Background Posterior cervical decompression with or without fusion (PCD/F) is used to manage degenerative spinal conditions. Malnutrition has been implicated for poor outcomes in spine surgery. The aim of this study was to assess the ability of the Geriatric Nutritional Risk Index (GNRI) as a risk calculator for postoperative complications in patients undergoing PCD/F. Methods The 2006 to 2018 American College of Surgeons National Surgery Quality Improvement Program Database was queried for patients undergoing PCD/F. Nutritional status was categorized as normal (GNRI greater than 98), moderately malnourished (GNRI 92–98), or severely malnourished (GNRI less than or equal to 92). Complications within 30 days of surgery were compared among the groups. Preoperative data that were statistically significant (P < 0.05) upon univariate χ² analysis were included in the univariate then multivariate binary regression model to calculate adjusted ORs. All ORs were assessed at the 95% CI. Results Of the 7597 PCD/F patients identified, 15.6% were severely malnourished and 19.1% were moderately malnourished. Severe and moderate malnourishment were independent risk factors for mortality (OR = 3.790, 95% CI 2.492–5.763, P < 0.001; OR = 2.150, 95% CI 1.351–3.421, P = 0.011). Severe malnourishment was an independent risk factor for sepsis/septic shock (OR = 3.448, 95% CI 2.402–4.948, P < 0.001). Conclusions In elderly patients undergoing PCD/F, severe malnutrition, as defined by the GNRI, was an independent risk factor for mortality and sepsis/septic shock. Clinical Relevance The GNRI may be more useful than other indices for risk stratification in elderly patients because it accounts for confounding variables such as hydration status and paradoxical malnourishment in obese patients. Level of Evidence 3

Background: Academic medical centers greatly benefit from retaining their physicians; that ensures continuity in patient care, enhances resident education, and maintains a pool of experienced clinicians and researchers. Despite its importance, little research has been published on the retainment of academic faculty in orthopaedics. To address this gap, this study investigates the demographic trends of academic orthopaedic surgeons from 2016 to 2022. By analyzing data pertaining to gender distribution, years of practice, research productivity, and institutional rankings, we aimed to gain insights into the factors influencing faculty retainment, institution changes, and new entrants into academic orthopaedics. Methods: A retrospective cross-sectional analysis of U.S. academic orthopaedic surgeons affiliated with programs under the Accreditation Council for Graduate Medical Education (ACGME) in 2016 and 2022 was performed. Faculty present in both the 2016 and the 2022 data were classified as being “retained” in academia; those present only in 2016, as having “left” academia; and those present only in 2022, as being “new” to academia. The retained group was then divided into movers (those who moved to other institutions) and non-movers. Results: Retained orthopaedists had fewer years of practice, a higher h-index (Hirsch index), and more publications. Non-fellowship-trained orthopaedists had less retainment in academia, and orthopaedists with fellowships in oncology had more retainment in academia. Additionally, movers also had fewer years in practice but an equal level of scholarly productivity when compared with non-movers. Lastly, higher-ranked academic programs retained a greater proportion of orthopaedic surgeons. Conclusions: Over the study period, a majority of orthopaedists (56.99%) chose to remain in academia. Those retained tended to be in the earlier stages of their careers, yet demonstrated higher research output. Notably, the representation of female orthopaedists in academic orthopaedics is on the rise. Conversely, lower-ranked programs faced higher turnover rates, highlighting the challenges that they encounter in retaining faculty members. Clinical Relevance: Academic medical centers benefit from retaining orthopaedic surgeons by maintaining patient relationships, having consistency in resident education, and building on clinical and research expertise. Likewise, orthopaedists benefit from understanding the trends in current academic employment, in order to optimize career planning decisions.

Introduction: Quantification of a researcher's productivity relies on objective bibliometric measurements, such as the Hirsch index (h-index). However, h-index is not field and time-normalized and possesses bias against newer researchers. Our study is the first to compare the relative citation ratio (RCR), a new article-level metric developed by the National Institutes of Health, with h-index in academic orthopaedics. Methods: Academic orthopaedic programs in the United States were identified using the 2022 Fellowship and Residency Electronic Interactive Database. Available demographic and training data for surgeons were collected. RCR was calculated using the National Institutes of Health iCite tool, and h-index was calculated using Scopus. Results: Two thousand eight hundred twelve academic orthopaedic surgeons were identified from 131 residency programs. H-index, weighted RCR (w-RCR), and mean RCR (m-RCR) all significantly differed by faculty rank and career duration. However, while h-index and w-RCR varied between sexes (P < 0.001), m-RCR did not (P = 0.066), despite men having a longer career duration (P < 0.001). Discussion: We propose that m-RCR be used in conjunction with w-RCR or h-index to promote a fairer, comprehensive depiction of an orthopaedic surgeon's academic effect and productivity. Use of m-RCR may reduce the historic bias against women and younger surgeons in orthopaedics, which has implications in employment, promotion, and tenure.

Purpose: Chat Generative Pre‐Trained Transformer (ChatGPT) may have implications as a novel educational resource. There are differences in opinion on the best resource for the Orthopaedic In‐Training Exam (OITE) as information changes from year to year. This study assesses ChatGPT's performance on the OITE for use as a potential study resource for residents.Methods: Questions for the OITE data set were sourced from the American Academy of Orthopaedic Surgeons (AAOS) website. All questions from the 2022 OITE were included. All questions, including those with images, were included in the analysis. The questions were formatted in the same manner as presented on the AAOS website, with the question, narrative text and answer choices separated by a line. Each question was evaluated in a new chat session to minimize confounding variables. Answers from ChatGPT were characterized by whether they contained logical, internal or external information. Incorrect responses were further categorized into logical, informational or explicit fallacies.Results: ChatGPT yielded an overall success rate of 48.3% based on the 2022 AAOS OITE. ChatGPT demonstrated the ability to apply logic and stepwise thinking in 67.6% of the questions. ChatGPT effectively utilized internal information from the question stem in 68.1% of the questions. ChatGPT also demonstrated the ability to incorporate external information in 68.1% of the questions. The utilization of logical reasoning (p < 0.001), internal information (p = 0.004) and external information (p = 0.009) was greater among correct responses than incorrect responses. Informational fallacy was the most common shortcoming of ChatGPT's responses. There was no difference in correct responses based on whether or not an image was present (p = 0.320).Conclusions: ChatGPT demonstrates logical, informational and explicit fallacies which, at this time, may lead to misinformation and hinder resident education.Level of Evidence: Level V.