[1]马 晨,陈 葳,张 祎,等.布鲁氏菌感染患者临床特征和实验室指标分析及预后模型建立研究[J].现代检验医学杂志,2023,38(06):142-147+152.[doi:10.3969/j.issn.1671-7414.2023.06.026]
　MA Chen,CHEN Wei,ZHANG Yi,et al.Analysis of Clinical Characteristics and Laboratory Indicators of Patients with Brucella Infection and Establishment of Prognostic Model[J].Journal of Modern Laboratory Medicine,2023,38(06):142-147+152.[doi:10.3969/j.issn.1671-7414.2023.06.026]
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布鲁氏菌感染患者临床特征和实验室指标分析及预后模型建立研究()
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《现代检验医学杂志》[ISSN:/CN:]

卷:
第38卷
期数:
2023年06期
页码:
142-147+152
栏目:
论著
出版日期:
2023-11-15

文章信息/Info

Title:
Analysis of Clinical Characteristics and Laboratory Indicators of Patients with Brucella Infection and Establishment of Prognostic Model
文章编号:
1671-7414（2023）06-142-07
作者:
马 晨; 陈 葳; 张 祎; 张 晶; 袁 晶
（西安交通大学第一附属医院检验科，西安 710061）
Author(s):
MA Chen; CHEN Wei; ZHANG Yi; ZHANG Jing; YUAN Jing
（Department of Clinical Laboratory, the First Affiliated Hospital of Xi’an Jiaotong University, Xi’an 710061, China）
关键词:
布鲁氏菌; 临床特征; 实验指标; 预后模型
分类号:
R378.5；R446.5
DOI:
10.3969/j.issn.1671-7414.2023.06.026
文献标志码:
A
摘要:
目的 探讨布鲁氏菌感染患者临床与实验室指标的差异，并以此构建预后模型，为临床诊治布鲁氏菌感染提供依据。方法 选取2013 年1 月～ 2021 年10 月于西安交通大学第一附属医院收治的布鲁氏菌感染患者120 例作为研究对象，根据治疗结果将患者分为预后不良组（n=40）和预后良好组（n=80）。对所有纳入对象一般资料、临床症状及体征、实验室指标、并发症情况进行分析，采用多因素Logistic 回归分析影响布鲁氏菌感染患者预后不良的影响因素，采用R软件构建预测其预后不良发生的列线图模型，采用ROC 曲线和校准曲线评价模型的区分度和准确度。结果 120 例患者，54.17% 患者年龄低于50 岁，男性患病率高于女性，有明确牲畜、生牛羊肉等方面接触史以及从事相关工作，且部分患者具有阳性家族史；布鲁氏菌感染临床表现前三位的症状为乏力（68.33%）、关节痛（64.17%）和盗汗（54.17%），体征为发热（63.33%）、体重减轻（19.17%）、睾丸肿胀和关节红肿（各占3.33%）；单因素分析发现年龄≥ 50 岁、病程≥ 31 天、关节痛、腰背痛、发热、淋巴细胞降低、ALT>40U/L，AST>42U/L，血培养阳性、服用多西环素+ 利福平比例与预后不良有关（χ2=4.271~13.070, 均P<0.05）；多元Logistic 回归模型结果显示，年龄、病程、关节痛和腰背痛均是布鲁氏菌感染患者预后不良发生的独立危险因素，淋巴细胞降低是保护因素（P<0.05）；根据多因素分析结果，构建预测列线图模型，得到的回归方程为Logit(P)=1.384+0.552X1+1.064X2-0.140X3+0.600X4+0.449X5，该模型AUC（95%CI）为0.853（95%CI:0.804 ～ 0.895），灵敏度和特异度分别为0.827，0.795，表明该预测模型区分度较好，校准曲线表明该模型准确度较高。结论 布鲁氏菌感染临床表现各异且不典型，可累及全身多个系统。年龄≥ 50 岁、病程≥ 31 天、关节痛、腰背痛均是患者预后不良的独立危险因素，而淋巴细胞<0.8×109/L 为保护因素，临床医生可结合以上指标做到早诊断和规范治疗。
Abstract:
Objective To explore the difference between clinical and laboratory indicators of patients with Brucella infection, and build a prognosis model based on this, so as to provide a basis for clinical diagnosis and treatment of Brucella infection. Methods 120 patients with Brucella infection who were admitted to the First Affiliated Hospital of Xi’an Jiaotong University from January 2013 to October 2021 were selected as the study objects. According to their prognosis, the patients were divided into poor prognosis group (n=40) and good prognosis group (n=80).The general data, clinical symptoms and signs, laboratory indicators and complications of all the subjects were analyzed. Multivariate logistic regression analysis was used to analyze the factors influencing the poor prognosis of patients with brucella infection, and used R software to build a nomograph model to predict the occurrence of poor prognosis, ROC curve and calibration curve were used to evaluate the discrimination and accuracy of the model. Results Among 120 patients，54.17% were younger than 50 years old, and the prevalence rate of males was higher than that of females，they had a clear history of contact with livestock, raw beef and mutton, and had engaged in relevant work, and some patients had a positive family history. The top three clinical manifestations of Brucella infection were fatigue (68.33%), arthralgia (64.17%) and night sweats (54.17%). The physical signs were fever (63.33%), weight loss (19.17%), testicular swelling and joint redness (3.33% each). Univariate analysis showed that patients in both groups had poor prognosis in terms of age ≥ 50 years, course ≥ 31 days，arthralgia，low back pain, fever，lymphopenia，ALT>40U/L，AST>42U/L，positive blood culture, and the proportion of taking doxycycline±rifampicin (χ2=4.271~13.070, all P<0.05). The results of multiple logistic regression model showed that age, course of disease，joint pain and low back pain were independent risk factors for poor prognosis of patients with Brucella infection, and lymphocytes was a protective factor (P<0.05). According to the results of multifactor analysis, a predictive nomogram model was constructed, and the regression equation was Logit(P)=1.384+ 0.552X1+1.064X2-0.140X3+0.600X4+0.449X5. The AUC（95%CI） of the model was 0.853 (95%CI: 0.804 ～ 0.895). The sensitivity and specificity was 0.827, 0.795, respectively, and indicating that the prediction model had good discrimination, and the calibration curve indicated that the model had high accuracy. Conclusion Brucella had different and atypical clinical manifestations, which could affect multiple systems of the whole body. If the patient’s age is ≥ 50 years old, the course of disease is ≥ 31 days, arthralgia, and low back pain could increase its risk, while lymphocytes<0.8×109/L could improve the possibility of cure. Clinicians can combine the above indicators to achieve early diagnosis and standardized treatment.

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备注/Memo

备注/Memo:
作者简介： 马晨（1988-），女，硕士研究生，主管检验师，研究方向：临床微生物检验、细菌耐药监测、微生物快速鉴定，E-mail：i4hmhh@126net.com.cn。
通讯作者：陈葳（1962-），女，博士研究生，主任检验师，研究方向：分子诊断方向，E-mail：2398023255@qq.com。
更新日期/Last Update: 2023-11-15