肝硬化合并脓毒症患者短期住院死亡的Cox比例风险预测模型建立及评价

薛淋淋; 李秉翰; 刘春云; 李卫昆; 常丽仙; 刘立

doi:10.3969/j.issn.1001-5256.2023.05.014

肝硬化合并脓毒症患者短期住院死亡的Cox比例风险预测模型建立及评价

DOI: 10.3969/j.issn.1001-5256.2023.05.014

1.
大理大学公共卫生学院，云南大理 671000
2.
昆明市第三人民医院云南省传染病临床医学中心，昆明 650041

基金项目:

佑安专科联盟科研专项基金 (LM202014)

伦理学声明：本研究于2021年12月6日经昆明市第三人民医院伦理委员会审批，批号：2021120608。

利益冲突声明：本文不存在任何利益冲突。

作者贡献声明：薛淋淋、刘立负责课题设计，撰写及修改论文；刘春云、李卫昆、李秉翰、常丽仙负责收集整理数据，统计分析；刘立负责拟定写作思路, 指导撰写文章并最后定稿。薛淋淋、刘立贡献等同，为共同第一作者。

详细信息

通信作者:
刘立，liuli197210@163.com (ORCID：0000-0001-7712-4931)

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出版历程
- 收稿日期: 2022-12-01
- 录用日期: 2023-02-21
- 出版日期: 2023-05-20

Establishment and evaluation of a multivariate Cox proportional-hazards prediction model for mortality during short-term hospitalization in patients with liver cirrhosis and sepsis

1.
School of Public Health, Dali University, Dali, Yunnan 671000, China
2.
Yunnan Clinical Medical Center for Infectious Diseases, The Third People's Hospital of Kunming, Kunming 650041, China

Research funding:

Special Fund for Scientific Research of You'an Professional Alliance (LM202014)

More Information

Corresponding author: LIU Li, liuli197210@163.com (ORCID: 0000-0001-7712-4931)

摘要

摘要: 目的构建肝硬化合并脓毒症患者短期住院死亡的Cox比例风险预测模型。方法回顾性收集2012年1月—2022年8月昆明市第三人民医院收治的336例肝硬化合并脓毒症患者的临床资料。依据患者短期住院期间是否死亡，分为死亡组(n=40)和生存组(n=296)。收集人口学资料、合并症及临床生化指标，比较各观察指标在两组中的差异。计量资料呈正态分布两组间比较采用成组t检验；计量资料呈偏态分布两组间比较采用Mann-Whitney U检验；计数资料两组间比较采用χ²检验。采用Cox多因素分析筛选变量，据此构建Cox比例风险预测模型并计算风险比(HR)及95%CI。计算C指数来检验其预测精度。绘制列线图可视化展示Cox比例风险预测模型，绘制校准曲线以观察模型预测结果与实际情况的符合程度。结果 336例患者中男261例(77.7%)，女75例(22.3%)，平均年龄(50.0±10.6)岁。其中死亡40例，住院时间8.2~23.0天，平均住院时间(16.8±11.3)天。与生存组相比较，死亡组的年龄(≥60岁)、近2周有创操作史、消化道出血、HE、HRS、改良MEWS评分、PT、APTT、INR、D-D、CD4/CD8、Lac、WBC、NE、TBil、IL-6、PCT、hsCRP、BUN、Cr水平均较高，差异具有统计学意义(P值均＜0.05)；RBC、Hb、TP、白蛋白(Alb)、TC、LDL、HDL水平均较低，差异均有统计学意义(P值均＜0.05)。多因素Cox回归分析，年龄(HR=2.602；95%CI：1.277~5.303，P=0.008)、HE(HR=2.516；95%CI：1.258~5.033，P=0.009)、HRS(HR=2.324；95%CI：1.010~5.349，P=0.047)、hsCRP(HR=1.008；95%CI：1.003~1.013，P=0.004)、改良早期预警评分(MEWS)(HR=1.205；95%CI：1.022~1.422，P=0.027)、PT(HR=1.076，95%CI：1.030~1.124，P=0.027)是肝硬化合并脓毒症患者死亡的独立影响因素。C-指数为0.857(95%CI：0.815~0.920)，提示模型的预测准确性较高。绘制校准图提示模型预测风险与实际发生风险的一致性较好。结论构建的肝硬化合并脓毒症患者短期住院死亡Cox比例风险预测模型可用于预测新诊断肝硬化合并脓毒症患者在短期住院期间发生死亡的风险，从而指导临床医护人员采取针对性的干预措施，最终避免或降低患者发生死亡的可能性。
- 肝硬化 /
- 脓毒症 /
- 危险因素 /
- 比例危险度模型
Abstract: Objective To establish a Cox proportional-hazards prediction model for mortality during short-term hospitalization in patients with liver cirrhosis and sepsis. Methods A retrospective analysis was performed for the clinical data of 336 patients with liver cirrhosis and sepsis who were admitted to The Third People's Hospital of Kunming from January 2012 to August 2022, and according to whether the patient died during short-term hospitalization, they were divided into death group with 40 patients and survival group with 296 patients. Demographic data, comorbidities, and clinical biochemical parameters were collected and compared between the two groups. The independent-samples t test was used for comparison of normally distributed continuous data between two groups, and the Mann-Whitney U test was used for comparison of non-normally distributed continuous data between two groups; the chi-square test was used for comparison of categorical data between two groups. The multivariate Cox analysis was used for screening of variables, then a Cox proportional-hazards prediction model was established, and hazard ratio (HR) and its 95% confidence interval [CI] were calculated; C-index index was used to evaluate the prediction accuracy of the model. The Cox proportional-hazards prediction model was visualized by a nomogram, and calibration curve was plotted to evaluate the consistency between the prediction results of the model and the actual condition. Results Among the 336 patients, there were 261 male patients (77.7%) and 75 female patients (22.3%), with a mean age of 50.0±10.6 years, and 40 patients died, with a mean hospital stay of 16.8±11.3 days (range 8.2-23.0 days). Compared with the survival group, the death group had a significantly higher proportion of patients with an age of ≥60 years, a history of invasive operation within the past two weeks, gastrointestinal bleeding, hepatic encephalopathy (HE) or hepatorenal syndrome (HRS), a significantly higher Modified Early Warning Score (MEWS) score, and significantly higher levels of prothrombin time (PT), activated partial thromboplastin time, international normalized ratio, D-dimer, CD4/CD8 ratio, lactate, white blood cell count, norepinephrine, total bilirubin, interleukin-6, procalcitonin, high-sensitivity C-reactive protein (hsCRP), blood urea nitrogen, and creatinine (all P < 0.05), as well as significantly lower levels of red blood cell count, hemoglobin, albumin, total cholesterol, low-density lipoprotein, and high-density lipoprotein (all P < 0.05). The multivariate Cox regression analysis showed that age (HR=2.602, 95%CI: 1.277-5.303, P=0.008), HE (HR=2.516, 95%CI: 1.258-5.033, P=0.009), HRS (HR=2.324, 95%CI: 1.010-5.349, P=0.047), hsCRP (HR=1.008, 95%CI: 1.003-1.013, P=0.004), MEWS score (HR=1.205, 95%CI: 1.022-1.422, P=0.027), and PT (HR=1.076, 95%CI: 1.030-1.124, P=0.027) were independent influencing factors for death in patients with liver cirrhosis and sepsis. The model showed a C-index of 0.857 (95%CI: 0.815-0.920), suggesting that the model had relatively high prediction accuracy, and the calibration curve showed good consistency between the predicted risk and the actual risk. Conclusion The Cox proportional-hazards prediction model established for death during short-term hospitalization in patients with liver cirrhosis and sepsis can be used to predict the risk of death during short-term hospitalization in patients with liver cirrhosis and sepsis, thereby guiding clinical medical staff to take targeted intervention measures to avoid or reduce the possibility of death in patients.
- Liver Cirrhosis /
- Sepsis /
- Risk Factors /
- Proportional Hazards Models

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图 1 基于Cox比例风险预测模型短期生存概率的列线图

Figure 1. Short-term survival probability based on Cox risk proportional prediction model

下载: 全尺寸图片幻灯片

图 2 基于Cox风险比例预测模型短期生存的校准图

Figure 2. Calibration chart of short-term survival based on Cox risk proportional prediction model

下载: 全尺寸图片幻灯片

表 1 两组基线特征的单因素分析

Table 1. Univariate analysis of baseline characteristics of general data

项目	生存组(n=296)	死亡组(n=40)	统计值	P值
性别[例(%)]			χ²=0.19	0.665
男	231(78.0)	30(75.0)
女	65(22.0)	10(25.0)
年龄[例(%)]			χ²=10.03	0.002
≥60岁	49(16.6)	15(37.5)
＜60岁	247(83.4)	25(62.5)
糖尿病[例(%)]	38(12.8)	9(22.5)	χ²=2.73	0.098
高血压[例(%)]	48(16.2)	5(12.5)	χ²=0.37	0.545
输注人血白蛋白[例(%)]	143(48.3)	19(47.5)	χ²=0.01	0.923
质子泵抑制剂[例(%)]	133(44.9)	15(37.5)	χ²=0.79	0.374
近2周有创操作史[例(%)]	132(44.6)	26(65.0)	χ²=5.10	0.024
腹水[例(%)]	131(44.3)	19(47.5)	χ²=0.15	0.699
消化道出血[例(%)]	64(21.6)	18 (45.0)	χ²=9.21	0.002
HE[例(%)]	40(13.5)	18(45.0)	χ²=24.46	＜0.001
HRS[例(%)]	14(4.7)	9(22.5)	χ²=17.45	＜0.001
改良MEWS评分	1.0(0.0 ~ 2.0)	3.0(0.0~5.0)	Z=-3.36	0.001
PT(s)	17.0(14.6~20.5)	24.3(17.9~30.6)	Z=-4.91	＜0.001
TT(s)	19.6(17.7~21.1)	20.8(18.4~22.9)	Z=-1.79	0.073
APTT(s)	41.2(35.9~46.2)	47.6(39.7~56.3)	Z=-3.78	＜0.001
INR	1.5(1.2~1.7)	2.1(1.5~2.5)	Z=-4.60	＜0.001
D-D(ug/mL)	9.7(5.3~9.7)	17.5(7.7~18.3)	Z=-4.31	＜0.001
CD4/CD8	1.9(1.6~1.9)	2.3(2.3~2.3)	Z=-4.87	＜0.001
PLT(×10⁹/L)	83.0(55.0~132.5)	83.0(59.0~140.3)	Z=-0.47	0.637
Lac (mmol/L)	3.3(2.3~3.3)	9.0(3.8~9.0)	Z=-6.56	＜0.001
WBC(×10⁹/L)	5.3(3.7~7.6)	7.5(4.7~13.5)	Z=-2.91	0.004
NE(×10⁹/L)	3.4(2.2~5.9)	6.3(3.2~11.8)	Z=-3.77	＜0.001
LYM(×10⁹/L)	1.0(0.5~1.5)	0.9(0.5~1.3)	Z=-1.09	0.276
RBC(×10⁹/L)	3.5(2.8~4.5)	3.2(2.5~3.9)	Z=-2.36	0.018
Hb(g/L)	119.5(87.3~145.0)	107.5(73.3~127.8)	Z=-2.50	0.013
TBil(μmol /L)	33.4(17.4~79.5)	74.8(34.0~206.0)	Z=-3.04	0.002
ALT(U/L)	38.0(22.0~69.0)	43.0(24.8~76.0)	Z=-0.58	0.559
AST(U/L)	53.0(34.0~99.7)	77.0(40.3~121.3)	Z=-1.72	0.085
TP(g/L)	62.9(54.8~70.6)	56.2(48.1~65.5)	Z=-3.29	0.001
Alb(g/L)	29.1(23.8~36.0)	23.8(20.2~29.4)	Z=-3.87	＜0.001
PAB(mg/L)	104.8(58.7~136.5)	90.2(60.9~112.4)	Z=-1.59	0.111
IL-6(pg/mL)	52.7(17.6~952.8)	1 951.5(197.8~5 414.3)	Z=-5.86	＜0.001
PCT(ng/mL)	1.1(0.1~4.8)	2.8(0.4~14.0)	Z=-3.07	0.002
hsCRP(mg/L)	14.6(2.5~29.8)	60.7(15.4~106.3)	Z=-4.91	＜0.001
C1q(mg/L)	176.1(138.9~194.8)	170.7(127.0~200.0)	Z=-0.92	0.359
BUN(mmol/L)	5.8(4.1~9.1)	15.1(6.3~24.6)	Z=-5.07	＜0.001
Cr(mmol/L)	73.0(57.0~103.8)	130.5(73.5~235.0)	Z=-4.36	＜0.001
TG(mmol/L)	1.1(0.7~3.1)	2.2(0.7~2.4)	Z=-0.87	0.385
TC(mmol/L)	2.9(2.0~3.3)	2.3(1.4~2.9)	Z=-2.73	0.006
LDL(mmol/L)	1.6(1.0~1.9)	1.3(0.7~1.6)	Z=-2.06	0.039
HDL(mmol/L)	0.7(0.4~1.0)	0.4(0.2~0.4)	Z=-4.62	＜0.001

下载: 导出CSV

表 2 各变量的多因素Cox比例风险回归分析

Table 2. Multivariate Cox proportional risk regression analysis of each variable

变量	β值	SE	Wald	HR	95%CI	P值
年龄(≥60岁)	0.956	0.363	6.931	2.602	1.277~5.303	0.008
HE	0.923	0.354	6.808	2.516	1.258~5.033	0.009
HRS	0.843	0.425	3.030	2.324	1.010~5.349	0.047
hsCRP	0.008	0.003	8.466	1.008	1.003~1.013	0.004
改良MEWS评分	0.187	0.084	4.905	1.205	1.022~1.422	0.027
PT	0.073	0.022	10.662	1.076	1.030~1.124	0.001

下载: 导出CSV

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