Department of Orthopedic Surgery, NYU Langone Health, New York, New York.
J Arthroplasty. 2024 Oct;39(10):2520-2524.e1. doi: 10.1016/j.arth.2024.07.006. Epub 2024 Jul 14.
Previous studies have attempted to validate the risk assessment and prediction tool (RAPT) in primary total hip arthroplasty (THA) patients. The purpose of this study was to: (1) identify patients who had an extended length of stay (LOS) following THA; and (2) compare the accuracy of 2 previously validated RAPT models.
We retrospectively reviewed all primary THA patients from 2014 to 2021 who had a completed RAPT score. Youden's J computational analysis was used to determine the LOS where facility discharge was statistically more likely. Based on the cut-offs proposed by Oldmeadow and Dibra, patients were separated into high- (O: 1 to 5 versus D: 1 to 3), medium- (O: 6 to 9 versus D: 4 to 7), and low- (O: 10 to 12 versus D: 8 to 12) risk groups.
We determined that an LOS of greater than 2 days resulted in a higher chance of facility discharge. In these patients (n = 717), the overall predictive accuracy (PA) of the RAPT was 79.8%. The Dibra model had a higher PA in the high-risk group (D: 68.2 versus O: 61.2% facility discharge). The Oldmeadow model had a higher PA in the medium-risk (O: 78.7 versus D: 61.4% home discharge) and low-risk (O: 97.0 versus D. 92.5% home discharge) groups.
As institutions continue to optimize LOS, the RAPT may need to be defined in the context of a patient's hospital stay. In patients requiring an LOS of greater than 2 days, the originally established RAPT cut-offs may be more accurate in predicting discharge disposition.
III Retrospective Cohort Study.
先前的研究试图验证原发性全髋关节置换术(THA)患者的风险评估和预测工具(RAPT)。本研究的目的是:(1)确定接受 THA 后住院时间延长(LOS)的患者;(2)比较 2 种先前验证的 RAPT 模型的准确性。
我们回顾性分析了 2014 年至 2021 年期间所有接受过完整 RAPT 评分的原发性 THA 患者。使用约登指数分析来确定 LOS,在此 LOS 下,医疗机构出院具有统计学上更大的可能性。根据 Oldmeadow 和 Dibra 的截止值,将患者分为高风险组(O:1 至 5 分与 D:1 至 3 分)、中风险组(O:6 至 9 分与 D:4 至 7 分)和低风险组(O:10 至 12 分与 D:8 至 12 分)。
我们确定 LOS 大于 2 天会增加医疗机构出院的可能性。在这些患者(n=717)中,RAPT 的总体预测准确性(PA)为 79.8%。在高风险组中,Dibra 模型的 PA 更高(D:68.2% vs. O:61.2%医疗机构出院)。在中风险组(O:78.7% vs. D:61.4%家庭出院)和低风险组(O:97.0% vs. D:92.5%家庭出院)中,Oldmeadow 模型的 PA 更高。
随着医疗机构继续优化 LOS,RAPT 可能需要根据患者的住院时间来定义。在需要 LOS 大于 2 天的患者中,最初建立的 RAPT 截止值可能更能准确预测出院去向。
III 级回顾性队列研究。