School of Rehabilitation, Faculty of Medicine, University of Montreal, Montreal, Quebec; and Orthopaedic Clinical Research Unit, Maisonneuve-Rosemont Hospital Research Center, Centre intégré universitaire de santé et de services sociaux de l'Est-de-l'Île-de-Montréal, Montreal, Quebec, Canada.
Department of Surgery, Maisonneuve-Rosemont Hospital, University of Montreal, Montreal, Quebec; and Centre intégré universitaire de santé et de services sociaux de l'Est-de-l'Île-de-Montréal, Montreal, Quebec, Canada.
PM R. 2018 May;10(5):472-482. doi: 10.1016/j.pmrj.2017.10.009. Epub 2017 Oct 27.
The current approach to the clinical diagnosis of traumatic and degenerative symptomatic meniscal tears (SMTs) proposes combining history elements and physical examination tests without systematic prescription of imaging investigations, yet the evidence to support this diagnostic approach is scarce.
To assess the validity of diagnostic clusters combining history elements and physical examination tests to diagnose or exclude traumatic and degenerative SMT compared with other knee disorders.
Prospective diagnostic accuracy study.
Patients were recruited from 2 orthopedic clinics, 2 family medicine clinics, and from a university community.
A total of 279 consecutive patients who underwent consultation for a new knee complaint.
Each patient was assessed independently by 2 evaluators. History elements and standardized physical examination tests performed by a physiotherapist were compared with the reference standard: an expert physicians' composite diagnosis including a clinical examination and confirmatory magnetic resonance imaging. Participating expert physicians were orthopedic surgeons (n = 3) or sport medicine physicians (n = 2). Penalized logistic regression (least absolute shrinkage and selection operator) was used to identify history elements and physical examination tests associated with the diagnosis of SMT and recursive partitioning was used to develop diagnostic clusters.
Diagnostic accuracy measures were calculated including sensitivity, specificity, positive and negative predictive values, and positive and negative likelihood ratios (LR+/-) with associated 95% confidence intervals (CIs).
Eighty patients had a diagnosis of SMT (28.7%), including 35 traumatic tears and 45 degenerative tears. The combination a history of trauma during a pivot, medial knee pain location, and a positive medial joint line tenderness test was able to diagnose (LR+ = 8.9; 95% CI 6.1-13.1) or exclude (LR- = 0.10; 95% CI 0.03-0.28) a traumatic SMT. Combining a history of progressive onset of pain, medial knee pain location, pain while pivoting, absence of valgus or varus knee misalignment, or full passive knee flexion was able to moderately diagnose (LR+ = 6.4; 95% CI 4.0-10.4) or exclude (LR- = 0.10; 95% CI 0.03-0.31) a degenerative SMT. Internal validation estimates were slightly lower for all clusters but demonstrated positive LR superior to 5 and negative LR inferior to 0.2 indicating moderate shift in posttest probability.
Diagnostic clusters combining history elements and physical examination tests can support the differential diagnosis of SMT. These results represent the initial derivation of the clusters and external validation is mandatory.
I.
目前,对于创伤性和退行性症状性半月板撕裂(SMT)的临床诊断,建议结合病史元素和体格检查测试,而无需系统进行影像学检查,但支持这种诊断方法的证据很少。
评估结合病史元素和体格检查测试来诊断或排除创伤性和退行性 SMT 与其他膝关节疾病的诊断簇的有效性。
前瞻性诊断准确性研究。
患者从 2 家骨科诊所、2 家家庭医学诊所和一所大学社区招募。
共 279 名连续就诊新膝关节疾病的患者。
每位患者由 2 位评估者独立评估。由物理治疗师进行的病史元素和标准化体格检查测试与参考标准进行了比较:专家医生的综合诊断,包括临床检查和确认性磁共振成像。参与的专家医生是骨科医生(n=3)或运动医学医生(n=2)。使用最小绝对收缩和选择算子(least absolute shrinkage and selection operator)进行惩罚逻辑回归,以识别与 SMT 诊断相关的病史元素和体格检查测试,并使用递归分区来开发诊断簇。
计算诊断准确性指标,包括敏感性、特异性、阳性和阴性预测值,以及阳性和阴性似然比(LR+/-)及其 95%置信区间(CI)。
80 名患者被诊断为 SMT(28.7%),其中 35 名患有创伤性撕裂,45 名患有退行性撕裂。膝关节内侧疼痛位置、膝关节内侧线压痛试验阳性、膝关节创伤史的组合能够诊断(LR+ = 8.9;95%CI 6.1-13.1)或排除(LR- = 0.10;95%CI 0.03-0.28)创伤性 SMT。膝关节疼痛逐渐发作、膝关节内侧疼痛位置、膝关节旋转时疼痛、无内翻或外翻膝关节对线不良、或完全被动膝关节伸展的病史组合能够适度诊断(LR+ = 6.4;95%CI 4.0-10.4)或排除(LR- = 0.10;95%CI 0.03-0.31)退行性 SMT。对于所有簇,内部验证估计值略低,但阳性 LR 大于 5,阴性 LR 小于 0.2,表明在测试后概率中存在适度的转移。
结合病史元素和体格检查测试的诊断簇可支持 SMT 的鉴别诊断。这些结果代表了聚类的初步推导,需要进行外部验证。
I。