Delivering Impactful Scientific Oral Presentations.

This Viewpoint highlights specific challenges of facing a scientific conference audience and provides practical recommendations to overcome these challenges.

The burden of readmissions after rib fractures among older adults.

BACKGROUND: The index hospitalization morbidity and mortality of rib fractures among older adults (aged ≥65 years) is well-known, yet the burden and risks for readmissions after rib fractures in this vulnerable population remain understudied. We aimed to characterize the burdens and etiologies associated with 3-month readmissions among older adults who suffer rib fractures. We hypothesized that readmissions would be common and associated with modifiable etiologies. METHODS: This survey-weighted retrospective study using the 2017 and 2019 National Readmissions Database evaluated adults aged ≥65 years hospitalized with multiple rib fractures and without major extrathoracic injuries. The main outcome was the proportion of patients experiencing all-cause 3-month readmissions. We assessed the 5 leading principal readmission diagnoses overall and delineated them by index hospitalization discharge disposition (home or facility). Sensitivity analysis using clinical classification categories characterized readmissions that could reasonably represent rib fracture-related sequelae. RESULTS: In 2017, 25,092 patients met the inclusion criteria, with 20% (N = 4,894) experiencing 3-month readmissions. Six percent of patients did not survive their readmission. The 5 leading principal readmission diagnoses were sepsis (many associated with secondary diagnoses of pneumonia [41%] or urinary tract infections [41%]), hypertensive heart/kidney disease, hemothorax, pneumonia, and respiratory failure. In 2019, a comparable 3-month readmission rate of 23% and identical 5 leading diagnoses were found. Principal readmission diagnosis of hemothorax was associated with the shortest time to readmission (median [interquartile range]:9 [5-23] days). Among patients discharged home after index hospitalization, pleural effusion-possibly representing mischaracterized hemothorax-was among the leading principal readmission diagnoses. Some patients readmitted with a principal diagnosis of hemothorax or pleural effusion had these diagnoses at index hospitalization; a lower proportion of these patients underwent pleural fluid intervention during index hospitalization compared with readmission. On sensitivity analysis, 30% of 3-month readmissions were associated with principal diagnoses suggesting rib fracture-related sequelae. CONCLUSION: Readmissions are not infrequent among older adults who suffer rib fractures, even in the absence of major extrathoracic injuries. Future studies should better characterize how specific complications associated with readmissions, such as pneumonia, urinary tract infections, and delayed hemothoraces, could be mitigated.

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.

Palliative Intervention for Malignant Bowel Obstruction Comes at a Cost: A National Inpatient Study.

Background: Malignant bowel obstruction (MBO) due to peritoneal carcinomatosis (PC) is associated with poor outcomes. Optimal management for palliation remains unclear. This study aims to characterize nonoperative, procedural, and operative management strategies for MBO and evaluate its association with mortality and cost.Materials and Methods: ICD-10 coding identified patient admissions from the 2018 to 2019 National Inpatient Sample (NIS) for MBO with PC from gastrointestinal or ovarian primary cancers. Management was categorized as nonoperative, procedural, or surgical. Multivariate analysis was used to associate treatment with mortality and cost.Results: 356,316 patient admissions were identified, with a mean age of 63 years. Gender, race, and insurance status were similar among groups. Length of stay (LOS) was longest in the surgical group (surgical: 17 days; procedural: 14 days; nonoperative: 7 days; P = .001). In comparison to nonoperative, procedural and surgical patients had statistically higher hospital charges, post-discharge medical needs, palliative care consults, and admission to rehab centers. Mortality was 7% in nonoperative, 9% in procedural, and 8% in surgical (P = .007) groups. In adjusted analyses, older age, palliative care consult, and non-Medicare payer status were associated with higher mortality. Compared to nonoperative, procedural and surgical groups resulted in increased costs (procedural: $17K more; surgical: $30K more).Conclusions: Admissions for procedural and surgical treatment of MBO are associated with increased LOS, hospital costs, and discharge needs. Optimal management remains challenging. Clinicians must examine all options prior to recommending palliative interventions given a trend towards higher resource utilization and mortality.

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.

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.

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.

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.

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.

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.

Disparities in detection of suspected child abuse.

BACKGROUND: Child abuse is a significant cause of injury and death among children, but accurate identification is often challenging. This study aims to assess whether racial disparities exist in the identification of child abuse. METHODS: The 2010-2014 and 2016-2017 National Trauma Data Bank was queried for trauma patients ages 1-17. Using ICD-9CM and ICD-10CM codes, children with injuries consistent with child abuse were identified and analyzed by race. RESULTS: Between 2010-2014 and 2016-2017, 798,353 patients were included in NTDB. Suspected child abuse victims (SCA) accounted for 7903 (1%) patients. Of these, 51% were White, 33% Black, 1% Asian, 0.3% Native Hawaiian/Other Pacific Islander, 2% American Indian, and 12% other race. Black patients were disproportionately overrepresented, composing 12% of the US population, but 33% of SCA patients (p < 0.001). Although White SCA patients were more severely injured (ISS 16-24: 20% vs 16%, p < 0.01) and had higher in-hospital mortality (9% vs. 6%, p = 0.01), Black SCA patients were hospitalized longer (7.2 ± 31.4 vs. 6.2 ± 9.9 days, p < 0.01) despite controlling for ISS (1-15: 4. 5.7 ± 35.7 vs. 4.2 ± 6.2 days, p < 0.01). In multivariate regression, Black children continued to have longer lengths of stay despite controlling for ISS and insurance type. CONCLUSIONS: Utilizing a nationally representative dataset, Black children were disproportionately identified as potential victims of abuse. They were also subjected to longer hospitalizations, despite milder injuries. Further studies are needed to better understand the etiology of the observed trends and whether they reflect potential underlying unconscious or conscious biases of mandated reporters. TYPE OF STUDY: Treatment study. LEVEL OF EVIDENCE: III.

Appraising the Quality of Development and Reporting in Surgical Prediction Models.

This cross-sectional study uses the Transparent Reporting of a Multivariable Prediction Model for Individual Prognosis or Diagnosis reporting guideline to assess 120 published studies about surgical prediction models.

Explainable Machine Learning to Bring Database to the Bedside: Development and Validation of the TROUT (Trauma fRailty OUTcomes) Index, a Point-of-Care Tool to Prognosticate Outcomes After Traumatic Injury Based on Frailty.

OBJECTIVE: Exemplify an explainable machine learning framework to bring database to the bedside; develop and validate a point-of-care frailty assessment tool to prognosticate outcomes after injury. BACKGROUND: A geriatric trauma frailty index that captures only baseline conditions, is readily-implementable, and validated nationwide remains underexplored. We hypothesized Trauma fRailty OUTcomes (TROUT) Index could prognosticate major adverse outcomes with minimal implementation barriers. METHODS: We developed TROUT index according to Transparent Reporting of a Multivariable Prediction Model for Individual Prognosis guidelines. Using nationwide US admission encounters of patients aged ≥65 years (2016-2017; 10% development, 90% validation cohorts), unsupervised and supervised machine learning algorithms identified baseline conditions that contribute most to adverse outcomes. These conditions were aggregated into TROUT Index scores (0-100) that delineate 3 frailty risk strata. After associative [between frailty risk strata and outcomes, adjusted for age, sex, and injury severity (as effect modifier)] and calibration analysis, we designed a mobile application to facilitate point-of-care implementation. RESULTS: Our study population comprised 1.6 million survey-weighted admission encounters. Fourteen baseline conditions and 1 mechanism of injury constituted the TROUT Index. Among the validation cohort, increasing frailty risk (low=reference group, moderate, high) was associated with stepwise increased adjusted odds of mortality {odds ratio [OR] [95% confidence interval (CI)]: 2.6 [2.4-2.8], 4.3 [4.0-4.7]}, prolonged hospitalization [OR (95% CI)]: 1.4 (1.4-1.5), 1.8 (1.8-1.9)], disposition to a facility [OR (95% CI): 1.49 (1.4-1.5), 1.8 (1.7-1.8)], and mechanical ventilation [OR (95% CI): 2.3 (1.9-2.7), 3.6 (3.0-4.5)]. Calibration analysis found positive correlations between higher TROUT Index scores and all adverse outcomes. We built a mobile application ("TROUT Index") and shared code publicly. CONCLUSION: The TROUT Index is an interpretable, point-of-care tool to quantify and integrate frailty within clinical decision-making among injured patients. The TROUT Index is not a stand-alone tool to predict outcomes after injury; our tool should be considered in conjunction with injury pattern, clinical management, and within institution-specific workflows. A practical mobile application and publicly available code can facilitate future implementation and external validation studies.