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

Incidence and mortality related risk factors in patients with severe traumatic brain injury: A meta‑analysis

The present study aimed to clarify the onset of traumatic brain injury (TBI) and identify mortality-related risk factors in patients with severe TBI, to enable the early identification of high-risk individuals and timely implementation of prevention and treatment strategies to minimize mortality rates. Comprehensive database searches were conducted across Web of Science, PubMed, CINAHL and EMBASE, covering publications from database inception until October 17, 2023. Search terms in English included 'head trauma', 'brain trauma', 'mortality', 'death' and 'risk factor'. In total, two independent researchers screened and extracted the data on mortality onset and associated risk factors in patients with severe TBI. Meta-analysis was performed using R 4.2.2. A total of 33 cohort studies, including 71,718 patients with severe TBI, were selected for meta-analysis. The data indicated an overall mortality rate of 27.8% (95%CI: 22.5-33.2%) from database inception until October 17, 2023. Subgroup analysis revealed a mortality rate of 25.2% (95%CI: 20.2-30.1%) in developed countries, compared with 38.0% (95%CI: 21.4-54.7%) in developing countries. Additionally, the mean age of deceased patients was significantly higher compared with that of survivors (41.53±16.47). Key risk factors found to be associated with mortality included anemia [relative risk (RR), 1.42; 95%CI, 1.04-1.93], diabetes mellitus (RR, 1.40; 95%CI, 1.00-1.96), coagulopathy (RR, 4.31; 95%CI, 2.31-8.05), shock (RR, 3.41; 95%CI, 2.31-5.04) and systolic blood pressure≤90 mmHg (RR, 2.32; 95%CI, 1.65-3.27). Furthermore, pre-hospital intubation (RR, 1.48; 95%CI, 1.13-1.92),hypotension (RR, 2.04; 95%CI: 1.58, 2.63), hypoxemia (RR, 1.42; 95%CI: 1.13, 1.79), subdural hemorrhage (RR, 1.99; 95%CI: 1.50, 2.62), subarachnoid hemorrhage (RR, 1.64; 95%CI: 1.09, 2.47) and subdural hematoma (SDH; RR, 1.50; 95%CI: 1.04, 2.17). was identified to be a significant risk factor during hospitalization treatment. These results suggest that various factors, such as age, anemia, diabetes, shock, hypotension, hypoxemia, trauma scores and brain injury types, can all contribute to mortality risk in patients with severe TBI. Addressing these risk factors will likely be important for reducing mortality in this patient population.

Gallic acid alleviates ferroptosis by negatively regulating APOC3 and improves nerve function deficit caused by traumatic brain injury

Traumatic brain injury (TBI) is more common than ever and is becoming a global public health issue. A variety of secondary brain injuries occur after TBI, including ferroptosis characterized by iron-dependent lipid peroxidation. Gallic acid is a kind of traditional Chinese medicine, which has many biological effects such as anti-inflammatory and antioxidant. We further investigated whether Gallic acid can improve the neurological impairment caused by ferroptosis after TBI by targeting APOC3. Weighted gene coexpression network analyses (WGCNA) and 3 kinds of machine-learning algorithms were used to find the potential biomarkers. Then the HERB database was used to select the Chinese herb that acted on the target gene APOC3. Finally, we selected Gallic acid as a drug targeting APOC3 and verified by Western blotting. The effect of Gallic acid on the improvement of neurological function was studied by Nissl staining and FJB staining. Finally, the effect of Gallic acid on the cognitive ability of TBI mice was explored through behavioral experiments. Gallic acid can inhibit the expression level of APOC3 and thus inhibit the level of ferroptosis after TBI. It can also reduce the degeneration of nerve tissue by inhibiting ferroptosis and improve the neurological function deficit. The behavioral experiment proved that Gallic acid can alleviate the behavioral cognitive impairment caused by TBI. Gallic acid can reduce ferroptosis by inhibiting APOC3, and then alleviate neurological impairment after TBI.

Biomechanical perspectives on traumatic brain injury in the elderly: a comprehensive review

Traumatic brain injuries (TBIs) pose a significant health concern among the elderly population, influenced by age-related physiological changes and the prevalence of neurodegenerative diseases. Understanding the biomechanical dimensions of TBIs in this demographic is vital for developing effective preventive strategies and optimizing clinical management. This comprehensive review explores the intricate biomechanics of TBIs in the elderly, integrating medical and aging studies, experimental biomechanics of head tissues, and numerical simulations. Research reveals that global brain atrophy in normal aging occurs at annual rates of -0.2% to -0.5%. In contrast, neurodegenerative diseases such as Alzheimer's, Parkinson's, and multiple sclerosis are associated with significantly higher rates of brain atrophy. These variations in atrophy rates underscore the importance of considering differing brain atrophy patterns when evaluating TBIs among the elderly. Experimental studies further demonstrate that age-related changes in the mechanical properties of critical head tissues increase vulnerability to head injuries. Numerical simulations provide insights into the biomechanical response of the aging brain to traumatic events, aiding in injury prediction and preventive strategy development tailored to the elderly. Biomechanical analysis is essential for understanding injury mechanisms and forms the basis for developing effective preventive strategies. By incorporating local atrophy and age-specific impact characteristics into biomechanical models, researchers can create targeted interventions to reduce the risk of head injuries in vulnerable populations. Future research should focus on refining these models and integrating clinical data to better predict outcomes and enhance preventive care. Advancements in this field promise to improve health outcomes and reduce injury risks for the aging population.

Online Dynamic Nomogram for Predicting 90-Day Prognosis of Patients With Primary Basal Ganglia Cerebral Hemorrhage After Microscopic Keyhole Craniotomy for Hematoma Removal

OBJECTIVE

Primary basal ganglia cerebral hemorrhage (PBGCH) is the most common type of hypertensive intracerebral hemorrhage. Microscopically removing the hematoma via keyhole or microbone window craniotomy remains the most common surgical method in many hospitals across China for treating cases of primary basal ganglia hemorrhage exceeding 30 mL. The aim of this study was to establish a new practical evaluation system based on preoperative clinical and imaging factors to predict the short-term prognosis of PBGCH after microscopic keyhole craniotomy for hematoma removal (MKCHR), providing a reference for clinicians and patients' families in deciding whether to proceed with surgery.

METHODS

A retrospective analysis was performed on 74 cases of PBGCH treated with MKCHR. Patient prognosis was assessed at 90 days postsurgery using the modified Rankin Scale. This study employed R software to conduct both univariate and multivariate logistic regression analyses aimed at identifying preoperative factors that influence short-term prognosis following MKCHR. Additionally, a web-based interactive nomogram was developed to forecast outcomes for PBGCH patients receiving MKCHR treatment. Model robustness was gauged using the concordance index (C-index) and receiver operating characteristic (ROC) curve. Internal validation involved bootstrap resampling and calibration. Clinical utility was assessed via decision curve analysis (DCA), clinical impact curve (CIC), and net reduction interventions (NRI).

RESULTS

Glasgow Coma Scale (GCS) score ≤ 6, hemorrhagic volume > 102 mL, brain herniation, age > 58 years (p < 0.05) were independent risk factors for poor prognosis after MKCHR. The online dynamic nomogram website is https://sjwkalg.shinyapps.io/DynNomapp/. The model's C-index and area under the ROC are both 0.899 (95% confidence interval [CI], 0.817-0.980). Following 1000 bootstrap resamples, the calibration curve indicates that the dynamic nomogram's predicted values closely match the observed values. The models of DCA, CIC, and NRI show good clinical application.

CONCLUSION

The online dynamic nomogram developed in this study demonstrates high predictive accuracy. This platform is characterized by its noninvasive and convenient nature, which facilitates the formulation of clinical treatment strategies. It offers a reliable data reference for preoperative surgical decision-making in patients with PBGCH, thereby aiming to achieve beneficial outcomes.

Risk factor analysis and predictive model construction for postoperative bleeding in early esophageal cancer

OBJECTIVE

A multivariate logistic regression model was developed to identify the risk factors for postoperative bleeding in patients undergoing endoscopic submucosal dissection (ESD) for early esophageal cancer.

METHODS

The clinical data of 258 patients with early esophageal cancer who received ESD in Jiujiang Number One People's Hospital from April 2019 to March 2022 were retrospectively analyzed. Patients with or without postoperative bleeding were included into a bleeding group and a control group, respectively, and general information with statistically significant difference between the two groups was included in the multivariate logistic regression model to screen the risk factors for postoperative bleeding in the patients. The risk factors were then used to construct a nomogram prediction model for postoperative bleeding, and internal (training set) and external (validation set) validation was performed.

RESULTS

(1) The incidence of post-ESD bleeding was 12.02% in the 258 patients with early esophageal cancer. (2) History of hypertension, lesion diameter, submucosal fibrosis, C-reactive protein (CRP), and albumin (ALB) were independent risk factors for postoperative bleeding after ESD in the patients (P<0.05). (3) The results of receiver operator characteristic curve (ROC) showed that the area under the curve (AUC) was 0.821 for the training set and 0.740 for the validation set. (4) The correction curve showed that the actual and predicted values of the training and validation sets were well fitted.

CONCLUSION

Hypertension history, lesion diameter, submucosal fibrosis, CRP, and ALB are risk factors for postoperative bleeding in patients with early esophageal cancer undergoing ESD. The nomograms established based on these factors has good predictive value for postoperative bleeding in these patients.

Platelet Contribution and Endothelial Activation and Stress Index-Potential Mortality Predictors in Traumatic Brain Injury

Coagulopathy and traumatic brain injury (TBI) are complexly intertwined. In isolated TBI, coagulopathy may contribute to hemorrhagic lesion development, progression, or recurrence, as it may lead to a particular pattern of coagulopathy called TBI-induced coagulopathy (TBI-IC). We performed a retrospective and descriptive evaluation of 63 patients admitted to the Emergency Clinical Hospital Bucharest with the diagnosis of moderate/severe brain injury. In addition to demographic data, all included patients had a complete paraclinical evaluation that included rotational thromboelastometric (ROTEM) blood-clot analysis. The platelet component (PLTEM) and the endotheliopathy activation and stress index score (EASIX) were calculated. These parameters were presented comparatively according to survival at 30 days and helped define the two study groups: survivors and non-survivors at 30 days. The contribution of platelets to clot strength is derived from maximum clot elasticity (MCE) and maximum clot firmness (MCF). MCE is defined as (MCF × 100)/(100 - MCF), and PLTEM is defined as EXTEM MCE-FIBTEM MCE. EASIX is a novel biomarker recently studied in TBI patients, calculated according to the following formula: lactate dehydrogenase (U/L) × creatinine (mg/dL)/platelets (109 cells/L). Regarding the demographic data, there were no significant differences between the survivors and non-survivors. All ROTEM parameters related to clot amplitude (A5, A10, A20, MCF in EXTEM and FIBTEM channels) were higher in the group of patients who survived. Also, PLTEM was decreased in the group of deceased patients (89.71 ± 22.86 vs. 132.3 ± 16.56 p < 0.0001). The cut-off point determined with the ROC curve is 114.10, with a sensitivity of 94.74% and a specificity of 93.18%, for the detection of the negative prognosis (death at 30 days). The EASIX score was significantly higher in the patients who survived the traumatic event, with a median difference value of 1.15 (p < 0.0001). The ROC analysis of this biomarker highlights a cut-off point of 2.12, with a sensitivity of 88.64% and a specificity of 94.74% (AUC = 0.95, p < 0.0001), for the prediction of mortality. The comparative analysis of the two studied markers was performed using the Cox proportional hazard ratio and highlighted the greater influence that PLTEM has on survival time (b value = -0.05, p < 0.0001) compared to EASIX (b value = 0.49, p = 0.0026). The present retrospective study indicates the potential of the TBI-IC reflecting parameters PLTEM and EASIX as markers of mortality prognosis. Larger prospective studies are needed to confirm their combined prognostic value and use in decision-making and reduction in the burden of disease by adequate allocation of resources in a personalized and timely manner.