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Clinical Nomogram Predicting Intracranial Injury in Pediatric Traumatic Brain Injury
Thara Tunthanathip1, Jarunee Duangsuwan2, Niwan Wattanakitrungroj2
1Division of Neurosurgery, Department of Surgery, Faculty of Medicine, Prince of Songkla University, Hat Yai, Thailand.
Insights
This study developed a clinical nomogram to predict intracranial injury in pediatric traumatic brain injury (TBI). The tool aids general practice by reducing unnecessary investigations with high specificity.
Area of Science:
- Pediatric Traumatology
- Neuroimaging Diagnostics
- Clinical Prediction Modeling
Background:
- Pediatric traumatic brain injury (TBI) presents varied injury mechanisms in developing nations.
- Unnecessary investigations for pediatric TBI are a concern in general practice.
- A validated clinical tool is needed to guide diagnostic decisions.
Purpose of the Study:
- To develop and validate a clinical nomogram for predicting intracranial injury in pediatric TBI.
- To assist general practitioners in balancing diagnostic investigations.
- To improve the accuracy of identifying significant intracranial injuries.
Main Methods:
- Retrospective analysis of 900 pediatric TBI patients (<15 years) in southern Thailand.
- Development of a nomogram using logistic regression on 80% of data.
- Validation of the nomogram using a separate 20% testing dataset.
Main Results:
- The nomogram incorporated age, road traffic accidents, loss of consciousness, scalp hematoma, motor weakness, basilar skull fracture signs, GCS score, and pupillary reflex.
- The nomogram achieved an accuracy of 0.83, with high specificity (1.00) and negative predictive value (0.81).
- Validation demonstrated the nomogram's effectiveness as a binary classifier.
Conclusions:
- A novel clinical nomogram for predicting intracranial injury in pediatric TBI has been developed.
- The nomogram serves as a valuable diagnostic aid in general practice.
- High specificity of the nomogram supports its role in reducing unnecessary investigations.
Background:
There are differences in injured mechanisms among pediatric traumatic brain injury (TBI) in developing countries. This study aimed to develop and validate clinical nomogram for predicting intracranial injury in pediatric TBI that will be implicated in balancing the unnecessary investigation in the general practice.
Materials And Methods:
The retrospective study was conducted in all patients who were younger than 15 years old and underwent computed tomography (CT) of the brain after TBI in southern Thailand. Injured mechanisms and clinical characteristics were identified and analyzed with binary logistic regression for predicting intracranial injury. Using random sampling without replacement, the total data was split into nomogram developing dataset (80%) and testing dataset (20%). Therefore, a nomogram was constructed and applied via the web-based application from the developing dataset. Using testing dataset, validation as binary classifiers was performed by various probabilities levels.
Results:
A total of 900 victims were enrolled. The mean age was 87.2 (standard deviation [SD] 57.4) months, and 65.3% of all patients injured were from road traffic accidents. The rate of positive findings in CT of the brain was 32.8%. A nomogram was developed from the significant variables, including age groups, road traffic accidents, loss of consciousness, scalp hematoma/laceration, motor weakness, signs of basilar skull fraction, low Glasgow Coma Scale score, and pupillary light reflex.Therefore, a nomogram was developed from 80% of data and was validated from 20% of data. The accuracy, sensitivity, specificity, positive, and negative predictive values of the nomogram were 0.83, 0.42, 1.00, 1.00, and 0.81 at a cutoff value of 0.5 probability.
Conclusion:
This study provides a clinical nomogram that will be applied to making decisions in general practice as a diagnostic tool from high specificity.
