用于预测重症监护室败血症患者侵袭性肺曲霉病发生风险的列线图模型的开发和内部验证

Development and Internal Validation of a Nomogram Model to Predict Invasive Pulmonary Aspergillosis Occurrence Risk in ICU Patients with Sepsis.

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摘要(中文译文)

脓毒症的特征是免疫失调和继发感染易感性增加。侵袭性肺曲霉病(IPA)是重症监护病房(ICU)脓毒症患者的重要并发症,且与不良预后相关。识别其预测因素并建立预测模型可能有助于早期风险评估和高危患者的识别。本研究为单中心回顾性队列研究,纳入2020年1月至2024年12月期间574例成人ICU脓毒症患者,按8:2比例随机分为训练集(n=459)和验证集(n=115)。IPA依据国际共识标准诊断。在训练集中,通过最小绝对收缩和选择算子(LASSO)回归筛选候选预测因素,随后进行多因素logistic回归分析。构建基于列线图的预测模型并在验证集中进行内部验证。分别采用受试者工作特征曲线下面积(ROC)、校准曲线和决策曲线分析(DCA)评估模型的区分度、校准度和临床实用性。574例ICU脓毒症患者中,86例(14.98%)发生IPA。LASSO回归后多因素logistic回归显示,吸烟史、糖皮质激素治疗、合并严重发热伴血小板减少综合征(SFTS)或新型冠状病毒感染(COVID-19)、机械通气时间、NRS 2002评分和SOFA评分与IPA独立相关。训练集ROC曲线下面积(AUC)为0.883(95% CI 0.842-0.924),验证集为0.844(95% CI 0.766-0.921)。由上述变量构建的列线图在训练队列和验证队列中均显示出良好的区分度和校准度。DCA表明在临床相关阈值概率范围内具有净临床获益。我们开发并内部验证了用于预测ICU脓毒症患者继发IPA发生风险的列线图。NRS 2002的纳入提示营养风险可能参与IPA发生风险。在更广泛的临床应用之前,尚需进行外部验证。

Abstract

Sepsis is characterized by immune dysregulation and increased susceptibility to secondary infections. Invasive pulmonary aspergillosis (IPA) is an important complication in intensive care unit (ICU) patients with sepsis and is associated with poor outcomes. Identifying its predictors and developing a prediction model may facilitate early risk assessment and identification of high-risk patients. A single-centre retrospective cohort of 574 adult ICU patients with sepsis (January 2020-December 2024) was randomly divided into a training set (n=459) and a validation set (n=115) in an 8:2 ratio. IPA was diagnosed according to international consensus criteria. In the training set, candidate predictors were screened by least absolute shrinkage and selection operator (LASSO) regression, followed by multivariable logistic regression. A nomogram-based prediction model was developed and internally validated in the validation set. Model discrimination, calibration, and clinical utility were assessed using the area under the receiver operating characteristic curve (ROC), calibration curves, and decision curve analysis (DCA), respectively. Among 574 ICU patients with sepsis, 86 (14.98%) developed IPA. LASSO followed by multivariable logistic regression showed that smoking history, corticosteroid therapy, coexisting SFTS or COVID-19, duration of mechanical ventilation, NRS 2002 score, and SOFA score were independently associated with IPA. The area under the ROC curve (AUC) for the training set was 0.883 (95% CI 0.842-0.924), and for the validation set, it was 0.844 (95% CI 0.766-0.921). The nomogram constructed from these variables suggested good discrimination and calibration in both the training and validation cohorts. DCA indicated a net clinical benefit across clinically relevant threshold probabilities. We developed and internally validated a nomogram for predicting secondary IPA occurrence risk in ICU patients with sepsis. The inclusion of NRS 2002 suggests that nutritional risk may contribute to IPA occurrence risk. External validation is warranted before broader clinical application.

如何引用

AMA

Hui Li, Yao Liang, Wenyan Xiao, Yao Zheng, Tianfeng Hua, Min Yang. Development and Internal Validation of a Nomogram Model to Predict Invasive Pulmonary Aspergillosis Occurrence Risk in ICU Patients with Sepsis.. Infection and drug resistance. 2026; doi:10.2147/IDR.S603823.

APA

Hui Li, Yao Liang, Wenyan Xiao, Yao Zheng, Tianfeng Hua, Min Yang (2026). Development and Internal Validation of a Nomogram Model to Predict Invasive Pulmonary Aspergillosis Occurrence Risk in ICU Patients with Sepsis.. Infection and drug resistance. https://doi.org/10.2147/IDR.S603823

GB/T 7714

Hui Li, Yao Liang, Wenyan Xiao, Yao Zheng, Tianfeng Hua, Min Yang. Development and Internal Validation of a Nomogram Model to Predict Invasive Pulmonary Aspergillosis Occurrence Risk in ICU Patients with Sepsis.[J]. Infection and drug resistance, 2026 doi:10.2147/IDR.S603823.

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