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一种利用ICU患者循环炎症指标诊断呼吸机相关性肺炎的列线图

A Nomogram for Diagnosing Ventilator-Associated Pneumonia Using Circulating Inflammation Indicators in ICU Patients.

作者信息

Yang Jiajia, Bao Weiyuan, Wang Hongmei, Zhou Jie, Hu Qiang, Wang Ying, Li Yuancheng

机构信息

Department of Infection Management, The Affiliated Suzhou Hospital of Nanjing Medical University, Suzhou Municipal Hospital, Gusu School, Nanjing Medical University, Suzhou, 215008, People's Republic of China.

Department of Logistics Support, The Affiliated Suzhou Hospital of Nanjing Medical University, Suzhou Municipal Hospital, Gusu School, Nanjing Medical University, Suzhou, 215008, People's Republic of China.

出版信息

J Inflamm Res. 2025 Apr 2;18:4615-4625. doi: 10.2147/JIR.S512083. eCollection 2025.

Abstract

PURPOSE

To construct a risk nomogram model of ventilator-associated pneumonia (VAP) patients with mechanical ventilation in the intensive care unit (ICU) based on peripheral blood inflammatory indicators and to evaluate its diagnostic value.

PATIENTS AND METHODS

A matched 1:2 case: control study was conducted. Fifty-five mechanically ventilated patients with VAP and 113 patients without VAP were admitted to the ICU of Suzhou City Hospital with mechanical ventilation from January 2022 to June 2023 and were retrospectively included as study subjects. Clinical data and laboratory indicators of all patients were collected; the neutrophil to lymphocyte ratio (NLR), platelet to lymphocyte ratio (PLR), lymphocyte to monocyte ratio (LMR), systemic immunoinflammatory index (SII), and systemic inflammatory response index (SIRI) were calculated, and endotracheal aspirate (ETA) culture results of VAP patients were recorded.

RESULTS

There were 61 pathogenic bacteria cultured in the ETA samples of 55 VAP patients, including 56 gram-negative bacilli, 4 gram-positive cocci, and 1 fungus. The proportions of hypoproteinemia, procalcitonin (PCT), NLR, PLR, SII, and SIRI in VAP patients were significantly higher than those in non-VAP patients, with statistical significance (P < 0.05). Univariate and multivariate logistic regression analyses showed that hypoproteinemia, PCT, NLR, PLR, and SIRI were independent influencing factors for VAP in ICU patients (P < 0.05). The ROC curve analysis results showed that the area under the curve of the model for diagnosing VAP in ICU patients was 0.894 [(95% CI = 0.844-0.945), P < 0.001], and the sensitivity and specificity were 87.3% and 74.3%, respectively. The calibration curve shows that the model has good accuracy, and the clinical decision curve indicates that the clinical net benefit rate is higher when the model is used to diagnose VAP.

CONCLUSION

Hypoproteinemia, PCT, NLR, PLR, and SIRI are the independent risk factors for VAP in ICU patients. The nomogram model constructed based on these easily accessible indicators may provide a promising tool for the early diagnosis of VAP in ICU patients, while requires further refinement for routine clinical use.

摘要

目的

基于外周血炎症指标构建重症监护病房(ICU)机械通气患者呼吸机相关性肺炎(VAP)的风险列线图模型,并评估其诊断价值。

患者与方法

进行一项1:2匹配的病例对照研究。2022年1月至2023年6月,苏州市立医院ICU收治的55例机械通气并发VAP患者和113例未发生VAP的机械通气患者被回顾性纳入研究对象。收集所有患者的临床资料和实验室指标;计算中性粒细胞与淋巴细胞比值(NLR)、血小板与淋巴细胞比值(PLR)、淋巴细胞与单核细胞比值(LMR)、全身免疫炎症指数(SII)和全身炎症反应指数(SIRI),并记录VAP患者的气管内吸出物(ETA)培养结果。

结果

55例VAP患者的ETA样本中共培养出61株病原菌,其中革兰阴性杆菌56株、革兰阳性球菌4株、真菌1株。VAP患者低蛋白血症、降钙素原(PCT)、NLR、PLR、SII和SIRI的比例显著高于非VAP患者,差异有统计学意义(P<0.05)。单因素和多因素logistic回归分析显示,低蛋白血症、PCT、NLR、PLR和SIRI是ICU患者发生VAP的独立影响因素(P<0.05)。ROC曲线分析结果显示,ICU患者VAP诊断模型的曲线下面积为0.894[(95%CI=0.844-0.945),P<0.001],灵敏度和特异度分别为87.3%和74.3%。校准曲线显示该模型具有良好的准确性,临床决策曲线表明该模型用于诊断VAP时临床净获益率更高。

结论

低蛋白血症、PCT、NLR、PLR和SIRI是ICU患者发生VAP的独立危险因素。基于这些易于获取的指标构建的列线图模型可能为ICU患者VAP的早期诊断提供一个有前景的工具,但在常规临床应用中还需要进一步完善。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f973/11972568/612b3bbd6c5e/JIR-18-4615-g0001.jpg

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