Severe Cerebral Vasospasm and Infarction After Minor Head Trauma

Interventional Treatment of Symptomatic Vasospasm in the Setting of Traumatic Brain Injury: A Systematic Review of Reported Cases

Traumatic subarachnoid hemorrhage (tSAH) is frequently comorbid with traumatic brain injury (TBI) and may induce secondary injury through vascular changes such as vasospasm and subsequent delayed cerebral ischemia (DCI). While aneurysmal SAH is well studied regarding vasospasm and DCI, less is known regarding tSAH and the prevalence of vasospasm and DCI, the consequences of vasospasm in this setting, when treatment is indicated, and which management strategies should be implemented. In this article, a systematic review of the literature that was conducted for cases of symptomatic vasospasm in patients with TBI is reported, association with tSAH is reported, risk factors for vasospasm and DCI are summarized, and commonalities in diagnosis and management are discussed. Clinical characteristics and treatment outcomes of 38 cases across 20 studies were identified in which patients with TBI with vasospasm underwent medical or endovascular management. Of the patients with data available for each category, the average age was 48.7 ± 20.3 years (n = 31), the Glasgow Coma Scale score at presentation was 10.6 ± 4.5 (n = 35), and 100% had tSAH (n = 29). Symptomatic vasospasm indicative of DCI was diagnosed on average at postinjury day 8.4 ± 3.0 days (n = 30). Of the patients, 56.6% (n = 30) had a new ischemic change associated with vasospasm confirming DCI. Treatment strategies are discussed, with 11 of 12 endovascularly treated and 19 of 26 medically treated patients surviving to discharge. tSAH is associated with vasospasm and DCI in moderate and severe TBI, and patients with clinical and radiographic evidence of symptomatic vasospasm and subsequent DCI may benefit from endovascular or medical management strategies.

Predictive role of shock index in the early formation of cerebral infarction in patients with TBI and cerebral herniation

Background and purpose

Traumatic brain injury (TBI) with brain herniation predisposes to posttraumatic cerebral infarction (PTCI), which in turn seriously affects the prognosis of patients. At present, there is a lack of effective indicators that can accurately predict the occurrence of PTCI. We aimed to find possible risk factors for the development of PTCI by comparing the preoperative and postoperative clinical data of TBI patients with brain herniation.

Methods

The clinical data of 120 patients with craniocerebral trauma and brain herniation were retrospectively analyzed. Among them, 54 patients had cerebral infarction within 3–7 days after injury. The two groups of patients were compared through univariate and multivariate logistic regression analysis, and a classification tree model and a nomogram model were constructed. Finally, receiver operating characteristic curve analysis and decision curve analysis were conducted to analyze the clinical utility of the prediction model.

Results

Logistic regression analysis showed that factors like the Glasgow Coma Scale (GCS) score (P = 0.002), subarachnoid hemorrhage (SAH) (P = 0.005), aspiration pneumonia (P < 0.001), decompressive craniectomy (P < 0.05), intracranial pressure (ICP) monitoring (P = 0.006), the shock index (SI) (P < 0.001), the mean arterial pressure (MAP) (P = 0.005), and blood glucose (GLU) (P < 0.011) appeared to show a significant statistical correlation with the occurrence of infarction (P < 0.05), while age, sex, body temperature (T), D-dimer levels, and coagulation tests were not significantly correlated with PTCI after cerebral herniation. Combined with the above factors, Classification and Regression Tree was established, and the recognition accuracy rate reached 76.67%.

Conclusions

GCS score at admission, no decompressive craniectomy, no ICP monitoring, combined SAH, combined aspiration pneumonia, SI, MAP, and high GLU were risk factors for infarction, of which SI was the primary predictor of PTCI in TBI with an area under the curve of 0.775 (95% CI = 0.689–0.861). Further large-scale studies are needed to confirm these results.