摘要目的 探讨成人复杂性阑尾炎发病高危因素,为制定合理的急性阑尾炎治疗策略提供参考.方法 采用回顾性病例对照研究方法,收集青岛大学附属医院2011年5月至2016年8月住院行阑尾切除术(包括开放和腹腔镜手术)并经病理确诊的312例成人急性阑尾炎患者的临床资料.排除年龄＜14周岁和孕妇以及合并阑尾周围脓肿、艾滋病、血液系统疾病、自身免疫性疾病、炎性肠病或进展期癌者.按术中所见和病理类型,将本组急性阑尾炎患者分为复杂性阑尾炎(112例,包括坏疽和穿孔)和非复杂性阑尾炎(200例,包括单纯性和非穿孔性阑尾炎即化脓性阑尾炎),比较两组患者的临床资料后,取有统计学意义的变量进行Logistic多因素回归分析,筛选出复杂性阑尾炎的高危因素,建立回归预测模型,采用Enter法建立回归方程:P=Expi∑BiXi/1+Exp∑BiXi,计算各变量的相对危险度.并对该预测模型进行回顾性和前瞻性(进一步收集2016年9月至2017年12月行阑尾切除手术的急性阑尾炎病例)验证,计算该模型预测复杂性阑尾炎的敏感度、特异度、准确度、阳性预测值和阴性预测值.结果 复杂性阑尾炎组与非复杂性阑尾炎组患者临床资料比较,发病时间[腹痛至入院,分别为(59.1±42.6) h 比(47.5±34.4) h,t =3.051,P=0.002]、白细胞计数[分别为(12.9±3.7)×109/L比(9.2±4.0)×109/L,t=9.755,P＜0.001]、中性粒细胞计数[分别为(9.8± 4.0)×109/L比(7.1±3.9)×109/L,t=6.020,P＜0.001]、中性粒细胞百分比[分别为(84.5±8.7)%比(68.2± 16.0)%,t=12.754,P＜0.001]、C反应蛋白水平[分别为(86.0±45.4) μg/L比(55.9±35.8) μg/L, t=7.614,P＜0.001]、血清白蛋白水平[分别为(334.0±4.8) g/L比(41.0±4.3) g/L,t =16.055,P＜0.001]、术前呕吐比例[分别为44.6%(50/112)比23.5%(47/200),χ2=14.980,P＜0.001]、术前高热(≥39℃)比例[分别为16.1%(18/112)比7.5%(15/200),χ2=5.577,P=0.022]、老年(≥60岁)患者比例[分别为22.3%(25/112)比13.0%(26/200),χ2=4.562,P=0.038]和既往阑尾炎病史[分别为16.1%(18/112)比7.5%(15/200),χ2=5.577,P=0.022]10项术前指标的差异有统计学意义.将上述10个变量纳入Logistic回归模型进行多因素分析,结果显示,6个变量与复杂性阑尾炎相关,根据其强弱依次为:老年(≥60岁)X1(OR=5.094)、高热(≥39℃)X2(OR=4.464)、中性粒细胞计数X6(OR=1.269)、中性粒细胞百分比X4 (OR=1.077)、C反应蛋白水平X5(OR=1.027)和血清白蛋白水平X3(OR=0.763).建立预测回归模型:P=1/[1+e(0.557+1.628X1+1.496X2－2.7X3+0.74X4+0.27X5+0.238X6)],其判断复杂性阑尾炎的灵敏度和特异度分别为76.8%(86/112)和90.0%(180/200).进一步前瞻性验证该模型对复杂性阑尾炎预测价值的灵敏度和特异度分别为76.2%(48/63)和81.1%(30/37).结论 60岁以上、体温≥39℃和中性粒细胞计数、中性粒细胞百分比、C反应蛋白水平升高以及低白蛋白血症是复杂性阑尾炎发病的高危因素,所建立的预测模型能较准确地判断复杂性阑尾炎.

abstractsObjective To explore the high risk factors of adult complex appendicitis, and to provide a reference for the development of a reasonable treatment strategy for acute appendicitis. Methods A retrospective case-control study was conducted to collect clinical data of 312 adult patients with acute appendicitis confirmed by pathology undergoing appendectomy, including open and laparoscopic surgery, from May 2011 to August 2016 at Affiliated Hospital of Qingdao University. Age ＜14 years old, pregnant women, complicating abscess around the appendix, AIDS, blood system diseases, autoimmune diseases, inflammatory bowel disease or progressive cancer patients were excluded. According to the intra-operative findings and pathological types, patients were divided into complex appendicitis(112 cases, including gangrene and perforation) and non-complex appendicitis (200 cases, including simple and non-perforated appendicitis, ie suppurative appendicitis). After comparing the clinical data of these two groups, statistically significant variables were induded for multivariate logistic regression analysis to identify risk factors of complex appendicitis, and to establish a regression model. Enter method was applied to establish the regression equation: P=Expi∑BiXi/1+Exp∑BiXi, and to calculate the relative risk of each variable. Meanwhile, retrospective and prospective verification was performed on this predictive model (cases of acute appendicitis from September 2016 to December 2017 were further collected).The sensitivity, specificity, accuracy, positive predictive value, and negative predictive value of complex appendicitis were calculated with the regression model. Results Comparison of the clinical data between the complex appendicitis group and the non-complex appendicitis group showed that differences of 10 preoperative indexes were statistically significant, including period from abdominal pain to admission [(59.1±42.6) hours vs.(47.5±34.4) hours, t=3.051, P=0.002], white blood cell count [(12.9±3.7)×109/L vs.(9.2±4.0)×109/L, t=9.755, P＜0.001], neutrophil count [(9.8± 4.0)×109/L vs.(7.1±3.9)×109/L, t=6.020, P＜0.001], neutrophil percentage [(84.5±8.7)%vs.(68.2± 16.0)%, t=12.754, P＜0.001], C-reactive protein levels [(86.0±45.4) μg/L vs.(55.9±35.8) μg/L, t=7.614, P＜0.001], serum albumin levels [(334.0±4.8) g/L vs.( 41.0±4.3) g/L, t=16.055, P＜0.001], vomiting ratio [44.6%(50/112) vs. 23.5%(47/200), χ2=14.980, P＜0.001], high fever(≥39°C) ratio [16.1%(18/112) vs. 7.5%(15/200), χ2=5.577, P=0.022], the proportion of patients ≥60 years old [22.3%(25/112) vs. 13.0%(26/200), χ2=4.562, P=0.038] and previous history of appendicitis [16.1%(18/112) vs. 7.5%(15/200), χ2=5.577, P=0.022]. The above 10 variables were included in the logistic regression model for multivariate analysis. The results showed that six variables were associated with complex appendicitis. According to their strength, they were old age (≥60 years old) X1(OR=5.094), high fever (≥39°C) X2(OR=4.464), neutrophil count X6 (OR=1.269), neutrophil percentage X4 (OR=1.077), C-reactive protein level X5 (OR=1.027), and serum albumin level X3 (OR=0.763).A predictive regression model was established: P=1/(1+e(0.557+1.628X1+1.496X2－2.7X3+0.74X4+0.27X5+0.238X6)), whose sensitivity and specificity of judging complex appendicitis were 76.8%(86/112) and 90.0%(180/200),respectively. Sensitivity and specificity for predictive value of complex appendicitis in further prospective validation of the model were 76.2%(48/63) and 81.1%(30/37), respectively. Conclusions Age ≥ 60 years old, body temperature ≥39°C, increased neutrophil count, neutrophil percentage and C-reactive protein levels, and hypoalbuminemia are risk factors for complex appendicitis. The establishment of predictive model may help determine complex appendicitis.