Coagulopathy and Traumatic Brain Injury: Overview of New Diagnostic and Therapeutic Strategies

Transfusion biomaterials for hemostasis

Bleeding is a leading cause of trauma deaths and surgical complications. Excessive bleeding has traditionally been treated with the transfusion of donated blood. However, the complicated logistics of sourcing and storing donated blood increases the cost and reduces the accessibility of treatment, particularly as rates of blood donation decline. Advances in biomaterials for targeted drug delivery have presented the opportunity for alternative synthetic injectable hemostats. Among these leading technologies are lipid and polymeric particles and polymer platforms that bind to ligands present at wound sites and amplify hemostatic pathways. As leading hemostatic biomaterials advance toward clinical application, we review current preclinical research models and findings as well as future research directions for next-generation biomaterial injectable hemostatic technologies.

Developing practical machine learning survival models to identify high-risk patients for in-hospital mortality following traumatic brain injury

Machine learning (ML) offers precise predictions and could improve patient care, potentially replacing traditional scoring systems. A retrospective study at Emtiaz Hospital analyzed 3,180 traumatic brain injury (TBI) patients. Nineteen variables were assessed using ML algorithms to predict outcomes. Data preparation addressed missing values and balancing methods corrected imbalances. Model building involved training-test splits, survival analysis, and ML algorithms like Random Survival Forest (RSF) and Gradient Boosting. Feature importance was examined, with patient risk stratification guiding survival analysis. The best-performing model, RSF with ROS resampling, achieved the highest mean AUC of 0.80, the lowest IBS of 0.11, and IPCW c-index of 0.79, maintaining strong predictive ability over time. Top predictors for in-hospital mortality included age, GCS, pupil condition, PTT, IPH, and Rotterdam score, with high variations in predictive abilities over time. A risk stratification cut-off value of 63.34 separated patients into low and high-risk categories, with Kaplan-Meier curves showing significant survival differences. Our high-performing predictive model, built on first-day features, enables time-dependent risk assessment for tailored interventions and monitoring. Our study highlights the feasibility of AI tools in clinical settings, offering superior predictive accuracy and enhancing patient care for TBI cases.

Coagulopathy prediction in traumatic brain injury

Traumatic brain injury (TBI) represents a significant public health concern. Besides the initial primary injury, a defining point of TBI is causing secondary, delayed damage through inflammatory biochemical processes. Among the complications arising from this inflammatory response, coagulopathy emerges as a critical concern. With an overall prevalence of 32.7 %, TBI-induced coagulopathy significantly contributes to increased mortality rates and unfavorable patient outcomes, through its clinical manifestations, such as progressive hemorrhagic injury (PHI). This chapter investigates biomarkers capable of accurately detecting coagulopathy and PHI in TBI, evaluating their potential utility based on statistical evidence from various studies and exploring their possible association in the biochemical processes guiding or following TBI-induced coagulopathy. Notably, glucose emerges as a standout candidate, exhibiting a sensitivity of 91.5 % and specificity of 87.5 % for predicting coagulopathy. Furthermore, interleukin-33, with a sensitivity of 93.3 % and specificity of 66.7 %, and galectin-3, with a sensitivity of 67.7 % and specificity of 85.5 %, are promising for PHI. Despite these encouraging findings, significant efforts remain necessary to translate biomarker diagnostic utility into clinical practice effectively. Further research and validation studies are imperative to elucidate the intricate biochemical processes underlying TBI-induced coagulopathy and to refine the clinical application of biomarkers for improved patient management and outcomes in real-world settings.

A machine learning model to predict neurological deterioration after mild traumatic brain injury in older adults

Objective

Neurological deterioration after mild traumatic brain injury (TBI) has been recognized as a poor prognostic factor. Early detection of neurological deterioration would allow appropriate monitoring and timely therapeutic interventions to improve patient outcomes. In this study, we developed a machine learning model to predict the occurrence of neurological deterioration after mild TBI using information obtained on admission.

Methods

This was a retrospective cohort study of data from the Think FAST registry, a multicenter prospective observational study of elderly TBI patients in Japan. Patients with an admission Glasgow Coma Scale (GCS) score of 12 or below or who underwent surgical treatment immediately upon admission were excluded. Neurological deterioration was defined as a decrease of 2 or more points from a GCS score of 13 or more within 24 h of hospital admission. The model predictive accuracy was judged with the area under the receiver operating characteristic curve (AUROC) and the area under the precision-recall curve (AUPRC), and the Youden index was used to determine the cutoff value.

Results

A total of 421 of 721 patients registered in the Think FAST registry between December 2019 and May 2021 were included in our study, among whom 25 demonstrated neurological deterioration. Among several machine learning algorithms, eXtreme Gradient Boosting (XGBoost) demonstrated the highest predictive accuracy in cross-validation, with an AUROC of 0.81 (±0.07) and an AUPRC of 0.33 (±0.08). Through SHapley Additive exPlanations (SHAP) analysis, five important features (D-dimer, fibrinogen, acute subdural hematoma thickness, cerebral contusion size, and systolic blood pressure) were identified and used to construct a better performing model (cross-validation AUROC of 0.84 and AUPRC of 0.34; testing data AUROC of 0.77 and AUPRC of 0.19). At the cutoff value from the Youden index, the model showed a sensitivity, specificity, and positive predictive value of 60, 96, and 38%, respectively. When neurosurgeons attempted to predict neurological deterioration using the same testing data, their values were 20, 94, and 19%, respectively.

Conclusion

In this study, our predictive model showed an acceptable performance in detecting neurological deterioration after mild TBI. Further validation through prospective studies is necessary to confirm these results.

Development and validation of a nomogram for predicting mortality in patients with acute severe traumatic brain injury: A retrospective analysis

BACKGROUND

Recent evidence links the prognosis of traumatic brain injury (TBI) to various factors, including baseline clinical characteristics, TBI specifics, and neuroimaging outcomes. This study focuses on identifying risk factors for short-term survival in severe traumatic brain injury (sTBI) cases and developing a prognostic model.

METHODS

Analyzing 430 acute sTBI patients from January 2018 to December 2023 at the 904th Hospital's Neurosurgery Department, this retrospective case-control study separated patients into survival outcomes: 288 deceased and 142 survivors. It evaluated baseline, clinical, hematological, and radiological data to identify risk and protective factors through univariate and Lasso regression. A multivariate model was then formulated to pinpoint independent prognostic factors, assessing their relationships via Spearman's correlation. The model's accuracy was gauged using the Receiver Operating Characteristic (ROC) curve, with additional statistical analyses for quantitative factors and model effectiveness. Internal validation employed ROC, calibration curves, Decision Curve Analysis (DCA), and Clinical Impact Curves (CIC) to assess model discrimination, utility, and accuracy. The International Mission for Prognosis and Analysis of Clinical Trials in TBI (IMPACT) and Corticosteroid Randomization After Significant Head injury (CRASH) models were also compared through multivariate regression.

RESULTS

Factors like unilateral and bilateral pupillary non-reactivity at admission, the derived neutrophil to lymphocyte ratio (dNLR), platelet to lymphocyte ratio (PLR), D-dimer to fibrinogen ratio (DFR), infratentorial hematoma, and Helsinki CT score were identified as independent risk factors (OR > 1), whereas serum albumin emerged as a protective factor (OR < 1). The model showed superior predictive performance with an AUC of 0.955 and surpassed both IMPACT and CRASH models in predictive accuracy. Internal validation confirmed the model's high discriminative capability, clinical relevance, and effectiveness.

CONCLUSIONS

Short-term survival in sTBI is significantly influenced by factors such as pupillary response, dNLR, PLR, DFR, serum albumin levels, infratentorial hematoma occurrence, and Helsinki CT scores at admission. The developed nomogram accurately predicts sTBI outcomes, offering significant clinical utility.

Anesthesia for traumatic brain injury

PURPOSE OF REVIEW

Traumatic brain injury (TBI) presents complex clinical challenges, requiring a nuanced understanding of its pathophysiology and current management principles to improve patient outcomes. Anesthetists play a critical role in care and need to stay updated with recent evidence and trends to ensure high-quality treatment. The Brain Trauma Foundation Guidelines, last updated in 2016, have shown moderate adherence, and much of the current management relies on expert opinions. This literature review synthesizes the current evidence and provides insights into the role of anesthetists in TBI management.

RECENT FINDINGS

Recent literature has emphasized the importance of tailored anesthetic management principles in treating TBI, focusing on minimizing secondary brain injury during neurosurgical interventions or extracranial surgery. Emerging trends include individualized intracranial pressure approaches and multimodal neuromonitoring for comprehensive assessment of cerebral physiology.

SUMMARY

Anesthesia for TBI patients requires a comprehensive approach that balances anesthetic goals with the unique pathophysiological factors of brain injury. Despite recent research expanding our understanding, challenges remain in standardizing protocols and addressing individual patient response variability. Adherence to established management principles, personalized approaches, and ongoing research is crucial for improving the outcomes.

Traumatic Brain Injury in Patients under Anticoagulant Therapy: Review of Management in Emergency Department

The best management of patients who suffer from traumatic brain injury (TBI) while on oral anticoagulants is one of the most disputed problems of emergency services. Indeed, guidelines, clinical decision rules, and observational studies addressing this topic are scarce and conflicting. Moreover, relevant issues such as the specific treatment (and even definition) of mild TBI, rate of delayed intracranial injury, indications for neurosurgery, and anticoagulant modulation are largely empiric. We reviewed the most recent evidence on these topics and explored other clinically relevant aspects, such as the promising role of dosing brain biomarkers, the strategies to assess the extent of anticoagulation, and the indications of reversals and tranexamic acid administration, in cases of mild TBI or as a bridge to neurosurgery. The appropriate timing of anticoagulant resumption was also discussed. Finally, we obtained an insight into the economic burden of TBI in patients on oral anticoagulants, and future directions on the management of this subpopulation of TBI patients were proposed. In this article, at the end of each section, a "take home message" is stated.

Establishment and validation of a bad outcomes prediction model based on EEG and clinical parameters in prolonged disorder of consciousness

Objective

This study aimed to explore the electroencephalogram (EEG) indicators and clinical factors that may lead to poor prognosis in patients with prolonged disorder of consciousness (pDOC), and establish and verify a clinical predictive model based on these factors.

Methods

This study included 134 patients suffering from prolonged disorder of consciousness enrolled in our department of neurosurgery. We collected the data of sex, age, etiology, coma recovery scales (CRS-R) score, complications, blood routine, liver function, coagulation and other laboratory tests, resting EEG data and follow-up after discharge. These patients were divided into two groups: training set (n = 107) and verification set (n = 27). These patients were divided into a training set of 107 and a validation set of 27 for this study. Univariate and multivariate regression analysis were used to determine the factors affecting the poor prognosis of pDOC and to establish nomogram model. We use the receiver operating characteristic (ROC) and calibration curves to quantitatively test the effectiveness of the training set and the verification set. In order to further verify the clinical practical value of the model, we use decision curve analysis (DCA) to evaluate the model.

Result

The results from univariate and multivariate logistic regression analyses suggested that an increased frequency of occurrence microstate A, reduced CRS-R scores at the time of admission, the presence of episodes associated with paroxysmal sympathetic hyperactivity (PSH), and decreased fibrinogen levels all function as independent prognostic factors. These factors were used to construct the nomogram. The training and verification sets had areas under the curve of 0.854 and 0.920, respectively. Calibration curves and DCA demonstrated good model performance and significant clinical benefits in both sets.

Conclusion

This study is based on the use of clinically available and low-cost clinical indicators combined with EEG to construct a highly applicable and accurate model for predicting the adverse prognosis of patients with prolonged disorder of consciousness. It provides an objective and reliable tool for clinicians to evaluate the prognosis of prolonged disorder of consciousness, and helps clinicians to provide personalized clinical care and decision-making for patients with prolonged disorder of consciousness and their families.

Association of fibrinolysis phenotype with patient outcomes following traumatic brain injury

BACKGROUND

Impaired coagulation is associated with elevated risk of mortality in trauma patients. Prior studies have demonstrated increased mortality in patients with hyperfibrinolysis (HF) and fibrinolysis shutdown (SD). In addition, prior studies have demonstrated no effect of tranexamic acid (TXA) on fibrinolysis phenotypes. We examined the association of admission fibrinolysis phenotype with traumatic brain injury (TBI) patient outcomes.

METHODS

Data were extracted from a placebo-controlled multicenter clinical trial. Patients ≥15 years with TBI (Glasgow Coma Scale score, 3-12) and systolic blood pressure ≥90 mm Hg were randomized in the out-of-hospital setting to receive placebo bolus/placebo infusion (Placebo), 1 gram (g) TXA bolus/1 g TXA infusion (bolus maintenance [BM]); or 2 g TXA bolus/placebo infusion (bolus only [BO]). Fibrinolysis phenotypes on admission were determined by clot lysis at 30 minutes (LY30): SD, ≤0.8%; physiologic, 0.9% to 2.9%; HF, ≥3%. Logistic regression was used to control for age, sex, penetrating injury, Injury Severity Score, maximum head AIS, and TXA treatment group.

RESULTS

Seven hundred forty-seven patients met inclusion criteria. Fibrinolysis shutdown was the most common phenotype in all treatment groups and was associated with increased age, Injury Severity Score, and presence of intracranial hemorrhage (ICH). Inpatient mortality was 15.2% for SD and HF, and 10.6% for physiologic ( p = 0.49). No differences in mortality, disability rating scale at 6 months, acute kidney injury, acute respiratory distress syndrome, or multi-organ failure were noted between fibrinolysis phenotypes.

CONCLUSION

SD is the most common phenotype expressed in moderate to severe TBI. In TBI, there is no association between fibrinolysis phenotype and mortality or other major complications.

LEVEL OF EVIDENCE

Prognostic and Epidemiological; Level IV.

Effect of low fibrinogen level on in-hospital mortality and 6-month functional outcome of TBI patients, a single center experience

In patients affected by traumatic brain injury (TBI), hypofibrinogenemia within the initial hours of trauma can be expected due to vascular and inflammatory changes. In this study, we aimed to evaluate the effect of hypofibrinogenemia on the in-hospital mortality and 6-month functional outcomes of TBI patients, admitted to Rajaee Hospital, a referral trauma center in Shiraz, Iran. This study included all TBI patients admitted to our center who had no prior history of coagulopathy or any systemic disease, were alive on arrival, and had not received any blood product before admission. On admission, hospitalization, imaging, and 6-month follow-up information of included patients were extracted from the TBI registry database. The baseline characteristics of patients with fibrinogen levels of less than 150 mg/dL were compared with the cases with higher levels. To assess the effect of low fibrinogen levels on in-hospital mortality, a uni- and multivariate was conducted between those who died in hospital and survivors. Based on the 6-month GOSE score of patients, those with GOSE < 4 (unfavorable outcome) were compared with those with a favorable outcome. A total of 3049 patients (84.3% male, 15.7% female), with a mean age of 39.25 ± 18.87, met the eligibility criteria of this study. 494 patients had fibrinogen levels < 150 mg/dl, who were mostly younger and had lower average GCS scores in comparison to cases with higher fibrinogen levels. By comparison of the patients who died during hospitalization and survivors, it was shown that fibrinogen < 150 mg/dl is among the prognostic factors for in-hospital mortality (OR:1.75, CI: 1.32:2.34, P-value < 0.001), while the comparison between patients with the favorable and unfavorable functional outcome at 6-month follow-up, was not in favor of prognostic effect of low fibrinogen level (OR: 0.80, CI: 0.58: 1.11, P-value: 0.19). Hypofibrinogenemia is associated with in-hospital mortality of TBI patients, along with known factors such as higher age and lower initial GCS score. However, it is not among the prognostic factors of midterm functional outcome.

A Case of Ruptured Carotid Traumatic Blood Blister-like Aneurysm

Ruptured cerebral aneurysms that occur in the anterior wall of the internal carotid artery (ICA) are known as blood blister-like aneurysms (BBAs); they have been reported to account for 0.3% to 1% of all ruptured ICA aneurysms. In this report, we describe the treatment of an unusual traumatic BBA (tBBA) with high-flow bypass using a radial artery graft, which resulted in a favorable outcome. A 59-year-old female suffered from an acute epidural hematoma, traumatic subarachnoid hemorrhage, and traumatic carotid-cavernous sinus fistula (tCCF) after being involved in a motor vehicle accident. Her angiography results showed tCCF and a tBBA on the anterior wall of the right ICA. On the fourth day after injury, we found rebleeding from the tBBA and performed an emergency high-flow bypass using a radial artery graft with lesion trapping as a curative procedure for the tCCF and tBBA. Postoperatively, right abducens nerve palsy appeared, but no other neurological symptoms were noted; the patient was thereafter transferred to a rehabilitation hospital 49 days after injury. Traumatic ICA aneurysms commonly occur close to the anterior clinoid process, form within 1 to 2 weeks of injury, and often rupture around 2 weeks after trauma. This case was considered rare as the ICA was likely injured and bleeding at the time of injury, resulting in a form of tBBA; this allowed early detection and appropriate treatment that resulted in a good outcome.

Acute Haemostatic Depletion and Failure in Patients with Traumatic Brain Injury (TBI): Pathophysiological and Clinical Considerations

BACKGROUND

Because of the aging population, the number of low falls in elderly people with pre-existing anticoagulation is rising, often leading to traumatic brain injury (TBI) with a social and economic burden. Hemostatic disorders and disbalances seem to play a pivotal role in bleeding progression. Interrelationships between anticoagulatoric medication, coagulopathy, and bleeding progression seem to be a promising aim of therapy.

METHODS

We conducted a selective search of the literature in databases like Medline (Pubmed), Cochrane Library and current European treatment recommendations using relevant terms or their combination.

RESULTS

Patients with isolated TBI are at risk for developing coagulopathy in the clinical course. Pre-injury intake of anticoagulants is leading to a significant increase in coagulopathy, so every third patient with TBI in this population suffers from coagulopathy, leading to hemorrhagic progression and delayed traumatic intracranial hemorrhage. In an assessment of coagulopathy, viscoelastic tests such as TEG or ROTEM seem to be more beneficial than conventional coagulation assays alone, especially because of their timely and more specific gain of information about coagulopathy. Furthermore, results of point-of-care diagnostic make rapid "goal-directed therapy" possible with promising results in subgroups of patients with TBI.

CONCLUSIONS

The use of innovative technologies such as viscoelastic tests in the assessment of hemostatic disorders and implementation of treatment algorithms seem to be beneficial in patients with TBI, but further studies are needed to evaluate their impact on secondary brain injury and mortality.

Gender-related differences in the coagulofibrinolytic responses and long-term outcomes in patients with isolated traumatic brain injury: A 2-center retrospective study

Coagulation function differs by gender, with women being characterized as more hypercoagulable. Even in the early stages of trauma, women have been shown to be hypercoagulable. Several studies have also examined the relationship between gender and the prognosis of trauma patients, but no certain conclusions have been reached. Patients with isolated traumatic brain injury (iTBI) are known to have coagulopathy, but no previous studies have examined the gender differences in detail. This is a retrospective analysis of a prospective registry conducted at 2 centers. The study included adult patients with iTBI enrolled from April 2018 to March 2021. Coagulofibrinolytic markers were measured in each patient at 1 hour, 24 hours, 3 days, and 7 days after injury, and neurological outcomes were assessed with the Glasgow Outcome Scale Extended at 6 months. Subgroup analysis was also performed by categorizing patients into groups according to neurological prognosis or age at 50 years. Males (n = 31) and females (n = 21) were included in the analysis. In males, there was a significant difference in the levels of activated partial thromboplastin time (P = .007), fibrin/fibrinogen degradation products (P = .025), D-dimer (P = .034), α2-plasmin inhibitor (P = .030), plasmin-α2-plasmin inhibitor complex (P = .004) at 1 hour after injury between favorable and unfavorable long-term neurological outcome groups, while in females there was no significant difference in these markers between 2 groups. In the age group under 50 years, there were significant gender differences in fibrinogen (day 3: P = .018), fibrin/fibrinogen degradation products (1 hour: P = .037, day 3: P = .009, day 7: P = .037), D-dimer (day 3: P = .005, day 7: P = .010), plasminogen (day 3: P = .032, day 7: P = .032), and plasmin-α2-plasmin inhibitor complex (day 3: P = .001, day 7: P = .001), and these differences were not evident in the age group over 50 years. There were differences in coagulofibrinolytic markers depending on gender in patients with iTBI. In male patients, aggravation of coagulofibrinolytic markers immediately after traumatic brain injury may be associated with poor neurologic outcome 6 months after injury.

Hyperfibrinolysis and fibrinolysis shutdown in patients with traumatic brain injury

Traumatic brain injury (TBI) is associated with coagulation/fibrinolysis disorders. We retrospectively evaluated 61 TBI cases transported to hospital within 1 h post-injury. Levels of thrombin-antithrombin III complex (TAT), D-dimer, and plasminogen activator inhibitor-1 (PAI-1) were measured on arrival and 3 h, 6 h, 12 h, 1 day, 3 days and 7 days after injury. Multivariate logistic regression analysis was performed to identify prognostic factors for coagulation and fibrinolysis. Plasma TAT levels peaked at admission and decreased until 1 day after injury. Plasma D-dimer levels increased, peaking up to 3 h after injury, and decreasing up to 3 days after injury. Plasma PAI-1 levels increased up to 3 h after injury, the upward trend continuing until 6 h after injury, followed by a decrease until 3 days after injury. TAT, D-dimer, and PAI-1 were elevated in the acute phase of TBI in cases with poor outcome. Multivariate logistic regression analysis showed that D-dimer elevation from admission to 3 h after injury and PAI-1 elevation from 6 h to 1 day after injury were significant negative prognostic indicators. Post-TBI hypercoagulation, fibrinolysis, and fibrinolysis shutdown were activated consecutively. Hyperfibrinolysis immediately after injury and subsequent fibrinolysis shutdown were associated with poor outcome.

Neurointensive Care of Traumatic Brain Injury Patients Based on Coagulation and Fibrinolytic Parameter Monitoring

Coagulopathy, a common complication of traumatic brain injury (TBI), is characterized by a hypercoagulable state developing immediately after injury, with hyperfibrinolysis and bleeding tendency peaking 3 h after injury, followed by fibrinolysis shutdown. Reflecting this timeframe, the coagulation factor fibrinogen is first consumed and then degraded after TBI, its concentration rapidly decreasing by 3 h post-TBI. The fibrinolytic marker D-dimer reaches its maximum concentration at the same time. Hyperfibrinolysis in the acute phase of TBI is associated with poor prognosis via hematoma expansion. In the acute phase, the coagulation and fibrinolysis parameters must be monitored to determine the treatment strategy. The combination of D-dimer plasma level at admission and the level of consciousness upon arrival at the hospital can be used to predict the patients who will "talk and deteriorate." Fibrinogen and D-dimer levels should determine case selection and the amount of fresh frozen plasma required for transfusion. Surgery around 3 h after injury, when fibrinolysis and bleeding diathesis peak, should be avoided if possible. In recent years, attempts have been made to estimate the time of injury from the time course of coagulation and fibrinolysis parameter levels, which has been particularly useful in some cases of pediatric abusive head trauma patients.

Blood biomarkers for predicting coagulopathy occurrence in patients with traumatic brain injury: a systematic review

Purpose: The occurrence of coagulopathy in patients with traumatic brain injury (TBI) is related to severe complications. The authors performed the first systematic review to investigate whether biomarkers can predict the occurrence of hypocoagulopathy or progressive hemorrhagic injury in patients with TBI. Methods: The authors included studies that performed a receiver operating characteristics analysis for the biomarker and provided a clear value along with the respective sensitivity and specificity. Additionally, they attempted to classify each biomarker, taking into account its physiological role. Results: Twelve studies were included. All biomarkers were protein molecules, except in one study that examined the prognostic role of glucose. Copeptin had the highest sensitivity, and S100A12 had the highest specificity in predicting coagulopathy, while IL-33 had the highest sensitivity and GALECTIN-3 had the highest specificity in predicting progressive hemorrhagic injury. Conclusion: The study of the role of biomarkers in predicting the occurrence of coagulopathy in patients with TBI remains in its infancy.