Department of Oral, Maxillofacial and Plastic Surgery, University Hospital Bonn, Bonn, Germany.
Department of Orthopedic and Trauma Surgery, University Hospital Bonn, Bonn, Germany.
J Arthroplasty. 2019 Apr;34(4):717-722. doi: 10.1016/j.arth.2018.12.034. Epub 2019 Jan 5.
Postoperative complications are the main consumers of technical, medical, and human resources. Especially in the field of elective joint replacement surgery, a specialized, easy-to-obtain, and cost-efficient preoperative stratification and risk-estimation model is missing.
With preoperatively surveyed patient parameters, we identified the most relevant parameters to predict postoperative medical complications. We devised a prospective risk model, measuring the individual probability for intermediate care unit (IMC) or intensive care unit (ICU) admission. The study includes all patients (n = 649) treated with primary or revision total knee arthroplasty in our clinic from 2008 to 2012.
The association between general comorbidity scores and mortality risk is well known. Among different comorbidity scores, the Charlson Comorbidity Index is not only relevant for overall postoperative complications (odds ratios [OR] = 2.20) but also predictive of specific complications such as the postoperative need for blood transfusion (OR = 1.94) and unexpected adverse events (OR = 1.74). Considering adverse events, c-reactive protein and leukocyte levels are also highly relevant. Upon predicting a necessary postoperative transfer to an IMC or ICU, the preoperative hemoglobin level, the Charlson Comorbidity Index, and the Index of Coexistent Disease stood out. The latter indicates an increased rate for an IMC/ICU stay by 341% per point. Condensing the most influential predictors, the probability for postoperative IMC/ICU transfer can be calculated for each individual patient. Using the routinely assessed patient's variables, no steadier prediction is possible.
The introduced risk-estimation model offers a specialized preoperative resource-stratification method in knee joint replacement surgery. It condenses the most influential, individual risk factors to avoid clinical test redundancy and improve resource efficiency and presurgical care planning. A prospective follow-up study could help validating the risk model in clinical routine.
术后并发症是消耗技术、医疗和人力资源的主要因素。特别是在择期关节置换手术领域，缺乏专门的、易于获取且具有成本效益的术前分层和风险评估模型。
我们通过术前调查患者参数，确定了预测术后医疗并发症的最相关参数。我们设计了一个前瞻性风险模型，测量个体入住中级护理病房（IMC）或重症监护病房（ICU）的概率。该研究包括 2008 年至 2012 年在我们诊所接受初次或翻修全膝关节置换术的所有患者（n=649）。
一般合并症评分与死亡率之间的关联是众所周知的。在不同的合并症评分中，Charlson 合并症指数不仅与整体术后并发症相关（比值比 [OR] =2.20），而且还能预测特定并发症，如术后需要输血（OR=1.94）和意外不良事件（OR=1.74）。考虑到不良事件，C 反应蛋白和白细胞水平也非常相关。在预测术后需要转移到 IMC 或 ICU 时，术前血红蛋白水平、Charlson 合并症指数和并存疾病指数尤为重要。后者表示每个点的 IMC/ICU 入住率增加 341%。通过浓缩最具影响力的预测因子，可以计算每位患者术后转移到 IMC/ICU 的概率。使用常规评估的患者变量，无法进行更稳定的预测。
所引入的风险评估模型为膝关节置换手术提供了一种专门的术前资源分层方法。它浓缩了最具影响力的个体风险因素，避免了临床测试的冗余，提高了资源效率和术前护理计划。前瞻性随访研究可以帮助验证风险模型在临床常规中的应用。
