Risk Factors for Cerebral Infarction After Microsurgical Clipping of Hunt-Hess Grade 0–2 Single Intracranial Aneurysm: A Retrospective Study

Yang, Yibing; He, Kejun; Liu, Linfeng; Li, Fanying; Xie, Baoshu; Li, Feng

doi:10.1016/j.wneu.2022.11.124

Cited by 2 publications

(2 citation statements)

References 33 publications

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“…For patients with CA rupture and bleeding, if conventional conservative therapy is difficult to achieve a hemostatic effect, it is recommended to combine Hunt-Hess grading to decide whether to undergo surgery. Among them, grade I and II patients require immediate surgery, while > grade II patients need to decide whether to undergo surgery based on their condition after bleeding situation stabilizes, in order to minimize degree of damage caused by surgery to patients' body and brain tissue [17].…”

Section: Discussionmentioning

confidence: 99%

Clinical efficacy of early microsurgical clipping of tumor neck in the treatment of cerebral aneurysm rupture and bleeding and its impact on oxidative stress response and prognosis of patients

Zhenglou Chen,

Hongsheng Wang,

Min Xu

et al. 2024

Cell Mol Biol (Noisy-le-grand)

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Cerebral aneurysm can rupture a blood vessel and cause bleeding in the brain. Microsurgical clipping of the tumor neck has been reported to be effective in treating cerebral aneurysm rupture and bleeding. This research attempted to clarify the clinical efficacy of early microsurgical clipping of tumor neck for treating cerebral aneurysm rupture and bleeding, and its impact on the prognosis of patients. One hundred patients with cerebral aneurysm rupture and bleeding patients were treated. They were selected and divided into experimental group (n=25) and control group (n=25) according to surgical time. All patients underwent microsurgical clipping of tumor neck for therapy. The control group chose to undergo surgery 72 hours after the onset of cerebral aneurysm rupture and bleeding, while the experimental group chose to undergo complete surgery within 72 hours after the onset of cerebral aneurysm rupture and bleeding. Primary outcome measures were incidence of complications, cognitive function scores, prognosis, surgical indicators, oxidative stress response and quality of life. Results showed that compared to the control group, the incidence of complications in experimental group exhibited depletion (P<0.05), the prognosis in experimental group exhibited elevation (P<0.05), the hospitalization time in experimental group exhibited depletion (P<0.05), the nomination, abstraction, language, orientation, attention, delayed recall and visual and executive function scores and total scores in experimental group exhibited elevation (P<0.05), serum levels of oxidative stress-related indicators in experimental group exhibited depletion (P<0.05) and the quality of life in experimental group exhibited elevation (P<0.05). In conclusion, early microsurgical clipping of the tumor neck can reduce the risk of complications and cognitive impairment in patients with cerebral aneurysm rupture and bleeding.

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Section: Discussionmentioning

confidence: 99%

Clinical efficacy of early microsurgical clipping of tumor neck in the treatment of cerebral aneurysm rupture and bleeding and its impact on oxidative stress response and prognosis of patients

Zhenglou Chen,

Hongsheng Wang,

Min Xu

et al. 2024

Cell Mol Biol (Noisy-le-grand)

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“…However, relevant predictive factors for postoperative Hunt–Hess grading in patients are lacking before the IA intervention. Currently, the assessment heavily relies on the clinical experience of healthcare provider to determine the extent of neurological impairment in patients following the procedure ( 8 ). However, the accuracy and objectivity of these assessments may be influenced by subjective factors, limiting the precision of patient prognosis evaluation.…”

Section: Introductionmentioning

confidence: 99%

Deep learning and machine learning predictive models for neurological function after interventional embolization of intracranial aneurysms

Peng,

Wang,

Wen

et al. 2024

Front. Neurol.

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ObjectiveThe objective of this study is to develop a model to predicts the postoperative Hunt-Hess grade in patients with intracranial aneurysms by integrating radiomics and deep learning technologies, using preoperative CTA imaging data. Thereby assisting clinical decision-making and improving the assessment and prognosis of postoperative neurological function.MethodsThis retrospective study encompassed 101 patients who underwent aneurysm embolization surgery. 851 radiomic features were extracted from CTA images. 512 deep learning features are extracted from last layer of ResNet50 deep convolutional neural network model. The feature screening process pipeline encompassed intraclass correlation coefficient analysis, principal component analysis, U test, spearman correlation analysis, minimum redundancy maximum relevance algorithm and Lasso regression, to identify features most correlated with postoperative Hunt-Hess grading. In the model construction phase, three distinct models were constructed: radiomics feature-based model (RSM), deep learning feature-based model (DLM), and deep learning-radiomics feature fusion model (DLRSCM). The study also calculated the radiomics score and combined it with clinical data to construct a Nomogram for predictive modeling. DLM, RSM and DLRSCM model was constructed by 9 base algorithms and 1 ensemble learning algorithm – Stacking ensemble model. Model performance was evaluated based on the area under the Receiver Operating Characteristic (ROC) curve (AUC), Matthews Correlation Coefficient (MCC), calibration curves, and decision curves analysis.Results5 significant radiomic feature and 4 significant deep learning features were obtained through the feature selection process. These features were utilized for model construction. Bootstrap resampling method was used for internal validation of the models. In terms of model evaluation, the DLM model, the stacking ensemble algorithm results achieved an AUC of 0.959 and MCC of 0.815. In the RSM model, the stacking ensemble model AUC was 0.935 and MCC was 0.793. The stacking ensemble model in DLRSCM outperformed others, with an AUC of 0.968 and MCC of 0.820. Results indicated that the ANN performed optimally among all base models, while the stacked ensemble learning model exhibited the highest predictive performance.ConclusionThis study demonstrates that the combination of radiomics and deep learning is an effective approach to predict the postoperative Hunt-Hess grade in patients with intracranial aneurysms. This holds significant value in the early identification of postoperative neurological complications and in enhancing clinical decision-making.

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Risk Factors for Cerebral Infarction After Microsurgical Clipping of Hunt-Hess Grade 0–2 Single Intracranial Aneurysm: A Retrospective Study

Cited by 2 publications

References 33 publications

Clinical efficacy of early microsurgical clipping of tumor neck in the treatment of cerebral aneurysm rupture and bleeding and its impact on oxidative stress response and prognosis of patients

Clinical efficacy of early microsurgical clipping of tumor neck in the treatment of cerebral aneurysm rupture and bleeding and its impact on oxidative stress response and prognosis of patients

Deep learning and machine learning predictive models for neurological function after interventional embolization of intracranial aneurysms

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