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用于预测急性胆管炎患者脓毒症风险的列线图。

A nomogram for predicting the risk of sepsis in patients with acute cholangitis.

作者信息

Liu Qingqing, Zhou Quan, Song Meina, Zhao Fanfan, Yang Jin, Feng Xiaojie, Wang Xue, Li Yuanjie, Lyu Jun

机构信息

Clinical Research Center, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, Shaanxi, China.

School of Public Health, Xi'an Jiaotong University Health Science Center, Xi'an, Shaanxi, China.

出版信息

J Int Med Res. 2020 Jan;48(1):300060519866100. doi: 10.1177/0300060519866100. Epub 2019 Aug 20.

DOI:10.1177/0300060519866100
PMID:31429338
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7140205/
Abstract

OBJECTIVE

Sepsis is a serious complication of acute cholangitis. We aimed to establish a nomogram for predicting the probability of sepsis in patients with acute cholangitis.

METHODS

Subjects were patients with acute cholangitis in the Medical Information Mart for Intensive Care database. Extraneous variables were excluded based on stepwise regression. The nomogram was established using logistic regression.

RESULTS

The predictive model comprised five variables: age (odds ratio [OR]: 1.03, 95% confidence interval [CI]: 1.01–1.04), ventilator-support time (OR: 1.004, 95% CI: 1.001–1.008), diabetes (OR: 10.74, 95% CI: 2.80–70.57), coagulopathy (OR: 2.92, 95% CI: 1.83–4.73) and systolic blood pressure (OR: 0.62, 95% CI: 0.41–0.93). The areas under the receiver operating characteristic curve of the nomogram for the training and validation sets were 0.700 and 0.647, respectively. The Hosmer–Lemeshow goodness-of-fit test revealed high concordance between the predicted and observed probabilities for both the training and validation sets. The calibration plot also demonstrated good agreement between the predicted and observed outcomes for both the training and validation sets.

CONCLUSIONS

We developed and validated a risk-prediction model for sepsis in patients with acute cholangitis. Our results will be helpful for preventing sepsis in patients with acute cholangitis.

摘要

目的

脓毒症是急性胆管炎的一种严重并发症。我们旨在建立一种列线图，用于预测急性胆管炎患者发生脓毒症的概率。

方法

研究对象为重症监护医学信息数据库中的急性胆管炎患者。基于逐步回归排除无关变量。使用逻辑回归建立列线图。

结果

预测模型包含五个变量：年龄（比值比[OR]：1.03，95%置信区间[CI]：1.01 - 1.04）、机械通气支持时间（OR：1.004，95%CI：1.001 - 1.008）、糖尿病（OR：10.74，95%CI：2.80 - 70.57）、凝血功能障碍（OR：2.92，95%CI：1.83 - 4.73）和收缩压（OR：0.62，95%CI：0.41 - 0.93）。训练集和验证集列线图的受试者工作特征曲线下面积分别为0.700和0.647。Hosmer - Lemeshow拟合优度检验显示训练集和验证集的预测概率与观察概率之间具有高度一致性。校准图也表明训练集和验证集的预测结果与观察结果之间具有良好的一致性。

结论

我们开发并验证了一种急性胆管炎患者脓毒症的风险预测模型。我们的结果将有助于预防急性胆管炎患者发生脓毒症。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7fd0/7140205/23471a9371f5/10.1177_0300060519866100-fig5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7fd0/7140205/b480cf6721d7/10.1177_0300060519866100-fig1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7fd0/7140205/3c02d643c3b6/10.1177_0300060519866100-fig2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7fd0/7140205/8aa7c5db7f9a/10.1177_0300060519866100-fig3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7fd0/7140205/1d07fc7e6259/10.1177_0300060519866100-fig4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7fd0/7140205/23471a9371f5/10.1177_0300060519866100-fig5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7fd0/7140205/b480cf6721d7/10.1177_0300060519866100-fig1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7fd0/7140205/3c02d643c3b6/10.1177_0300060519866100-fig2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7fd0/7140205/8aa7c5db7f9a/10.1177_0300060519866100-fig3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7fd0/7140205/1d07fc7e6259/10.1177_0300060519866100-fig4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7fd0/7140205/23471a9371f5/10.1177_0300060519866100-fig5.jpg

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Sepsis: Current Definition, Pathophysiology, Diagnosis, and Management.脓毒症：当前的定义、病理生理学、诊断及管理
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Implications of Type 2 Diabetes Mellitus in Patients with Acute Cholangitis: A Systematic Review of Current Literature.2型糖尿病对急性胆管炎患者的影响：当前文献的系统评价
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