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Clinical Nomogram Predicting Intracranial Injury in Pediatric Traumatic Brain Injury

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 investigat...

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Autores principales: Tunthanathip, Thara, Duangsuwan, Jarunee, Wattanakitrungroj, Niwan, Tongman, Sasiporn, Phuenpathom, Nakornchai
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Wolters Kluwer - Medknow 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8078639/
https://www.ncbi.nlm.nih.gov/pubmed/33936306
http://dx.doi.org/10.4103/jpn.JPN_11_20
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author Tunthanathip, Thara
Duangsuwan, Jarunee
Wattanakitrungroj, Niwan
Tongman, Sasiporn
Phuenpathom, Nakornchai
author_facet Tunthanathip, Thara
Duangsuwan, Jarunee
Wattanakitrungroj, Niwan
Tongman, Sasiporn
Phuenpathom, Nakornchai
author_sort Tunthanathip, Thara
collection PubMed
description 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.
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spelling pubmed-80786392021-04-30 Clinical Nomogram Predicting Intracranial Injury in Pediatric Traumatic Brain Injury Tunthanathip, Thara Duangsuwan, Jarunee Wattanakitrungroj, Niwan Tongman, Sasiporn Phuenpathom, Nakornchai J Pediatr Neurosci Original Article 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. Wolters Kluwer - Medknow 2020 2021-01-19 /pmc/articles/PMC8078639/ /pubmed/33936306 http://dx.doi.org/10.4103/jpn.JPN_11_20 Text en Copyright: © 2021 Journal of Pediatric Neurosciences https://creativecommons.org/licenses/by-nc-sa/4.0/This is an open access journal, and articles are distributed under the terms of the Creative Commons Attribution-NonCommercial-ShareAlike 4.0 License, which allows others to remix, tweak, and build upon the work non-commercially, as long as appropriate credit is given and the new creations are licensed under the identical terms.
spellingShingle Original Article
Tunthanathip, Thara
Duangsuwan, Jarunee
Wattanakitrungroj, Niwan
Tongman, Sasiporn
Phuenpathom, Nakornchai
Clinical Nomogram Predicting Intracranial Injury in Pediatric Traumatic Brain Injury
title Clinical Nomogram Predicting Intracranial Injury in Pediatric Traumatic Brain Injury
title_full Clinical Nomogram Predicting Intracranial Injury in Pediatric Traumatic Brain Injury
title_fullStr Clinical Nomogram Predicting Intracranial Injury in Pediatric Traumatic Brain Injury
title_full_unstemmed Clinical Nomogram Predicting Intracranial Injury in Pediatric Traumatic Brain Injury
title_short Clinical Nomogram Predicting Intracranial Injury in Pediatric Traumatic Brain Injury
title_sort clinical nomogram predicting intracranial injury in pediatric traumatic brain injury
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8078639/
https://www.ncbi.nlm.nih.gov/pubmed/33936306
http://dx.doi.org/10.4103/jpn.JPN_11_20
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