Valsamis Epaminondas Markos, Sayers Adrian, Ma Jie, Dhiman Paula, Gwilym Stephen E, Rees Jonathan L
Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences, University of Oxford, Oxford, UK.
NIHR Oxford Biomedical Research Centre, Oxford, UK.
BMJ Med. 2025 Aug 10;4(1):e001283. doi: 10.1136/bmjmed-2024-001283. eCollection 2025.
To determine the importance of comorbidity measures when predicting mortality and revision surgery after elective primary shoulder replacement surgery.
Population based cohort study.
Linked data from the National Joint Registry and NHS Hospital Episode Statistics were used to identify all elective primary shoulder replacements in England, 6 January 2012 to 30 March 2022.
37 176 consenting patients, aged 18-100 years, who had elective primary shoulder replacement surgery.
Risk of mortality at 90 and 365 days, and risk of long term revision surgery after the primary surgery.
37 176 primary shoulder replacement procedures were included; 102 patients died within 90 days and 445 within 365 days of the primary surgery. 1219 patients had revision surgery over a maximum follow-up period of >10 years. The addition of comorbidity measures derived from Hospital Episode Statistics (Charlson comorbidity index with summary hospital mortality index weights, Elixhauser comorbidity index, and hospital frailty risk score) to simpler models resulted in little improvement in predictive performance. Optimism adjusted performance (C index) of the models that included age, sex, American Society of Anesthesiologists (ASA) grade, and main surgical indication was 0.76 (95% confidence interval (CI) 0.72 to 0.81) for 90 day mortality, 0.74 (0.71 to 0.76) for 365 day mortality, and 0.64 (0.63 to 0.66) for revision surgery. The best performing models that included a comorbidity measure had an optimism adjusted C index of 0.77 (95% CI 0.73 to 0.81) for 90 day mortality, 0.76 (0.74 to 0.78) for 365 day mortality, and 0.65 (0.63 to 0.66) for revision surgery. Heterogeneity in model performance across regions of England was low, and decision curve analysis showed minimal improvement in net benefit when including comorbidity measures.
In this study, patient comorbidity scores added little improvement to simpler models that included age, sex, ASA grade, and main surgical indication for predicting mortality and revision surgery after elective primary shoulder replacement surgery. This improvement needs to be balanced against the additional challenges of routine data linkage to obtain these scores.
确定合并症指标在预测择期初次肩关节置换术后死亡率和翻修手术方面的重要性。
基于人群的队列研究。
利用国家关节注册中心和英国国民健康服务体系医院事件统计的关联数据,识别出2012年1月6日至2022年3月30日在英格兰进行的所有择期初次肩关节置换手术。
37176名年龄在18至100岁之间、同意接受择期初次肩关节置换手术的患者。
90天和365天的死亡风险,以及初次手术后长期翻修手术的风险。
纳入了37176例初次肩关节置换手术;102例患者在初次手术后90天内死亡,445例在365天内死亡。1219例患者在最长超过10年的随访期内接受了翻修手术。将源自医院事件统计的合并症指标(带有汇总医院死亡率指数权重 的查尔森合并症指数、埃利克斯豪泽合并症指数和医院衰弱风险评分)添加到更简单的模型中,预测性能几乎没有改善。包含年龄、性别、美国麻醉医师协会(ASA)分级和主要手术指征的模型,其90天死亡率的乐观度调整性能(C指数)为0.76(95%置信区间(CI)0.72至0.81),365天死亡率为0.74(0.71至0.76),翻修手术为0.64(0.63至0.66)。包含合并症指标的表现最佳的模型,其90天死亡率的乐观度调整C指数为0.77(95%CI 0.73至0.81),365天死亡率为0.76(0.74至0.78),翻修手术为0.65(0.63至0.66)。英格兰各地区模型性能的异质性较低,决策曲线分析表明,纳入合并症指标时净效益的改善微乎其微。
在本研究中,对于预测择期初次肩关节置换术后的死亡率和翻修手术,患者合并症评分在包含年龄、性别、ASA分级和主要手术指征的更简单模型基础上,几乎没有带来更多改善。这种改善需要与获取这些评分所需的常规数据关联的额外挑战相权衡。