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

Early intervention-oriented: a clinical predictive model for identifying the high risk of intra- abdominal hypertension in patients with traumatic brain injury | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Early intervention-oriented: a clinical predictive model for identifying the high risk of intra- abdominal hypertension in patients with traumatic brain injury Fuliang Jiang, Yue Zhao, Yuxuan Xiong, Qing Zhang, Fuchi Zhang, and 5 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8765814/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract 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. Traumatic brain injury Intra-abdominal hypertension Predictive model Figures Figure 1 Figure 2 Figure 3 Introduction Traumatic brain injury (TBI) ranks among the primary causes of global disability and mortality 1 . As a systemic disease, it can cause dysfunction in organs throughout the body, leading to a wide range of systemic complications 2 . This results in secondary brain injury in TBI patients, thereby affecting treatment outcomes. Intra-abdominal pressure (IAP) refers to the steady pressure within the abdominal cavity (World Society of the Abdominal Compartment Syndrome, 2006) 3 . It results in pressure on the central nervous system through two pathways. One pathway involves the valveless spinal venous plexus connecting to intracranial veins, forming an anatomical conduit from the pelvis directly to the eyes and brain. The other pathway involves a mechanical transmission process: increased intra-abdominal pressure first transmits upward, causing diaphragmatic displacement and elevated intrathoracic pressure. The subsequent rise in central venous pressure impedes blood return to the central nervous system via the jugular veins, ultimately resulting in reduced intracranial venous return. It is increasingly recognized as a vital physiological indicator for monitoring the onset of IAH in t he gravely ill or as the sixth vital sign following blood pressure, heart rate, respiratory rate, body temperature, and blood oxygen saturation 4 , 5 . IAH is one of the complications occurring during the treatment of patients with TBI. It is conceptualized as persistent IAP elevation to 12 mmHg or higher, accompanied by a heightened risk of multi-organ failure (involving abdominal and distant systems) and mortality 6 . It is estimated that 50.0% to 80.0% of severely ill adult patients are in danger of progressing to intra-abdominal hypertension (IAH), with 2.7% to 51.7% of these cases progressing to abdominal compartment syndrome (ACS) 7 , 8 . Increased IAP triggers a series of pathophysiological processes. First, IAH directly impairs arterial and venous blood flow to abdominal organs, disrupts intestinal perfusion, and obstructs lymphatic drainage. This progressively leads to intestinal obstruction, edema, and ischemia, resulting in disruption of the intestinal mucosal barrier function, translocation of gut microbiota, and secondary infections 9 . Second, IAH directly leads to impaired cerebral venous outflow, elevated jugular venous pressure, disruption of the blood-brain barrier, reduced blood flow in the lumbar venous plexus, and increased cerebral blood flow. This subsequently causes elevated intracranial pressure and decreased cerebral perfusion pressure 10 . Third, IAH leads to diaphragmatic elevation and increased intrathoracic pressure, accompanied by cardiac compression and inferior vena cava compression. This results in increased right ventricular afterload, decreased cardiac output, and reduced ventricular compliance/contractility. Consequently, cerebral blood flow and perfusion are impaired, leading to secondary cerebral tissue hypoxia 11 . Fourth, IAH leads to lung compression, alveolar atelectasis, reduced pulmonary capillary blood flow, and impaired lymphatic drainage. This subsequently causes elevated airway peak pressure, increased plateau pressure, decreased lung compliance, reduced tidal volume, decreased functional residual capacity, ventilation/perfusion incompatibility, and hypercapnia. These effects induce cerebral hypoxia and cerebral edema, exacerbating increased intracranial pressure 12 , 13 . These pathophysiological processes undoubtedly contribute to the progression of TBI patients' conditions, with their impact on intracranial pressure being of particular concern to neurosurgeons. Among severely ill patients in the intensive care unit (ICU), published studies have identified general risk contributors for IAH, including obesity, sepsis/infection, the patient's initial diagnosis, abdominal surgery, acidosis, hypotension, mechanical ventilation/acute respiratory distress syndrome (ARDS), and crystalloid and non-crystalloid fluid resuscitation 14 . For non-abdominal trauma patients, literature reports indicate that the frequency of secondary ACS following trauma is 0.09% of the total trauma cohort, accounting for 0.7% of all trauma patients 15 . Crystalloid resuscitation is generally recognized as a contributor for ACS in trauma patients 16 – 18 , but no in-depth research has been conducted on the onset rate of IAH and its associated risk factors in trauma patients. There is currently no published research on the occurrence of IAH in TBI patients or its associated risk factors. Additionally, nutritional therapy constitutes a vital component of comprehensive treatment for TBI patients. It plays a crucial physiological role in improving malnutrition, maintaining internal environmental stability, protecting gastrointestinal function, reducing gut microbiota dysbiosis, and mitigating secondary brain injury. Literature reports that improper enteral nutrition therapy is a high-risk contributor for the occurrence of IAH in patients in critical condition, including feeding routes and enteral nutrition formulas 19 , 20 . However, for patients with TBI, the relationship between enteral nutrition therapy and IAH remains unclear and warrants further investigation. Therefore, this study focuses on the onset rate and contributors of IAH in TBI patients, aiming to explore the development of an early prediction model. This model seeks to advance the timing of interventional measures for IAH in TBI patients, thereby significantly improving their prognosis. This retrospective analysis examined the occurrence of IAH in 209 patients with TBI. According to statistically significant differential indicators, a predictive model for IAH occurrence was proposed to aid medical practice. Methods and Materials Patient Selection and Ethical Approval This retrospective study was conducted at Tongji Hospital, affiliated with Tongji Medical College of Huazhong University of Science and Technology. Inclusion criteria are as follows: 1) Age > 18. 2) The patient has a clear history of trauma. 3)Admitted within 24 hours of traumatic brain injury. 4) All surgical procedures performed on patients were conducted at this hospital. Exclusion criteria are as follows: 1) Survival time less than 3 days following traumatic brain injury. 2) Pregnant or breastfeeding women (Fig. 1 ). From January 2020 to December 2024, our hospital admitted a total of 209 patients meeting the aforementioned criteria. We collected and analyzed their basic information, clinical manifestations, management strategies, and laboratory results. All procedures involving human participants in this study strictly adhered to the ethical guidelines of the Declaration of Helsinki and the International Committee of Medical Journal Editors (ICMJE) and were approved by the Medical Ethics Committee of Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology. Informed consent was waived. Data Collection Demographic data (gender, age), medical history (injury mechanism, symptoms, and signs), body mass index (BMI), and Glasgow Coma Scale (GCS) score (the specific grading criteria shall be based on the scale presented by Neal Cook 21 ) were retrieved from the medical record system. Collect hematological test data, including white blood cell (WBC) count, neutrophil count, and lymphocyte count at admission; admission neutrophil to lymphocyte ratio (NLR) and delta neutrophil index-to-lymphocyte ratio (dNLR) indices; white blood cell count, neutrophil count, and lymphocyte count during hospitalization (three days after admission); NLR and dNLR indices during hospitalization; and the ratio of white blood cell count, neutrophil count, lymphocyte count, NLR, and dNLR at admission to WBC count, neutrophil count, lymphocyte count, NLR, and dNLR during hospitalization. Collect information related to intensive care, including enteral nutrition strategy, administration of sedation, use of mechanical ventilation, and application of temperature control treatment. IAP was indirectly measured by the detection of intravesical pressure six times a day. IAH was confirmed as IAP ≥ 12 mmHg according to the diagnostic criteria established by the World Society of the Abdominal Compartment Syndrome (WSACS; http://www.wsacs.org ). The formulas for calculating the NLR and dNLR indices are as follows: NLR = Neutrophil count / Lymphocyte count, dNLR = Neutrophil Count / (Total White Blood Cell Count - Neutrophil Count). Nutrition therapy was applied in all TBI patients according to the guideline of the European Society for Enteral and Parenteral Nutrition (ESPEN; https://www.espen.org ). Enteral nutrition (EN) treatment was applied by nasogastric tube (NGT) feeding or nasointestinal tube (NIT) feeding. Peripheral nutrition (PN) was added when enteral nutrition fails to meet 60% of the target energy and protein requirements. Statistical Analysis Descriptions of categorical variables are presented as percentages (%). The normality of continuous variables was examined with the Kolmogorov-Smirnov (K-S) test. For variables meeting normality criteria, mean and standard deviation (SD) were reported; for those not meeting normality criteria, median and interquartile range (IQR) were used. Employ the t-test to compare the difference between two samples. To compare categorical variables across sets, the chi-square test was employed. For p-values less than 5, Fisher's exact test was applied. Normally distributed variables were analyzed with Student's t-test, and non-normally distributed variables with the Mann-Whitney U test. Variables associated with IAH in TBI patients and showing significant differences between groups were covered in a multivariate logistic regression model. Given the limited number of available events, variables were carefully selected to ensure model parsimony. The final outcome for each variable was expressed as the odds ratio (OR) and 95% confidence interval (95% CI). Select the ROC (Receiver Operating Characteristic) curve to assess the sensitivity and specificity of the predictive model for IAH incidence in TBI patients. Select continuous variables associated with IAH (BMI, delta neutrophil index-to-lymphocyte ratio (dNLR-H)) that demonstrate statistically significant differences between the poor-outcome subgroup and the favorable-outcome subgroup, and incorporate these variables into the predictive model. In addition to individual tests, these variables were also combined. All statistical analyses were performed using SPSS 23.0 software (Chicago, IL, USA). For all tests, a two-tailed p-value < 0.05 was considered statistically significant. Result Clinical Features Overall, 209 patients with TBI were included in the survey. Males accounted for 40.7% and females for 59.3%. The median age was 56 years, with a median admission GCS score of 8. Among these patients, 40.2% also had concomitant chest injuries. In the medical history, the prevalence rates of hypertension, diabetes, and cardiac dysfunction were 27.8%, 25.4%, and 11.0%, respectively. Monitoring status: 31.6% of patients received high-dose sedation; 47.8% required mechanical ventilation; 29.7% did not develop fever. Different enteral nutrition strategies were implemented based on individual patient circumstances, with 63.2% receiving nutrition via nasogastric tube and 36.8% via nasointestinal tube. Complete blood counts were recorded upon admission and during hospitalization (three days after admission). At admission, the median total WBC count was 15.3 × 10⁹/L, the median neutrophil count was 13.3 × 10⁹/L, and the median lymphocyte count was 0.8 × 10⁹/L. Calculations yielded median NLR and dNLR values of 18.1 and 2.0, respectively. During hospitalization, the median WBC count was 14.3 × 10⁹/L, the median neutrophil count was 11.5 × 10⁹/L, and the median lymphocyte count was 1.1 × 10⁹/L. Calculations yielded median NLR and dNLR values of 10.1 and 1.8, respectively. Data on IAP obtained via transvesical indirect measurement: 38 patients with IAH and 171 patients without IAH (Table 1 ). Table 1 Clinical characteristics of 209 TBI patients Variants Content (N = 209) Age (yrs) 56.0 (50.0, 63.0) Gender Male 85 (40.7%) Female 124 (59.3%) BMI (kg/m 2 ) 23.1 (21.5, 24.8) Comorbidity Hypertension 79 (27.8%) Diabetes Mellitus 53 (25.4%) Heart dysfunction 23 (11.0%) Complications Thoracic injury 84 (40.2%) GCS 8.0 (5.0, 10.0) EN application strategy NIT 132 (63.2%) NGT 77 (36.8%) Supported PN 123 (58.9%) Sedation 66 (31.6%) Mechanical ventilation 100 (47.8%) Temperature control 62 (29.7%) Laboratory tests at admission WBC-A (x10 9 /L) 15.3 (12.7, 17.9) Neutrophil-A (x10 9 /L) 13.3 (11.2, 15.9) Lymphocyte-A (x10 9 /L) 0.75 (0.56, 1.01) NLR-A 18.1 (11.6, 26.8) dNLR-A 0.9 (0.92, 0.96) Laboratory tests during hospitalization WBC-H (x10 9 /L) 14.3 (10.9, 17.5) Neutrophil-H (x10 9 /L) 11.5 (8.6, 15.3) Lymphocyte-H (x10 9 /L) 1.08 (0.83, 1.40) NLR-H 10.1 (7.0, 15.5) dNLR-H 0.92 (0.89, 0.94) Trends in laboratory test results change WBC-R 0.94 (0.72, 1.20) Neutrophil-R 0.89 (0.66, 1.15) Lymphocyte-R 1.49 (0.91, 2.20) NLR-R 0.57 (0.36, 1.03) dNLR-R 0.97 (0.94, 1.01) IAH 38(18.2%) BMI: body mass index, GCS: glasgow coma scale, EN: enteral nutrition, PN: parenteral nutrition, NGT: nasogastric tube, NIT: nasointestinal tube, WBC-A: white blood cell at adimission, NLR-A: neutrophil to lymphocyte ratio at admission, dNLR-A: delta neutrophil index-to-lymphocyte ratio at admission, WBC-H: white blood cell during hospitalization, IAH:intra-abdominal hypertension. Two sets of differences Patients were categorized into an IAH subset (n = 38) and a non-IAH subset (n = 171) on the basis of intra-abdominal pressure measurements. Comparative analysis of characteristic data revealed a marked difference in admission BMI between groups (p = 0.001), with the non-IAH group exhibiting markedly superior admission GCS scores in comparison to the IAH subgroup (p = 0.001). There were also noticeable differences in enteral nutrition strategies (p < 0.001), while the use of supportive parenteral nutrition was similar (p = 0.389). Compared with the non-IAH subgroup, a higher proportion of patients in the IAH subgroup received high-dose sedation (p < 0.007). The two sets did not differ significantly in the use of mechanical ventilation for respiratory support and temperature control. The two subgroups were comparable in terms of WBC count, neutrophil count, lymphocyte count, NLR index, or dNLR index at admission. During hospitalization, there were no differences in white blood cell counts, neutrophil counts, or NLR index between the two sets. However, notable differences were observed in lymphocyte counts (p = 0.017), and dNLR (p < 0.001) indices between the two subgroups during hospitalization. The analysis revealed no differences between the two subsets in the ratio of admission WBC count, neutrophil count, and NLR to the respective values during hospitalization. However, the ratio of lymphocyte count and dNLR index at admission to those during hospitalization showed significant differences between the two subsets (Fig. 2 ). Risk Factors for Outcomes To adjust for potential confounders, variables showing significant differences were entered into a multivariate logistic regression model. Results indicated that BMI > 23.1 kg/m², NGT, and dNLR-H 23.1 kg/m 2 ) 1.110 6.262 3.033 1.272–7.232 0.012* GCS (<8) 0.478 0.952 1.613 0.617–4.213 0.329 NGT 1.626 11.918 5.083 2.019–12.793 0.001** Sedation 0.395 0.765 1.484 0.613–3.594 0.382 Lymphocyte-H (<1.08 x10 9 /L) 0.843 3.235 2.324 0.927–5.825 0.072 dNLR-H (< 0.92) 1.588 8.102 4.895 1.640-14.614 0.004** Lymphocyte-R (< 1.49) 0.426 0.904 1.530 0.636–3.680 0.342 dNLR-R (< 0.94) 0.087 0.027 1.090 0.386–3.077 0.87 BMI: body mass index, GCS: glasgow coma scale, NGT: nasogastric tube, dNLR-H: delta neutrophil index-to-lymphocyte ratio during hospitalization, dNLR-R: the ratio of dNLR at admission to that during hospitalization. * p < 0.05 and **p < 0.01 Outcome Prediction Mode l A predictive model for IAH occurrence in TBI patients was established using the receiver operating characteristic (ROC) curve (Fig. 3 ). BMI demonstrated a sensitivity of 60.5% and specificity of 73.7%; dNLR-H showed a sensitivity of 63.2% and specificity of 69.6%. Further analysis combining BMI and dNLR-H yielded an area under curve (AUC) of 0.732, which has a predictive sensitivity of 57.9% and specificity of 81.3% (Table 4 ). Table 4 Predictive value of BMI, dNLR-H and their combinations Youden AUC 95% CI Sensitivity Specificity BMI 0.342 0.673 0.570–0.776 60.5% 73.7% dNLR-H 0.328 0.700 0.606–0.793 63.2% 69.6% BMI+dNLR 0.392 0.732 0.636–0.828 57.9% 81.3% BMI: body mass index, dNLR-H: delta neutrophil index-to-lymphocyte ratio during hospitalization, AUC: area under the curve Discussion Among U.S. residents aged below 45, TBI accounts for a leading share of disability and mortality 22 . IAH as one of the adverse prognostic risk factors for TBI patients, has a high incidence rate and warrants our full attention. Approximately one-quarter to 33.3% of patients exhibit IAH upon admission to the ICU, while approximately half contract IAH within the first week of ICU admission 23 . Among patients undergoing emergency exploratory laparotomy, the incidence of IAH was 25% in the pediatric group and 17.4% in the adult group 24 . In a specific cohort of TBI patients, our study revealed that 38 out of 209 enrolled TBI patients developed IAH. We hypothesize that the cause lies in the elevated intracranial pressure following TBI triggering an extreme stress response in the body, which prioritizes the “protect the brain” command, leading to a redistribution of systemic blood flow. This leads to reduced blood flow to the abdominal viscera. Under conditions of ischemia and hypoxia, the gastrointestinal mucosa becomes damaged, triggering bacterial translocation and endotoxin release, systemic inflammatory response, and multiple organ dysfunction, ultimately resulting in IAH. Additionally, some TBI patients exhibit higher fluid resuscitation rates and transfusion frequencies compared to general patients, which also increases the likelihood of IAH occurrence 25 。The occurrence of IAH further exacerbates cerebral edema and elevates intracranial pressure 4 , leading to secondary brain injury and creating a vicious cycle. Therefore, preventing the occurrence of IAH and breaking the vicious cycle is an indispensable step in ensuring a favorable prognosis for TBI patients. IAP can be measured directly by placing a probe within the abdominal cavity or indirectly by measuring pressures in other abdominal organs to reflect IAP levels, such as bladder pressure, gastric pressure, colonic pressure, and uterine pressure 26 . Several new non-invasive measurement methods have recently been proposed, including ultrasound-based IAP monitoring technology, bioelectrical impedance analysis, microwave reflection methods, digital image correlation, and the application of wireless motion capsules 27 . Our study employed the transvesical indirect measurement method, which is currently recognized as the gold standard for IAP measurement, demonstrating good correlation with IAP while avoiding the infection risks associated with direct measurement techniques. Through statistical analysis of the relevant data obtained, we identified several predictors of IAH, as shown in Table 2 . Previous research has suggested that BMI is an independent predictor of IAH 28 , 29 , and has indicated that obesity (defined as a BMI > 30 kg/m²) is a high-risk factor for the progression of IAH in mixed ICU patients 30 . Numerous studies have also documented that obesity is associated with increased ICU mortality, prolonged duration of mechanical ventilation, and extended hospital stays among patients with traumatic brain injury 5 , 31 , 32 . However, some studies suggest there is no conclusive evidence linking obesity to long-term functional prognosis or mortality following TBI. While obesity may influence hospital stay and ICU duration, its impact on mortality is not significant 33 . This is in general agreement with the findings from our multivariate logistic regression model, indicating that BMI > 23.1 kg/m² is a risk factor of IAH. Additionally, our analysis indicates that enteral nutrition via nasogastric tube is a risk factor for IAH. This result corroborates earlier research, which found that post-pyloric enteral nutrition is more effective than gastric nutrition in reducing the incidence of gastrointestinal dysfunction 19 . The derived novel inflammatory marker dNLR holds significant predictive value for the onset, prognosis, and treatment efficacy in cancer patients and various other diseases 34 – 37 . However, studies investigating the correlation between dNLR and IAH remain scarce. In this study, we sought to utilize the dNLR to predict the occurrence of IAH in patients with TBI. Both univariate and multivariate analyses revealed that the dNLR during hospitalization was associated with the development of IAH. Furthermore, the post-treatment inflammatory status (as reflected by dNLR) demonstrated greater predictive value for IAH than the baseline NLR at admission. This suggests that monitoring the dynamic changes in NLR holds significant importance in predicting IAH within clinical practice. Table 2 The differences between TBI patients with and without IAH. Variants IAH Non-IAH p-value N = 38 N = 171 Age (yrs) 55.0 (46.8, 63.8) 58.0 (51.0, 63.0) 0.154 Gender 0.207 Male 12 (31.6%) 73 (42.7%) Female 26 (68.4%) 98 (57.3%) BMI (kg/m 2 ) 24.7 (22.5, 26.1) 22.8 (21.5, 24.3) 0.001** Comorbidity Hypertension 12 (31.6%) 67 (39.2%) 0.382 Diabetes Mellitus 7 (18.4%) 46 (26.9%) 0.277 Heart dysfunction 4 (10.5%) 19 (11.0%) 0.917 Complication Thoracic injury 16 (42.1%) 68 (39.8%) 0.790 GCS 6.0 (4.0, 9.0) 8.0 (5.0, 11.0) 0.001** EN application strategy <0.001*** NIT 13 (34.2%) 119 (69.6%) NGT 25 (65.8%) 52 (30.4%) Supported PN 20 (52.6%) 103 (60.2%) 0.389 Sedation 19 (50.0%) 47 (27.5%) <0.007** Mechanical ventilation 23 (60.5%) 77 (45.0%) 0.084 Temperature control 16 (42.1%) 46 (26.9%) 0.063 Laboratory tests at admission WBC-A (x10 9 /L) 15.8 (12.8, 18.8) 15.1 (12.6, 17.4) 0.150 Neutrophil-A (x10 9 /L) 13.3 (10.2, 16.5) 13.3 (11.4, 15.6) 0.954 Lymphocyte-A (x10 9 /L) 0.75 (0.56, 1.32) 0.74 (0.55, 1.01) 0.524 NLR-A 16.7 (11.0, 26.1) 18.4 (11.8, 26.9) 0.534 dNLR-A 0.94 (0.91, 0.96) 0.94 (0.92, 0.97) 0.235 Laboratory tests during hospitalization WBC-H (x10 9 /L) 14.8 (11.7, 18.4) 14.1 (10.6, 17.4) 0.178 Neutrophil-H (x10 9 /L) 11.8 (8.5, 15.0) 11.5 (8.7, 15.3) 0.853 Lymphocyte-H (x10 9 /L) 0.91 (0.75, 1.21) 1.13 (0.87, 1.42) 0.017* NLR-H 11.8 (7.2, 21.5) 10.1 (7.0, 14.1) 0.073 dNLR-H 0.89 (0.86, 0.92) 0.92 (0.89, 0.95) <0.001*** Trends in laboratory test results change WBC-R 0.93 (0.77, 1.14) 0.94 (0.66, 1.21) 0.876 Neutrophil-R 0.85 (0.61, 1.13) 0.90 (0.67, 1.17) 0.687 Lymphocyte-R 1.11 (0.63, 1.82) 1.61 (1.02, 2.28) 0.005** NLR-R 0.75 (0.38, 1.54) 0.54 (0.36, 0.94) 0.063 dNLR-R 0.94 (0.90, 1.00) 0.97 (0.94, 1.01) 0.008** BMI: body mass index, GCS: glasgow coma scale, EN: enteral nutrition, PN: parenteral nutrition, NGT: nasogastric tube, NIT: nasointestinal tube, WBC-A: white blood cell at adimission, NLR-A: neutrophil to lymphocyte ratio at admission, dNLR-A: delta neutrophil index-to-lymphocyte ratio at admission, WBC-H: white blood cell during hospitalization, WBC-R: the ratio of WBC count at admission to WBC count during hospitalization, IAH:intra-abdominal hypertension. *p<0.05, **p<0.01 and ***p<0.001 Based on the predictors identified through logistic multivariate analysis, we selected the two most statistically significant and readily obtainable indicators: BMI and dNLR at three days post-admission. ROC curves were plotted for each indicator individually and for their combined use to predict the occurrence of IAH. The combined ROC curve achieved the highest AUC, with sensitivity reaching 57.9% and specificity reaching 81.3%. This undoubtedly represents a welcome advancement. In the future, TBI patients and potentially all ICU patients may be screened for high-risk IAH using a predictive model established through BMI and dNLR measured three days after admission. This undoubtedly holds significance for enhancing the prognostic outcomes of TBI patients and advancing the specialty of critical care. This study is a retrospective controlled study. During case selection, we only included cases treated surgically at our hospital with relatively complete documentation, making it difficult to avoid selection bias. Moreover, clinical treatment involves numerous confounding factors, making it difficult to comprehensively include all influencing factors in our data collection and statistical analysis. Subsequently, we may expand the inclusion of influencing factors for further research or confirm these findings in prospective cohort studies or randomized controlled trials. This approach will transform retrospective evidence into more reliable clinical and public health decision-making bases, paving the way for deeper investigation. Conclusion This retrospective study indicates that risk factors for IAH include a BMI > 23.1 kg/m², enteral feeding via NGT, and a dNLR-H < 0.92. The combined predictive model of BMI and dNLR during hospitalization holds significance for the early prediction of IAH. Both BMI and dNLR are readily obtainable data in the routine clinical management of TBI patients, paving the way for this model's widespread adoption as a standard predictive tool. Abbreviations Intra-abdominal hypertension IAH traumatic brain injury TBI Intra-abdominal pressure IAP abdominal compartment syndrome ACS intensive care unit ICU acute respiratory distress syndrome ARDS body mass index BMI Glasgow Coma Scale GCS neutrophil to lymphocyte ratio NLR delta neutrophil index-to-lymphocyte ratio dNLR white blood cell WBC enteral nutrition EN nasogastric tube NGT nasointestinal tube NIT Peripheral nutrition PN dNLR during hospitalization dNLR-H receiver operating characteristic ROC area under curve AUC World Society of the Abdominal Compartment Syndrome WSACS European Society for Enteral and Parenteral Nutrition ESEPN Declarations Ethical Approval and Participant Consent This study has been approved by the Medical Ethics Committee of Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology (Protocol Code: TJ-IRB20251225; Approval Date: December 23, 2025). Since this retrospective observational study only involves statistical analysis of existing clinical data without any additional interventions on patients, and all data are used after de-identification (removing personal information such as patient names, ID numbers, and hospital admission numbers), the ethics committee approved the exemption from obtaining informed consent from patients. This study strictly adheres to the ethical guidelines of the Declaration of Helsinki and the International Committee of Medical Journal Editors (ICMJE), ensuring patient privacy and data security. Since this study is retrospective observational research that does not affect the health or rights of the subjects, the requirement for written informed consent was waived. Approved for publication The requirement for written informed consent was waived. Availability of data and materials The data utilized in this study were derived from the medical records system of Tongji Hospital, affiliated with Huazhong University of Science and Technology. The datasets used and analyzed in this study may be obtained from the corresponding author upon reasonable request. Conflict of interest All authors confirm that there are no conflicts of interest of any kind in this research. Funding This research received Hubei Province Association of Pathophysiology (No.2025HBAP015). Author Contributions Dr. Fuliang Jiang, Dr. Yue Zhao, and Dr. Yuxuan Xiong participated in data collection and analysis. Dr. Kai Zhao contributed to the study design. Dr. Fuliang Jiang drafted the manuscript. Dr. Kai Zhao edited the manuscript. Dr. Fuchi Zhang, Dr. Zhi Cai, and Dr. Yu Li conducted statistical analysis and reviewed the manuscript. Dr. Qing Zhang contributed to the conception of the project. Dr. Kai Zhao, Dr. Hongquan Niu, and Dr. Kai Shu provide resources and seek funding support. Acknowledgements We would like to express our gratitude to all authors for their support of this research. References Manley GT, et al. A new characterisation of acute traumatic brain injury: the NIH-NINDS TBI Classification and Nomenclature Initiative. Lancet Neurol. 2025;24:512–23. Maas AIR, et al. Traumatic brain injury: progress and challenges in prevention, clinical care, and research. Lancet Neurol. 2022;21:1004–60. Cheatham ML et al. Results from the International Conference of Experts on Intra-abdominal Hypertension and Abdominal Compartment Syndrome. II. Recommendations. Intensive Care Med 33, 951–962 (2007). Malbrain MLNG, Deeren D, De Potter TJ. R. Intra-abdominal hypertension in the critically ill: it is time to pay attention. Curr Opin Crit Care. 2005;11:156. Marta R, et al. Potential Predictors of Mortality in Adults with Severe Traumatic Brain Injury. Brain Sci. 2025;15:1014. 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Technical review of European Respiratory Society monograph, number 55, March 2012: new developments in mechanical ventilation, edited by M. Ferrer and P. Pelosi. Semin Cardiothorac Vasc Anesth 16, 250 (2012). Ventilation in. patients with intra-abdominal hypertension: what every critical care physician needs to know - PubMed. https://pubmed.ncbi.nlm.nih.gov/31025221/ Holodinsky JK, et al. Risk factors for intra-abdominal hypertension and abdominal compartment syndrome among adult intensive care unit patients: a systematic review and meta-analysis. Crit Care. 2013;17:R249. Balogh Z, Moore FA, Moore EE, Biffl WL. Secondary abdominal compartment syndrome: A potential threat for all trauma clinicians. Injury. 2007;38:272–9. Li Z, et al. Awareness, knowledge and practices related to intra-abdominal hypertension and abdominal compartment syndrome among intensive care providers: a systematic scoping review. Ann Intensive Care. 2025;15:106. Leon M, Chavez L, Surani S. Abdominal compartment syndrome among surgical patients. World J Gastrointest Surg. 2021;13:330–9. Holodinsky JK, et al. Risk factors for intra-abdominal hypertension and abdominal compartment syndrome among adult intensive care unit patients: a systematic review and meta-analysis. Crit Care. 2013;17:R249. Shi L, Shao J, Luo Y, Liu G, OuYang M. The incidence and risk factors of gastrointestinal dysfunction during enteral nutrition in mechanically ventilated critically ill patients. Nurs Open. 2024;11:e2247. Kuo Y-S, et al. Evaluation of the Preventive Effects of Fish Oil and Sunflower Seed Oil on the Pathophysiology of Sepsis in Endotoxemic Rats. Front Nutr. 2022;9:857255. The Glasgow Coma. Scale: an international standard for education and practice with adults. Br J Neurosci Nurs (2025). Nguyen R, et al. The International Incidence of Traumatic Brain Injury: A Systematic Review and Meta-Analysis. Can J Neurol Sci. 2016;43:774–85. Kuteesa J, et al. Intra-abdominal hypertension; prevalence, incidence and outcomes in a low resource setting; a prospective observational study. World J Emerg Surg. 2015;10:57. Regli A, Pelosi P, Malbrain ML. N. G. Ventilation in patients with intra-abdominal hypertension: what every critical care physician needs to know. Ann Intensive Care. 2019;9:52. Malbrain MLNG, et al. Prevalence of intra-abdominal hypertension in critically ill patients: a multicentre epidemiological study. Intensive Care Med. 2004;30:822–9. Kong Y, Chang T, Cui Y, Ding X, Liu W. Behaviour and cognition of adult critical care nurses regarding intra-abdominal pressure monitoring: a cross-sectional study. BMC Nurs. 2025;24:1108. Tayebi S, et al. A concise overview of non-invasive intra-abdominal pressure measurement techniques: from bench to bedside. J Clin Monit Comput. 2021;35:51–70. De Keulenaer BL, De Waele JJ, Powell B, Malbrain ML. N. G. What is normal intra-abdominal pressure and how is it affected by positioning, body mass and positive end-expiratory pressure? Intensive Care Med. 2009;35:969–76. de Soler Morejón C D., Tamargo Barbeito TO. Effect of mechanical ventilation on intra-abdominal pressure in critically ill patients without other risk factors for abdominal hypertension: an observational multicenter epidemiological study. Ann Intensive Care. 2012;2(Suppl 1):22. Holodinsky JK, et al. Risk factors for intra-abdominal hypertension and abdominal compartment syndrome among adult intensive care unit patients: a systematic review and meta-analysis. Crit Care. 2013;17:R249. Chabok SY, et al. The impact of body mass index on treatment outcomes among traumatic brain injury patients in intensive care units. Eur J Trauma Emerg Surg. 2014;40:51–5. Huang GS, Dunham CM, Chance EA, Hileman BM, DelloStritto DJ. Body mass index interaction effects with hyperglycemia and hypocholesterolemia modify blunt traumatic brain injury outcomes: a retrospective study. Int J Burns Trauma. 2020;10:314–23. Mishra R, et al. Obesity as a predictor of outcome following traumatic brain injury: A systematic review and meta-analysis. Clin Neurol Neurosurg. 2022;217:107260. Proctor MJ, et al. A derived neutrophil to lymphocyte ratio predicts survival in patients with cancer. Br J Cancer. 2012;107:695–9. Carbone MG, Marazziti D. Bipolar disorder and inflammation: a clinical study of NLR and dNLR across mood states and subtypes. World J Biol Psychiatry. 2025;1–7. 10.1080/15622975.2025.2586514 . Gong L, et al. The Value of Dynamic of Alkaline Phosphatase and Neutrophil-to-Lymphocyte Ratio in Predicting the Efficacy of Neoadjuvant Immunochemotherapy in Patients with Non-Small Cell Lung Cancer. J Inflamm Res. 2025;18:14827–39. Cao Y-D, et al. Validated nomograms for non-metastatic colorectal cancer prognosis prediction: a population-based study. Front Oncol. 2025;15:1691693. Additional Declarations No competing interests reported. Supplementary Files strobechecklist.docx Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-8765814","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":592995178,"identity":"a74064a4-6c26-43d2-89eb-615765c16d8a","order_by":0,"name":"Fuliang Jiang","email":"","orcid":"","institution":"Tongji Hospital","correspondingAuthor":false,"prefix":"","firstName":"Fuliang","middleName":"","lastName":"Jiang","suffix":""},{"id":592995179,"identity":"05212c7a-e5d1-49df-aa61-553eccfbff43","order_by":1,"name":"Yue Zhao","email":"","orcid":"","institution":"Tongji Hospital","correspondingAuthor":false,"prefix":"","firstName":"Yue","middleName":"","lastName":"Zhao","suffix":""},{"id":592995180,"identity":"c17d06c9-c6e7-41d6-8491-82664ed3e534","order_by":2,"name":"Yuxuan Xiong","email":"","orcid":"","institution":"Tongji Hospital","correspondingAuthor":false,"prefix":"","firstName":"Yuxuan","middleName":"","lastName":"Xiong","suffix":""},{"id":592995181,"identity":"6414dd51-9729-436f-bb65-5ca66750e194","order_by":3,"name":"Qing Zhang","email":"","orcid":"","institution":"Tongji Hospital","correspondingAuthor":false,"prefix":"","firstName":"Qing","middleName":"","lastName":"Zhang","suffix":""},{"id":592995182,"identity":"69c0bdac-9e50-478e-8421-0bfdee5d48e4","order_by":4,"name":"Fuchi Zhang","email":"","orcid":"","institution":"Tongji Hospital","correspondingAuthor":false,"prefix":"","firstName":"Fuchi","middleName":"","lastName":"Zhang","suffix":""},{"id":592995183,"identity":"52de6514-5bba-48c2-b9ca-4cf1facd3100","order_by":5,"name":"Zhi 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Zhao","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA/UlEQVRIiWNgGAWjYDACCQYGxgYGCTkGhjNAHg9YzIAoLcY8IC0HSNDCkNgDsuEAAxFa5Gc3P3w4o8YifT/j2QPMH2S2JTawN2+TYKi5g1ML45xjxoYbjknk9jCcSwA67HZiA8+xMgmGY89wamGWSDCTfMAG0nLGAKJFIsdMgrHhME4tbBLp3yQf/JNI54FrkX+DXwsP0EzJjW0SCQgtEjz4tUhI5BQbzuyTMOw5cMbgwBme28ZtPGnFFgnHcGuRn5G+8WHPtzp59hlnDB9U9tyW7Wc/vPHGhxrcWpDsO8BwgLEH6DsQJ4EIDQwM/A1A4gdRSkfBKBgFo2CEAQCdi1ZZlUqNogAAAABJRU5ErkJggg==","orcid":"","institution":"Tongji Hospital","correspondingAuthor":true,"prefix":"","firstName":"Kai","middleName":"","lastName":"Zhao","suffix":""},{"id":592995187,"identity":"95bdf714-5ce4-4bae-9ad1-e0a3c45448bd","order_by":8,"name":"Hongquan Niu","email":"","orcid":"","institution":"Tongji 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Process\u003c/p\u003e","description":"","filename":"OnlineAdmissionandPlacementProcessfigure1.png","url":"https://assets-eu.researchsquare.com/files/rs-8765814/v1/78c09d1d0c9e6e01d2117326.png"},{"id":103167412,"identity":"3de064af-fc81-442d-aca3-d1e26e4a8703","added_by":"auto","created_at":"2026-02-22 12:47:37","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":51557,"visible":true,"origin":"","legend":"\u003cp\u003eBar chart\u003c/p\u003e","description":"","filename":"OnlineBarchartfigure2.png","url":"https://assets-eu.researchsquare.com/files/rs-8765814/v1/bf105fd3fbf8a2acd2403741.png"},{"id":103504472,"identity":"bde6a80e-e746-4b2c-8118-1b4a1c1489b5","added_by":"auto","created_at":"2026-02-26 13:20:09","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":46046,"visible":true,"origin":"","legend":"\u003cp\u003eROC Curve\u003c/p\u003e","description":"","filename":"OnlineROCfigure3.png","url":"https://assets-eu.researchsquare.com/files/rs-8765814/v1/c4c5261feea4c7ccc3cecc0c.png"},{"id":104803379,"identity":"e4eb629a-f398-44a9-8498-0ce19e983d2e","added_by":"auto","created_at":"2026-03-17 10:58:08","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1225735,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8765814/v1/546e03cb-9122-475c-8182-2fea44466858.pdf"},{"id":103167413,"identity":"b1096513-a4d8-4d30-a329-5f1210735b57","added_by":"auto","created_at":"2026-02-22 12:47:37","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":109988,"visible":true,"origin":"","legend":"","description":"","filename":"strobechecklist.docx","url":"https://assets-eu.researchsquare.com/files/rs-8765814/v1/a8b81c71c1b660b968b71534.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Early intervention-oriented: a clinical predictive model for identifying the high risk of intra- abdominal hypertension in patients with traumatic brain injury","fulltext":[{"header":"Introduction","content":"\u003cp\u003eTraumatic brain injury (TBI) ranks among the primary causes of global disability and mortality \u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e. As a systemic disease, it can cause dysfunction in organs throughout the body, leading to a wide range of systemic complications \u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e. This results in secondary brain injury in TBI patients, thereby affecting treatment outcomes. Intra-abdominal pressure (IAP) refers to the steady pressure within the abdominal cavity (World Society of the Abdominal Compartment Syndrome, 2006)\u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e. It results in pressure on the central nervous system through two pathways. One pathway involves the valveless spinal venous plexus connecting to intracranial veins, forming an anatomical conduit from the pelvis directly to the eyes and brain. The other pathway involves a mechanical transmission process: increased intra-abdominal pressure first transmits upward, causing diaphragmatic displacement and elevated intrathoracic pressure. The subsequent rise in central venous pressure impedes blood return to the central nervous system via the jugular veins, ultimately resulting in reduced intracranial venous return. It is increasingly recognized as a vital physiological indicator for monitoring the onset of IAH in \u003cb\u003et\u003c/b\u003ehe gravely ill or as the sixth vital sign following blood pressure, heart rate, respiratory rate, body temperature, and blood oxygen saturation\u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e,\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e. IAH is one of the complications occurring during the treatment of patients with TBI. It is conceptualized as persistent IAP elevation to 12 mmHg or higher, accompanied by a heightened risk of multi-organ failure (involving abdominal and distant systems) and mortality\u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e. It is estimated that 50.0% to 80.0% of severely ill adult patients are in danger of progressing to intra-abdominal hypertension (IAH), with 2.7% to 51.7% of these cases progressing to abdominal compartment syndrome (ACS)\u003csup\u003e\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e,\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e. Increased IAP triggers a series of pathophysiological processes. First, IAH directly impairs arterial and venous blood flow to abdominal organs, disrupts intestinal perfusion, and obstructs lymphatic drainage. This progressively leads to intestinal obstruction, edema, and ischemia, resulting in disruption of the intestinal mucosal barrier function, translocation of gut microbiota, and secondary infections\u003csup\u003e\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u003c/sup\u003e. Second, IAH directly leads to impaired cerebral venous outflow, elevated jugular venous pressure, disruption of the blood-brain barrier, reduced blood flow in the lumbar venous plexus, and increased cerebral blood flow. This subsequently causes elevated intracranial pressure and decreased cerebral perfusion pressure\u003csup\u003e\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u003c/sup\u003e. Third, IAH leads to diaphragmatic elevation and increased intrathoracic pressure, accompanied by cardiac compression and inferior vena cava compression. This results in increased right ventricular afterload, decreased cardiac output, and reduced ventricular compliance/contractility. Consequently, cerebral blood flow and perfusion are impaired, leading to secondary cerebral tissue hypoxia\u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e. Fourth, IAH leads to lung compression, alveolar atelectasis, reduced pulmonary capillary blood flow, and impaired lymphatic drainage. This subsequently causes elevated airway peak pressure, increased plateau pressure, decreased lung compliance, reduced tidal volume, decreased functional residual capacity, ventilation/perfusion incompatibility, and hypercapnia. These effects induce cerebral hypoxia and cerebral edema, exacerbating increased intracranial pressure\u003csup\u003e\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e,\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e. These pathophysiological processes undoubtedly contribute to the progression of TBI patients' conditions, with their impact on intracranial pressure being of particular concern to neurosurgeons.\u003c/p\u003e \u003cp\u003eAmong severely ill patients in the intensive care unit (ICU), published studies have identified general risk contributors for IAH, including obesity, sepsis/infection, the patient's initial diagnosis, abdominal surgery, acidosis, hypotension, mechanical ventilation/acute respiratory distress syndrome (ARDS), and crystalloid and non-crystalloid fluid resuscitation\u003csup\u003e\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/sup\u003e. For non-abdominal trauma patients, literature reports indicate that the frequency of secondary ACS following trauma is 0.09% of the total trauma cohort, accounting for 0.7% of all trauma patients\u003csup\u003e\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e. Crystalloid resuscitation is generally recognized as a contributor for ACS in trauma patients\u003csup\u003e\u003cspan additionalcitationids=\"CR17\" citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u003c/sup\u003e, but no in-depth research has been conducted on the onset rate of IAH and its associated risk factors in trauma patients. There is currently no published research on the occurrence of IAH in TBI patients or its associated risk factors. Additionally, nutritional therapy constitutes a vital component of comprehensive treatment for TBI patients. It plays a crucial physiological role in improving malnutrition, maintaining internal environmental stability, protecting gastrointestinal function, reducing gut microbiota dysbiosis, and mitigating secondary brain injury. Literature reports that improper enteral nutrition therapy is a high-risk contributor for the occurrence of IAH in patients in critical condition, including feeding routes and enteral nutrition formulas\u003csup\u003e\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e,\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u003c/sup\u003e. However, for patients with TBI, the relationship between enteral nutrition therapy and IAH remains unclear and warrants further investigation.\u003c/p\u003e \u003cp\u003eTherefore, this study focuses on the onset rate and contributors of IAH in TBI patients, aiming to explore the development of an early prediction model. This model seeks to advance the timing of interventional measures for IAH in TBI patients, thereby significantly improving their prognosis. This retrospective analysis examined the occurrence of IAH in 209 patients with TBI. According to statistically significant differential indicators, a predictive model for IAH occurrence was proposed to aid medical practice.\u003c/p\u003e"},{"header":"Methods and Materials","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003ePatient Selection and Ethical Approval\u003c/h2\u003e \u003cp\u003eThis retrospective study was conducted at Tongji Hospital, affiliated with Tongji Medical College of Huazhong University of Science and Technology. Inclusion criteria are as follows: 1) Age\u0026thinsp;\u0026gt;\u0026thinsp;18. 2) The patient has a clear history of trauma. 3)Admitted within 24 hours of traumatic brain injury. 4) All surgical procedures performed on patients were conducted at this hospital. Exclusion criteria are as follows: 1) Survival time less than 3 days following traumatic brain injury. 2) Pregnant or breastfeeding women (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eFrom January 2020 to December 2024, our hospital admitted a total of 209 patients meeting the aforementioned criteria. We collected and analyzed their basic information, clinical manifestations, management strategies, and laboratory results.\u003c/p\u003e \u003cp\u003e All procedures involving human participants in this study strictly adhered to the ethical guidelines of the Declaration of Helsinki and the International Committee of Medical Journal Editors (ICMJE) and were approved by the Medical Ethics Committee of Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology. Informed consent was waived.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eData Collection\u003c/h3\u003e\n\u003cp\u003eDemographic data (gender, age), medical history (injury mechanism, symptoms, and signs), body mass index (BMI), and Glasgow Coma Scale (GCS) score (the specific grading criteria shall be based on the scale presented by Neal Cook\u003csup\u003e\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e) were retrieved from the medical record system. Collect hematological test data, including white blood cell (WBC) count, neutrophil count, and lymphocyte count at admission; admission neutrophil to lymphocyte ratio (NLR) and delta neutrophil index-to-lymphocyte ratio (dNLR) indices; white blood cell count, neutrophil count, and lymphocyte count during hospitalization (three days after admission); NLR and dNLR indices during hospitalization; and the ratio of white blood cell count, neutrophil count, lymphocyte count, NLR, and dNLR at admission to WBC count, neutrophil count, lymphocyte count, NLR, and dNLR during hospitalization.\u003c/p\u003e \u003cp\u003eCollect information related to intensive care, including enteral nutrition strategy, administration of sedation, use of mechanical ventilation, and application of temperature control treatment.\u003c/p\u003e \u003cp\u003eIAP was indirectly measured by the detection of intravesical pressure six times a day. IAH was confirmed as IAP\u0026thinsp;\u0026ge;\u0026thinsp;12 mmHg according to the diagnostic criteria established by the World Society of the Abdominal Compartment Syndrome (WSACS; \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://www.wsacs.org\u003c/span\u003e\u003cspan address=\"http://www.wsacs.org\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe formulas for calculating the NLR and dNLR indices are as follows: NLR\u0026thinsp;=\u0026thinsp;Neutrophil count / Lymphocyte count, dNLR\u0026thinsp;=\u0026thinsp;Neutrophil Count / (Total White Blood Cell Count - Neutrophil Count).\u003c/p\u003e \u003cp\u003eNutrition therapy was applied in all TBI patients according to the guideline of the European Society for Enteral and Parenteral Nutrition (ESPEN; \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.espen.org\u003c/span\u003e\u003cspan address=\"https://www.espen.org\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e). Enteral nutrition (EN) treatment was applied by nasogastric tube (NGT) feeding or nasointestinal tube (NIT) feeding. Peripheral nutrition (PN) was added when enteral nutrition fails to meet 60% of the target energy and protein requirements.\u003c/p\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eStatistical Analysis\u003c/h2\u003e \u003cp\u003eDescriptions of categorical variables are presented as percentages (%). The normality of continuous variables was examined with the Kolmogorov-Smirnov (K-S) test. For variables meeting normality criteria, mean and standard deviation (SD) were reported; for those not meeting normality criteria, median and interquartile range (IQR) were used. Employ the t-test to compare the difference between two samples. To compare categorical variables across sets, the chi-square test was employed. For p-values less than 5, Fisher's exact test was applied. Normally distributed variables were analyzed with Student's t-test, and non-normally distributed variables with the Mann-Whitney U test.\u003c/p\u003e \u003cp\u003eVariables associated with IAH in TBI patients and showing significant differences between groups were covered in a multivariate logistic regression model. Given the limited number of available events, variables were carefully selected to ensure model parsimony. The final outcome for each variable was expressed as the odds ratio (OR) and 95% confidence interval (95% CI).\u003c/p\u003e \u003cp\u003eSelect the ROC (Receiver Operating Characteristic) curve to assess the sensitivity and specificity of the predictive model for IAH incidence in TBI patients. Select continuous variables associated with IAH (BMI, delta neutrophil index-to-lymphocyte ratio (dNLR-H)) that demonstrate statistically significant differences between the poor-outcome subgroup and the favorable-outcome subgroup, and incorporate these variables into the predictive model. In addition to individual tests, these variables were also combined. All statistical analyses were performed using SPSS 23.0 software (Chicago, IL, USA). For all tests, a two-tailed p-value\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was considered statistically significant.\u003c/p\u003e \u003c/div\u003e"},{"header":"Result","content":"\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eClinical Features\u003c/h2\u003e \u003cp\u003eOverall, 209 patients with TBI were included in the survey. Males accounted for 40.7% and females for 59.3%. The median age was 56 years, with a median admission GCS score of 8. Among these patients, 40.2% also had concomitant chest injuries.\u003c/p\u003e \u003cp\u003eIn the medical history, the prevalence rates of hypertension, diabetes, and cardiac dysfunction were 27.8%, 25.4%, and 11.0%, respectively.\u003c/p\u003e \u003cp\u003eMonitoring status: 31.6% of patients received high-dose sedation; 47.8% required mechanical ventilation; 29.7% did not develop fever. Different enteral nutrition strategies were implemented based on individual patient circumstances, with 63.2% receiving nutrition via nasogastric tube and 36.8% via nasointestinal tube.\u003c/p\u003e \u003cp\u003eComplete blood counts were recorded upon admission and during hospitalization (three days after admission). At admission, the median total WBC count was 15.3 \u0026times; 10⁹/L, the median neutrophil count was 13.3 \u0026times; 10⁹/L, and the median lymphocyte count was 0.8 \u0026times; 10⁹/L. Calculations yielded median NLR and dNLR values of 18.1 and 2.0, respectively. During hospitalization, the median WBC count was 14.3 \u0026times; 10⁹/L, the median neutrophil count was 11.5 \u0026times; 10⁹/L, and the median lymphocyte count was 1.1 \u0026times; 10⁹/L. Calculations yielded median NLR and dNLR values of 10.1 and 1.8, respectively.\u003c/p\u003e \u003cp\u003eData on IAP obtained via transvesical indirect measurement: 38 patients with IAH and 171 patients without IAH (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eClinical characteristics of 209 TBI patients\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"2\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariants\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eContent (N\u0026thinsp;=\u0026thinsp;209)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge (yrs)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e56.0 (50.0, 63.0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGender\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e85 (40.7%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e124 (59.3%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBMI (kg/m\u003csup\u003e2\u003c/sup\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e23.1 (21.5, 24.8)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eComorbidity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHypertension\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e79 (27.8%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDiabetes Mellitus\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e53 (25.4%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHeart dysfunction\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e23 (11.0%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eComplications\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eThoracic injury\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e84 (40.2%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGCS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e8.0 (5.0, 10.0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEN application strategy\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNIT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e132 (63.2%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNGT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e77 (36.8%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSupported PN\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e123 (58.9%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSedation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e66 (31.6%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMechanical ventilation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e100 (47.8%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTemperature control\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e62 (29.7%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLaboratory tests at admission\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWBC-A (x10\u003csup\u003e9\u003c/sup\u003e/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e15.3 (12.7, 17.9)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNeutrophil-A (x10\u003csup\u003e9\u003c/sup\u003e/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e13.3 (11.2, 15.9)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLymphocyte-A (x10\u003csup\u003e9\u003c/sup\u003e/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.75 (0.56, 1.01)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNLR-A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e18.1 (11.6, 26.8)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003edNLR-A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.9 (0.92, 0.96)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLaboratory tests during hospitalization\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWBC-H (x10\u003csup\u003e9\u003c/sup\u003e/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e14.3 (10.9, 17.5)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNeutrophil-H (x10\u003csup\u003e9\u003c/sup\u003e/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e11.5 (8.6, 15.3)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLymphocyte-H (x10\u003csup\u003e9\u003c/sup\u003e/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.08 (0.83, 1.40)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNLR-H\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e10.1 (7.0, 15.5)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003edNLR-H\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.92 (0.89, 0.94)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTrends in laboratory test results change\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWBC-R\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.94 (0.72, 1.20)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNeutrophil-R\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.89 (0.66, 1.15)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLymphocyte-R\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.49 (0.91, 2.20)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNLR-R\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.57 (0.36, 1.03)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003edNLR-R\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.97 (0.94, 1.01)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIAH\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e38(18.2%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"2\"\u003eBMI: body mass index, GCS: glasgow coma scale, EN: enteral nutrition, PN: parenteral nutrition, NGT: nasogastric tube, NIT: nasointestinal tube, WBC-A: white blood cell at adimission, NLR-A: neutrophil to lymphocyte ratio at admission, dNLR-A: delta neutrophil index-to-lymphocyte ratio at admission, WBC-H: white blood cell during hospitalization, IAH:intra-abdominal hypertension.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eTwo sets of differences\u003c/h2\u003e \u003cp\u003ePatients were categorized into an IAH subset (n\u0026thinsp;=\u0026thinsp;38) and a non-IAH subset (n\u0026thinsp;=\u0026thinsp;171) on the basis of intra-abdominal pressure measurements. Comparative analysis of characteristic data revealed a marked difference in admission BMI between groups (p\u0026thinsp;=\u0026thinsp;0.001), with the non-IAH group exhibiting markedly superior admission GCS scores in comparison to the IAH subgroup (p\u0026thinsp;=\u0026thinsp;0.001). There were also noticeable differences in enteral nutrition strategies (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), while the use of supportive parenteral nutrition was similar (p\u0026thinsp;=\u0026thinsp;0.389). Compared with the non-IAH subgroup, a higher proportion of patients in the IAH subgroup received high-dose sedation (p\u0026thinsp;\u0026lt;\u0026thinsp;0.007). The two sets did not differ significantly in the use of mechanical ventilation for respiratory support and temperature control.\u003c/p\u003e \u003cp\u003eThe two subgroups were comparable in terms of WBC count, neutrophil count, lymphocyte count, NLR index, or dNLR index at admission. During hospitalization, there were no differences in white blood cell counts, neutrophil counts, or NLR index between the two sets. However, notable differences were observed in lymphocyte counts (p\u0026thinsp;=\u0026thinsp;0.017), and dNLR (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) indices between the two subgroups during hospitalization. The analysis revealed no differences between the two subsets in the ratio of admission WBC count, neutrophil count, and NLR to the respective values during hospitalization. However, the ratio of lymphocyte count and dNLR index at admission to those during hospitalization showed significant differences between the two subsets (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eRisk Factors for Outcomes\u003c/h3\u003e\n\u003cp\u003eTo adjust for potential confounders, variables showing significant differences were entered into a multivariate logistic regression model. Results indicated that BMI\u0026thinsp;\u0026gt;\u0026thinsp;23.1 kg/m\u0026sup2;, NGT, and dNLR-H\u0026thinsp;\u0026lt;\u0026thinsp;0.92 were all high-risk factors for IAH (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eThe multivariate logistic analysis of risk factors for IAH occurrence\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eB\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eWald\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eOR\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e95% CI\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBMI (\u0026gt;23.1 kg/m\u003csup\u003e2\u003c/sup\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.110\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e6.262\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3.033\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.272\u0026ndash;7.232\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e0.012*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGCS (\u0026lt;8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.478\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.952\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.613\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.617\u0026ndash;4.213\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.329\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNGT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.626\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e11.918\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e5.083\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e2.019\u0026ndash;12.793\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e0.001**\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSedation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.395\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.765\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.484\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.613\u0026ndash;3.594\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.382\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLymphocyte-H (\u0026lt;1.08 x10\u003csup\u003e9\u003c/sup\u003e/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.843\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3.235\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2.324\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.927\u0026ndash;5.825\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.072\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003edNLR-H (\u0026lt;\u0026thinsp;0.92)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.588\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e8.102\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e4.895\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.640-14.614\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e0.004**\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLymphocyte-R (\u0026lt;\u0026thinsp;1.49)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.426\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.904\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.530\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.636\u0026ndash;3.680\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.342\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003edNLR-R (\u0026lt;\u0026thinsp;0.94)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.087\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.027\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.090\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.386\u0026ndash;3.077\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.87\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"6\"\u003eBMI: body mass index, GCS: glasgow coma scale, NGT: nasogastric tube, dNLR-H: delta neutrophil index-to-lymphocyte ratio during hospitalization, dNLR-R: the ratio of dNLR at admission to that during hospitalization. \u003cb\u003e*\u003c/b\u003ep\u0026thinsp;\u0026lt;\u0026thinsp;0.05 and **p\u0026thinsp;\u0026lt;\u0026thinsp;0.01\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003eOutcome Prediction Mode\u003c/b\u003el\u003c/p\u003e \u003cp\u003eA predictive model for IAH occurrence in TBI patients was established using the receiver operating characteristic (ROC) curve (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). BMI demonstrated a sensitivity of 60.5% and specificity of 73.7%; dNLR-H showed a sensitivity of 63.2% and specificity of 69.6%. Further analysis combining BMI and dNLR-H yielded an area under curve (AUC) of 0.732, which has a predictive sensitivity of 57.9% and specificity of 81.3% (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003ePredictive value of BMI, dNLR-H and their combinations\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYouden\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAUC\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e95% CI\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eSensitivity\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eSpecificity\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBMI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.342\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.673\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.570\u0026ndash;0.776\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e60.5%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e73.7%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003edNLR-H\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.328\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.700\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.606\u0026ndash;0.793\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e63.2%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e69.6%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBMI+dNLR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.392\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.732\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.636\u0026ndash;0.828\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e57.9%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e81.3%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"6\"\u003eBMI: body mass index, dNLR-H: delta neutrophil index-to-lymphocyte ratio during hospitalization, AUC: area under the curve\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eAmong U.S. residents aged below 45, TBI accounts for a leading share of disability and mortality\u003csup\u003e\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u003c/sup\u003e. IAH as one of the adverse prognostic risk factors for TBI patients, has a high incidence rate and warrants our full attention. Approximately one-quarter to 33.3% of patients exhibit IAH upon admission to the ICU, while approximately half contract IAH within the first week of ICU admission\u003csup\u003e\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u003c/sup\u003e. Among patients undergoing emergency exploratory laparotomy, the incidence of IAH was 25% in the pediatric group and 17.4% in the adult group\u003csup\u003e\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u003c/sup\u003e. In a specific cohort of TBI patients, our study revealed that 38 out of 209 enrolled TBI patients developed IAH. We hypothesize that the cause lies in the elevated intracranial pressure following TBI triggering an extreme stress response in the body, which prioritizes the \u0026ldquo;protect the brain\u0026rdquo; command, leading to a redistribution of systemic blood flow. This leads to reduced blood flow to the abdominal viscera. Under conditions of ischemia and hypoxia, the gastrointestinal mucosa becomes damaged, triggering bacterial translocation and endotoxin release, systemic inflammatory response, and multiple organ dysfunction, ultimately resulting in IAH. Additionally, some TBI patients exhibit higher fluid resuscitation rates and transfusion frequencies compared to general patients, which also increases the likelihood of IAH occurrence\u003csup\u003e\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u003c/sup\u003e。The occurrence of IAH further exacerbates cerebral edema and elevates intracranial pressure\u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e, leading to secondary brain injury and creating a vicious cycle. Therefore, preventing the occurrence of IAH and breaking the vicious cycle is an indispensable step in ensuring a favorable prognosis for TBI patients.\u003c/p\u003e \u003cp\u003eIAP can be measured directly by placing a probe within the abdominal cavity or indirectly by measuring pressures in other abdominal organs to reflect IAP levels, such as bladder pressure, gastric pressure, colonic pressure, and uterine pressure\u003csup\u003e\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u003c/sup\u003e. Several new non-invasive measurement methods have recently been proposed, including ultrasound-based IAP monitoring technology, bioelectrical impedance analysis, microwave reflection methods, digital image correlation, and the application of wireless motion capsules\u003csup\u003e\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u003c/sup\u003e. Our study employed the transvesical indirect measurement method, which is currently recognized as the gold standard for IAP measurement, demonstrating good correlation with IAP while avoiding the infection risks associated with direct measurement techniques.\u003c/p\u003e \u003cp\u003eThrough statistical analysis of the relevant data obtained, we identified several predictors of IAH, as shown in Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e2\u003c/span\u003e. Previous research has suggested that BMI is an independent predictor of IAH \u003csup\u003e\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e,\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u003c/sup\u003e, and has indicated that obesity (defined as a BMI\u0026thinsp;\u0026gt;\u0026thinsp;30 kg/m\u0026sup2;) is a high-risk factor for the progression of IAH in mixed ICU patients\u003csup\u003e\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e\u003c/sup\u003e. Numerous studies have also documented that obesity is associated with increased ICU mortality, prolonged duration of mechanical ventilation, and extended hospital stays among patients with traumatic brain injury\u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e,\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e,\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e\u003c/sup\u003e. However, some studies suggest there is no conclusive evidence linking obesity to long-term functional prognosis or mortality following TBI. While obesity may influence hospital stay and ICU duration, its impact on mortality is not significant\u003csup\u003e\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e\u003c/sup\u003e. This is in general agreement with the findings from our multivariate logistic regression model, indicating that BMI\u0026thinsp;\u0026gt;\u0026thinsp;23.1 kg/m\u0026sup2; is a risk factor of IAH. Additionally, our analysis indicates that enteral nutrition via nasogastric tube is a risk factor for IAH. This result corroborates earlier research, which found that post-pyloric enteral nutrition is more effective than gastric nutrition in reducing the incidence of gastrointestinal dysfunction\u003csup\u003e\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u003c/sup\u003e. The derived novel inflammatory marker dNLR holds significant predictive value for the onset, prognosis, and treatment efficacy in cancer patients and various other diseases\u003csup\u003e\u003cspan additionalcitationids=\"CR35 CR36\" citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e\u003c/sup\u003e. However, studies investigating the correlation between dNLR and IAH remain scarce. In this study, we sought to utilize the dNLR to predict the occurrence of IAH in patients with TBI. Both univariate and multivariate analyses revealed that the dNLR during hospitalization was associated with the development of IAH. Furthermore, the post-treatment inflammatory status (as reflected by dNLR) demonstrated greater predictive value for IAH than the baseline NLR at admission. This suggests that monitoring the dynamic changes in NLR holds significant importance in predicting IAH within clinical practice.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eThe differences between TBI patients with and without IAH.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariants\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eIAH\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNon-IAH\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eN\u0026thinsp;=\u0026thinsp;38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eN\u0026thinsp;=\u0026thinsp;171\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge (yrs)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e55.0 (46.8, 63.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e58.0 (51.0, 63.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.154\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGender\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.207\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e12 (31.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e73 (42.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e26 (68.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e98 (57.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBMI (kg/m\u003csup\u003e2\u003c/sup\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e24.7 (22.5, 26.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e22.8 (21.5, 24.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.001**\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eComorbidity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHypertension\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e12 (31.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e67 (39.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.382\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDiabetes Mellitus\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7 (18.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e46 (26.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.277\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHeart dysfunction\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4 (10.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e19 (11.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.917\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eComplication\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eThoracic injury\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e16 (42.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e68 (39.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.790\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGCS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6.0 (4.0, 9.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8.0 (5.0, 11.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.001**\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEN application strategy\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;0.001***\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNIT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e13 (34.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e119 (69.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNGT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e25 (65.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e52 (30.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSupported PN\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e20 (52.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e103 (60.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.389\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSedation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e19 (50.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e47 (27.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;0.007**\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMechanical ventilation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e23 (60.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e77 (45.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.084\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTemperature control\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e16 (42.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e46 (26.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.063\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLaboratory tests at admission\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWBC-A (x10\u003csup\u003e9\u003c/sup\u003e/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e15.8 (12.8, 18.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e15.1 (12.6, 17.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.150\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNeutrophil-A (x10\u003csup\u003e9\u003c/sup\u003e/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e13.3 (10.2, 16.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e13.3 (11.4, 15.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.954\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLymphocyte-A (x10\u003csup\u003e9\u003c/sup\u003e/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.75 (0.56, 1.32)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.74 (0.55, 1.01)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.524\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNLR-A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e16.7 (11.0, 26.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e18.4 (11.8, 26.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.534\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003edNLR-A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.94 (0.91, 0.96)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.94 (0.92, 0.97)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.235\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLaboratory tests during hospitalization\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWBC-H (x10\u003csup\u003e9\u003c/sup\u003e/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e14.8 (11.7, 18.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e14.1 (10.6, 17.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.178\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNeutrophil-H (x10\u003csup\u003e9\u003c/sup\u003e/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e11.8 (8.5, 15.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11.5 (8.7, 15.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.853\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLymphocyte-H (x10\u003csup\u003e9\u003c/sup\u003e/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.91 (0.75, 1.21)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.13 (0.87, 1.42)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.017*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNLR-H\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e11.8 (7.2, 21.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10.1 (7.0, 14.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.073\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003edNLR-H\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.89 (0.86, 0.92)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.92 (0.89, 0.95)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;0.001***\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTrends in laboratory test results change\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWBC-R\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.93 (0.77, 1.14)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.94 (0.66, 1.21)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.876\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNeutrophil-R\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.85 (0.61, 1.13)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.90 (0.67, 1.17)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.687\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLymphocyte-R\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.11 (0.63, 1.82)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.61 (1.02, 2.28)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.005**\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNLR-R\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.75 (0.38, 1.54)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.54 (0.36, 0.94)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.063\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003edNLR-R\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.94 (0.90, 1.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.97 (0.94, 1.01)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.008**\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003eBMI: body mass index, GCS: glasgow coma scale, EN: enteral nutrition, PN: parenteral nutrition, NGT: nasogastric tube, NIT: nasointestinal tube, WBC-A: white blood cell at adimission, NLR-A: neutrophil to lymphocyte ratio at admission, dNLR-A: delta neutrophil index-to-lymphocyte ratio at admission, WBC-H: white blood cell during hospitalization, WBC-R: the ratio of WBC count at admission to WBC count during hospitalization, IAH:intra-abdominal hypertension. *p\u0026lt;0.05, **p\u0026lt;0.01 and ***p\u0026lt;0.001\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eBased on the predictors identified through logistic multivariate analysis, we selected the two most statistically significant and readily obtainable indicators: BMI and dNLR at three days post-admission. ROC curves were plotted for each indicator individually and for their combined use to predict the occurrence of IAH. The combined ROC curve achieved the highest AUC, with sensitivity reaching 57.9% and specificity reaching 81.3%. This undoubtedly represents a welcome advancement. In the future, TBI patients and potentially all ICU patients may be screened for high-risk IAH using a predictive model established through BMI and dNLR measured three days after admission. This undoubtedly holds significance for enhancing the prognostic outcomes of TBI patients and advancing the specialty of critical care.\u003c/p\u003e \u003cp\u003eThis study is a retrospective controlled study. During case selection, we only included cases treated surgically at our hospital with relatively complete documentation, making it difficult to avoid selection bias. Moreover, clinical treatment involves numerous confounding factors, making it difficult to comprehensively include all influencing factors in our data collection and statistical analysis. Subsequently, we may expand the inclusion of influencing factors for further research or confirm these findings in prospective cohort studies or randomized controlled trials. This approach will transform retrospective evidence into more reliable clinical and public health decision-making bases, paving the way for deeper investigation.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThis retrospective study indicates that risk factors for IAH include a BMI\u0026thinsp;\u0026gt;\u0026thinsp;23.1 kg/m\u0026sup2;, enteral feeding via NGT, and a dNLR-H\u0026thinsp;\u0026lt;\u0026thinsp;0.92. The combined predictive model of BMI and dNLR during hospitalization holds significance for the early prediction of IAH. Both BMI and dNLR are readily obtainable data in the routine clinical management of TBI patients, paving the way for this model's widespread adoption as a standard predictive tool.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cdiv class=\"DefinitionList\"\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eIntra-abdominal hypertension\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003e \u003cb\u003eIAH\u003c/b\u003e \u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003etraumatic brain injury\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003e \u003cb\u003eTBI\u003c/b\u003e \u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eIntra-abdominal pressure\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003e \u003cb\u003eIAP\u003c/b\u003e \u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eabdominal compartment syndrome\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003e \u003cb\u003eACS\u003c/b\u003e \u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eintensive care unit\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003e \u003cb\u003eICU\u003c/b\u003e \u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eacute respiratory distress syndrome\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003e \u003cb\u003eARDS\u003c/b\u003e \u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003ebody mass index\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003e \u003cb\u003eBMI\u003c/b\u003e \u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eGlasgow Coma Scale\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003e \u003cb\u003eGCS\u003c/b\u003e \u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eneutrophil to lymphocyte ratio\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003e \u003cb\u003eNLR\u003c/b\u003e \u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003edelta\u0026nbsp;neutrophil\u0026nbsp;index-to-lymphocyte\u0026nbsp;ratio\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003e \u003cb\u003edNLR\u003c/b\u003e \u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003ewhite blood cell\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003e \u003cb\u003eWBC\u003c/b\u003e \u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eenteral nutrition\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003e \u003cb\u003eEN\u003c/b\u003e \u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003enasogastric tube\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003e \u003cb\u003eNGT\u003c/b\u003e \u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003enasointestinal tube\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003e \u003cb\u003eNIT\u003c/b\u003e \u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003ePeripheral\u0026nbsp;nutrition\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003e \u003cb\u003ePN\u003c/b\u003e \u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003edNLR during hospitalization\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003e \u003cb\u003edNLR-H\u003c/b\u003e \u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003ereceiver operating characteristic\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003e \u003cb\u003eROC\u003c/b\u003e \u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003earea under curve\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003e \u003cb\u003eAUC\u003c/b\u003e \u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eWorld Society of the Abdominal Compartment Syndrome\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003e \u003cb\u003eWSACS\u003c/b\u003e \u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eEuropean Society for Enteral and Parenteral Nutrition\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003e \u003cb\u003eESEPN\u003c/b\u003e \u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthical Approval and Participant Consent\u003c/strong\u003e This study has been approved by the Medical Ethics Committee of Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology (Protocol Code: TJ-IRB20251225; Approval Date: December 23, 2025). Since this retrospective observational study only involves statistical analysis of existing clinical data without any additional interventions on patients, and all data are used after de-identification (removing personal information such as patient names, ID numbers, and hospital admission numbers), the ethics committee approved the exemption from obtaining informed consent from patients. This study strictly adheres to the ethical guidelines of the Declaration of Helsinki and the International Committee of Medical Journal Editors (ICMJE), ensuring patient privacy and data security. Since this study is retrospective observational research that does not affect the health or rights of the subjects, the requirement for written informed consent was waived.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eApproved for publication\u0026nbsp;\u003c/strong\u003eThe requirement for written informed consent was\u0026nbsp;waived.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u0026nbsp;\u003c/strong\u003eThe data utilized in this study were derived from the medical records system of Tongji Hospital, affiliated with Huazhong University of Science and Technology. The datasets used and analyzed in this study may be obtained from the corresponding author upon reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflict of interest\u0026nbsp;\u003c/strong\u003eAll authors confirm that there are no conflicts of interest of any kind in this research.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003eThis research received Hubei Province Association of Pathophysiology (No.2025HBAP015).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor Contributions\u0026nbsp;\u003c/strong\u003eDr. Fuliang Jiang, Dr. Yue Zhao, and Dr. Yuxuan Xiong participated in data collection and analysis. Dr. Kai Zhao contributed to the study design. Dr. Fuliang Jiang drafted the manuscript. Dr. Kai Zhao edited the manuscript. Dr. Fuchi Zhang, Dr. Zhi Cai, and Dr. Yu Li conducted statistical analysis and reviewed the manuscript. Dr. Qing Zhang contributed to the conception of the project. Dr. Kai Zhao, Dr. Hongquan Niu, and Dr. Kai Shu provide resources and seek funding support.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u0026nbsp;\u003c/strong\u003eWe would like to express our gratitude to all authors for their support of this research.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eManley GT, et al. A new characterisation of acute traumatic brain injury: the NIH-NINDS TBI Classification and Nomenclature Initiative. Lancet Neurol. 2025;24:512\u0026ndash;23.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMaas AIR, et al. Traumatic brain injury: progress and challenges in prevention, clinical care, and research. Lancet Neurol. 2022;21:1004\u0026ndash;60.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCheatham ML et al. Results from the International Conference of Experts on Intra-abdominal Hypertension and Abdominal Compartment Syndrome. II. 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Front Oncol. 2025;15:1691693.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Traumatic brain injury, Intra-abdominal hypertension, Predictive model","lastPublishedDoi":"10.21203/rs.3.rs-8765814/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8765814/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eIntra-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.\u003c/p\u003e\u003ch2\u003eMethod\u003c/h2\u003e \u003cp\u003eWe 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.\u003c/p\u003e\u003ch2\u003eResult\u003c/h2\u003e \u003cp\u003eA 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\u0026thinsp;\u0026gt;\u0026thinsp;23.1 kg/m\u0026sup2;, dNLR-H (\u0026lt;\u0026thinsp;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%.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eBMI\u0026thinsp;\u0026gt;\u0026thinsp;23.1 kg/m\u0026sup2;, dNLR-H\u0026thinsp;\u0026lt;\u0026thinsp;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.\u003c/p\u003e","manuscriptTitle":"Early intervention-oriented: a clinical predictive model for identifying the high risk of intra- abdominal hypertension in patients with traumatic brain injury","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-02-22 12:47:32","doi":"10.21203/rs.3.rs-8765814/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"338cb59e-513c-4a4e-95f5-ab7131ff6e52","owner":[],"postedDate":"February 22nd, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-03-17T10:57:14+00:00","versionOfRecord":[],"versionCreatedAt":"2026-02-22 12:47:32","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8765814","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8765814","identity":"rs-8765814","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}