真菌性鼻-鼻窦炎发病相关因素及临床特征分析

目的 探讨真菌性鼻．鼻窦炎发病相关因素及临床特征。方法 对110例真菌性鼻-鼻窦炎和慢性鼻-鼻窦炎患者的临床资料进行回顾性对照研究，对术前资料进行多因素Logistic回归分析和χ^2检验，以分析真菌性鼻-鼻窦炎发病相关因素和临床特征。采用真菌特异性六胺银染色方法，对110例真菌性鼻-鼻窦炎进行分型。结果 建立了以病程（x1）、涕血（x2）、头痛（x3）、钙化斑（x4）、年龄（x5）、单侧或双侧病变（x6）为变量的真菌性鼻-鼻窦炎发病Logistic回归预测方程：y=-8．713＋0．496x1＋4．575x2＋1．190x3＋4．119x4＋1．199x5＋2．698x6，P=exp（y）／1＋exp（y）]，并与慢性鼻-鼻窦炎组相比。真菌性鼻-鼻窦炎的临床特征为女性患者、40岁以上、病程3年以内，以头痛、涕血为主要症状，影像学表现为单侧病变、有钙化斑出现（P〈0．05）。110例真菌性鼻-鼻窦炎患者中，34例为慢性侵袭性、76例为非侵袭性。结论 真菌性鼻-鼻窦炎的临床表现特征性明显，其发病可通过相关因素的Logistic回归预测方程进行预测。

Study on correlated factors and clinical features of fungal rhinosinusitis

Objective To investigate the correlated factors and clinical features of fungal rhinosinusitis. Methods The clinical data of 110 patients with fungal rhinosinusitis treaed by surgery and another group of 110 patients with chronic rhinosinusitis who were sampled randomly between January 1999 and June 2004 in our hospital were retrospectively compared. The correlated factors and the clinical features of fungal rhinosinusitis were investigated by using the multiple factor Logistic regression analysis and chi-square test. The pathological types of 110 fungal rhinosinusitis were classified by using Gomori methenamine silver staining which was special for fungi. Results The logistic regression predictive equation for fungal rhinosinusitis was : y=-8.713+0.496x_1+4.575x_2+1.190x_3+4.119x_4+1.199x_5+2.698x_6,P=exp(y) /1+exp(y), in which the concomitant variables were course of the disease(x_1), haem-nasal discharge(x_2), headache(x_3),calcified plaque in CT scan(x_4), age(x_5)and unilateral / bilateral sinus lesion(x_6), respectively. The P value meant the probability of suffering fungal rhinosinusitis. Compared with chronic rhinosinusitis, the clinical features of fungal rhinosinusitis were female, over 40-year-old, course of disease < 3 years, headache, haem-nasal discharge, unilateral sinus lesion and calcified plaque in CT scan. Among the 110 patients with fungal rhinosinusitis, 34 cases were chronic invasive and 76 were non-invasive. Conclusions The clinical features of fungal rhinosinusitis are significant for the diagnosis, and it can be predicted by using the suitable logistic predictable equation.