ABSTRACT
BACKGROUND: Basketball-related fractures involving the lower extremities frequently present to emergency departments (ED) in the United States (US). This study aimed to identify the primary mechanisms, distribution, and trends of these injuries. HYPOTHESIS: We hypothesize that (1) lower extremity fracture frequency will decrease from 2013 to 2022, (2) the ankle will be the most common fracture site, and (3) noncontact twisting will be the most common injury mechanism. STUDY DESIGN: Descriptive epidemiological. LEVEL OF EVIDENCE: Level 3. METHODS: The National Electronic Injury Surveillance System (NEISS) was queried for lower extremity fractures from basketball presenting to US EDs from January 1, 2013 to December 31, 2022. Patient demographics, injury location, and disposition were recorded. The injury mechanism was characterized using the provided narrative. National estimates (NEs) were calculated using the NEISS statistical sample weight. Injury trends were evaluated by linear regression. RESULTS: There were 6259 cases (NE: 185,836) of basketball-related lower extremity fractures. Linear regression analysis of annual trends demonstrated a significant decrease in lower extremity fractures over the study period (2013-2022: P = 0.01; R2 = 0.64). The most common injury mechanism was a noncontact twisting motion (NE: 49,897, 26.9%) followed by jumping (NE: 39,613, 21.3%). The ankle was the most common fracture site (NE: 69,936, 37.6%) followed by the foot (NE: 49,229, 26.49%). While ankle and foot fractures decreased significantly (P < 0.05), fractures of the lower leg, knee, toe, and upper leg showed no significant trends (P = 0.09, 0.75, 0.07, and 0.85, respectively). CONCLUSION: Basketball-related lower extremity fractures decreased from 2013 to 2022, with the ankle being the most common fracture site and most fractures arising from a noncontact twist. Increasing utilization of outpatient clinics may have contributed to the decline, particularly for ankle and foot fractures. The prevalence of ankle fractures and twisting-related injuries reinforces the importance of protective footwear and targeted strengthening protocols.
ABSTRACT
BACKGROUND CONTEXT: Venous thromboembolism is a negative outcome of elective spine surgery. However, the use of thromboembolic chemoprophylaxis in this patient population is controversial due to the possible increased risk of epidural hematoma. ChatGPT is an artificial intelligence model which may be able to generate recommendations for thromboembolic prophylaxis in spine surgery. PURPOSE: To evaluate the accuracy of ChatGPT recommendations for thromboembolic prophylaxis in spine surgery. STUDY DESIGN/SETTING: Comparative analysis. PATIENT SAMPLE: None. OUTCOME MEASURES: Accuracy, over-conclusiveness, supplemental, and incompleteness of ChatGPT responses compared to the North American Spine Society (NASS) clinical guidelines. METHODS: ChatGPT was prompted with questions from the 2009 NASS clinical guidelines for antithrombotic therapies and evaluated for concordance with the clinical guidelines. ChatGPT-3.5 responses were obtained on March 5, 2023, and ChatGPT-4.0 responses were obtained on April 7, 2023. A ChatGPT response was classified as accurate if it did not contradict the clinical guideline. Three additional categories were created to further evaluate the ChatGPT responses in comparison to the NASS guidelines: over-conclusiveness, supplementary, and incompleteness. ChatGPT was classified as over-conclusive if it made a recommendation where the NASS guideline did not provide one. ChatGPT was classified as supplementary if it included additional relevant information not specified by the NASS guideline. ChatGPT was classified as incomplete if it failed to provide relevant information included in the NASS guideline. RESULTS: Twelve clinical guidelines were evaluated in total. Compared to the NASS clinical guidelines, ChatGPT-3.5 was accurate in 4 (33%) of its responses while ChatGPT-4.0 was accurate in 11 (92%) responses. ChatGPT-3.5 was over-conclusive in 6 (50%) of its responses while ChatGPT-4.0 was over-conclusive in 1 (8%) response. ChatGPT-3.5 provided supplemental information in 8 (67%) of its responses, and ChatGPT-4.0 provided supplemental information in 11 (92%) responses. Four (33%) responses from ChatGPT-3.5 were incomplete, and 4 (33%) responses from ChatGPT-4.0 were incomplete. CONCLUSIONS: ChatGPT was able to provide recommendations for thromboembolic prophylaxis with reasonable accuracy. ChatGPT-3.5 tended to cite nonexistent sources and was more likely to give specific recommendations while ChatGPT-4.0 was more conservative in its answers. As ChatGPT is continuously updated, further validation is needed before it can be used as a guideline for clinical practice.
ABSTRACT
Thrombocytopenia is a common condition characterized by a low platelet count, typically less than 150,000/µL. This article outlines key considerations for field medical providers to effectively identify the early signs of thrombocytopenia and treat different etiologies in the prehospital environment. Following a representative case study, we present a review of basic pathophysiology to include different manifestations of thrombocytopenia as well as diagnostic methods, treatments, and other necessary interventions in this unique setting. With an adequate understanding of typical patient histories and physical presentations leading to this diagnosis, field medics and physicians can be armed with useful information to potentially improve patient outcomes.
