OBJECTIVE Osteoporosis contributes to mechanical complications, such as pedicle screw loosening, instrumentation failure, and pseudarthrosis, following adult spinal deformity (ASD) correction surgery. Research has shown that preoperative medical optimization of patients with osteoporosis can reduce complication rates to levels similar to those seen in patients with normal bone density. However, clinical practices for preoperative bone health optimization remain inconsistent. This study evaluates the proportion of …

Classic health-related quality of life (HRQOL) metrics are cumbersome, time-intensive, and subject to biases based on the patient’s native language, educational level, and cultural values. Natural language processing (NLP) converts text into quantitative metrics. Sentiment analysis enables subject matter experts to construct domain-specific lexicons that assign a value of either negative (−1) or positive (1) to certain words. The growth of telehealth provides opportunities to apply sentiment analysis to transcript…

Study Design Cross-Sectional. Objectives Adult spinal deformity (ASD) affects 68% of the elderly, with surgical intervention carrying complication rates of up to 50%. Effective patient education is essential for managing expectations, yet high patient volumes can limit preoperative counseling. Language learning models (LLMs), such as ChatGPT, may supplement patient education. This study evaluates ChatGPT-3.5’s accuracy and readability in answering common patient questions regarding ASD surgery. Methods Structured …

Study Design Systematic Review. Objectives While substantial research has explored the impact of osteoporosis on patients undergoing adult spinal deformity (ASD) correction, the literature remains inconclusive. As such, the purpose of this study is to synthesize and analyze existing studies pertaining to osteoporosis as a predictor of postoperative outcomes in ASD surgery. Methods We performed a systematic review and meta-analysis to determine the effect that a diagnosis of osteoporosis, based on ICD-10 coding, du…

Adult spinal deformity (ASD) surgery is still associated with high surgical risks. Machine learning algorithms applied to multicenter databases have been created to predict outcomes and complications, optimize patient selection, and improve overall results. However, the multiple data points currently used to create these models allow for 70% of accuracy in prediction. We need to find new variables that can capture the spectrum of probability that is escaping from our control. These proposed variables are based on …