Rosenfeld Scott, Bernstein Derek T, Daram Shiva, Dawson John, Zhang Wei
*Pediatric Orthopaedic Surgery, Texas Children's Hospital, Baylor College of Medicine †Houston Methodist Hospital ‡Baylor College of Medicine §Texas Children's Hospital Outcomes and Impact Service, Houston, TX.
J Pediatr Orthop. 2016 Jan;36(1):70-4. doi: 10.1097/BPO.0000000000000389.
The gold standard for treatment of septic arthritis is urgent surgical debridement. Preoperative magnetic resonance imaging (MRI) may identify osteomyelitis, subperiosteal abscesses, and intramuscular abscesses, which frequently occur with septic arthritis. If these adjacent infections are not recognized, initial treatment may be inadequate. The purpose of this study is to develop a prediction algorithm to distinguish septic arthritis with adjacent infections from isolated septic arthritis to determine which patients should undergo preoperative MRI.
An IRB-approved retrospective review of 87 children treated for septic arthritis was performed. All patients underwent MRI. Sixteen variables (age, sex, temperature, WBC, CRP, ESR, ANC, hematocrit, platelet count, heart rate, systolic blood pressure, diastolic blood pressure, symptom duration, weight-bearing status, prior antibiotic therapy, and prior hospitalization) from admission were reviewed. Graphical and logistical regression analysis was used to determine variables independently predictive of adjacent infection. Optimal cutoff values were determined for each variable and a prediction algorithm was created. Finally, the model was applied to our patient database and each patient with isolated septic arthritis or adjacent infection was stratified based upon the number of positive predictive factors.
A total of 36 (41%) patients had isolated septic arthritis and 51 (59%) had septic arthritis with adjacent foci. Five variables (age above 3.6 y, CRP>13.8 mg/L, duration of symptoms >3 d, platelets <314×10 cells/μL, and ANC>8.6×10 cells/μL) were found to be predictive of adjacent infection and were included in the algorithm. Patients with ≥3 risk factors were classified as high risk for septic arthritis with adjacent infection (sensitivity: 90%, specificity: 67%, positive predictive value: 80%, negative predictive value: 83%).
Age, CRP, duration of symptoms, platelet count, and ANC were predictive of adjacent infections. Patients who met ≥3 criteria are at high risk for adjacent infection and may benefit from preoperative MRI.
Level III—retrospective comparative study.
化脓性关节炎的治疗金标准是紧急手术清创。术前磁共振成像(MRI)可识别骨髓炎、骨膜下脓肿和肌肉内脓肿,这些情况常与化脓性关节炎并发。如果未识别出这些相邻感染,初始治疗可能不充分。本研究的目的是开发一种预测算法,以区分伴有相邻感染的化脓性关节炎和孤立性化脓性关节炎,从而确定哪些患者应接受术前MRI检查。
对87例接受化脓性关节炎治疗的儿童进行了一项经机构审查委员会(IRB)批准的回顾性研究。所有患者均接受了MRI检查。回顾了入院时的16项变量(年龄、性别、体温、白细胞计数(WBC)、C反应蛋白(CRP)、红细胞沉降率(ESR)、中性粒细胞计数(ANC)、血细胞比容、血小板计数、心率、收缩压、舒张压、症状持续时间、负重状态、既往抗生素治疗和既往住院情况)。采用图形分析和逻辑回归分析来确定独立预测相邻感染的变量。确定每个变量的最佳临界值并创建一个预测算法。最后,将该模型应用于我们的患者数据库,并根据阳性预测因素的数量对每例孤立性化脓性关节炎或伴有相邻感染的患者进行分层。
共有36例(41%)患者为孤立性化脓性关节炎,51例(59%)患者为伴有相邻病灶的化脓性关节炎。发现5项变量(年龄大于3.6岁、CRP>13.8mg/L、症状持续时间>3天、血小板<314×10⁹细胞/μL和ANC>8.6×10⁹细胞/μL)可预测相邻感染,并纳入该算法。具有≥3个危险因素的患者被归类为伴有相邻感染的化脓性关节炎高危患者(敏感性:90%,特异性:67%,阳性预测值:80%,阴性预测值:83%)。
年龄、CRP、症状持续时间、血小板计数和ANC可预测相邻感染。符合≥3条标准的患者发生相邻感染的风险较高,可能从术前MRI检查中获益。
III级——回顾性比较研究。