Department of Orthopedics, Hospital of South West Jutland, Esbjerg.
The Orthopedic Research Unit, Department of Orthopedic Surgery and Traumatology, Odense University Hospital, Odense, Department of Clinical Research, University of Southern Denmark.
Acta Orthop. 2021 Apr;92(2):137-142. doi: 10.1080/17453674.2020.1868708. Epub 2021 Jan 13.
Background and purpose - Dislocation of total hip arthroplasties (THA) is often treated with closed reduction and traditionally not registered in orthopedic registers. This study aimed to create an algorithm designed to identify cases of dislocations of THAs with high sensitivity, specificity, and positive predictive value (PPV) based on codes from the Danish National Patient Register (DNPR).Patients and methods - All patients (n = 31,762) with primary osteoarthritis undergoing THA from January 1, 2010 to December 31, 2014 were included from the Danish Hip Arthroplasty Register (DHR). We extracted available data for every hospital contact in the DNPR during a 2-year follow-up period, then conducted a comprehensive nationwide review of 5,096 patient files to register all dislocations and applied codes.Results - We identified 1,890 hip dislocations among 1,094 of the included 31,762 THAs. More than 70 different diagnoses and 55 procedural codes were coupled to the hospital contacts with dislocation. A combination of the correct codes produced a sensitivity of 63% and a PPV of 98%. Adding alternative and often applied codes increased the sensitivity to 91%, while the PPV was maintained at 93%. Additional steps increased sensitivity to 95% but at the expense of an unacceptable decrease in the PPV to 82%. Specificity was, in all steps, greater than 99%.Interpretation - The developed algorithm achieved high and acceptable values for sensitivity, specificity, and predictive values. We found that surgeons in most cases coded correctly. However, the codes were not always transferred to the discharge summary. In perspective, this kind of algorithm may be used in Danish quality registers.
背景与目的-全髋关节置换术后脱位(THA)通常采用闭合复位治疗,传统上并不在骨科登记处登记。本研究旨在创建一种算法,该算法旨在基于丹麦国家患者登记处(DNPR)的代码,以高灵敏度、特异性和阳性预测值(PPV)识别 THA 脱位病例。
患者和方法-从丹麦髋关节置换登记处(DHR)纳入 2010 年 1 月 1 日至 2014 年 12 月 31 日期间接受原发性骨关节炎初次 THA 的所有患者(n=31762)。我们从 DNPR 中提取了 2 年随访期间每例医院就诊的可用数据,然后对 5096 例患者的档案进行了全面的全国性审查,以登记所有脱位并应用代码。
结果-我们在 1094 例纳入的 31762 例 THA 中发现了 1890 例髋关节脱位。超过 70 种不同的诊断和 55 种手术代码与脱位的医院接触相关联。正确代码的组合产生了 63%的灵敏度和 98%的 PPV。添加替代和常用的代码可将灵敏度提高到 91%,而 PPV 保持在 93%。额外的步骤将灵敏度提高到 95%,但以牺牲可接受的 PPV 降至 82%为代价。特异性在所有步骤中均大于 99%。
解释-所开发的算法在灵敏度、特异性和预测值方面达到了较高且可接受的值。我们发现大多数情况下,外科医生的编码都是正确的。然而,这些代码并不总是被转移到出院小结中。从这个角度来看,这种算法可能会在丹麦质量登记处使用。