Background and Purpose:Spontaneous intracerebral hemorrhage (sICH) patients were susceptible to pulmonary embolism (PE), which is frequently neglected due to the absence of predictive tools for early detection. This study aimed to investigate the risk factors of PE in sICH patients and develop a efficient model for the prediction of PE in clinical practice. Materials and methods: We conducted a retrospective study involving 1129 sICH patients. The enrolled patients were divided into training set, internal validation set and external set (n=525: 357: 247). The univariate and multivariate stepwise logistic regression analyses were employed to screen the independent risk factors of the PE in sICH patients. A nomogram model (Model P-P) was constructed based on R language and subsequently validated. For further evaluation, the Model P-P was compared with another similar model (Model A). Results: The analyses revealed that deep vein thrombosis, age, Glasgow coma scale score, fibrinogen degradation product, D-dimer, hemoglobin, hemorrhage volume, plasma osmolality, and surgical method were significant risk factors for PE in sICH patients (p<0.05). The Model P-P was established based on these factors, and its sensitivity, specificity were 84.2%, 94% and 0.910, respectively. Furthermore, the AUC of Model P-P (0.894) was significantly higher than that of Model A (0.785) (p<0.05). Conclusion: The Model P-P developed in this study exhibited reliable predictive efficiency, making it an applicable tool for the early evaluation and prediction of PE after sICH surgery. This model is potential to assist personalized treatment decisions in clinical practice, especially in the neurosurgical intensive care unit.

The authors have declared no competing interest.

The authors declare financial support was received for the research, authorship, and publication of this article. This work was supported by the Chongqing Medical Scientific Research Project (joint project of Chongqing Health Commission and Science and Technology Bureau) (2022MSXM041 and 2024MSXM077), the CQMU Program for Youth Innovation in Future Medicine (Scientific Research and Innovation Team, No. W0169), the National Natural Science Foundation for Youth of China (No. 81701226), the 2023 Chongqing Technology Innovation and Application Development Special Science and Technology Assistance to Tibet and Xinjiang Project (CSTB2023TIAD-KPX0001), and 2023 Natural Science Foundation of Xizang Autonomous Region [XZ2023ZR-ZY67 (Z)], and Chongqing Natural Science Foundation General Project (No. CSTB2022NSCQ-MSX0152).

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The study received approval from the Ethics Committee of the First Affiliated Hospital of Chongqing Medical University (K2023-581).

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