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A novel preoperative scoring system for the indication of unicompartmental knee arthroplasty, as predictor of clinical outcome and satisfaction

机译:一种新的术前评分系统,用于指示Unicompartmmmental膝关节置换术,作为临床结果和满足的预测因子

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Introduction Proper patient selection is a crucial factor for the outcome of the unicompartmental knee arthroplasty (UKA). However, there is still not a clear consensus on which patients could benefit the utmost from a UKA. The purpose of this prospective study was to introduce a novel, preoperative, predictive score (Unicompartmental Indication Score, UIS) to aid proper patient selection in UKA.Materials and methods A total of 152 patients with an average age of 68 years and a mean follow-up of 27 months were evaluated preoperatively with the UIS and postoperative at every follow-up. Correlation analysis was applied to identify potential relationships between the UIS, functional outcomes, pain relief, patient satisfaction, and range of motion. The ROC analysis was used to identify the best cutoff value of the UIS, which would have predicted an optimal outcome following UKA.Results The majority of the patients (91%) were satisfied with the operation, with 61% reporting excellent and 30% good satisfaction. The UIS was positively correlated to the postoperative Knee Society Score (KSS) for both pain (r = 0.26, /?<0.001) and function (r = 0.31, p<0.00). The UIS was also positively correlated to the patient satisfaction (p = 0A6, p< 0.001) and maximum postoperative flexion (r = 0.25, p< 0.001). The ROC analysis provided an ideal cutoff for UIS at 25 points (sensitivity: 75%, sensibility: 93%, area under the curve: 86%). At a mean follow-up of 27 months (range 24-37), we observed three revisions in 152 consecutive UKA with a mean UIS of 27 points (range 20-30).Conclusions The newly introduced UIS score might be a reliable preoperative scoring system to predict patients with excellent satisfaction, functional outcome, pain relief and possibly implant survivorship following UKA, and therefore, could help the proper patient selection and decision-making in UKA.
机译:引言适当的患者选择是单位膝关节置换术(UKA)的结果的关键因素。但是,仍然没有明确的共识,患者可以从UKA中获得最大的患者。这项前瞻性研究的目的是引入一种新颖,术前,预测评分(Unicommmmmmmmental指示得分,UI),以帮助您在UKA中适当的患者选择.80例,平均年龄为68岁和平均患者的82例患者在每次随访中,术前和术后评估了27个月的27个月。应用相关性分析来识别UIS,功能性结果,疼痛缓解,患者满意度和运动范围之间的潜在关系。 ROC分析用于识别UIS的最佳截止值,这将预测UKA.Results对该患者的大多数患者(91%)对该行动感到满意,报告优秀61%优秀和30%满意。 UIS与术后膝关节协会得分(KSS)正相关(R = 0.26,/?< 0.001)和功能(r = 0.31,p <0.00 )。 UIS也与患者满意度呈正相关(p = 0a6,p <0.001)和最大术后屈曲(r = 0.25,p <0.001)。 ROC分析为UI的理想截止值为25分(灵敏度:75%,敏感性:93%,曲线下的区域:86%)。在27个月的平均随访(范围24-37)中,我们在152个连续的UKA中观察了三个修订,其平均UIS为27分(范围20-30)。结论新介绍的UIS得分可能是可靠的术前得分系统以预测满意度优异,功能结果,疼痛缓解和可能植入的患者,因此,可以帮助您在UKA中适当的患者选择和决策。

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