摘要
目的 构建基于C-反应蛋白、红细胞沉降率及血常规指标等构建化脓性脊柱感染(PSI)和非化脓性脊柱感染(NPSI)的鉴别诊断模型.方法 收集2019年1月-2022年9月湘雅医院及湘雅博爱医院收治的疑似脊柱感染患者158例为研究对象,根据病理鉴定结果分为PSI组(87例)和非PSI组(71例);分析两组临床资料,比较两组各指标的差异;筛选出C-反应蛋白、红细胞沉降率与病程并得出诊断模型,绘制受试者工作特征(ROC)曲线,评估模型的诊断价值.结果 两组C-反应蛋白、红细胞沉降率、白细胞计数、红细胞计数、血红蛋白、中性粒细胞、中性粒细胞百分比、单核细胞百分比及病程差异有统计学意义(P＜0.05);通过Logistic回归,筛选出红细胞沉降率、白细胞计数、病程三项指标建立联合诊断模型,该模型ROC曲线下的面积(AUC)为0.802,敏感度为0.678,特异度为0.845.结论 通过红细胞沉降率,白细胞计数,病程三项指标建立的联合诊断模型,能辅助鉴别化脓性与非化脓性脊柱感染,可更好地指导临床,及时开展针对性治疗改善患者预后.
Abstract
OBJECTIVE To construct a differential diagnostic model for pyogenic spinal infection(PSI)and non-py-ogenic spinal infection(NPSI)based on C-reactive protein,erythrocyte sedimentation rate,and blood routine indi-cators.METHODS Totally 158 suspected spinal infection patients admitted to Xiangya and Xiangya Boai Hospital from Jan.2019 to Sep.2022 were collected as the study subjects,and they were divided into a PSI group(87 ca-ses)and a non PSI group(71 cases)according to pathological identification results.Clinical data of the two groups were analyzed,and the differences in various indicators between the two groups were compared.C-reactive pro-tein,erythrocyte sedimentation rate,and disease course were screened to develop a diagnostic model,receiver op-erating characteristic(ROC)curves were plotted to evaluated the diagnostic value of the model.RESULTS There were statistically significant differences in C-reactive protein,erythrocyte sedimentation rate,white blood cell count,red blood cell count,hemoglobin,neutrophils,neutrophil percentage,monocyte percentage,and disease course between the two groups(P＜0.05);Through logistic regression,the three indicators of red blood cell sed-imentation rate,white blood cell count,and disease course were screened to establish a joint diagnostic model,which had an area under the ROC curve(AUC)of 0.802,a sensitivity of 0.678,and a specificity of 0.845.CONCLUSION The joint diagnostic model established by red blood cell sedimentation rate,white blood cell count,and disease course can assist in differentiating pyogenic and non-pyogenic spinal infections,which can better guide the clinic and improve the prognosis of patients with timely and targeted treatment.
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