Dataset Information

Comparison of aneurysmal subarachnoid hemorrhage grading scores in patients with aneurysm clipping and coiling.

ABSTRACT: Past studies revealed the prognosis differed between aneurysmal subarachnoid hemorrhage (aSAH) patients with surgical clipping and endovascular coiling. We retrospectively reviewed aSAH patients in our institution to investigate the effectiveness of grading scores between two groups. In the surgical clipping group (n?=?349), VASOGRADE had a favorable performance for predicting delayed cerebral ischemia (DCI) (area under curve (AUC)?>?0.750), and had better results than clinical (World Federation of Neurosurgical Societies (WFNS), Hunt & Hess (HH) and radiological scores (modified Fisher Scale (mFS), Subarachnoid Hemorrhage Early Brain Edema Score) (P??0.750), and had better results than radiological scores (P??0.700, with better performance than mFS (P??0.750), and were better than the radiological scores (P?

SUBMITTER: Fang Y

PROVIDER: S-EPMC7280262 | biostudies-literature | 2020 Jun

REPOSITORIES: biostudies-literature

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Comparison of aneurysmal subarachnoid hemorrhage grading scores in patients with aneurysm clipping and coiling.

Fang Yuanjian Y Lu Jianan J Zheng Jingwei J Wu Haijian H Araujo Camila C Reis Cesar C Lenahan Cameron C Zhu Suijun S Chen Sheng S Zhang Jianmin J

Scientific reports 20200608 1

Past studies revealed the prognosis differed between aneurysmal subarachnoid hemorrhage (aSAH) patients with surgical clipping and endovascular coiling. We retrospectively reviewed aSAH patients in our institution to investigate the effectiveness of grading scores between two groups. In the surgical clipping group (n = 349), VASOGRADE had a favorable performance for predicting delayed cerebral ischemia (DCI) (area under curve (AUC) > 0.750), and had better results than clinical (World Federation ...[more]

PMID: 32513925

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Project description:Reliable prediction of outcomes of aneurysmal subarachnoid hemorrhage (aSAH) based on factors available at patient admission may support responsible allocation of resources as well as treatment decisions. Radiographic and clinical scoring systems may help clinicians estimate disease severity, but their predictive value is limited, especially in devising treatment strategies. In this study, we aimed to examine whether a machine learning (ML) approach using variables available on admission may improve outcome prediction in aSAH compared to established scoring systems. Combined clinical and radiographic features as well as standard scores (Hunt & Hess, WFNS, BNI, Fisher, and VASOGRADE) available on patient admission were analyzed using a consecutive single-center database of patients that presented with aSAH (n = 388). Different ML models (seven algorithms including three types of traditional generalized linear models, as well as a tree bosting algorithm, a support vector machine classifier (SVMC), a Naive Bayes (NB) classifier, and a multilayer perceptron (MLP) artificial neural net) were trained for single features, scores, and combined features with a random split into training and test sets (4:1 ratio), ten-fold cross-validation, and 50 shuffles. For combined features, feature importance was calculated. There was no difference in performance between traditional and other ML applications using traditional clinico-radiographic features. Also, no relevant difference was identified between a combined set of clinico-radiological features available on admission (highest AUC 0.78, tree boosting) and the best performing clinical score GCS (highest AUC 0.76, tree boosting). GCS and age were the most important variables for the feature combination. In this cohort of patients with aSAH, the performance of functional outcome prediction by machine learning techniques was comparable to traditional methods and established clinical scores. Future work is necessary to examine input variables other than traditional clinico-radiographic features and to evaluate whether a higher performance for outcome prediction in aSAH can be achieved.

Dataset Information

Comparison of aneurysmal subarachnoid hemorrhage grading scores in patients with aneurysm clipping and coiling.

Publications

Comparison of aneurysmal subarachnoid hemorrhage grading scores in patients with aneurysm clipping and coiling.

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