 34.3% of patients. Multivariable analysis showed that late initiation of thromboprophylaxis (OR = 1.69 [1.16-2.45], p = 0.006) and use of UFH (OR = 2.61 [1.80-3.79], p < 0.001) were associated with increased rate of amputation. Early initiation of anticoagulation (OR = 2.16 [1.63-2.85], p < 0.001) was associated with increased risk of bleeding complications requiring blood transfusions. Similarly, the use of UFH was associated with a higher rate of bleeding events compared to LWMH (OR = 2.61, [1.80-3.79], p < 0.001). CONCLUSION: Patients with the operative repair of arterial injuries receiving early perioperative anticoagulation demonstrated an improved limb salvage outcome than those who received late thromboprophylaxis. Our data also suggest that early initiation of prophylaxis may be associated with increased bleeding risk, which may be attenuated using LMWH compared to UFH.

The use of POTTER (Predictive Optimal Trees in Emergency Surgery Risk) calculator to predict mortality and complications in patients submitted to Emergency Surgery / O uso do aplicativo POTTER (Predictive Optimal Trees in Emergency Surgery Risk) para prever mortalidade e complicações em pacientes submetidos à cirurgia de emergência

ABSTRACT Introduction: the ability of the care team to reliably predict postoperative risk is essential for improvements in surgical decision-making, patient and family counseling, and resource allocation in hospitals. The Artificial Intelligence (AI)-powered POTTER (Predictive Optimal Trees in Emergency Surgery Risk) calculator represents a user-friendly interface and has since been downloaded in its iPhone and Android format by thousands of surgeons worldwide. It was originally developed to be used in non-traumatic emergency surgery patients. However, Potter has not been validated outside the US yet. In this study, we aimed to validate the POTTER calculator in a Brazilian academic hospital. Methods: mortality and morbidity were analyzed using the POTTER calculator in both trauma and non-trauma emergency surgery patients submitted to surgical treatment between November 2020 and July 2021. A total of 194 patients were prospectively included in this analysis. Results: regarding the presence of comorbidities, about 20% of the population were diabetics and 30% were smokers. A total of 47.4% of the patients had hypertensive prednisone. After the analysis of the results, we identified an adequate capability to predict 30-day mortality and morbidity for this group of patients. Conclusion: the POTTER calculator presented excellent performance in predicting both morbidity and mortality in the studied population, representing an important tool for surgical teams to define risks, benefits, and outcomes for the emergency surgery population.

RESUMO Introdução: a capacidade da equipe de atendimento de prever de forma confiável o risco pós-operatório é essencial para melhorar a tomada de decisões cirúrgicas, o aconselhamento ao paciente e à família e a alocação de recursos nos hospitais. A calculadora POTTER (Predictive Optimal Trees in Emergency Surgery Risk), alimentada por inteligência artificial (IA) e com uma interface amigável, foi baixada em seu formato para iPhone e Android por milhares de cirurgiões em todo o mundo e foi originalmente desenvolvida para ser usada em pacientes de cirurgia de emergência não traumática. No entanto, a POTTER ainda não foi validada fora dos EUA. Neste estudo, nosso objetivo foi validar a calculadora POTTER em um hospital acadêmico brasileiro. Métodos: a mortalidade e a morbidade foram analisadas usando a calculadora POTTER em pacientes de cirurgia de emergência com e sem trauma submetidos a tratamento cirúrgico entre novembro de 2020 e julho de 2021. Um total de 194 pacientes foi incluído prospectivamente nessa análise. Resultados: Em relação à presença de comorbidades, cerca de 20% da população era diabética e 30%, fumante. Um total de 47,4% dos pacientes eram hipertensos antes da admissão. Após a análise dos resultados, identificamos uma capacidade adequada de prever a mortalidade e a morbidade em 30 dias para esse grupo de pacientes. Conclusão: a calculadora POTTER apresentou um excelente desempenho para prever a morbidade e a mortalidade na população estudada, representando uma ferramenta importante para as equipes cirúrgicas definirem riscos, benefícios e resultados para a população de cirurgia de emergência.

Mesenteric Ischemia in Patients with Coronavirus 2019: A Scoping Review.

Background: Coronavirus 2019 (COVID-19) is a systemic disease associated with severe gastrointestinal complications including life-threatening mesenteric ischemia. We sought to review and summarize the currently available literature on the presentation, management, and outcomes of mesenteric ischemia in patients with COVID-19. Patients and Methods: The PubMed database was searched to identify studies published between January 2020 and January 2021 that reported one or more adult (≥18 years) patients with COVID-19 who developed mesenteric ischemia during hospitalization. The demographic characteristics, clinical and imaging findings, management, and outcomes of patients from each study were extracted and summarized. Results: A total of 35 articles reporting on 61 patients with COVID-19 with mesenteric ischemia met the eligibility and were included in our study. The mean age was 60 (±15.9) years, and 53% of patients were male. Imaging findings of these patients included mesenteric arterial or venous thromboembolism, followed by signs of mesenteric ischemia. Sixty-seven percent of patients were taken to the operating room for an exploratory laparotomy and bowel resection and 21% were managed conservatively. The terminal ileum was the most commonly involved area of necrosis (26%). The mortality rate of patients with COVID-19 with mesenteric ischemia was 33%, and the most common cause of death was multiorgan failure or refractory septic shock. Twenty-seven percent of patients managed operatively died during the post-operative period. Conclusions: Mesenteric ischemia in patients with COVID-19 is a devastating complication associated with a high rate of morbidity and mortality. Further efforts should focus on developing strategies for early recognition and management.

The variation of opioid prescription after injury and its association with long-term chronic pain: A multicenter cohort study.

BACKGROUND: Opioid overprescription in trauma contributes to the opioid epidemic through diversion of unused pills. Through our study, we sought to do the following: (1) understand the variation in opioid prescription after injury and its relationship to patient and/or clinical variables, and (2) study the relationship between opioid prescribing and long-term pain and analgesic use. METHOD: Trauma patients with an injury severity score ≥9 admitted to 3 level 1 trauma centers were screened for chronic pain and analgesic use 6 to 12 months postinjury. First, multivariable linear regression models were constructed with "oral morphine equivalents" and "number of opioid pills prescribed" at discharge as dependent variables. The coefficients of determination were calculated to determine how much of the variation in opioid prescription was explained by patient and clinical variables. Second, a multivariable logistic regression analysis was created to study the association between opioid prescription at discharge and chronic pain/analgesic use at 6 to 12 months. Analyses were adjusted for patient demographics, socioeconomics, comorbidities, injury parameters, and hospital course. RESULTS: Of the 2,702 patients included (mean [standard deviation] age: 61.0 [21.5]; 55% males), 74% were prescribed opioids at discharge (mean number of pills [standard deviation]: 24.0 [26.5]; mean oral morphine equivalent [standard deviation]: 204.8 [348.1]). The adjusted coefficients of determination for oral morphine equivalents and number of pills was 0.12 and 0.21, respectively, suggesting that the measured patient and clinical factors explain <21% of the variation in opioid prescribing in trauma. Patients prescribed opioids were more likely to have chronic pain (odds ratio [95%] confidence interval: 1.34 [1.05-1.71]) and use analgesics daily (odds ratio [95%] confidence interval: 1.86 [1.25-2.77]) 6 to 12 months postinjury. CONCLUSION: The variation in opioid prescription after traumatic injury is more affected by system and provider level rather than clinical or patient-related factors, and opioid prescribing correlates independently with long-term chronic pain and continued analgesic use postinjury. Efforts to decrease opioid use should prioritize standardizing prescription practices after traumatic injury.