Pediatric Trauma Center Access, Regional Injury Burden, and Socioeconomic Disadvantage.

This cross-sectional study assesses whether populations in socioeconomically disadvantaged regions in the US lack timely access to pediatric trauma centers.

Career Trajectory After General Surgery Residency: Do Academic Program Graduates Pursue Academic Surgery?

OBJECTIVE: Determine the proportion of contemporary US academic general surgery residency program graduates who pursue academic careers and identify factors associated with pursuing academic careers. SUMMARY BACKGROUND DATA: Many academic residency programs aim to cultivate academic surgeons, yet the proportion of contemporary graduates who choose academic careers is unclear. The potential determinants that affect graduates' decisions to pursue academic careers remain underexplored. METHODS: We collected program and individual-level data on 2015 and 2018 graduates across 96 US academic general surgery residency programs using public resources. We defined those pursuing academic careers as faculty within US allopathic medical school-affiliated surgery departments who published two or more peer-reviewed publications as the first or senior author between 2020-2021. After variable selection using sample splitting LASSO regression, multivariable regression evaluated association with pursuing academic careers among all graduates, and graduates of top-20 residency programs. Secondary analysis using multivariable ordinal regression explored factors associated with high research productivity during early faculty years. RESULTS: Among 992 graduates, 166 (17%) were pursuing academic careers according to our definition. Graduating from a top-20 ranked residency program (OR[95%CI]: 2.34[1.40-3.88]), working with a longitudinal research mentor during residency (OR[95%CI]: 2.21[1.24-3.95]), holding an advanced degree (OR[95%CI]: 2.20[1.19-3.99]), and the number of peer-reviewed publications during residency as first or senior author (OR[95%CI]: 1.13[1.07-1.20]) were associated with pursuing an academic surgery career, while the number of peer-reviewed publications before residency was not (OR[95%CI]: 1.08[0.99-1.20]). Among top 20 program graduates, working with a longitudinal research mentor during residency (OR[95%CI]: 0.95[0.43-2.09]) was not associated with pursuing an academic surgery career. The number of peer-reviewed publications during residency as first or senior author was the only variable associated with higher productivity during early faculty years (OR[95%CI]: 1.12[1.07-1.18]). CONCLUSIONS: Our findings suggest programs that aim to graduate academic surgeons may benefit from ensuring trainees receive infrastructural support and demonstrate sustained commitment to research throughout residency. Our results should be interpreted cautiously as the impact of unmeasured confounders is unclear.

Management of Uncomplicated Appendicitis in Adults: A Nationwide Analysis From 2018 to 2019.

INTRODUCTION: Nonoperative management (NOM) of uncomplicated appendicitis (UA) has been increasingly utilized in recent years. The aim of this study was to describe nationwide trends of sociodemographic characteristics, outcomes, and costs of patients undergoing medical versus surgical management for UA. METHODS: The 2018-2019 National (Nationwide) Inpatient Sample was queried for adults (age ≥18 y) with UA; diagnosis, as well as laparoscopic and open appendectomy, were defined by the International Classification of Diseases, 10th Revision, Clinical Modification codes. We examined several characteristics, including cost of care and length of hospital stay. RESULTS: Among the 167,125 patients with UA, 137,644 (82.4%) underwent operative management and 29,481 (17.6%) underwent NOM. In bivariate analysis, we found that patients who had NOM were older (53 versus 43 y, P < 0.001) and more likely to have Medicare (33.6% versus 16.1%, P < 0.001), with higher prevalence of comorbidities such as diabetes (7.8% versus 5.5%, P < 0.001). The majority of NOM patients were treated at urban teaching hospitals (74.5% versus 66.3%, P < 0.001). They had longer LOS's (5.4 versus 2.3 d, P < 0.001) with higher inpatient costs ($15,584 versus $11,559, P < 0.001) than those who had an appendectomy. Through logistic regression we found that older patients had up to 4.03-times greater odds of undergoing NOM (95% CI: 3.22-5.05, P < 0.001). CONCLUSIONS: NOM of UA is more commonly utilized in patients with comorbidities, older age, and those treated in teaching hospitals. This may, however, come at the price of longer length of stay and higher costs. Further guidelines need to be developed to clearly delineate which patients could benefit from NOM.

Firearm-Related Injuries and the US Opioid and Other Substance Use Epidemic: A Nationwide Evaluation of Emergency Department Encounters.

INTRODUCTION: There has been a sharp climb in the Unites States' death rate among opioid and other substance abuse patients, as well as an increased prevalence in gun violence. We aimed to investigate the association between substance abuse and gun violence in a national sample of patients presenting to US emergency departments (EDs). METHODS: We queried the 2018-2019 Nationwide Emergency Department Sample for patients ≥18 years with substance abuse disorders (opioid and other) using International Classification of Diseases, 10th Revision, Clinical Modification codes. Within this sample, we analyzed characteristics and outcomes of patients with firearm-related injuries. The primary outcome was mortality; secondary outcomes were ED charges and length of stay. RESULTS: Among the 25.2 million substance use disorder (SUD) patients in our analysis, 35,306 (0.14%) had a firearm-related diagnosis. Compared to other SUD patients, firearm-SUD patients were younger (33.3 versus 44.7 years, P < 0.001), primarily male (88.6% versus 54.2%, P < 0.001), of lower-income status (0-25th percentile income: 56.4% versus 40.5%, P < 0.001), and more likely to be insured by Medicaid or self-pay (71.6% versus 53.2%, P < 0.001). Firearm-SUD patients had higher mortality (1.4% versus 0.4%, P < 0.001), longer lengths of stay (6.5 versus 4.9 days, P < 0.001), and higher ED charges ($9269 versus $5,164, P < 0.001). Firearm-SUD patients had a 60.3% rate of psychiatric diagnoses. Firearm-SUD patients had 5.5 times greater odds of mortality in adjusted analyses (adjusted odds ratio: 5.5, P < 0.001). CONCLUSIONS: Opioid-substance abuse patients with firearm injuries have higher mortality rates and costs among these groups, with limited discharge to postacute care resources. All these factors together point to the urgent need for improved screening and treatment for this vulnerable group of patients.

Impact of Medicaid Expansion and Firearm Legislation on Cost of Firearm Injuries.

INTRODUCTION: Firearm injury-related hospitalizations in the U.S. cost $900 million annually. Before the Affordable Care Act, government insurance programs covered 41% of the costs. This study describes the impact of Affordable Care Act Medicaid expansion and state-level firearm legislation on coverage and costs for firearm injuries. METHODS: This cross-sectional study included 35,854,586 hospitalizations from 27 states in 2013 and 2016. Data analyses were performed in 2022. Firearm injuries were classified by mechanism: assault, unintentional, self-harm, or undetermined. The impact of the Affordable Care Act expansion was determined using difference-in-differences analysis. Differences in per capita costs between states with stronger and weak firearm legislation were compared using univariable and multivariable analyses. RESULTS: The authors identified 31,451 initial firearm injury-related hospitalizations. In states with weak firearm legislation, hospitalization costs per 100,000 residents were higher from unintentional ($25,834; p=0.04) and self-inflicted ($11,550; p=0.02) injuries; there were no state-level differences in assault or total per capita firearm-related hospitalization costs. Affordable Care Act expansion increased government coverage of costs by 15 percentage points (95% CI=3, 29) and decreased costs to uninsured/self-pay by 14 percentage points (95% CI=6, 21). In 2016, states with weak firearm legislation and no Affordable Care Act expansion had the highest proportion of hospitalization costs attributed to uninsured/self-pay patients (24%, 95% CI=15, 34). CONCLUSIONS: Affordable Care Act expansion increased government coverage of hospitalizations for firearm injuries. Unintentional and self-harm costs were significantly higher for states with weak firearm legislation. States with weak firearm legislation that did not expand Medicaid had the highest proportion of uninsured/self-pay patients.

Development and Initial Performance of the Hospital Mental Health Risk Screen.

BACKGROUND: Patients hospitalized after emergency care are at risk for later mental health problems such as depression, anxiety, and posttraumatic stress disorder symptoms. The American College of Surgeons Committee on Trauma standards for verification require Level I and II trauma centers to screen patients at high risk for mental health problems. This study aimed to develop and examine the performance of a novel mental health risk screen for hospitalized patients based on samples that reflect the diversity of the US population. STUDY DESIGN: We studied patients admitted after emergency care to 3 hospitals that serve ethnically, racially, and socioeconomically diverse populations. We assessed risk factors during hospitalization and mental health symptoms at follow-up. We conducted analyses to identify the most predictive risk factors, selected items to assess each risk, and determined the fewest items needed to predict mental health symptoms at follow-up. Analyses were conducted for the entire sample and within 5 ethnic and racial subgroups. RESULTS: Among 1,320 patients, 10 items accurately identified 75% of patients who later had elevated levels of mental health symptoms and 71% of those who did not. Screen performance was good to excellent within each of the ethnic and racial groups studied. CONCLUSIONS: The Hospital Mental Health Risk Screen accurately predicted mental health outcomes overall and within ethnic and racial subgroups. If performance is replicated in a new sample, the screen could be used to screen patients hospitalized after emergency care for mental health risk. Routine screening could increase health and mental health equity and foster preventive care research and implementation.

Development and Validation of a Model to Quantify Injury Severity in Real Time.

Importance: Quantifying injury severity is integral to trauma care benchmarking, decision-making, and research, yet the most prevalent metric to quantify injury severity-Injury Severity Score (ISS)- is impractical to use in real time. Objective: To develop and validate a practical model that uses a limited number of injury patterns to quantify injury severity in real time through 3 intuitive outcomes. Design, Setting, and Participants: In this cohort study for prediction model development and validation, training, development, and internal validation cohorts comprised 223 545, 74 514, and 74 514 admission encounters, respectively, of adults (age ≥18 years) with a primary diagnosis of traumatic injury hospitalized more than 2 days (2017-2018 National Inpatient Sample). The external validation cohort comprised 3855 adults admitted to a level I trauma center who met criteria for the 2 highest of the institution's 3 trauma activation levels. Main Outcomes and Measures: Three outcomes were hospital length of stay, probability of discharge disposition to a facility, and probability of inpatient mortality. The prediction performance metric for length of stay was mean absolute error. Prediction performance metrics for discharge disposition and inpatient mortality were average precision, precision, recall, specificity, F1 score, and area under the receiver operating characteristic curve (AUROC). Calibration was evaluated using calibration plots. Shapley addictive explanations analysis and bee swarm plots facilitated model explainability analysis. Results: The Length of Stay, Disposition, Mortality (LDM) Injury Index (the model) comprised a multitask deep learning model trained, developed, and internally validated on a data set of 372 573 traumatic injury encounters (mean [SD] age = 68.7 [19.3] years, 56.6% female). The model used 176 potential injuries to output 3 interpretable outcomes: the predicted hospital length of stay, probability of discharge to a facility, and probability of inpatient mortality. For the external validation set, the ISS predicted length of stay with mean absolute error was 4.16 (95% CI, 4.13-4.20) days. Compared with the ISS, the model had comparable external validation set discrimination performance (facility discharge AUROC: 0.67 [95% CI, 0.67-0.68] vs 0.65 [95% CI, 0.65-0.66]; recall: 0.59 [95% CI, 0.58-0.61] vs 0.59 [95% CI, 0.58-0.60]; specificity: 0.66 [95% CI, 0.66-0.66] vs 0.62 [95%CI, 0.60-0.63]; mortality AUROC: 0.83 [95% CI, 0.81-0.84] vs 0.82 [95% CI, 0.82-0.82]; recall: 0.74 [95% CI, 0.72-0.77] vs 0.75 [95% CI, 0.75-0.76]; specificity: 0.81 [95% CI, 0.81-0.81] vs 0.76 [95% CI, 0.75-0.77]). The model had excellent calibration for predicting facility discharge disposition, but overestimated inpatient mortality. Explainability analysis found the inputs influencing model predictions matched intuition. Conclusions and Relevance: In this cohort study using a limited number of injury patterns, the model quantified injury severity using 3 intuitive outcomes. Further study is required to evaluate the model at scale.

TraumaICDBERT, A Natural Language Processing Algorithm to Extract Injury ICD-10 Diagnosis Code from Free Text.

OBJECTIVE: To develop and validate TraumaICDBERT, a natural language processing algorithm to predict injury ICD-10 diagnosis codes from trauma tertiary survey notes. SUMMARY BACKGROUND DATA: The adoption of ICD-10 diagnosis codes in clinical settings for injury prediction is hindered by the lack of real-time availability. Existing natural language processing algorithms have limitations in accurately predicting injury ICD-10 diagnosis codes. METHODS: Trauma tertiary survey notes from hospital encounters of adults between January 2016 and June 2021 were used to develop and validate TraumaICDBERT, an algorithm based on BioLinkBERT. The performance of TraumaICDBERT was compared to Amazon Web Services Comprehend Medical, an existing natural language processing tool. RESULTS: A dataset of 3,478 tertiary survey notes with 15,762 4-character injury ICD-10 diagnosis codes was analyzed. TraumaICDBERT outperformed Amazon Web Services Comprehend Medical across all evaluated metrics. On average, each tertiary survey note was associated with 3.8 (standard deviation: 2.9) trauma registrar-extracted 4-character injury ICD-10 diagnosis codes. CONCLUSIONS: TraumaICDBERT demonstrates promising initial performance in predicting injury ICD-10 diagnosis codes from trauma tertiary survey notes, potentially facilitating the adoption of downstream prediction tools in clinical settings.

Mental health symptoms are comparable in patients hospitalized with acute illness and patients hospitalized with injury.

BACKGROUND: High rates of mental health symptoms such as depression, anxiety, and posttraumatic stress disorder (PTSD) have been found in patients hospitalized with traumatic injuries, but little is known about these problems in patients hospitalized with acute illnesses. A similarly high prevalence of mental health problems in patients hospitalized with acute illness would have significant public health implications because acute illness and injury are both common, and mental health problems of depression, anxiety, and PTSD are highly debilitating. METHODS AND FINDINGS: In patients admitted after emergency care for Acute Illness (N = 656) or Injury (N = 661) to three hospitals across the United States, symptoms of depression, anxiety, and posttraumatic stress were compared acutely (Acute Stress Disorder) and two months post-admission (PTSD). Patients were ethnically/racially diverse and 54% female. No differences were found between the Acute Illness and Injury groups in levels of any symptoms acutely or two months post-admission. At two months post-admission, at least one symptom type was elevated for 37% of the Acute Illness group and 39% of the Injury group. Within racial/ethnic groups, PTSD symptoms were higher in Black patients with injuries than for Black patients with acute illness. A disproportionate number of Black patients had been assaulted. CONCLUSIONS: This study found comparable levels of mental health sequelae in patients hospitalized after emergency care for acute illness as in patients hospitalized after emergency care for injury. Findings of significantly higher symptoms and interpersonal violence injuries in Black patients with injury suggest that there may be important and actionable differences in mental health sequelae across ethnic/racial identities and/or mechanisms of injury or illness. Routine screening for mental health risk for all patients admitted after emergency care could foster preventive care and reduce ethnic/racial disparities in mental health responses to acute illness or injury.

The relationship and predictive value of dementia and frailty for mortality in patients with surgically managed hip fractures.

BACKGROUND: Both dementia and frailty have been associated with worse outcomes in patients with hip fractures. However, the interrelation and predictive value of these two entities has yet to be clarified. The current study aimed to investigate the predictive relationship between dementia, frailty, and in-hospital mortality after hip fracture surgery. METHODS: All patients registered in the 2019 National Inpatient Sample Database who were 50 years or older and underwent emergency hip fracture surgery following a traumatic fall were eligible for inclusion. Logistic regression (LR) models were constructed with in-hospital mortality as the response variables. One model was constructed including markers of frailty and one model was constructed excluding markers of frailty [Orthopedic Frailty Score (OFS) and weight loss]. The feature importance of all variables was determined using the permutation importance method. New LR models were then fitted using the top ten most important variables. The area under the receiver-operating characteristic curve (AUC) was used to compare the predictive ability of these models. RESULTS: An estimated total of 216,395 patients were included. Dementia was the 7th most important variable for predicting in-hospital mortality. When the OFS and weight loss were included, they replaced dementia in importance. There was no significant difference in the predictive ability of the models when comparing the model that included markers of frailty [AUC for in-hospital mortality (95% CI) 0.79 (0.77-0.81)] with the model that excluded markers of frailty [AUC for in-hospital mortality (95% CI) 0.79 (0.77-0.80)]. CONCLUSION: Dementia functions as a surrogate for frailty when predicting in-hospital mortality in hip fracture patients. This finding highlights the importance of early frailty screening for improvement of care pathways and discussions with patients and their families in regard to expected outcomes.

For-Profit Status and Geographic Distribution of Trauma Centers in the US.

This cohort study assesses geographic distribution of for-profit and not-for-profit trauma centers in the US designated by their states between 2014 and 2018.

The acute care surgery model and elective surgery.

ABSTRACT: Two senior surgeons with active elective surgery practices call on their personal experiences to encourage acute care surgery programs to explore ways to incorporate elective surgery into their practice models. Although there are obstacles, these are not insurmountable problems, potential solutions exist, and this may help protect against burnout.

Validation of the orthopedic frailty score for measuring frailty in hip fracture patients: a cohort study based on the United States National inpatient sample.

BACKGROUND: The Orthopedic Frailty Score (OFS) has been proposed as a tool for measuring frailty in order to predict short-term postoperative mortality in hip fracture patients. This study aims to validate the OFS using a large national patient register to determine its relationship with adverse outcomes as well as length of stay and cost of hospital stay. METHODS: All adult patients (18 years or older) registered in the 2019 National Inpatient Sample Database who underwent emergency hip fracture surgery following a traumatic fall were eligible for inclusion. The association between the OFS and mortality, complications, and failure-to-rescue (FTR) was determined using Poisson regression models adjusted for potential confounders. The relationship between the OFS and length of stay and cost of hospital stay was instead determined using a quantile regression model. RESULTS: An estimated 227,850 cases met the study inclusion criteria. There was a stepwise increase in the rate of complications, mortality, and FTR for each additional point on the OFS. After adjusting for potential confounding, OFS 4 was associated with an almost ten-fold increase in the risk of in-hospital mortality [adjusted IRR (95% CI): 10.6 (4.02-27.7), p < 0.001], a 38% increased risk of complications [adjusted IRR (95% CI): 1.38 (1.03-1.85), p = 0.032], and an almost 11-fold increase in the risk of FTR [adjusted IRR (95% CI): 11.6 (4.36-30.9), p < 0.001], compared to OFS 0. Patients with OFS 4 also required a day and a half additional care [change in median length of stay (95% CI): 1.52 (0.97-2.08), p < 0.001] as well as cost approximately $5,200 more to manage [change in median cost of stay (95% CI): 5166 (1921-8411), p = 0.002], compared to those with OFS 0. CONCLUSION: Patients with an elevated OFS display a substantially increased risk of mortality, complications, and failure-to-rescue as well as a prolonged and more costly hospital stay.

FasterRib: A deep learning algorithm to automate identification and characterization of rib fractures on chest computed tomography scans.

OBJECTIVE: Characterizing and enumerating rib fractures are critical to informing clinical decisions, yet in-depth characterization is rarely performed because of the manual burden of annotating these injuries on computed tomography (CT) scans. We hypothesized that our deep learning model, FasterRib , could predict the location and percentage displacement of rib fractures using chest CT scans. METHODS: The development and internal validation cohort comprised more than 4,700 annotated rib fractures from 500 chest CT scans within the public RibFrac. We trained a convolutional neural network to predict bounding boxes around each fracture per CT slice. Adapting an existing rib segmentation model, FasterRib outputs the three-dimensional locations of each fracture (rib number and laterality). A deterministic formula analyzed cortical contact between bone segments to compute percentage displacements. We externally validated our model on our institution's data set. RESULTS: FasterRib predicted precise rib fracture locations with 0.95 sensitivity, 0.90 precision, 0.92 f1 score, with an average of 1.3 false-positive fractures per scan. On external validation, FasterRib achieved 0.97 sensitivity, 0.96 precision, and 0.97 f1 score, and 2.24 false-positive fractures per scan. Our publicly available algorithm automatically outputs the location and percent displacement of each predicted rib fracture for multiple input CT scans. CONCLUSION: We built a deep learning algorithm that automates rib fracture detection and characterization using chest CT scans. FasterRib achieved the highest recall and the second highest precision among known algorithms in literature. Our open source code could facilitate FasterRib's adaptation for similar computer vision tasks and further improvements via large-scale external validation. LEVEL OF EVIDENCE: Diagnostic Tests/Criteria; Level III.

Ensuring excellence in patient care, research, and education: thoughts on leadership and teamwork.

There are many ways to develop your leadership skills and many ways to be an effective leader. This is one perspective. The best style is the one that works for you and your environment. I would encourage you to spend some time and effort exploring your leadership style, develop new leadership skills, and look for opportunities to serve others.

Developing an Inpatient Relationship Centered Communication Curriculum (I-RCCC) rounding framework for surgical teams.

BACKGROUND: Morning rounds by an acute care surgery (ACS) service at a level one trauma center are uniquely demanding, given the fast pace, high acuity, and increased patient volume. These demands notwithstanding, communication remains integral to the success of surgical teams. Yet there are limited published curricula that address trauma inpatient communication needs. Observations at our institution confirmed that the surgical team lacked a shared mental model for communication. We hypothesized that creating a relationship-centered rounding conceptual framework model would enhance the provider-patient experience. STUDY DESIGN: A mixed-methods approach was used for this study. A multi-pronged needs assessment was conducted. Provider communion items for Press Ganey and Hospital Consumer Assessment of Healthcare Providers and Systems (HCAHPS) surveys were used to measure patients' expressed needs. Faculty with experience in relationship-centered communication observed morning rounds and documented demonstrated behaviors. A five-hour workshop was designed based on the identified needs. A pre-and post-course Assessment and course evaluation were conducted. Provider-related patient satisfaction items were measured six months before the course and six months after the workshop. RESULTS: Needs assessment revealed a lack of a shared communication framework and a lack of leadership skills for senior trauma residents. Barriers included: time constraints, patient load, and interruptions during rounds. The curriculum was very well received. The self-reflected behaviors that demonstrated the most dramatic change between the pre and post-workshop surveys were: I listened without interrupting; I spoke clearly and at a moderate pace; I repeated key points; and I checked that the patient understood. All these changed from being performed by 50% of respondents "about half of the time" to 100% of them "always". Press Ganey top box likelihood to recommend (LTR) and provider-related top box items showed a trend towards improvement after implementing the training with a percentage difference of up to 20%. CONCLUSION: The Inpatient Relationship Centered Communication Curriculum (I-RCCC) targeting senior residents and Nurse Practitioners (NP) was feasible, practical, and well-received by participants. There was a trend of an increase in LTRs and provider-specific patient satisfaction items. This curriculum will be refined based on the study results and potentially scalable to other surgical specialties.

Insurance churn after adult traumatic injury: A national evaluation among a large private insurance database.

BACKGROUND: Traumatic injury leads to significant disability, with injured patients often requiring substantial health care resources to return to work and baseline health. Temporary disability or inability to work can result in changes or loss of employer-based private insurance coverage, which may significantly impact health care access and outcomes. Among privately insured patients, we hypothesized increased instability in insurance coverage for patients with higher severity of injury. METHODS: Adults 18 years and older presenting to a hospital with traumatic injury were evaluated for insurance churn using Clinformatics Data Mart private-payer claims. Insurance churn was defined as cessation of enrollment in the patient's private health insurance plan. Using Injury Severity Score (ISS), we compared insurance churn over the year following injury between patients with mild (ISS, <9), moderate (ISS, 9-15), severe (ISS, 16-24), and very severe (ISS, >24) injuries. Kaplan-Meier analysis was used to compare time with insurance churn by ISS category. Flexible parametric regression was used to estimate hazard ratios for insurance churn. RESULTS: Among 750,862 privately insured patients suffering from a traumatic injury, 50% experienced insurance churn within 1 year after injury. Compared with patients who remained on their insurance plan, patients who experienced insurance churn were younger and more likely male and non-White. The median time to insurance churn was 7.7 months for those with mild traumatic injury, 7.5 months for moderately or severely injured, and 7.1 months for the very severely injured. In multivariable analysis, increasing injury severity was associated with higher rates of insurance churn compared with mild injury, up to 14% increased risk for the very severely injured. CONCLUSION: Increasing severity of traumatic injury is associated with higher levels of health coverage churn among the privately insured. Lack of continuous access to health services may prolong recovery and further aggravate the medical and social impact of significant traumatic injury. LEVEL OF EVIDENCE: Economic and Value Based Evaluations; Level III.

A National Evaluation of Emergency General Surgery Outcomes Among Hospitalized Cardiac Patients.

INTRODUCTION: Emergency general surgery among cardiac surgery patients is increasingly common and consequential. We sought to characterize the true burden of emergency general surgery among hospitalized complex cardiac patients. METHODS: We performed a retrospective analysis of the 2016-2017 National Inpatient Sample. We included adult patients with a primary diagnosis of complex cardiac disease. We then compared patients who underwent emergency general surgery (GS-OR) with those who did not (non-GS-OR). The primary outcome was mortality; secondary outcomes included length of stay and hospitalization costs. RESULTS: We identified 10.2 million patients with a primary diagnosis of complex cardiac disease, of which 148,309 (1.4%) underwent GS-OR. Mortality rates were significantly higher in the GS-OR group (11.0% versus 5.0%, P < 0.001). Among all cardiac patients, GS-OR was associated with 2.2 times increased odds of death (aOR: 2.2, P < 0.001). GS-OR patients also had longer length of stays (14.1 versus 5.8 d, P < 0.001). Among all cardiac patients, GS-OR was associated with an 8.1-day longer length of stay (P < 0.001). GS-OR patients were less often routinely discharged home (31.7% versus 45.3%, P < 0.001) and incurred higher inpatient costs ($46,136 versus $16,303, P < 0.001). Among all cardiac patients, GS-OR patients incurred $30,102 higher hospitalization costs (P < 0.001). CONCLUSIONS: Emergency general surgery among cardiac surgery patients is associated with a greater than two-fold increase in mortality, longer length of stays, higher rates of nonroutine discharge, and higher hospitalization costs. Emergency general surgery complications account for 4.0% of total inpatient costs of cardiac surgery patients and merit further study.