Validation of the Surgical Intervention for Traumatic Injury scale in the pediatric population

Predicting and improving outcome in severe pediatric traumatic brain injury

INTRODUCTION

Severe pediatric traumatic brain injury (spTBI), including abusive head trauma (AHT) in young children, is a major public health problem. Long-term consequences of spTBI include a large variety of physical, neurological, biological, cognitive, behavioral and social deficits and impairments.

AREAS COVERED

The present narrative review summarizes studies and reviews published from January 2019 to February 2024 on spTBI. Significant papers published before 2019 were also included. The article gives coverage to the causes of spTBI, its epidemiology and fatality rates; disparities, inequalities, and socioeconomic factors; critical care; outcomes; and interventions.

EXPERT OPINION

There are disparities between countries and according to socio-economic factors regarding causes, treatments and outcomes of spTBI. AHT has an overall poor outcome. Adherence to critical care guidelines is imperfect and the evidence-base of guidelines needs further investigations. Neuroimaging and biomarker predictors of outcomes is a rapidly evolving domain. Long-term cognitive, behavioral and psychosocial difficulties are the most prevalent and disabling. Their investigation should make a clear distinction between objective (clinical examination, cognitive tests, facts) and subjective measures (estimations using patient- and proxy-reported questionnaires), considering possible common source bias in reported difficulties. Family/caregiver-focused interventions, ecological approaches, and use of technology in delivery of interventions are recommended to improve long-term difficulties after spTBI.

Association of initial assessment variables and mortality in severe pediatric traumatic brain injury

Background

Predictive scales have been used to prognosticate long-term outcomes of traumatic brain injury (TBI), but gaps remain in predicting mortality using initial trauma resuscitation data. We sought to evaluate the association of clinical variables collected during the initial resuscitation of intubated pediatric severe patients with TBI with in-hospital mortality.

Methods

Intubated pediatric trauma patients <18 years with severe TBI (Glasgow coma scale (GCS) score ≤8) from January 2011 to December 2020 were included. Associations between initial trauma resuscitation variables (temperature, pulse, mean arterial blood pressure, GCS score, hemoglobin, international normalized ratio (INR), platelet count, oxygen saturation, end tidal carbon dioxide, blood glucose and pupillary response) and mortality were evaluated with multivariable logistic regression.

Results

Among 314 patients, median age was 5.5 years (interquartile range (IQR): 2.2-12.8), GCS score was 3 (IQR: 3-6), Head Abbreviated Injury Score (hAIS) was 4 (IQR: 3-5), and most had a severe (25-49) Injury Severity Score (ISS) (48.7%, 153/314). Overall mortality was 26.8%. GCS score, hAIS, ISS, INR, platelet count, and blood glucose were associated with in-hospital mortality (all p<0.05). As age and GCS score increased, the odds of mortality decreased. Each 1-point increase in GCS score was associated with a 35% decrease in odds of mortality. As hAIS, INR, and blood glucose increased, the odds of mortality increased. With each 1.0 unit increase in INR, the odds of mortality increased by 1427%.

Conclusions

Pediatric patients with severe TBI are at substantial risk for in-hospital mortality. Studies are needed to examine whether earlier interventions targeting specific parameters of INR and blood glucose impact mortality.

Development and validation of a Bayesian network predicting neurosurgical intervention after injury in children and adolescents

BACKGROUND

Timely surgical decompression improves functional outcomes and survival among children with traumatic brain injury and increased intracranial pressure. Previous scoring systems for identifying the need for surgical decompression after traumatic brain injury in children and adults have had several barriers to use. These barriers include the inability to generate a score with missing data, a requirement for radiographic imaging that may not be immediately available, and limited accuracy. To address these limitations, we developed a Bayesian network to predict the probability of neurosurgical intervention among injured children and adolescents (aged 1-18 years) using physical examination findings and injury characteristics observable at hospital arrival.

METHODS

We obtained patient, injury, transportation, resuscitation, and procedure characteristics from the 2017 to 2019 Trauma Quality Improvement Project database. We trained and validated a Bayesian network to predict the probability of a neurosurgical intervention, defined as undergoing a craniotomy, craniectomy, or intracranial pressure monitor placement. We evaluated model performance using the area under the receiver operating characteristic and calibration curves. We evaluated the percentage of contribution of each input for predicting neurosurgical intervention using relative mutual information (RMI).

RESULTS

The final model included four predictor variables, including the Glasgow Coma Scale score (RMI, 31.9%), pupillary response (RMI, 11.6%), mechanism of injury (RMI, 5.8%), and presence of prehospital cardiopulmonary resuscitation (RMI, 0.8%). The model achieved an area under the receiver operating characteristic curve of 0.90 (95% confidence interval [CI], 0.89-0.91) and had a calibration slope of 0.77 (95% CI, 0.29-1.26) with a y intercept of 0.05 (95% CI, -0.14 to 0.25).

CONCLUSION

We developed a Bayesian network that predicts neurosurgical intervention for all injured children using four factors immediately available on arrival. Compared with a binary threshold model, this probabilistic model may allow clinicians to stratify management strategies based on risk.

LEVEL OF EVIDENCE

Prognostic and Epidemiological; Level III.