ArticleShoulder & elbow2026
Predictors of prolonged length of stay in shoulder arthroplasty: A study using the National Joint Registry and Hospital Episode Statistics for England.
Article in Shoulder & elbow, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
1 citing paper in PubMed.
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Introduction: The volume of shoulder arthroplasties in the United Kingdom continues to rise, with 8221 cases recorded in the National Joint Registry (NJR) in 2023. Amid increasing demand and pressure on NHS resources, reducing hospital length of stay (LOS) is a key priority for improving efficiency. This study aimed to identify independent predictors of prolonged LOS following shoulder arthroplasty. Methods: NJR data from April 2012 to March 2022 were linked with Hospital Episode Statistics (HES) for England. Prolonged LOS was defined as >2 nights (above the cohort median). Variables analysed included age, sex, Charlson comorbidity index (CCI), comorbidities, surgical indication, implant type, operating surgeon volume, and day of surgery. Univariable and multivariable logistic regression models were used to identify predictors. Results: Among 47,145 patients, older age, higher CCI, and ASA grades 3 and 4 were significantly associated with extended LOS. Male patients had a 45% reduced risk of prolonged stay. Trauma-related procedures and surgeries conducted Friday-Sunday were associated with increased LOS. Patients treated by high-volume surgeons had a 19% lower risk of prolonged LOS. Several comorbidities were independently predictive; however, differed across implants. Conclusion: Both patient-level and system-level factors contribute to prolonged LOS. Optimising perioperative care and scheduling may reduce LOS and improve NHS resource utilisation.
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