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

Hui Li,1,2 Yao Liang,1,2 Wenyan Xiao,1,2 Yao Zheng,1,2 Tianfeng Hua,1,2 Min Yang1,2 1The Second Department of Critical Care Medicine, The Second Affiliated Hospital of Anhui Medical University, Hefei, Anhui, People’s Republic of China; 2The Laboratory of Cardiopulmonary Resuscitation and Critical Care Medicine, the Second Affiliated Hospital of Anhui Medical University, Hefei, Anhui, People’s Republic of ChinaCorrespondence: Min Yang, Email yangmin@ahmu.edu.cnBackground: 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.Methods: 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.Results: 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.Conclusion: 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.