第三代头孢菌素治疗社区获得性自发性细菌性腹膜炎的疗效预测模型

朱龙川; 吴蔚; 邹波; 甘达凯; 林学; 周炜; 熊墨龙

doi:10.3969/j.issn.1001-5256.2022.11.012

第三代头孢菌素治疗社区获得性自发性细菌性腹膜炎的疗效预测模型

DOI: 10.3969/j.issn.1001-5256.2022.11.012

朱龙川^1a, , ,,
吴蔚²,
邹波^1a,
甘达凯^1a,
林学^1a,
周炜^1b,
熊墨龙^1a

1a.
南昌市第九医院肝病科，南昌 330002
1b.
南昌市第九医院信息科，南昌 330002
2.
江西省儿童医院消化科，南昌 330000

基金项目:

江西省重点研发计划项目 (20181BBG78010)

伦理学声明：本研究于2017年8月14日通过南昌市第九医院伦理委员会批准并同意豁免知情同意，批号：[2017]伦简审字(03)号。

利益冲突声明：本研究不存在研究者、伦理委员会成员、受试者监护人以及与公开研究成果有关的利益冲突。

作者贡献声明：朱龙川负责课题设计，资料分析，论文撰写和定稿；吴蔚负责资料分析与论文撰写；邹波、甘达凯、林学、周炜参与收集数据，修改论文；熊墨龙参与修改论文。

详细信息

通信作者:
朱龙川，zlcy1984@sina.com

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出版历程
- 收稿日期: 2022-04-05
- 录用日期: 2022-05-07
- 出版日期: 2022-11-20

Establishment of a model for predicting the efficacy of third-generation cephalosporin in treatment of community-acquired spontaneous bacterial peritonitis

Longchuan ZHU^{1a
, ,
,},
Wei WU²,
Bo ZOU^1a,
Dakai GAN^1a,
Xue LIN^1a,
Wei ZHOU^1b,
Molong XIONG^1a

1a.
Department of Liver Disease, The Ninth Hospital of Nanchang, Nanchang 330002, China
1b.
Department of Information Technology, The Ninth Hospital of Nanchang, Nanchang 330002, China
2.
Department of Digestion, Children's Hospital of Jiangxi Province, Nanchang 330000, China

Research funding:

Key Research and Development Program of Jiangxi Province (20181BBG78010)

More Information

Corresponding author: ZHU Longchuan, zlcy1984@sina.com(ORCID: 0000-0002-4461-6195)

摘要

摘要: 目的探讨第三代头孢菌素(3^rd GC)治疗社区获得性自发性细菌性腹膜炎(CASBP)疗效的预测因素，构建并验证3^rd GC治疗CASBP的疗效预测模型。方法回顾性收集南昌市第九医院的肝硬化伴CASBP患者，均单用3^rd GC进行初始治疗，依据疗效分为无效组与有效组。2013年—2018年住院的纳入建模库(无效组55例和有效组110例)，2019年—2020年住院的纳入验证库(无效组17例和有效组43例)。在建模库中比较两组的一般资料、基础病、既往史、临床表现和实验室检查等指标，采用单因素分析(符合正态分布的计量资料组间比较采用t检验；不符合正态分布的计量资料组间比较采用Mann-Whitney U检验, 计数资料组间比较采用χ²检验或Fisher精确概率法)和二元Logistic回归分析识别疗效预测因素，根据Logistic回归方程构建疗效预测模型。采用受试者工作特征(ROC)曲线分别在建模库和验证库中对模型行内部验证和外部验证。结果全组以男性为主(占80.0%)，平均(51.6±12.0)岁，肝硬化病因以乙型肝炎为主(66.7%)，3^rd GC总有效率为68.0%。建模库中，无效组的SBP首次发病占比、腹水多形核细胞(PMN)计数及腹水白细胞计数明显低于有效组(P值均＜0.05)，而无效组的广谱抗生素暴露占比与血小板均显著高于有效组(P值均＜0.05)；Logistic回归分析显示，SBP首次发病[比值比(OR)=0.158，95%置信区间(CI)：0.064~0.392，P＜0.001]、腹水PMN计数(OR=0.728，95%CI：0.530~0.998，P=0.046)、广谱抗生素暴露(OR=9.152，95%CI：1.513~55.351，P=0.016)及血小板(OR=1.012，95%CI：1.006~1.019，P＜0.001)是3^rd GC治疗无效的独立预测因素；疗效预测模型的ROC曲线下面积为0.840，依据约登指数最大原则，预测评分≥0.207是预测治疗无效的最佳界值，对应的约登指数为0.536，敏感度89.1%，特异度63.6%，阳性预测值55.1%，阴性预测值92.1%。验证库中，该模型的ROC曲线下面积为0.837。结论 SBP首次发病和更高的腹水PMN计数是3^rd GC治疗CASBP无效的保护因素，广谱抗生素暴露和更高的血小板是其危险因素，以此建立的3rd GC治疗CASBP的疗效预测模型具有良好的预测效能，具备临床应用潜能。
- 肝硬化 /
- 腹膜炎 /
- 社区获得性感染 /
- 头孢菌素类 /
- Logistic模型
Abstract: Objective To investigate the factors for predicting the efficacy of third-generation cephalosporin (3^rd GC) in the treatment of community-acquired spontaneous bacterial peritonitis (CASBP), and to establish and validate an efficacy predictive model for 3^rd GC in the treatment of CASBP. Methods A retrospective analysis was performed for the clinical data of the patients with liver cirrhosis and CASBP who received 3^rd GC monotherapy for initial treatment in The Ninth Hospital of Nanchang, and according to their treatment outcome, they were divided into non-response group and response group. The patients hospitalized from 2013 to 2018 were included in the modeling cohort (55 patients the non-response group and 110 in the response group), and those hospitalized from 2019 to 2020 were included in the validation cohort (17 patients in the non-response group and 43 in the response group). In the modeling cohort, the two groups were compared in terms of the indices including general information, underlying diseases, past history, clinical manifestation, and laboratory test results. Univariate analyses (the t-test was used for comparison of normally distributed continuous data between groups, and the Mann-Whitney U test was used for comparison of non-normally distributed continuous data between groups; the chi-square test or the Fisher's exact test was used for comparison of categorical data between groups) and a binary Logistic regression analysis were used to identify efficacy predictors, and an efficacy predictive model was established based on the logistic regression equation. The receiver operating characteristic (ROC) curve was plotted to perform internal and external validations of the model in the modeling cohort and the validation cohort, respectively. Results The study population had a mean age of 51.6±12.0 years, and male patients accounted for 80.0%; hepatitis B was the main cause of liver cirrhosis (66.7%), and 3^rd GC had an overall response rate of 68.0%. In the modeling cohort, compared with the response group, the non-response group had significantly lower proportion of patients with the first onset of SBP, polymorphonuclear (PMN) count in ascites, and leukocyte count in ascites (all P < 0.05), as well as significantly higher proportion of patients with exposure to broad-spectrum antibiotic and platelet count (both P < 0.05). The Logistic regression analysis showed that the first onset of SBP (odds ratio [OR]=0.158, 95% confidence interval [CI]: 0.064-0.392, P < 0.001), ascites PMN count (OR=0.728, 95%CI: 0.530-0.998, P=0.046), exposure to broad-spectrum antibiotic (OR=9.152, 95%CI: 1.513-55.351, P=0.016), and platelet count (OR=1.012, 95%CI: 1.006-1.019, P < 0.001) were independent predictive factors for non-response to 3^rd GC. The efficacy predictive model had an area under the ROC curve (AUC) of 0.840, and based on the maximum Youden index, predictive score ≥ 0.207 was the optimal cut-off value for predicting non-response, with a corresponding Youden index of 0.536, a sensitivity of 89.1%, a specificity of 63.6%, a positive predictive value of 55.1%, and a negative predictive value of 92.1%. This model had an AUC of 0.837 in the validation cohort. Conclusion The first onset of SBP and higher ascites PMN count are the protective factors against non-response to 3^rd GC for the treatment of CASBP, and exposure to broad-spectrum antibiotic and higher platelet count are the risk factors for such non-response. The model established for predicting the efficacy of 3^rd GC in the treatment of CASBP has good predictive performance and thus holds promise for clinical application.
- Liver Cirrhosis /
- Peritonitis /
- Community-Acquired Infections /
- Cephalosporins /
- Logistic Models

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图 1 建模库疗效预测模型的ROC曲线

Figure 1. Receiver operating characteristics curve of the efficacy predictive model in modeling cohort

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图 2 验证库疗效预测模型的ROC曲线

Figure 2. Receiver operating characteristics curve of the efficacy predictive model in validation cohort

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表 1 建模库与验证库患者的临床特征

Table 1. Clinical characteristics of modeling cohort and validation cohort

指标	建模库(n=165)	验证库(n=60)	统计值	P值
男[例(%)]	133(80.6)	47(78.3)	χ²=0.142	0.706
年龄(岁)	51.2±11.9	52.5±12.4	t=-0.615	0.539
2型糖尿病[例(%)]	21(12.7)	8(13.3)	χ²=0.014	0.905
肝癌[例(%)]	43(26.1)	15(25.0)	χ²=0.026	0.872
既往脾切除术[例(%)]	19(11.5)	5(8.3)	χ²=0.467	0.494
广谱抗生素暴露[例(%)]	16(9.7)	6(10.0)	χ²=0.005	0.946
SBP首次发病[例(%)]	127(77.0)	49(81.7)	χ²=0.570	0.450
诺氟沙星预防SBP[例(%)]	4(2.4)	2(3.3)	χ²=0.009	0.925
Child-Pugh评分	10.3±1.9	10.5±1.9	t=-0.675	0.500
MELD评分	14.1±7.2	13.9±6.7	t=0.202	0.840
肝性脑病[例(%)]	11(6.7)	7(11.7)	χ²=1.495	0.222
消化道出血[例(%)]	1(0.6)	0(0)		＞0.05
中大量腹水[例(%)]	124(75.2)	48(80.0)	χ²=0.574	0.449
腹痛[例(%)]	16(9.7)	5(8.3)	χ²=0.097	0.756
腹部压痛[例(%)]	66(40.0)	25(41.7)	χ²=0.051	0.822
腹部反跳痛[例(%)]	66(40.0)	26(43.3)	χ²=0.202	0.653
体温(℃)	36.9±0.7	36.8±0.6	t=-0.324	0.746
血白细胞(×10⁹/L)	5.9(4.2~8.0)	6.3(4.1~7.8)	Z=-0.102	0.919
血红蛋白(g/L)	104.7±20.7	101.4±20.3	t=1.084	0.280
血小板(×10¹²/L)	89.0(53.5~135.0)	65.0(46.3~146.8)	Z=-1.041	0.298
ALT(U/L)	38.0(23.0~80.5)	35.0(18.4~71.8)	Z=-0.393	0.695
AST(U/L)	66.1(36.0~129.5)	79.0(36.4~132.0)	Z=-0.354	0.723
TBil(μmol/L)	54.2(26.9~72.4)	56.3(29.7~70.6)	Z=-0.058	0.954
Alb(g/L)	28.3±5.4	28.5±5.3	t=-0.269	0.788
血尿素氮(mmol/L)	5.3(3.6~7.4)	5.0(3.9~7.0)	Z=-0.036	0.971
血肌酐(μmol/L)	72.0(58.5~89.0)	64.5(54.0~88.5)	Z=-1.232	0.218
血钠(mmol/L)	135.5±5.4	135.6±5.4	t=-0.223	0.824
血碳酸氢盐(mmol/L)	22.5±3.8	23.0±3.6	t=-0.810	0.419
凝血酶原时间(s)	20.0±6.7	19.9±6.9	t=0.064	0.949
国际标准化比值	1.7±0.6	1.6±0.6	t=0.119	0.905
腹水PMN计数(×10⁹/L)	0.400(0.290~1.000)	0.398(0.293~0.885)	Z=-0.119	0.905
腹水白细胞计数(×10⁹/L)	0.940(0.600~1.940)	0.945(0.603~1.873)	Z=-0.161	0.872

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表 2 建模库单因素分析的阳性结果

Table 2. Positive results of univariate analysis in modeling cohort

指标	无效组(n=55)	有效组(n=110)	统计值	P值
广谱抗生素暴露[例(%)]	11(20.0)	5(4.5)	χ²=10.001	0.002
SBP首次发病[例(%)]	30(54.5)	97(88.2)	χ²=23.403	＜0.001
血小板(×10¹²/L)	125.0(81.0~178.0)	72.0(49.0~119.0)	Z=-4.328	＜0.001
腹水PMN计数(×10⁹/L)	0.340(0.270~0.540)	0.475(0.300~1.583)	Z=-3.465	0.001
腹水白细胞计数(×10⁹/L)	0.750(0.570~1.290)	1.140(0.608~2.428)	Z=-2.235	0.025

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表 3 建模库的二元Logistic回归分析结果

Table 3. Binary Logistic regression analysis in modeling cohort

指标	回归系数	标准误	Wald值	P值	OR(95%CI)
SBP首次发病(是=1，否=0)	-1.844	0.463	15.843	＜0.001	0.158(0.064~0.392)
腹水PMN计数(×10⁹/L)	-0.318	0.162	3.853	0.046	0.728(0.530~0.998)
广谱抗生素暴露(是=1，否=0)	2.214	0.918	5.813	0.016	9.152(1.513~55.351)
血小板(×10¹²/L)	0.012	0.003	14.822	＜0.001	1.012(1.006~1.019)
常数项	-0.543	0.519	1.093	0.029	0.581(NA)

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