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一种用于预测碳青霉烯类耐药呼吸机相关性肺炎治疗失败风险因素的新型多变量逻辑模型。

A novel multivariate logistic model for predicting risk factors of failed treatment with carbapenem-resistant ventilator-associated pneumonia.

机构信息

Department of Pharmacy, The First Hospital of Shanxi Medical University, Taiyuan, China.

Shanxi Province People's Hospital, Taiyuan, China.

出版信息

Front Public Health. 2024 May 9;12:1385118. doi: 10.3389/fpubh.2024.1385118. eCollection 2024.

Abstract

BACKGROUND

This study aimed to explore the risk factors for failed treatment of carbapenem-resistant ventilator-associated pneumonia (CRAB-VAP) with tigecycline and to establish a predictive model to predict the incidence of failed treatment and the prognosis of CRAB-VAP.

METHODS

A total of 189 CRAB-VAP patients were included in the safety analysis set from two Grade 3 A national-level hospitals between 1 January 2022 and 31 December 2022. The risk factors for failed treatment with CRAB-VAP were identified using univariate analysis, multivariate logistic analysis, and an independent nomogram to show the results.

RESULTS

Of the 189 patients, 106 (56.1%) patients were in the successful treatment group, and 83 (43.9%) patients were in the failed treatment group. The multivariate logistic model analysis showed that age (OR = 1.04, 95% CI: 1.02, 1.07,  = 0.001), yes. of hypoproteinemia (OR = 2.43, 95% CI: 1.20, 4.90,  = 0.013), the daily dose of 200 mg (OR = 2.31, 95% CI: 1.07, 5.00,  = 0.034), yes. of medication within 14 days prior to surgical intervention (OR = 2.98, 95% CI: 1.19, 7.44,  = 0.019), and no. of microbial clearance (OR = 0.31, 95% CI: 0.14, 0.70,  = 0.005) were risk factors for the failure of tigecycline treatment. Receiver operating characteristic (ROC) analysis showed that the AUC area of the prediction model was 0.745 (0.675-0.815), and the decision curve analysis (DCA) showed that the model was effective in clinical practice.

CONCLUSION

Age, hypoproteinemia, daily dose, medication within 14 days prior to surgical intervention, and microbial clearance are all significant risk factors for failed treatment with CRAB-VAP, with the nomogram model indicating that high age was the most important factor. Because the failure rate of CRAB-VAP treatment with tigecycline was high, this prediction model can help doctors correct or avoid risk factors during clinical treatment.

摘要

背景

本研究旨在探讨替加环素治疗碳青霉烯类耐药呼吸机相关性肺炎(CRAB-VAP)失败的危险因素,并建立预测模型来预测 CRAB-VAP 治疗失败的发生率和预后。

方法

2022 年 1 月 1 日至 12 月 31 日,从两家三级甲等国家级医院的安全分析集中共纳入 189 例 CRAB-VAP 患者。采用单因素分析、多因素 logistic 分析和独立列线图来确定 CRAB-VAP 治疗失败的危险因素,并展示结果。

结果

在 189 例患者中,106 例(56.1%)患者为治疗成功组,83 例(43.9%)患者为治疗失败组。多因素 logistic 模型分析表明,年龄(OR=1.04,95%CI:1.02,1.07, =0.001)、低蛋白血症(OR=2.43,95%CI:1.20,4.90, =0.013)、每日 200mg 剂量(OR=2.31,95%CI:1.07,5.00, =0.034)、手术干预前 14 天内用药(OR=2.98,95%CI:1.19,7.44, =0.019)和微生物清除率(OR=0.31,95%CI:0.14,0.70, =0.005)是替加环素治疗失败的危险因素。受试者工作特征(ROC)分析显示,预测模型的 AUC 面积为 0.745(0.675-0.815),决策曲线分析(DCA)显示模型在临床实践中有效。

结论

年龄、低蛋白血症、每日剂量、手术干预前 14 天内用药和微生物清除率都是 CRAB-VAP 治疗失败的显著危险因素,列线图模型表明高龄是最重要的因素。由于替加环素治疗 CRAB-VAP 的失败率较高,该预测模型可以帮助医生在临床治疗中纠正或避免危险因素。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3674/11111873/2a0ed12b3847/fpubh-12-1385118-g001.jpg

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