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Purpose: We sought to characterize trends in demographics, comorbidities, and postoperative complications among patients undergoing primary and revision cervical disc replacement (pCDR/rCDR) procedures. Methods: In this retrospective database study, the Premier Healthcare database was queried from 2006 to 2019. Annual proportions or medians were calculated for patient and hospital characteristics, comorbidities, and postoperative complications associated with CDR surgery. Trends were assessed using linear regression analyses with year of service as the sole predictor. Results: A total of 16,178 pCDR and 758 rCDR cases were identified, with a median (IQR) age of 46 (39; 53) and 51 (43; 60) years among patients, respectively. The annual number of both procedures increased between 2006 and 2019, from 135 to 2220 for pCDR (p < 0.001), and from 17 to 49 for rCDR procedures (p < 0.001), with radiculopathy being the main indication for surgery in both groups. Mechanical failure was identified as a major indication for rCDR procedures with an increase over time (p = 0.002). Baseline patient comorbidity burden (p = 0.045) and complication rates (p < 0.001) showed an increase. For both procedures, an increase in outpatient surgeries and procedures performed in rural hospitals was seen (pCDR: p = 0.045; p = 0.006; rCDR: p = 0.028; p = 0.034). Conclusion: PCDR and rCDR procedures significantly increased from 2006 to 2019. At the same time, comorbidity burden and complication rates increased, while procedures were more often performed in an outpatient and rural setting. The identification of these trends can help guide future practice and lead to further areas of research. [ABSTRACT FROM AUTHOR]

Background: The development of hyponatremia after total joint arthroplasty (TJA) may lead to several adverse events and is associated with prolonged inpatient length of stay as well as increased hospital costs. The purpose of this study was to develop and internally validate machine learning algorithms for predicting hyponatremia after TJA.Methods: A consecutive cohort of 30,703 TJA patients from an institutional registry at a large, tertiary academic hospital were included. A total of 19 potential predictor variables were collected. Hyponatremia was defined as a serum sodium concentration of <135 mEq/L. Five machine learning algorithms were developed using a training set and internally validated using an independent testing set. Algorithm performance was evaluated through discrimination, calibration, decision-curve analysis, and Brier score.Results: The charts of 30,703 patients undergoing TJA were reviewed. Of those patients, 5,480 (17.8%) developed hyponatremia postoperatively. A combination of 6 variables were demonstrated to optimize algorithm prediction: preoperative serum sodium concentration, age, intraoperative blood loss, procedure time, body mass index (BMI), and American Society of Anesthesiologists (ASA) score. Threshold values that were associated with greater hyponatremia risk were a preoperative serum sodium concentration of ≤138 mEq/L, an age of ≥73 years, an ASA score of >2, intraoperative blood loss of >407 mL, a BMI of ≤26 kg/m2, and a procedure time of >111 minutes. The stochastic gradient boosting (SGB) algorithm demonstrated the best performance (c-statistic: 0.75, calibration intercept: -0.02, calibration slope: 1.02, and Brier score: 0.12). This algorithm was turned into a tool that can provide real-time predictions (https://orthoapps.shinyapps.io/Hyponatremia_TJA/).Conclusions: The SGB algorithm demonstrated the best performance for predicting hyponatremia after TJA. The most important factors for predicting hyponatremia were preoperative serum sodium concentration, age, intraoperative blood loss, procedure time, BMI, and ASA score. A real-time hyponatremia risk calculator was developed, but it is imperative to perform external validation of this model prior to using this calculator in clinical practice.Level Of Evidence: Prognostic Level IV. See Instructions for Authors for a complete description of levels of evidence. [ABSTRACT FROM AUTHOR]