Construction of an individualized early-warning model for predicting multidrug-resistant bacterial infection in ICU mechanically ventilated severe pneumonia patients
Construction of an individualized early-warning model for predicting multidrug-resistant bacterial infection in ICU mechanically ventilated severe pneumonia patients
闫静静 1肖转南 1王丽丽1
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作者信息
1. 230000,安徽医科大学合肥第三临床学院ICU(合肥市第三人民医院)
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摘要
目的 通过探讨重症监护室(intensive care unit,ICU)机械通气重症肺炎患者多重耐药菌(multi-drug resistant organisms,MDROs)感染的危险因素,构建ICU机械通气重症肺炎患者MDROs感染的列线图模型.方法 选取2019年5月至2022年11月收入合肥市第三人民医院ICU的240例机械通气重症肺炎患者作为研究对象,根据MDROs感染情况分为MDROs感染组和无MDROs感染组.采用Lasso分析筛选ICU机械通气重症肺炎患者MDROs感染的预测因素,采用Logistic回归筛选ICU机械通气重症肺炎患者MDROs感染的危险因素,采用R软件构建ICU机械通气重症肺炎患者MDROs感染的列线图模型,并对ICU机械通气重症肺炎患者MDROs感染的列线图模型进行内部验证.结果 240例ICU机械通气重症肺炎患者中有94例发生MDROs感染,MDROs感染的发生率为39.17％.Logistic回归分析结果显示,糖尿病、低蛋白血症、意识障碍、院内获得性肺炎等是ICU机械通气重症肺炎患者MDROs感染的危险因素(P均<0.05).ICU机械通气重症肺炎患者MDROs感染的列线图模型校正曲线的预测值与实际值的一致性良好;模型的受试者工作曲线下面积为0.721(95％置信区间:0.653～0.790);决策曲线显示阈值概率是19％～100％时,列线图预测ICU机械通气重症肺炎患者MDROs感染的净获益值较高.结论 本研究构建的ICU机械通气重症肺炎患者MDROs感染的列线图模型的准确性及临床应用价值较高.
Abstract
Objective To construct a nomogram model of multi-drug resistant organisms (MDROs) infection in the intensive care unit (ICU) mechanically ventilated patients with severe pneumonia,by exploring the risk factors for infection with MDROs in mechanically ventilated patients with severe pneumonia in ICU. Methods A total of 240 mechanically ventilated patients with severe pneumonia admitted to Hefei Third People' s Hospital ICU from May 2019 to November 2022 were selected as the study subjects,and were divided into MDROs infection group and no MDROs infection group according to the MDROs infection status. Lasso analysis was used to screen the predictive factors of MDROs infection in ICU mechanically ventilated patients with severe pneumonia,Logistic regression was used to screen the risk factors of MDROs infection in ICU mechanically ventilated patients with severe pneumonia,and R software was used to build a nomogram model of MDROs infection in ICU mechanically ventilated patients with severe pneumonia. The nomogram model of MDROs infection in ICU mechanically ventilated patients with severe pneumonia was internally verified. Results Among 240 ICU patients with mechanical ventilation severe pneumonia,94 cases developed MDROs infection,and the incidence of MDROs infection was 39.17％ (94/240). Logistic regression analysis showed that diabetes,hypoproteinemia,disturbance of consciousness and nosocomial pneumonia were risk factors for MDROs infection in ICU patients with severe pneumonia due to mechanical ventilation (P<0.05 ). The predicted value of the correction curve of the nomogram model for MDROs infection in ICU patients with mechanically ventilated severe pneumonia was in good agreement with the actual value. The area under ROC curve of the model was 0.721 (95％CI:0.653～0.790 ). When the decision curve showed a threshold probability of 19％-100％,the omogram predicted a higher net benefit of MDROs infection in ICU mechanically ventilated patients with severe pneumonia. Conclusion The nomogram model of MDROs infection in ICU mechanically ventilated patients with severe pneumonia established in this study has high accuracy and clinical application value.
关键词
重症监护室/机械通气/重症肺炎/多重耐药菌/感染/列线图
Key words
intensive care unit/mechanical ventilation/severe pneumonia/multidrug resistant bacteria/to be infected/nomogram
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