Contemporary Trends in the Orthopaedic Surgery Residency Match and the Effects of COVID-19.

Objective: We aimed to elucidate associations between geographic location, size, and ranking of medical schools that orthopaedic surgery residents graduate from and the residencies that they match both pre-COVID-19 and post-COVID-19 pandemic by examining the 2017 to 2022 orthopaedic surgery residency cohorts. Methods: Demographics were extracted using Doximity Residency Navigator platform, the 2021 US News and World Report, and program websites. Medical schools were classified as large if they had >613 medical students. Postgraduate year 1 (PGY-1) (2021 match) and PGY-2 (2022 match) residents were classified as the COVID-19 cohort. Location was categorized as Northeast, Midwest, South, and West. Chi-square tests, Cohen's H value, and descriptive statistics were used for analysis with statistical significance set at p <0.05. Results: Four thousand two hundred forty-three residents from 160 accredited US orthopaedic residency programs (78.4%) were included. Northeastern applicants were most likely to match in the same region (p <0.01), and southern applicants were most likely to match at their home program (p <0.001). Applicants affected by the COVID-19 pandemic did not differ from their predecessors with regards to matching to the same region (p = 0.637) or home program (p = 0.489). Applicants from public medical schools were more likely to match in the same region and at their home program (p <0.001), whereas those from private medical schools were more likely to match at top-ranked residencies (p <0.001). Students from both top 25- and top 50-ranked medical schools were more likely to match at their home program (p <0.01) and attend top 20-ranked residency programs (p <0.0001). Conclusion: These results demonstrate significant associations between matched residencies and attended medical schools' geographic location, school type, and ranking. During the pandemic, geographic trends were overall unchanged, whereas residents from large or lower-ranked schools were more likely to match at home programs, and those from private or top-ranked schools were less likely to attend top residencies.

The association of thromboembolic complications and the use of tranexamic acid during resection of intracranial meningiomas: systematic review and meta-analysis of randomized controlled trials.

OBJECTIVE: Antifibrinolytics, such as tranexamic acid (TXA), have been shown to decrease intraoperative blood loss across multiple surgical disciplines. However, they carry the theoretical risk of thromboembolic events secondary to induced hypercoagulability. Therefore, the aim of this study was to systematically review the available literature and perform a meta-analysis on the use of TXA in meningioma resection to assess thromboembolic risks. METHODS: The PubMed, Web of Science, and Google Scholar databases were reviewed for all randomized controlled trials presenting primary data on TXA use during resection of intracranial meningiomas. Data were gathered on operative duration, venous thromboembolic complications, deep venous thrombosis, use of allogeneic blood transfusion, estimated blood loss (EBL), and postoperative hemoglobin. Patients who received TXA were compared with controls who did not receive TXA intraoperatively using random-effects models. RESULTS: A total of 508 unique articles were identified, of which 493 underwent full-text review. Ultimately, 6 studies with 381 total patients (190 receiving TXA) were included in the final analysis. All 6 trials were randomized, blinded, and placebo controlled with a TXA administration rate of a 20-mg/kg load followed by a 1-mg/kg/hr infusion. All studies were performed in lower-middle-income countries. There were no reported instances of venous thromboembolism (VTE) in the TXA and non-TXA cohorts. Patients receiving TXA exhibited fewer allogeneic transfusions (21.5% vs 41.6% [OR 0.26, 95% CI 0.09-0.77], p = 0.02) and lower EBL (MD -282.48 mL [95% CI -367.77 to -197.20 mL], p < 0.001) compared with patients who did not receive TXA, and they also had lower rates of perioperative complications (10.7% vs 19.9% [OR 0.47, 95% CI 0.2-0.95], p = 0.04). CONCLUSIONS: Current literature suggests that TXA is not associated with increased risk for VTE when administered during resection of intracranial meningioma. TXA appears to decrease intraoperative blood loss and allogeneic transfusion requirements during meningioma resection and thus may improve the safety of surgical management of this pathology.

Field Measures Are All You Need: Predicting Need for Surgery in Elderly Ground-Level Fall Patients via Machine Learning.

BACKGROUND: As ground-level falls (GLFs) are a significant cause of mortality in elderly patients, field triage plays an essential role in patient outcomes. This research investigates how machine learning algorithms can supplement traditional t-tests to recognize statistically significant patterns in medical data and to aid clinical guidelines. METHODS: This is a retrospective study using data from 715 GLF patients over 75 years old. We first calculated P-values for each recorded factor to determine the factor's significance in contributing to a need for surgery (P < .05 is significant). We then utilized the XGBoost machine learning method to rank contributing factors. We applied SHapley Additive exPlanations (SHAP) values to interpret the feature importance and provide clinical guidance via decision trees. RESULTS: The three most significant P-values when comparing patients with and without surgery are as follows: Glasgow Coma Scale (GCS) (P < .001), no comorbidities (P < .001), and transfer-in (P = .019). The XGBoost algorithm determined that GCS and systolic blood pressure contribute most strongly. The prediction accuracy of these XGBoost results based on the test/train split was 90.3%. DISCUSSION: When compared to P-values, XGBoost provides more robust, detailed results regarding the factors that suggest a need for surgery. This demonstrates the clinical applicability of machine learning algorithms. Paramedics can use resulting decision trees to inform medical decision-making in real time. XGBoost's generalizability power increases with more data and can be tuned to prospectively assist individual hospitals.

Analysis of Current Neurological Surgery Residents and Prior Medical Education: Do Medical School Attributes Matter?

BACKGROUND: With the recent changes to the U.S. Medical Licensing Examination grading system, an understanding of the factors that influence the neurological surgery residency match process is crucial for residency directors. The aim of the present retrospective study was to explore the associations of medical school location, ranking, private school status, size, and presence of an American Association of Neurological Surgeons (AANS) chapter or neurological surgery interest group (NSIG) with the neurosurgery match outcomes. METHODS: An enrollment list of all accredited U.S. neurosurgery residency programs was compiled on June 28, 2021. For the included residents, the residency program, degree, and previously attended medical school were retrieved. The geographic location, ranking, private school status, and size were collected for the residency programs and medical schools attended by the residents at each program. RESULTS: A total of 1437 residents from 101 neurosurgery residency programs (89%) were included. Graduates from the top 25 medical schools were more likely to match into their home residency programs (P < 0.001) and highly ranked residency programs (P < 0.001). Students from larger medical schools were also more likely to match into larger (P < 0.001) and highly ranked (P < 0.001) programs than were applicants from smaller schools. Students from medical schools with an AANS chapter or NSIG were also more likely to match into top ranked programs (P < 0.001 for both). CONCLUSIONS: Medical students from the top 25 medical schools, private medical schools, medical schools with an AANS chapter, and medical schools with an NSIG were more likely to match into a prestigious residency program. These findings suggest that underlying biases might be present for program directors to consider in the resident selection process.