Early intervention-oriented: a clinical predictive model for identifying the high risk of intra- abdominal hypertension in patients with traumatic brain injury

Background Intra-abdominal hypertension (IAH) is one of the complications in traumatic brain injury (TBI) patients, which is often correlated with poor clinical outcomes and mortality. Identifying the risk contributors for IAH occurrence in TBI patients is of significant importance. Previous studies have examined epidemiological analyses of IAH in patients requiring intensive care, those with pancreatitis, and those with diabetes. However, no research has yet established a link between TBI and IAH. Method We carried out a retrospective analysis of the basic characteristics, clinical manifestations, management strategies, and blood count test results at different time points for 209 TBI patients who were admitted to the Neurosurgery Department, Tongji Hospital, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology from January 2020 to December 2024. Intra-abdominal pressure (IAP) was indirectly measured via the bladder, and IAH was identified as intra-abdominal pressure repeatedly or persistently exceeding 12 mmHg. Result A total of 209 patients with TBI were included, comprising 38 cases with IAH and 171 cases without IAH. Univariate analysis revealed statistically notable differences between the IAH subset and the non-IAH subset in body mass index (BMI), Glasgow Coma Scale (GCS) score, enteral nutrition (EN) application strategy, administration of sedation, lymphocyte count during hospitalization (Lymphocyte-H), neutrophil to lymphocyte ratio (NLR) during hospitalization (NLR-H), delta neutrophil index-to-lymphocyte ratio (dNLR) during hospitalization (dNLR-H), the ratio of lymphocyte count at admission to that during hospitalization, and the ratio of dNLR at admission to that during hospitalization. Multivariate analysis identified BMI > 23.1 kg/m², dNLR-H (< 0.92), and nasogastric tube (NGT) enteral nutrition as independent risk factors for IAH (P values: 0.012, 0.004, and 0.001, respectively). In the three prediction models, the BMI combined with the dNLR-H prediction model demonstrated the strongest discriminatory ability (maximum area under curve (AUC)), which has a sensitivity of 57.9% and a specificity of 81.3%. Conclusion BMI > 23.1 kg/m², dNLR-H < 0.92, and NGT feeding are contributors to IAH in TBI patients, with the combined use of BMI and dNLR-H being particularly significant for predicting IAH occurrence.