Risk of serious adverse events after primary shoulder replacement: development and external validation of a prediction model using linked national data from England and Denmark.

BACKGROUND: Despite a rising rate of serious medical complications after shoulder replacement surgery, there are no prediction models in widespread use to guide surgeons in identifying patients at high risk and to provide patients with personalised risk estimates to support shared decision making. Our aim was to develop and externally validate a prediction model for serious adverse events within 90 days of primary shoulder replacement surgery. METHODS: Linked data from the National Joint Registry, National Health Service Hospital Episode Statistics Admitted Patient Care of England, and Civil Registration Mortality databases and Danish Shoulder Arthroplasty Registry and National Patient Register were used for our modelling study. Patients aged 18-100 years who had a primary shoulder replacement between April 1, 2012, and Oct 2, 2020, in England, and April 1, 2012, and Oct 2, 2018, in Denmark, were included. We developed a multivariable logistic regression model using the English dataset to predict the risk of 90-day serious adverse events, which were defined as medical complications requiring admission to hospital and all-cause death. We undertook internal validation using bootstrapping, and internal-external cross-validation across different geographical regions of England. The English model was externally validated on the Danish dataset. FINDINGS: Data for 40 631 patients undergoing primary shoulder replacement (mean age 72·5 years [SD 9·9]; 28 709 [70·7%] women and 11 922 [29·3%] men) were used for model development, of whom 2270 (5·6%) had a 90-day serious adverse event. On internal validation, the model had a C-statistic of 0·717 (95% CI 0·707-0·728) and was well calibrated. Internal-external cross-validation showed consistent model performance across all regions in England. Upon external validation on the Danish dataset (n=6653; mean age 70·5 years [SD 10·3]; 4503 [67·7%] women and 2150 [32·3%] men), the model had a C-statistic of 0·750 (95% CI 0·723-0·776). Decision curve analysis showed clinical utility, with net benefit across all risk thresholds. INTERPRETATION: This externally validated prediction model uses commonly available clinical variables to accurately predict the risk of serious medical complications after primary shoulder replacement surgery. The model is generalisable and applicable to most patients in need of a shoulder replacement. Its use offers support to clinicians and could inform and empower patients in the shared decision-making process. FUNDING: National Institute for Health and Care Research and the Department of Orthopaedic Surgery, Herlev and Gentofte Hospital, Denmark.

Reverse total shoulder replacement versus anatomical total shoulder replacement for osteoarthritis: population based cohort study using data from the National Joint Registry and Hospital Episode Statistics for England.

OBJECTIVES: To answer a national research priority by comparing the risk-benefit and costs associated with reverse total shoulder replacement (RTSR) and anatomical total shoulder replacement (TSR) in patients having elective primary shoulder replacement for osteoarthritis. DESIGN: Population based cohort study using data from the National Joint Registry and Hospital Episode Statistics for England. SETTING: Public hospitals and publicly funded procedures at private hospitals in England, 2012-20. PARTICIPANTS: Adults aged 60 years or older who underwent RTSR or TSR for osteoarthritis with intact rotator cuff tendons. Patients were identified from the National Joint Registry and linked to NHS Hospital Episode Statistics and civil registration mortality data. Propensity score matching and inverse probability of treatment weighting were used to balance the study groups. MAIN OUTCOME MEASURES: The main outcome measure was revision surgery. Secondary outcome measures included serious adverse events within 90 days, reoperations within 12 months, prolonged hospital stay (more than three nights), change in Oxford Shoulder Score (preoperative to six month postoperative), and lifetime costs to the healthcare service. RESULTS: The propensity score matched population comprised 7124 RTSR or TSR procedures (126 were revised), and the inverse probability of treatment weighted population comprised 12 968 procedures (294 were revised) with a maximum follow-up of 8.75 years. RTSR had a reduced hazard ratio of revision in the first three years (hazard ratio local minimum 0.33, 95% confidence interval 0.18 to 0.59) with no clinically important difference in revision-free restricted mean survival time, and a reduced relative risk of reoperations at 12 months (odds ratio 0.45, 95% confidence interval 0.25 to 0.83) with an absolute risk difference of -0.51% (95% confidence interval -0.89 to -0.13). Serious adverse events and prolonged hospital stay risks, change in Oxford Shoulder Score, and modelled mean lifetime costs were similar. Outcomes remained consistent after weighting. CONCLUSIONS: This study's findings provide reassurance that RTSR is an acceptable alternative to TSR for patients aged 60 years or older with osteoarthritis and intact rotator cuff tendons. Despite a significant difference in the risk profiles of revision surgery over time, no statistically significant and clinically important differences between RTSR and TSR were found in terms of long term revision surgery, serious adverse events, reoperations, prolonged hospital stay, or lifetime healthcare costs.