Xiuyi Alexander Yang

Introduction: Patients undergoing total shoulder arthroplasty (TSA) may experience postoperative new-onset depression (NOD), which is gaining attention because of its detrimental effect on patient outcomes. Methods: The PearlDiver Mariner database from 2010 through October 2022 was queried for adult patients undergoing first-time TSA. Exclusion criteria included patients with diagnoses of tumors, trauma, and infections within 30 days before surgery and patients with previous depression or psychiatric risk factors for depression. The incidence of NOD diagnoses within 1 year after surgery was identified. Those with and without NOD were exact matched 1:4 based on age, sex, and Elixhauser Comorbidity Index and compared on multivariate logistic regression to determine whether various 90-day postoperative complications were associated with the development of NOD. After Bonferroni correction, significance was established at P < 0.003. Five-year revision rates were also compared with the log-rank test. Results: Overall, 144,773 TSA patients meeting inclusion criteria were identified. NOD diagnoses in the year after surgery were identified for 4,321 (3.0%). Those with NOD were more likely to be female and have greater comorbidity burden ( P < 0.003 for both). Among matched comparisons, those with NOD had higher odds of experiencing various 90-day complications, visits to the emergency department, hospital readmission, and were more likely to undergo revision TSA within 5 years ( P < 0.003). Conclusions: Postoperative NOD was diagnosed in 3% of patients after TSA. Having NOD was associated with various postoperative complications and higher revision rates. Recognizing predisposing factors for NOD may help target risk mitigation strategies.

Patient-specific technologies within the field of adult spinal deformity (ASD) aid surgeons in pre-surgical planning, accurately help identify anatomical landmarks, and can project optimal post-surgical sagittal alignment. This narrative review aims to discuss the current uses of patient-specific technologies in ASD and identify new innovations that may very soon be integrated into patient care. Pre-operatively, machine learning or artificial intelligence helps surgeons to simulate post-operative alignment and provide information for the 3D-printing of pre-contoured rods and patient-specific cages. Intraoperatively, robotic surgery and intraoperative guides allow for more accurate positioning of implants. Implant materials are being developed to allow for better osseointegration and patient outcome monitoring. Despite the significant promise of these technologies, work still needs to be performed to ensure their accuracy, safety, and cost efficacy.