Deep Sedation in Traumatic Brain Injury Patients

Dexmedetomidine is Associated with Reduced In-Hospital Mortality Risk of Patients with Subarachnoid Hemorrhage Undergoing Surgery

BACKGROUND

Subarachnoid hemorrhage (SAH) is a severe neurologic event with high mortality. The choice of sedatives in SAH management may influence patient outcomes. This study aimed to investigate the association between sedatives and in-hospital mortality among patients with SAH.

METHODS

This study analyzed data from the MIMIC-IV database, and in-hospital mortality was the primary outcome. Key variables collected included sedatives, demographics, comorbidities, vital signs, laboratory tests, and severity scores. Univariate and multivariate logistic regression analyses were used to assess associations between sedative use and in-hospital mortality, with adjustments for confounding factors. Further stratified analyses explored the effects of dexmedetomidine across different patient subgroups, and mediation analysis evaluated the role of creatinine in the relationship between dexmedetomidine and mortality.

RESULTS

A total of 527 patients were included in this study, with 301 males. Compared with propofol and midazolam, the use of dexmedetomidine was significantly related to the reduction of in-hospital mortality in patients with SAH (odds ratio, 0.369; 95% confidence interval, 0.237-0.574; P < 0.001). After adjusting for variables such as demographics, comorbidities, and laboratory tests, dexmedetomidine remained associated with lower in-hospital mortality. In addition, our findings indicated that dexmedetomidine use was associated with a reduced risk of in-hospital mortality regardless of the presence of cerebrovascular disease. We discovered that creatinine acted as a mediator in the protective effect of dexmedetomidine on in-hospital mortality.

CONCLUSIONS

Dexmedetomidine is associated with significantly lower in-hospital mortality in patients with SAH. These findings underscore the importance of sedative choice for patients with SAH, suggesting that dexmedetomidine could enhance patient outcomes.

Predictive Modeling of Long-Term Care Needs in Traumatic Brain Injury Patients Using Machine Learning

BACKGROUND

Traumatic brain injury (TBI) research often focuses on mortality rates or functional recovery, yet the critical need for long-term care among patients dependent on institutional or Respiratory Care Ward (RCW) support remains underexplored. This study aims to address this gap by employing machine learning techniques to develop and validate predictive models that analyze the prognosis of this patient population.

METHOD

Retrospective data from electronic medical records at Chi Mei Medical Center, encompassing 2020 TBI patients admitted to the ICU between January 2016 and December 2021, were collected. A total of 44 features were included, utilizing four machine learning models and various feature combinations based on clinical significance and Spearman correlation coefficients. Predictive performance was evaluated using the area under the curve (AUC) of the receiver operating characteristic (ROC) curve and validated with the DeLong test and SHAP (SHapley Additive exPlanations) analysis.

RESULT

Notably, 236 patients (11.68%) were transferred to long-term care centers. XGBoost with 27 features achieved the highest AUC (0.823), followed by Random Forest with 11 features (0.817), and LightGBM with 44 features (0.813). The DeLong test revealed no significant differences among the best predictive models under various feature combinations. SHAP analysis illustrated a similar distribution of feature importance for the top 11 features in XGBoost, with 27 features, and Random Forest with 11 features.

CONCLUSIONS

Random Forest, with an 11-feature combination, provided clinically meaningful predictive capability, offering early insights into long-term care trends for TBI patients. This model supports proactive planning for institutional or RCW resources, addressing a critical yet often overlooked aspect of TBI care.

Traumatic brain injury in companion animals: Pathophysiology and treatment

Traumatic brain injuries (TBI) are common in dogs and cats that have sustained head trauma from a variety of causes. In moderate to severe TBI, damage from both the primary and secondary injuries can be life-threatening. TBI management may be further complicated by concurrent injuries in polytrauma patients. Thorough initial and serial examinations are key in detecting neurologic changes quickly and guiding treatment. Intensive treatments such as nursing care, fluid therapy, hyperosmolar agents, analgesia, sedation, anticonvulsants, oxygen supplementation, surgery, and rehabilitation may be employed in TBI management. Prognostication resources for an individual patient are limited and a perceived poor prognosis may worsen clinical outcomes. In this paper, we review the pathophysiology of TBI, identification, injury stratification and prognosis of patients with TBI as well as propose treatment and monitoring recommendations for companion animals based on severity of TBI.

Thromboelastometry-Based Prophylaxis for Venous Thromboembolism in the Acute Period Following Isolated Severe Traumatic Brain Injury

Objective

Traumatic brain injury (TBI) is an independent risk factor for venous thromboembolism (VTE). This study aimed to determine the optimal timing for initiating pharmacological thromboprophylaxis for VTE in patients with isolated severe TBI using rotational thromboelastometry (ROTEM).

Methods

This single-center observational study enrolled 115 patients aged 18-59 years with isolated severe TBI within the first 48 hours after injury.

Results

Using ROTEM data, we identified hypercoagulation due to an increase in clot density (MCF EXTEM >72), which was attributed to fibrinogen (MCF FIBTEM >25). From day 4, hypercoagulation occurred in 14.8% of the patients. By day 7, these changes were observed in 85.2% of patients. According to brain computed tomography findings, patients who received early VTE chemoprophylaxis on days 3-4 after severe TBI did not experience progression of hemorrhagic foci.

Conclusion

Our results emphasize the clinical significance of thromboelastometry in patients with isolated severe traumatic TBI. Anticoagulant prophylaxis started on 3-4 days after severe TBI was relatively safe, and most patients did not experience hemorrhagic foci progression. The data acquired in this study may enable the optimization of VTE chemoprophylactic approaches, thereby reducing the associated risks to patients.