Cargando…
Prediction of Mortality in Patients with Isolated Traumatic Subarachnoid Hemorrhage Using a Decision Tree Classifier: A Retrospective Analysis Based on a Trauma Registry System
Background: In contrast to patients with traumatic subarachnoid hemorrhage (tSAH) in the presence of other types of intracranial hemorrhage, the prognosis of patients with isolated tSAH is good. The incidence of mortality in these patients ranges from 0–2.5%. However, few data or predictive models a...
Autores principales: | , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2017
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5708059/ https://www.ncbi.nlm.nih.gov/pubmed/29165330 http://dx.doi.org/10.3390/ijerph14111420 |
_version_ | 1783282578083545088 |
---|---|
author | Rau, Cheng-Shyuan Wu, Shao-Chun Chien, Peng-Chen Kuo, Pao-Jen Chen, Yi-Chun Hsieh, Hsiao-Yun Hsieh, Ching-Hua |
author_facet | Rau, Cheng-Shyuan Wu, Shao-Chun Chien, Peng-Chen Kuo, Pao-Jen Chen, Yi-Chun Hsieh, Hsiao-Yun Hsieh, Ching-Hua |
author_sort | Rau, Cheng-Shyuan |
collection | PubMed |
description | Background: In contrast to patients with traumatic subarachnoid hemorrhage (tSAH) in the presence of other types of intracranial hemorrhage, the prognosis of patients with isolated tSAH is good. The incidence of mortality in these patients ranges from 0–2.5%. However, few data or predictive models are available for the identification of patients with a high mortality risk. In this study, we aimed to construct a model for mortality prediction using a decision tree (DT) algorithm, along with data obtained from a population-based trauma registry, in a Level 1 trauma center. Methods: Five hundred and forty-five patients with isolated tSAH, including 533 patients who survived and 12 who died, between January 2009 and December 2016, were allocated to training (n = 377) or test (n = 168) sets. Using the data on demographics and injury characteristics, as well as laboratory data of the patients, classification and regression tree (CART) analysis was performed based on the Gini impurity index, using the rpart function in the rpart package in R. Results: In this established DT model, three nodes (head Abbreviated Injury Scale (AIS) score ≤4, creatinine (Cr) <1.4 mg/dL, and age <76 years) were identified as important determinative variables in the prediction of mortality. Of the patients with isolated tSAH, 60% of those with a head AIS >4 died, as did the 57% of those with an AIS score ≤4, but Cr ≥1.4 and age ≥76 years. All patients who did not meet the above-mentioned criteria survived. With all the variables in the model, the DT achieved an accuracy of 97.9% (sensitivity of 90.9% and specificity of 98.1%) and 97.7% (sensitivity of 100% and specificity of 97.7%), for the training set and test set, respectively. Conclusions: The study established a DT model with three nodes (head AIS score ≤4, Cr <1.4, and age <76 years) to predict fatal outcomes in patients with isolated tSAH. The proposed decision-making algorithm may help identify patients with a high risk of mortality. |
format | Online Article Text |
id | pubmed-5708059 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-57080592017-12-05 Prediction of Mortality in Patients with Isolated Traumatic Subarachnoid Hemorrhage Using a Decision Tree Classifier: A Retrospective Analysis Based on a Trauma Registry System Rau, Cheng-Shyuan Wu, Shao-Chun Chien, Peng-Chen Kuo, Pao-Jen Chen, Yi-Chun Hsieh, Hsiao-Yun Hsieh, Ching-Hua Int J Environ Res Public Health Article Background: In contrast to patients with traumatic subarachnoid hemorrhage (tSAH) in the presence of other types of intracranial hemorrhage, the prognosis of patients with isolated tSAH is good. The incidence of mortality in these patients ranges from 0–2.5%. However, few data or predictive models are available for the identification of patients with a high mortality risk. In this study, we aimed to construct a model for mortality prediction using a decision tree (DT) algorithm, along with data obtained from a population-based trauma registry, in a Level 1 trauma center. Methods: Five hundred and forty-five patients with isolated tSAH, including 533 patients who survived and 12 who died, between January 2009 and December 2016, were allocated to training (n = 377) or test (n = 168) sets. Using the data on demographics and injury characteristics, as well as laboratory data of the patients, classification and regression tree (CART) analysis was performed based on the Gini impurity index, using the rpart function in the rpart package in R. Results: In this established DT model, three nodes (head Abbreviated Injury Scale (AIS) score ≤4, creatinine (Cr) <1.4 mg/dL, and age <76 years) were identified as important determinative variables in the prediction of mortality. Of the patients with isolated tSAH, 60% of those with a head AIS >4 died, as did the 57% of those with an AIS score ≤4, but Cr ≥1.4 and age ≥76 years. All patients who did not meet the above-mentioned criteria survived. With all the variables in the model, the DT achieved an accuracy of 97.9% (sensitivity of 90.9% and specificity of 98.1%) and 97.7% (sensitivity of 100% and specificity of 97.7%), for the training set and test set, respectively. Conclusions: The study established a DT model with three nodes (head AIS score ≤4, Cr <1.4, and age <76 years) to predict fatal outcomes in patients with isolated tSAH. The proposed decision-making algorithm may help identify patients with a high risk of mortality. MDPI 2017-11-22 2017-11 /pmc/articles/PMC5708059/ /pubmed/29165330 http://dx.doi.org/10.3390/ijerph14111420 Text en © 2017 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Rau, Cheng-Shyuan Wu, Shao-Chun Chien, Peng-Chen Kuo, Pao-Jen Chen, Yi-Chun Hsieh, Hsiao-Yun Hsieh, Ching-Hua Prediction of Mortality in Patients with Isolated Traumatic Subarachnoid Hemorrhage Using a Decision Tree Classifier: A Retrospective Analysis Based on a Trauma Registry System |
title | Prediction of Mortality in Patients with Isolated Traumatic Subarachnoid Hemorrhage Using a Decision Tree Classifier: A Retrospective Analysis Based on a Trauma Registry System |
title_full | Prediction of Mortality in Patients with Isolated Traumatic Subarachnoid Hemorrhage Using a Decision Tree Classifier: A Retrospective Analysis Based on a Trauma Registry System |
title_fullStr | Prediction of Mortality in Patients with Isolated Traumatic Subarachnoid Hemorrhage Using a Decision Tree Classifier: A Retrospective Analysis Based on a Trauma Registry System |
title_full_unstemmed | Prediction of Mortality in Patients with Isolated Traumatic Subarachnoid Hemorrhage Using a Decision Tree Classifier: A Retrospective Analysis Based on a Trauma Registry System |
title_short | Prediction of Mortality in Patients with Isolated Traumatic Subarachnoid Hemorrhage Using a Decision Tree Classifier: A Retrospective Analysis Based on a Trauma Registry System |
title_sort | prediction of mortality in patients with isolated traumatic subarachnoid hemorrhage using a decision tree classifier: a retrospective analysis based on a trauma registry system |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5708059/ https://www.ncbi.nlm.nih.gov/pubmed/29165330 http://dx.doi.org/10.3390/ijerph14111420 |
work_keys_str_mv | AT rauchengshyuan predictionofmortalityinpatientswithisolatedtraumaticsubarachnoidhemorrhageusingadecisiontreeclassifieraretrospectiveanalysisbasedonatraumaregistrysystem AT wushaochun predictionofmortalityinpatientswithisolatedtraumaticsubarachnoidhemorrhageusingadecisiontreeclassifieraretrospectiveanalysisbasedonatraumaregistrysystem AT chienpengchen predictionofmortalityinpatientswithisolatedtraumaticsubarachnoidhemorrhageusingadecisiontreeclassifieraretrospectiveanalysisbasedonatraumaregistrysystem AT kuopaojen predictionofmortalityinpatientswithisolatedtraumaticsubarachnoidhemorrhageusingadecisiontreeclassifieraretrospectiveanalysisbasedonatraumaregistrysystem AT chenyichun predictionofmortalityinpatientswithisolatedtraumaticsubarachnoidhemorrhageusingadecisiontreeclassifieraretrospectiveanalysisbasedonatraumaregistrysystem AT hsiehhsiaoyun predictionofmortalityinpatientswithisolatedtraumaticsubarachnoidhemorrhageusingadecisiontreeclassifieraretrospectiveanalysisbasedonatraumaregistrysystem AT hsiehchinghua predictionofmortalityinpatientswithisolatedtraumaticsubarachnoidhemorrhageusingadecisiontreeclassifieraretrospectiveanalysisbasedonatraumaregistrysystem |