Cushing’s sign and severe traumatic brain injury in children after blunt trauma: a nationwide retrospective cohort study in Japan

Yumoto, Tetsuya; Naito, Hiromichi; Yorifuji, Takashi; Maeyama, Hiroki; Kosaki, Yoshinori; Yamamoto, Hirotsugu; Tsukahara, Kohei; Osako, Takaaki; Nakao, Atsunori

doi:10.1136/bmjopen-2017-020781

Cited by 7 publications

(8 citation statements)

References 36 publications

(27 reference statements)

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“…Moreover, a low heart rate value was associated with neurosurgery. The association of a high blood pressure and a low heart rate known as the Cushing's reflex corresponds to the adaptive response of the brain to severe intracranial hypertension [ 19 , 20 ]. It has already been demonstrated that this reflex was a predictor for neurosurgery [ 21 ].…”

Section: Discussionmentioning

confidence: 99%

Machine learning-based prediction of emergency neurosurgery within 24 h after moderate to severe traumatic brain injury

et al. 2022

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Background Rapid referral of traumatic brain injury (TBI) patients requiring emergency neurosurgery to a specialized trauma center can significantly reduce morbidity and mortality. Currently, no model has been reported to predict the need for acute neurosurgery in severe to moderate TBI patients. This study aims to evaluate the performance of Machine Learning-based models to establish to predict the need for neurosurgery procedure within 24 h after moderate to severe TBI. Methods Retrospective multicenter cohort study using data from a national trauma registry (Traumabase®) from November 2011 to December 2020. Inclusion criteria correspond to patients over 18 years old with moderate or severe TBI (Glasgow coma score ≤ 12) during prehospital assessment. Patients who died within the first 24 h after hospital admission and secondary transfers were excluded. The population was divided into a train set (80% of patients) and a test set (20% of patients). Several approaches were used to define the best prognostic model (linear nearest neighbor or ensemble model). The Shapley Value was used to identify the most relevant pre-hospital variables for prediction. Results 2159 patients were included in the study. 914 patients (42%) required neurosurgical intervention within 24 h. The population was predominantly male (77%), young (median age 35 years [IQR 24–52]) with severe head injury (median GCS 6 [3–9]). Based on the evaluation of the predictive model on the test set, the logistic regression model had an AUC of 0.76. The best predictive model was obtained with the CatBoost technique (AUC 0.81). According to the Shapley values method, the most predictive variables in the CatBoost were a low initial Glasgow coma score, the regression of pupillary abnormality after osmotherapy, a high blood pressure and a low heart rate. Conclusion Machine learning-based models could predict the need for emergency neurosurgery within 24 h after moderate and severe head injury. Potential clinical benefits of such models as a decision-making tool deserve further assessment. The performance in real-life setting and the impact on clinical decision-making of the model requires workflow integration and prospective assessment.

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Section: Discussionmentioning

confidence: 99%

Machine learning-based prediction of emergency neurosurgery within 24 h after moderate to severe traumatic brain injury

et al. 2022

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“…TBI that induces neuronal cell death and cerebral edema may cause increased intracranial pressure (IICP) ( 19 ). Severe IICP is associated with hypertension and bradycardia, known as the Cushing triad, which impairs SI accuracy ( 20 , 21 ). Odom et al ( 15 ) reported a bimodal relationship between SBP and mortality in a TBI population.…”

Section: Discussionmentioning

confidence: 99%

Shock index, modified shock index, age shock index score, and reverse shock index multiplied by Glasgow Coma Scale predicting clinical outcomes in traumatic brain injury: Evidence from a 10-year analysis in a single center

et al. 2022

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ObjectivesEarly identification of traumatic brain injury (TBI) patients at a high risk of mortality is very important. This study aimed to compare the predictive accuracy of four scoring systems in TBI, including shock index (SI), modified shock index (MSI), age-adjusted shock index (ASI), and reverse shock index multiplied by the Glasgow Coma Scale (rSIG).Patients and methodsThis is a retrospective analysis of a registry from the Taipei Tzu Chi trauma database. Totally, 1,791 patients with TBI were included. We investigated the accuracy of four major shock indices for TBI mortality. In the subgroup analysis, we also analyzed the effects of age, injury mechanism, underlying diseases, TBI severity, and injury severity.ResultsThe predictive accuracy of rSIG was significantly higher than those of SI, MSI, and ASI in all the patients [area under the receiver operating characteristic curve (AUROC), 0.710 vs. 0.495 vs. 0.527 vs. 0.598], especially in the moderate/severe TBI (AUROC, 0.625 vs. 0.450 vs. 0.476 vs. 0.529) and isolated head injury populations (AUROC 0.689 vs. 0.472 vs. 0.504 vs. 0.587). In the subgroup analysis, the prediction accuracy of mortality of rSIG was better in TBI with major trauma [Injury Severity Score (ISS) ≥ 16], motor vehicle collisions, fall injury, and healthy and cardiovascular disease population. rSIG also had a better prediction effect, as compared to SI, MSI, and ASI, both in the non-geriatric (age < 65 years) and geriatric (age ≥ 65 years).ConclusionrSIG had a better prediction accuracy for mortality in the overall TBI population than SI, MSI, and ASI. Although rSIG have better accuracy than other indices (ROC values indicate poor to moderate accuracy), the further clinical studies are necessary to validate our results.

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“…These findings are similar to studies in people that assessed the ability of the Cushing reflex to predict impending brain herniation secondary to severe traumatic brain injury. [15][16][17] In human trauma patients, several multicenter retrospective cohort studies suggested that the Cushing reflex is a weak but important predictor of severe traumatic brain injury requiring immediate intervention in adults and children after severe blunt trauma. 15,16 Similarly, in this study, significantly higher SBP-HR in dogs with brain herniation compared to the control group highlights the nature of the Cushing reflex.…”

Section: Discussionmentioning

confidence: 99%

“…[15][16][17] In human trauma patients, several multicenter retrospective cohort studies suggested that the Cushing reflex is a weak but important predictor of severe traumatic brain injury requiring immediate intervention in adults and children after severe blunt trauma. 15,16 Similarly, in this study, significantly higher SBP-HR in dogs with brain herniation compared to the control group highlights the nature of the Cushing reflex. The most notable finding was that a higher SBP-HR with a cutoff value of >60 provides 90% specificity when diagnosing dogs with brain herniation.…”

Section: Discussionmentioning

confidence: 99%

Retrospective evaluation of the relationship between admission variables and brain herniation in dogs (2010–2019): 54 cases

Her

Yanke

Gerken

et al. 2021

J Vet Emergen Crit Care

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Cushing’s sign and severe traumatic brain injury in children after blunt trauma: a nationwide retrospective cohort study in Japan

Cited by 7 publications

References 36 publications

Machine learning-based prediction of emergency neurosurgery within 24 h after moderate to severe traumatic brain injury

Machine learning-based prediction of emergency neurosurgery within 24 h after moderate to severe traumatic brain injury

Shock index, modified shock index, age shock index score, and reverse shock index multiplied by Glasgow Coma Scale predicting clinical outcomes in traumatic brain injury: Evidence from a 10-year analysis in a single center

Retrospective evaluation of the relationship between admission variables and brain herniation in dogs (2010–2019): 54 cases

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