山东大学耳鼻喉眼学报 ›› 2026, Vol. 40 ›› Issue (4): 90-95.doi: 10.6040/j.issn.1673-3770.0.2025.284

• 论著 • 上一篇    下一篇

颈深部脓肿预后影响因素分析及评分量表的建立

袁江慧,汪李琴,陈曦,张立庆,周涵   

  1. 南京医科大学第一附属医院/江苏省人民医院耳鼻咽喉科, 江苏 南京 210029
  • 发布日期:2026-07-10
  • 基金资助:
    江苏省卫生健康委面上项目(H2019001)

Study on prognostic factors and development of a scoring scale for deep neck space abscess

YUAN Jianghui, WANG Liqin, CHEN Xi, ZHANG Liqing, ZHOU Han   

  1. Department of Otorhinolaryngology, The First Affiliated Hospital, Nanjing Medical University, Nanjing 210029, Jiangsu, China
  • Published:2026-07-10

摘要: 目的 探讨影响颈深部脓肿患者预后的相关因素,并基于这些因素构建预后评分量表。 方法 回顾性分析129例颈深部脓肿患者的临床资料,分析主要临床特征、实验室指标和影像学表现等相关因素与预后不良结局的关系。采用单因素及多因素Logistic回归分析筛选预后不良的独立危险因素。根据受试者工作特征(receiver operating characteristic, ROC)曲线确定连续变量的最佳截断值,并将其转换为分类变量。基于多因素回归模型中各独立预测因子的回归系数(B),以最小绝对B值为基准进行标准化并四舍五入赋分,构建简易预后评分量表。采用5折交叉验证对模型进行内部验证。进一步利用ROC曲线及曲线下面积(area under the curve, AUC)评价模型区分度,并计算不同风险分组下的敏感度、特异度、阳性预测值、阴性预测值和准确率;采用Hosmer-Lemeshow检验评价模型校准度。 结果 多因素Logistic回归分析显示,纵隔受累(OR=15.715,95%CI:4.847~50.952,P<0.001)、APTT≥33.3 s(OR=7.138,95%CI:1.143~44.589,P=0.036)和CAR≥3.8(OR=15.422,95%CI:4.834~49.206,P<0.001)是颈深部脓肿患者预后不良的独立危险因素。基于上述3个因素构建简易评分量表,各赋值1分,总分范围为0~3分。根据ROC曲线分析,确定总分≥2分为高风险组,总分<2分为低风险组。该评分量表预测患者不良结局的AUC为0.925(95%CI:0.878~0.972,P<0.001),敏感度为96.6%,特异度为69.1%,阳性预测值为73.1%,阴性预测值为95.9%,准确率为81.8%。Hosmer-Lemeshow检验显示模型拟合良好(χ2=1.291,P=0.863)。 结论 本研究构建的评分量表对颈深部脓肿患者的预后评估具有一定价值,有助于优化该病的个体化治疗决策。

关键词: 颈深部脓肿, 预后评估, 评分量表, 风险分层, 个体化治疗

Abstract: Objective To investigate the factors associated with the prognosis of patients with deep neck abscesses and to develop a prognostic scoring system based on these factors. Methods We conducted a retrospective analysis of clinical data from 129 patients with deep neck abscesses to examine the relationship between relevant factors-including major clinical characteristics, laboratory parameters, and imaging findings-and poor clinical outcomes. Univariate and multivariate logistic regression analyses were performed to identify independent risk factors for poor prognosis.The optimal cutoff value for continuous variables was determined using receiver operating characteristic(ROC)curves, and these variables were then converted into categorical variables. A simple prognostic scoring system was developed by standardizing and rounding the regression coefficients(B values)of each independent predictor in the multivariate regression model, using the minimum absolute B value as the reference.The model was internally validated using 5-fold cross-validation. The model's discriminatory performance was further evaluated using ROC curves and the area under the curve(AUC), and sensitivity, specificity, positive predictive value, negative predictive value, and accuracy were calculated for different risk groups; the Hosmer-Lemeshow test was used to assess model calibration. Results Multivariate logistic regression analysis showed that mediastinal involvement(OR=15.715, 95%CI: 4.847-50.952, P<0.001), APTT≥33.3 s(OR=7.138, 95%CI: 1.143-44.589, P=0.036), and CAR≥3.8(OR=15.422, 95%CI: 4.834-49.206, P<0.001)were independent risk factors for poor prognosis in patients with deep neck abscesses.A simple scoring scale was developed based on the above three factors, with each factor assigned a score of 1, resulting in a total score ranging from 0 to 3. Based on ROC curve analysis, a total score of ≥2 was defined as the high-risk group, and a total score of <2 as the low-risk group. The AUC of this scoring system for predicting adverse outcomes in patients was 0.925(95%CI: 0.878-0.972, P<0.001), with a sensitivity of 96.6%, a specificity of 69.1%, a positive predictive value of 73.1%, a negative predictive value of 95.9%, and an accuracy of 81.8%. The Hosmer-Lemeshow test indicated that the model fit well(χ2=1.291, P=0.863). Conclusion The scoring scale developed in this study is of some value for assessing the prognosis of patients with deep neck abscesses and can help optimize individualized treatment decisions for this condition.

Key words: Deep Neck Space Abscess, Prognostic assessment, Scoring scale, Risk stratification, Individualized treatment

中图分类号: 

  • R766.15
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