Falls and Traumatic Brain Injury in the Elderly on Aspirin or Anticoagulant Therapy

Introduction: Traumatic brain injury (TBI) after a fall in individuals aged 65 and older is a leading cause of morbidity and mortality, but the effect of aspirin and anticoagulant therapy on TBI severity is not fully understood. This study evaluated whether the severity of TBI is associated with use of aspirin or anticoagulant therapy or in combination. Methods: Using retrospective chart review, we identified patients age 65 or older who fell and sustained head trauma that were admitted to Thomas Jefferson University Hospital trauma service from 2017-2018. Based on final diagnosis, patients were classified into three groups of TBI in order of increasing severity: mild TBI, extra-axial hemorrhage, and intra-axial hemorrhage. ANOVA and regression analysis will be used to compare use of aspirin, anticoagulant therapy, both in combination, or neither in the three groups. Results: We hypothesize that patients with more severe head trauma will have increased use of aspirin or anticoagulant therapy or both in combination compared to patients who are on neither aspirin nor anticoagulant therapy. Preliminary results show patients with any diagnosis of TBI were more likely to be on aspirin compared to controls (OR 1.74, p\u3c0.001). Patients with any diagnosis of TBI and anticoagulant therapy had no statistical significant association compared to controls (OR 1.25, p=0.25). Discussion: These findings will guide the understanding of how aspirin and anticoagulant therapy affect severity of TBI. Judicious use of aspirin and anticoagulant therapy in the elderly who are at risk of falling may reduce the incidence of severe TBI

The Role of the Uncinate Margin in Pancreaticoduodenectomy for Pancreatic Ductal Adenocarcinoma: A Survival Analysis

Introduction: Positive margins during pancreaticoduodenectomy for pancreatic cancer portend worse survival, but additional resection of the uncinate margin is typically unfeasible without major vascular reconstruction. The survival benefit of resecting additional neck or bile duct margins in the face of a positive uncinate is also unknown. We examined the impact of re-resection of these margins on survival. Methods: Patients with pancreatic adenocarcinoma who underwent pancreaticoduodenectomy from 2006-2015. Pancreatic neck, bile duct, uncinate, and duodenal frozen section margins were assessed before and after resection of positive margins. Kaplan-Meier survival curves were compared with log-rank tests. Multivariable Cox regression was used to assess the effect of margin status on overall survival. Results: Among 508 patients identified, 388 (76.4%) underwent a pylorus-preserving procedure, 435 (85.6%) had T3 tumors, and 379 (74.6%) had nodal involvement. There were 21 instances where an uncinate margin was concurrently positive with a neck or bile duct margin; this additional neck or bile duct margin was resected in 13 cases (61.9%). Resection of additional margins when the uncinate was concurrently positive was not associated with improved survival (p=0.36). Median survival with and without positive uncinate margins was 13.8 vs. 19.7 months (p=0.04). A positive uncinate margin was associated with decreased survival independent of other margins and cancer stage (HR 1.28 [95% CI 1.00-1.65]). Conclusion: In patients with pancreatic adenocarcinoma, positive uncinate margins are associated with decreased overall survival; resection of additional margins at the neck and bile duct in those with a positive uncinate margin is not warranted

Asymptomatic Fluid Collections Following Distal Pancreatectomy – Is Intervention Warranted?

Objective To determine the incidence, associated factors, natural history, and interventions for FCs

Surgical Evacuation for Chronic Subdural Hematoma: Predictors of Reoperation and Functional Outcomes

Background Although chronic subdural hematoma (CSDH) incidence has increased, there is limited evidence to guide patient management after surgical evacuation. Objective To identify predictors of reoperation and functional outcome after CSDH surgical evacuation. Methods We identified all patients with CSDH between 2010 and 2018. Clinical and radiographic variables were collected from the medical records. Outcomes included reoperation within 90 days and poor (3–6) modified Rankin Scale score at 3 months. Results We identified 461 surgically treated CSDH cases (396 patients). The mean age was 70.1 years, 29.7 % were females, 298 (64.6 %) underwent burr hole evacuation, 152 (33.0 %) craniotomy, and 11 (2.4 %) craniectomy. Reoperation rate within 90 days was 12.6 %, whereas 24.2 % of cases had a poor functional status at 3 months. Only female sex was associated with reoperation within 90 days (OR = 2.09, 95 % CI: 1.17–3.75, P = 0.013). AMS on admission (OR = 5.19, 95 % CI: 2.15–12.52, P \u3c 0.001) and female sex (OR = 3.90, 95 % CI: 1.57–9.70, P = 0.003) were independent predictors of poor functional outcome at 3 months. Conclusion Careful management of patients with the above predictive factors may reduce CSDH reoperation and improve long-term functional outcomes. However, larger randomized studies are necessary to assess long-term prognosis after surgical evacuation

Toward Zero Prescribed Opioids for Outpatient General Surgery Procedures: A Prospective Cohort Trial

INTRODUCTION: Achieving satisfactory post-operative pain control for common elective general surgical procedures, while minimizing opioid utilization, remains challenging. Utilizing pre-operative educational strategies, as well as multimodal analgesia, we sought to reduce the post-operative opioid use in elective general surgery cases. METHODS: Between November 2019 and July 2021, patients undergoing elective inguinal hernia repair or cholecystectomy were enrolled in the study. Patients were divided into three cohorts: Control, opioid sparing (OS), or zero-opioid (ZO). Control patients did not have any intervention; OS patients had an opioid reduction intervention protocol applied (patient education and perioperative multimodal analgesia) and were provided an opioid prescription at discharge; the ZO had the same protocol, however, patients were not provided opioid prescriptions at discharge. Two weeks after discharge, patients were interviewed to record opioid consumption, pain scores, and level of satisfaction since discharge. RESULTS: A total of 129 patients were recruited for the study. Eighty-eight patients underwent inguinal hernia repair and 41 patients underwent cholecystectomy. Median post-operative morphine equivalents consumed in the Control cohort (n = 58); 46 (37.5-75) were significantly reduced when the OS protocol was enacted (n = 42); 15 (11-22.5) and further reduced to zero for every patient in the ZO cohort (n = 29) (P = 0.0001). There were no differences in patient-reported average pain scores after discharge (P = 0.08) or satisfaction levels with experience (P = 0.8302). CONCLUSIONS: Our study demonstrates that patient education and preoperative interventions can result in zero opioids prescribed after common general surgery procedures with equivalent patient satisfaction and pain scores

Discrepancies in Stroke Distribution and Dataset Origin in Machine Learning for Stroke.

BACKGROUND: Machine learning algorithms depend on accurate and representative datasets for training in order to become valuable clinical tools that are widely generalizable to a varied population. We aim to conduct a review of machine learning uses in stroke literature to assess the geographic distribution of datasets and patient cohorts used to train these models and compare them to stroke distribution to evaluate for disparities. AIMS: 582 studies were identified on initial searching of the PubMed database. Of these studies, 106 full texts were assessed after title and abstract screening which resulted in 489 papers excluded. Of these 106 studies, 79 were excluded due to using cohorts from outside the United States or being review articles or editorials. 27 studies were thus included in this analysis. SUMMARY OF REVIEW: Of the 27 studies included, 7 (25.9%) used patient data from California, 6 (22.2%) were multicenter, 3 (11.1%) were in Massachusetts, 2 (7.4%) each in Illinois, Missouri, and New York, and 1 (3.7%) each from South Carolina, Washington, West Virginia, and Wisconsin. 1 (3.7%) study used data from Utah and Texas. These were qualitatively compared to a CDC study showing the highest distribution of stroke in Mississippi (4.3%) followed by Oklahoma (3.4%), Washington D.C. (3.4%), Louisiana (3.3%), and Alabama (3.2%) while the prevalence in California was 2.6%. CONCLUSIONS: It is clear that a strong disconnect exists between the datasets and patient cohorts used in training machine learning algorithms in clinical research and the stroke distribution in which clinical tools using these algorithms will be implemented. In order to ensure a lack of bias and increase generalizability and accuracy in future machine learning studies, datasets using a varied patient population that reflects the unequal distribution of stroke risk factors would greatly benefit the usability of these tools and ensure accuracy on a nationwide scale