Mehta Bella, Yiyuan Yi, Pearce-Fisher Diyu, Ho Kaylee, Goodman Susan M, Parks Michael L, Wang Fei, Fontana Mark A, Ibrahim Said, Cram Peter, Caruana Rich
Hospital for Special Surgery and Weill Cornell Medicine, New York, New York.
Weill Cornell Medicine, New York, New York.
Arthritis Care Res (Hoboken). 2025 Jul;77(7):892-899. doi: 10.1002/acr.25511. Epub 2025 Mar 21.
Social determinants of health (SDOH), including race, have a key role in total hip arthroplasty (THA) disparities. We compared the collective influence of community-level SDOH to the influence of individual factors such as race, on THA outcomes.
This retrospective cohort study of the Pennsylvania Health Care Cost Containment Council Database (2012-2018) included 105,336 patients undergoing unilateral primary elective THA. We extracted "community" factors from the US census by geocoding patient zip codes, including walkability index, household income, foreign-born individuals, English proficiency, computer and internet access, unpaid family workers, those lacking health insurances, and education. We trained an explainable boosting machine, a modern form of generalized additive models, to predict 90-day readmission, 90-day mortality, one-year revision, and length of stay (LOS). Mean absolute scores were aggregated to measure variable importance (ie, variables that contributed most to the prediction).
The rates of readmission, revision, and mortality were 8%, 1.5%, and 0.3%, respectively, with a median LOS of two days. Predictive performance measured by area under the receiver operating characteristic curve was 0.76 for mortality, 0.66 for readmission, and 0.57 for one-year revision. For LOS, the root mean squared error was 0.41 (R = 0.2). The top three predictors of mortality were community, discharge location, and age; for readmission, they were discharge location, age, and comorbidities; for revision, they were community, discharge location, and comorbidities; and for LOS, they were discharge location, community, and comorbidities.
Community-level SDOH were significantly more important than individual race in contributing to the prediction of THA outcomes, especially for 90-day mortality.
包括种族在内的健康社会决定因素（SDOH）在全髋关节置换术（THA）差异中起关键作用。我们比较了社区层面SDOH与种族等个体因素对THA结局的综合影响。
这项对宾夕法尼亚医疗成本控制委员会数据库（2012 - 2018年）的回顾性队列研究纳入了105336例行单侧初次择期THA的患者。我们通过对患者邮政编码进行地理编码，从美国人口普查中提取“社区”因素，包括步行适宜性指数、家庭收入、外国出生个体、英语熟练程度、计算机和互联网接入情况、无薪家庭工人、缺乏医疗保险者以及教育程度。我们训练了一种可解释的增强机器，这是广义相加模型的一种现代形式，以预测90天再入院率、90天死亡率、一年翻修率和住院时长（LOS）。汇总平均绝对得分以衡量变量重要性（即对预测贡献最大的变量）。
再入院率、翻修率和死亡率分别为8%、1.5%和0.3%，中位住院时长为两天。通过受试者工作特征曲线下面积衡量的预测性能，死亡率为0.76，再入院率为0.66，一年翻修率为0.57。对于住院时长，均方根误差为0.41（R = 0.2）。死亡率的前三大预测因素是社区、出院地点和年龄；再入院率的是出院地点、年龄和合并症；翻修率的是社区、出院地点和合并症；住院时长的是出院地点、社区和合并症。
社区层面的SDOH在预测THA结局方面比个体种族重要得多，尤其是对于90天死亡率。
