Risk factor analysis and prediction model to establish recurrence or progression of non-functioning pituitary adenomas in men after transnasal sphenoidal surgery.

This paper aims to analyze the risk factors for the recurrence or progression of non-functioning pituitary adenomas (NFPAs) in male patients after transnasal sphenoidal surgery and to develop a predictive model for prognosis. Clinical and follow-up data of 126 male patients with NFPAs treated by transnasal sphenoidal surgery from January 2011 to January 2021 in Fuzhou 900th Hospital were retrospectively analyzed. Lasso regression analysis was used to screen the best predictors, and the predictors were further screened by multivariate logistic regression analysis, and the nomogram prediction model was constructed. The performance of the model was verified by three aspects: discrimination, calibration and clinical utility by using the consistency index (C-index), receiver operating characteristic curve (ROC), calibration curve, clinical decision curve (DCA) and Clinical impact curve (CIC). Out of 126 cases, 7 (5.56%) showed postoperative tumor recurrence, and 18 (14.29%) exhibited postoperative residual regrowth (progression). Age (P = 0.024), maximum tumor diameter (P < 0.001), modified Knosp grade (P < 0.001), resection extent (P < 0.001), Ki67 (P < 0.001), pressure symptom (P < 0.001), Pre-op hypopituitarism (P = 0.048), Post-op new hypopituitarism (P = 0.017) showed significant differences among the recurrence group, the progression group, and the alleviation group. Three independent risk factors (Ki67, modified Knosp grade, and resection extent) affecting postoperative remission were used to construct a predictive model for long-term postoperative failure to remit. The C-index of the nomogram model was 0.823, suggesting that the model had a high discriminatory power, and the AUC of the area under the ROC curve was 0.9[95% CI (0.843, 0.958)]. A nomogram prediction model based on modified Knosp grading (grades 3B-4), resection extent (partial resection), and Ki-67 (≥ 3%) predicts the recurrence or progression of NFPAs in men after transnasal sphenoidal surgery.

Predictive modeling of arginine vasopressin deficiency after transsphenoidal pituitary adenoma resection by using multiple machine learning algorithms.

This study aimed to predict arginine vasopressin deficiency (AVP-D) following transsphenoidal pituitary adenoma surgery using machine learning algorithms. We reviewed 452 cases from December 2013 to December 2023, analyzing clinical and imaging data. Key predictors of AVP-D included sex, tumor height, preoperative and postoperative changes in sellar diaphragm height and pituitary stalk length, preoperative ACTH levels, changes in ACTH levels, and preoperative cortisol levels. Six machine learning algorithms were tested: logistic regression (LR), support vector classification (SVC), random forest (RF), decision tree (DT), k-nearest neighbors (KNN), and extreme gradient boosting (XGBoost). After cross-validation and parameter optimization, the random forest model demonstrated the highest performance, with an accuracy (ACC) of 0.882 and an AUC of 0.96. The decision tree model followed, achieving an accuracy of 0.843 and an AUC of 0.95. Other models showed lower performance: LR had an ACC of 0.522 and an AUC of 0.54; SVC had an ACC of 0.647 and an AUC of 0.67; KNN achieved an ACC of 0.64 and an AUC of 0.70; and XGBoost had an ACC of 0.794 and an AUC of 0.91. The study found that a shorter preoperative pituitary stalk length, significant intraoperative stretching, and lower preoperative ACTH and cortisol levels were associated with a higher likelihood of developing AVP-D post-surgery.

Integrating large-scale single-cell RNA sequencing in central nervous system disease using self-supervised contrastive learning.

The central nervous system (CNS) comprises a diverse range of brain cell types with distinct functions and gene expression profiles. Although single-cell RNA sequencing (scRNA-seq) provides new insights into the brain cell atlases, integrating large-scale CNS scRNA-seq data still encounters challenges due to the complexity and heterogeneity among CNS cell types/subtypes. In this study, we introduce a self-supervised contrastive learning method, called scCM, for integrating large-scale CNS scRNA-seq data. scCM brings functionally related cells close together while simultaneously pushing apart dissimilar cells by comparing the variations of gene expression, effectively revealing the heterogeneous relationships within the CNS cell types/subtypes. The effectiveness of scCM is evaluated on 20 CNS datasets covering 4 species and 10 CNS diseases. Leveraging these strengths, we successfully integrate the collected human CNS datasets into a large-scale reference to annotate cell types and subtypes in neural tissues. Results demonstrate that scCM provides an accurate annotation, along with rich spatial information of cell state. In summary, scCM is a robust and promising method for integrating large-scale CNS scRNA-seq data, enabling researchers to gain insights into the cellular and molecular mechanisms underlying CNS functions and diseases.

Assessment of cerebrovascular alterations induced by inflammatory response and oxidative-nitrative stress after traumatic intracranial hypertension and a potential mitigation strategy.

The rapid perfusion of cerebral arteries leads to a significant increase in intracranial blood volume, exposing patients with traumatic brain injury to the risk of diffuse brain swelling or malignant brain herniation during decompressive craniectomy. The microcirculation and venous system are also involved in this process, but the precise mechanisms remain unclear. A physiological model of extremely high intracranial pressure was created in rats. This development triggered the TNF-α/NF-κB/iNOS axis in microglia, and released many inflammatory factors and reactive oxygen species/reactive nitrogen species, generating an excessive amount of peroxynitrite. Subsequently, the capillary wall cells especially pericytes exhibited severe degeneration and injury, the blood-brain barrier was disrupted, and a large number of blood cells were deposited within the microcirculation, resulting in a significant delay in the recovery of the microcirculation and venous blood flow compared to arterial flow, and this still persisted after decompressive craniectomy. Infliximab is a monoclonal antibody bound to TNF-α that effectively reduces the activity of TNF-α/NF-κB/iNOS axis. Treatment with Infliximab resulted in downregulation of inflammatory and oxidative-nitrative stress related factors, attenuation of capillary wall cells injury, and relative reduction of capillary hemostasis. These improved the delay in recovery of microcirculation and venous blood flow.

Intraventricular Shunt as a Treatment for Entrapped Temporal Horn After Removal of Ventricular Meningioma: A Report of Two Cases.

Entrapped temporal horn (ETH) is a complication following resection of ventricular trigone tumors. It is a special localized hydrocephalus. Obstruction of cerebrospinal fluid outflow following resection of ventricular trigone tumors leads to dilation of the temporal horn and the production of the local space-occupying effect. This article presents two cases of ETH following the resection of ventricular trigone tumors. Our Intraventricular shunt is an effective treatment that uses a T-connector to connect a reservoir with two catheters. We presented temporal-frontal horn shunt and trigone-front horn shunt. A patient presented with ETH shunt dependency. Our intraventricular shunt surgery achieved a good prognosis.

Analysis of MRI features and associated factors of the pituitary neuroendocrine tumor streaky sign.

OBJECTIVES: Observation of pituitary neuroendocrine tumors with streaky sign on MRI, analysis of their features on imaging and further investigation of the relationship between the direction of the streak sign and the direction of optimal tumor expansion. METHODS: The MR images of 237 patients with pituitary neuroendocrine tumors were retrospectively analyzed. The streaky-like high signal with a substantial length of more than 10 mm and obvious enhancement on T1WI was defined as the streaky sign. Finally, 66 patients were included in the study, comprising 33 patients with streaky sign pituitary neuroendocrine tumors and 33 randomly selected patients with non-streaky sign pituitary neuroendocrine tumors. The general condition of these 66 patients, the imaging features of the tumor, and the measurement and analysis of the direction of the streaky sign in relation to the direction of optimal tumor extension were observed and analyzed. RESULTS: On MRI, 85 streaky signs were observed. The average deviation between the direction angle of all the streaky signs and the optimal extension direction angle of the tumor was approximately 11°. The longest streaky sign angle was positively correlated with the optimal extension angle of the tumor, with a correlation coefficient of 0.967. CONCLUSION: The presence of a streaky sign of pituitary neuroendocrine tumors may indicate a dilated sinus or a small blood vessel. Its direction is highly consistent with the optimal extension direction of the tumor, which has a certain supporting effect on the long-distance growth of the tumor.

Adenomyosis Accompanied by Multiple Hemorrhagic Cerebral Infarction: A Case Report.

This study aims to present a case of uterine adenomyosis accompanied by multiple hemorrhagic cerebral infarctions (CIs), summarize therapeutic experiences based on the literature review, and improve the clinical diagnosis and treatment of multiple hemorrhagic CIs. This paper describes a 46-year-old female with a four-year history of uterine adenomyosis complicated by multiple hemorrhagic CIs. During treatment, elevated levels of D-dimer, CA-125, and severe anemia were observed. Following internal medicine treatment targeting uterine adenomyosis and hemorrhagic CIs, the cerebral hemorrhage gradually resolved. Women presenting with multiple CIs, particularly hemorrhagic ones, should be evaluated for the presence of gynecological diseases. Treating gynecological conditions may aid in the management of multiple CIs.

The Ang-(1-7)/MasR axis ameliorates neuroinflammation in hypothermic traumatic brain injury in mice by modulating phenotypic transformation of microglia.

The Ang-(1-7)/MasR axis is critically involved in treating several diseases; For example, Ang-(1-7) improves inflammatory response and neurological function after traumatic brain injury and inhibits post-inflammatory hypothermia. However, its function in traumatic brain injury (TBI) combined with seawater immersion hypothermia remains unclear. Here, we used a mice model of hypothermic TBI and a BV2 cell model of hypothermic inflammation to investigate whether the Ang-(1-7)/MasR axis is involved in ameliorating hypothermic TBI. Quantitative reverse transcription PCR, western blotting assay, and immunofluorescence assay were performed to confirm microglia polarization and cytokine regulation. Hematoxylin-eosin staining, Nissl staining, and immunohistochemical assay were conducted to assess the extent of hypothermic TBI-induced damage and the ameliorative effect of Ang-(1-7) in mice. An open field experiment and neurological function scoring with two approaches were used to assess the degree of recovery and prognosis in mice. After hypothermic TBI establishment in BV2 cells, the Ang-(1-7)/MasR axis induced phenotypic transformation of microglia from M1 to M2, inhibited IL-6 and IL-1ß release, and upregulated IL-4 and IL-10 levels. After hypothermic TBI development in mice, intraperitoneally administered Ang-(1-7) attenuated histological damage and promoted neurological recovery. These findings suggest that hypothermia exacerbates TBI-induced damage and that the Ang-(1-7)/MasR axis can ameliorate hypothermic TBI and directly affect prognosis.

The role of coagulopathy and subdural hematoma thickness at admission in predicting the prognoses of patients with severe traumatic brain injury: a multicenter retrospective cohort study from China.

BACKGROUND: Traumatic brain injury (TBI) is one of the diseases with high disability and mortality worldwide. Recent studies have shown that TBI-related factors may change the complex balance between bleeding and thrombosis, leading to coagulation disorders. The aim of this retrospective study was to investigate the prediction of coagulopathy and subdural hematoma thickness at admission using the Glasgow Outcome Scale (GOS) in patients with severe TBI at 6 months after discharge. METHODS: In this retrospective cohort study, a total of 1006 patients with severe TBI in large medical centers in three different provinces of China from June 2015 to June 2021 were enrolled after the exclusion criteria, and 800 patients who met the enrollment criteria were included. A receiver operating characteristic (ROC) curve was used to determine the best cut-off values of platelet (PLT), international normalized ratio (INR), activated partial thromboplastin time (APTT), and subdural hematoma (SDH) thickness. The ROC curve, nomogram, calibration curve, and the decision curve were used to evaluate the predictive effect of the coagulopathy and Coagulopathy-SDH(X1) models on the prognoses of patients with severe TBI, and the importance of predictive indicators was ranked by machine learning. RESULTS: Among the patients with severe TBI on admission, 576/800 (72%) had coagulopathy, 494/800 (61%) had SDH thickness ≥14.05 mm, and 385/800 (48%) had coagulopathy combined with SDH thickness ≥14.05 mm. Multivariate logistic regression analyses showed that age, pupil, brain herniation, WBC, CRP, SDH, coagulopathy, and X1 were independent prognostic factors for GOS after severe TBI. Compared with other single indicators, X1 as a predictor of the prognosis of severe TBI was more accurate. The GOS of patients with coagulopathy and thick SDH (X1, 1 point) at 6 months after discharge was significantly worse than that of patients with coagulopathy and thin SDH (X1, 2 points), patients without coagulopathy and thick SDH (X1, 3 point), and patients without coagulopathy and thin SDH (X1, 4 points). In the training group, the C-index based on the coagulopathy nomogram was 0.900. The C-index of the X1-based nomogram was 0.912. In the validation group, the C-index based on the coagulopathy nomogram was 0.858. The C-index of the X1-based nomogram was 0.877. Decision curve analysis also confirmed that the X1-based model had a higher clinical net benefit of GOS at 6 months after discharge than the coagulopathy-based model in most cases, both in the training and validation groups. In addition, compared with the calibration curve based on the coagulopathy model, the prediction of the X1 model-based calibration curve for the probability of GOS at 6 months after discharge showed better agreement with actual observations. Machine learning compared the importance of each independent influencing factor in the evaluation of GOS prediction after TBI, with results showing that the importance of X1 was better than that of coagulopathy alone. CONCLUSION: Coagulopathy combined with SDH thickness could be used as a new, accurate, and objective clinical predictor, and X1, based on combining coagulopathy with SDH thickness could be used to improve the accuracy of GOS prediction in patients with TBI, 6 months after discharge.

The Effect of Dexamethasone on Neuroinflammation and Cerebral Edema in Rats With Traumatic Brain Injury Combined With Seawater Drowning.

OBJECTIVE: To investigate the effect and mechanism of dexamethasone (DX) on axonal injury after traumatic brain injury (TBI) combined with seawater drowning (SWD) in rats. METHODS: To gain an in-depth understanding of TBI + SWD in rats, we established the compound injury model of rats by the Marmarou method and intratracheal pumping of seawater to simulate the pathological conditions. Rats in the DX group received intraperitoneal injections of DX (1 mg/kg) immediately after injury, and rats in the sham group and TBI + SWD group received intraperitoneal injections of the same amount of normal saline. RESULTS: Hematoxylin-eosin (HE) showed that DX improved matrix looseness, cell swelling, and nuclear condensation 168 hours after injury. Immunohistochemistry (IHC) staining showed that the protein expression of AQP4 was decreased in the DX group compared with the TBI + SWD group from 12 hours to 168 hours after injury. DX decreased the modified neurological severity score (mNSS) significantly at 24 hours and 168 hours after injury (P < 0.05). At 72 h and 168 h after injury, DX significantly lowered the expressions of IL-8 and TNF-α (P < 0.05). CONCLUSION: DX may play a neuroprotective role by reducing cerebral edema and inflammatory response after TBI + SWD injury in rats.

Incidence, risk factors, and clinical outcomes of acute brain swelling associated with traumatic acute subdural hematoma: a retrospective study utilizing novel diagnostic criteria.

Background: Post-traumatic acute brain swelling (ABS) is a major cause of elevated intracranial pressure and thus mortality. The current definition of post-traumatic ABS has certain limitations, and there is limited information available regarding ABS associated with traumatic acute subdural hematoma (ASDH). Objectives: To investigate the incidence, risk factors, and clinical outcomes of ABS associated with traumatic ASDH. Design: Retrospective study. Methods: Data for 161 patients diagnosed with traumatic ASDH were retrospectively collected. Novel computed tomography-based criteria were proposed for diagnosing ABS in patients with ASDH and determining its incidence. Univariate and multivariate logistic regression analyses were performed to explore the risk factors of post-traumatic ABS. The Glasgow Outcome Scale (GOS) score, mortality, and functional prognosis of all patients at discharge and the proportion of intraoperative malignant brain bulge in surgical patients were taken as clinical outcome measures. Results: A total of 45 (28%) patients experienced post-traumatic ABS, exhibiting significantly lower Glasgow Coma Scale scores on admission (p < 0.001). The incidence of hemispheric and whole-brain swelling was 8.1% and 19.9%, respectively. Risk factors independently associated with post-traumatic ABS were: (1) age [odds ratio (OR) = 0.917, p < 0.001]; (2) platelet to white blood cell ratio (PWR) (OR = 0.887, p = 0.012); and (3) traumatic subarachnoid hemorrhage (SAH) (OR = 4.346, p = 0.005). The ABS cohort had a lower GOS score [2 (1-3) versus 4 (3-5); p < 0.001], higher mortality (46.7% versus 6.9%; p < 0.001), and higher proportion of unfavorable functional prognosis (75.6% versus 34.5%; p < 0.001) upon discharge compared to the no ABS cohort, along with higher proportion of intraoperative malignant brain bulge (43.8% versus 0%; p < 0.001). Conclusion: The incidence of ABS associated with ASDH is significantly high overall. Patients with ASDH who have young age, low PWR, and traumatic SAH are at an increased risk of developing post-traumatic ABS, and therefore of poor clinical outcomes.

TAK-3 Inhibits Lipopolysaccharide-Induced Neuroinflammation in Traumatic Brain Injury Rats Through the TLR-4/NF-κB Pathway.

Purpose: The activation of the inflammatory response is regarded as a pivotal factor in the pathogenesis of TBI. Central nervous system infection often leads to the exacerbation of neuroinflammation following TBI, primarily caused by Gram-negative bacteria. This study aims to elucidate the effects of the novel anti-inflammatory drug TAK-3 on LPS-induced neuroinflammation in TBI rats. Methods: In conjunction with the rat controlled cortical impact model, we administered local injections of Lipopolysaccharide to the impact site. Subsequently, interventions were implemented through intraperitoneal injections of TAK-3 and NF-κB activitor2 to modulate the TLR4/NF-κB axis The impact of LPS on neurological function was assessed using mNSS, open field test, and brain water content measurement. Inflammatory markers, including TNF-α, IL-1ß, IL-6 and IL-10 were assessed to evaluate the condition of neuritis by Elisa. The activation of the TLR-4/NF-κB signaling pathway was detected by immunofluorescence staining and Western blot to assess the anti-inflammatory effects of TAK-3. Results: The administration of LPS exacerbated neurological damage in rats with TBI, as evidenced by a reduction in motor activity and an increase in anxiety-like behavior. Furthermore, LPS induced disruption of the blood-brain barrier integrity and facilitated the development of brain edema. The activation of microglia and astrocytes by LPS at the cellular and molecular levels has been demonstrated to induce a significant upregulation of neuroinflammatory factors. The injection of TAK-3 attenuated the neuroinflammatory response induced by LPS. Conclusion: The present study highlights the exacerbating effects of LPS on neuroinflammation in TBI through activation of the TLR-4/NF-κB signaling pathway. TAK-3 can modulate the activity of this signaling axis, thereby attenuating neuroinflammation and ultimately reducing brain tissue damage.

Predictive value of cyst/tumor volume ratio of pituitary adenoma for tumor cell proliferation.

BACKGROUND: MRI has been widely used to predict the preoperative proliferative potential of pituitary adenoma (PA). However, the relationship between the cyst/tumor volume ratio (C/T ratio) and the proliferative potential of PA has not been reported. Herein, we determined the predictive value of the C/T ratio of PA for tumor cell proliferation. METHODS: The clinical data of 72 patients with PA and cystic change on MRI were retrospectively analyzed. PA volume, cyst volume, and C/T ratio were calculated. The corresponding intraoperative specimens were collected. Immunohistochemistry and hematoxylin-eosin staining were performed to evaluate the Ki67 index and nuclear atypia. Patients were categorized according to the Ki67 index (< 3% and ≥ 3%) and nuclear atypia (absence and presence). Univariate and multivariate analyses were used to identify the significant predictors of the Ki67 index and nuclear atypia. The receiver operating characteristic curve assessed the prediction ability of the significant predictors. RESULTS: Larger tumor volumes, smaller cyst volumes, and lower C/T ratios were found in patients with higher Ki67 indexes and those with nuclear atypia (P < 0.05). C/T ratio was an independent predictor of the Ki67 index (odds ratio = 0.010, 95% confidence interval = 0.000-0.462) and nuclear atypia (odds ratio = 0.010, 95% confidence interval = 0.000-0.250). The predictive value of the C/T ratio did not differ significantly from that of tumor volume (P > 0.05) but was better than that of cyst volume (P < 0.05). The area under the curve of the C/T ratio for predicting the Ki67 index and nuclear atypia was larger than that for predicting cyst volume and tumor volume. CONCLUSIONS: C/T ratios can be used to predict PA tumor proliferation preoperatively. Our findings may facilitate the selection of surgery timing and the efficacy evaluation of surgery.

Rathke's Cleft Cyst Leads to Stunted Growth in Children: A Case Report Written With the Help of ChatGPT.

In recent times, ChatGPT has become a globally renowned AI tool, revolutionizing academic research by offering innovative methods and opportunities. The integration of AI into various domains is a prevailing topic, focusing on optimizing its utility. This article presents a case study of a child with Rathke's cyst, primarily exhibiting symptoms of growth and developmental delay. The patient's self-perception of stunted growth, coupled with previous assessments indicating partial growth hormone deficiency, prompted further investigation. Laboratory assessments revealed low growth hormone and insulin-like growth factor levels, while imaging disclosed a pituitary lesion. Rathke's cyst was postulated as the probable cause of the growth hormone deficiency. Rathke's cyst remains a rare medical condition with substantial research knowledge gaps. In this article, we synergize ChatGPT responses with a comprehensive case report of a child with Rathke's cyst as the primary symptom-growth and developmental delay. We explore the methods and feasibility of employing ChatGPT within this case report.

MRI 3D SPACE T2WI for Pituitary Adenoma Cavernous Sinus Invasion Diagnosis.

OBJECTIVE: This study aims to assess the utility of magnetic resonance imaging (MRI) 3D SPACE T2-weighted imaging (T2WI) sequences in evaluating cavernous sinus invasion by pituitary adenomas. METHODS: Data were collected from patients who underwent continuous pituitary MRIexaminations at the Medical Imaging Center of our hospital from October 2019 to February 2021. Eligible cases were evaluated for sagittal and axial T1WI sequences, coronal 3D SPACE T2WI sequences, and sagittal and coronal enhanced T1-weighted imaging (T1WI) sequences using the INFINITT PACS workstation. The Wilcoxon signed-rank test for paired samples and the Mann-Whitney U test for 2 independent samples were used to statistically analyze differences in image quality scores among various groups. In addition, the sensitivity, specificity, positive predictive value, and negative predictive value of each observation index were compared with intraoperative results. RESULTS: 3D SPACE T2WI showed superior cavernous sinus imaging quality compared with contrast enhanced T1WI and T2WI plain scans (P < 0.05). The sensitivity, specificity, positive predictive value, and negative predictive value were 100%, 90.0%, 55.60%, and 100.0%, respectively. The accuracy for pituitary adenoma invasiveness diagnosis based on cavernous sinus medial wall integrity was 94.40%. CONCLUSIONS: The imaging quality of the medial wall of the cavernous sinus on the 3D SPACE T2WI plain scan sequence surpassed that of contrast enhanced T1WI TSE-enhanced scans and T2WI TSE plain scans. The continuous observation of the medial wall of the cavernous sinus using this sequence holds great diagnostic value for assessing cavernous sinus invasion by pituitary adenomas. This strategy is more reliable than traditional MRI observation indicators.

A dynamic nomogram for predicting intraoperative brain bulge during decompressive craniectomy in patients with traumatic brain injury: a retrospective study.

OBJECTIVE: The aim of this paper is to investigate the risk factors associated with intraoperative brain bulge (IOBB), especially the computed tomography (CT) value of the diseased lateral transverse sinus, and to develop a reliable predictive model to alert neurosurgeons to the possibility of IOBB. METHODS: A retrospective analysis was performed on 937 patients undergoing traumatic decompressive craniectomy. A total of 644 patients from Fuzong Clinical Medical College of Fujian Medical University were included in the development cohort, and 293 patients from the First Affiliated Hospital of Shantou University Medical College were included in the external validation cohort. Univariate and multifactorial logistic regression analyses identified independent risk factors associated with IOBB. The logistic regression models consisted of independent risk factors, and receiver operating characteristic curves, calibration, and decision curve analyses were used to assess the performance of the models. Various machine learning models were used to compare with the logistic regression model and analyze the importance of the factors, which were eventually jointly developed into a dynamic nomogram for predicting IOBB and published online in the form of a simple calculator. RESULTS: IOBB occurred in 93/644 (14.4%) patients in the developmental cohort and 47/293 (16.0%) in the validation cohort. Univariate and multifactorial regression analyses showed that age, subdural hematoma, contralateral fracture, brain contusion, and CT value of the diseased lateral transverse sinus were associated with IOBB. A logistic regression model (full model) consisting of the above risk factors had excellent predictive power in both the development cohort [area under the curve (AUC)=0.930] and the validation cohort (AUC=0.913). Among the four machine learning models, the AdaBoost model showed the best predictive value (AUC=0.998). Factors in the AdaBoost model were ranked by importance and combined with the full model to create a dynamic nomogram for clinical application, which was published online as a practical and easy-to-use calculator. CONCLUSIONS: The CT value of the diseased lateral transverse is an independent risk factor and a reliable predictor of IOBB. The online dynamic nomogram formed by combining logistic regression analysis models and machine learning models can more accurately predict the possibility of IOBBs in patients undergoing traumatic decompressive craniectomy.