Proposal of a Machine Learning Based Prognostic Score for Ruptured Microsurgically Treated Anterior Communicating Artery Aneurysms - read online free

Aug 5, 2026

Aneurysmal subarachnoid hemorrhage (aSAH) leads to substantial mortality and long-term disability, and rebleeding remains a critical threat, especially in anterior communicating artery (AcoA) aneurysms. This retrospective study examines preoperative and intraoperative variables in 50 patients treated with microsurgical clipping and uses machine learning for outcome prediction. Feature selection via MRMR and predictive modeling with LASSO linear models identify key predictors of Glasgow outcome score at discharge and 6-month follow-up, supporting a proposed AcoA prognostic score.

LanguageEnglish

CategoryHealthcare

FormatPDF

Pages15

Reading Time38 min

AccessFree to download

Abstract

Introduction

Epidemiology and outcomes in aSAH

Clinical importance of early aneurysm occlusion

Prevalence and rupture tendency of AcoA aneurysms

Materials and Methods

Results

Conclusions

POLITECNICO DI TORINO Repository ISTITUZIONALE Proposal of a Machine Learning Based Prognostic Score for Ruptured Microsurgically Treated Anterior Communicating Artery Aneurysms Original Proposal of a Machine Learning Based Prognostic Score for Ruptured Microsurgically Treated Anterior Communicating Artery Aneurysms / Minardi, Massimiliano; Bianconi, Andrea; Mesin, Luca; Salvati, Luca Francesco; Griva, Federico; Narducci, Alessandro. -In: JOURNAL OF CLINICAL MEDICINE. -ISSN 2077-0383. -14:2(2025), pp. 1-14.[10.3390/jcm14020578] Availability: This version is available at: 11583/2996718 since: 2025-01-21T07:33:51Z Publisher: MDPI Published DOI:10.3390/jcm14020578 Terms of use: This article is made available under terms and conditions as specified in the corresponding bibliographic description in the repository Publisher copyright (Article begins on next page) 17 February 2025 Article Proposal of a Machine Learning Based Prognostic Score for Ruptured Microsurgically Treated Anterior Communicating Artery Aneurysms Massimiliano Minardi 1, Andrea Bianconi 2,3, *, Luca Mesin 4, Luca Francesco Salvati 5, Federico Griva 6 and Alessandro Narducci 6 Received: 13 November 2024 Revised: 26 December 2024 Accepted: 14 January 2025 Published: 17 January 2025 Citation: Minardi, M.; Bianconi, A.; Mesin, L.; Salvati, L.F.; Griva, F.; Narducci, A. Proposal of a Machine Learning Based Prognostic Score for Ruptured Microsurgically Treated Anterior Communicating Artery Aneurysms. J. Clin. Med. 2025, 14, 578 . [https://doi.org/10.3390/](https://doi.org/10.3390/)[ ](https://doi.org/10.3390/)jcm14020578 Copyright: © 2025 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 ([https://creativecommons.org/](https://creativecommons.org/)[ ](https://creativecommons.org/)[licenses/by/4.0/](licenses/by/4.0/)) . 1 Neurosurgery, Santa Croce and Carle Hospital, 12100 Cuneo, Italy 2 Neurosurgery, IRCCS Policlinico S. Martino, 16132 Genova, Italy 3 Department of Neuroscience, Rehabilitation, Ophthalmology, Genetics and Maternal and Child Health (DINOGMI), University of Genoa, 16126 Genova, Italy 4 Department of Electronics and Telecommunications, Polytechnic University of Turin, 10129 Turin, Italy; luca.mesin@polito.it 5 Neurosurgery, Santa Corona Hospital, 17027 Pietra Ligure, Italy 6 Neurosurgery, San Giovanni Bosco Hospital, 10154 Turin, Italy * Correspondence: andrea.bianconi@edu.unito.it Abstract: Background: Aneurysmal subarachnoid hemorrhage (aSAH) carries significant mortality and disability rates, with rebleeding posing a grave risk, particularly in anterior communicating artery (AcoA) aneurysms. This retrospective study aims to analyze preoperative and intraoperative variables of patients with ruptured AcoA aneurysms, evaluating the association of these variables with patient outcomes using machine learning techniques, proposing a prognostic score. Materials and Methods: A retrospective study was conducted on 50 patients who underwent microsurgical clipping for a ruptured AcoA aneurysm at San Giovanni Bosco Hospital, Turin, Italy. The clinical and aneurysmal data—including clinical evaluations, risk factors, aneurysmal characteristics, and intraand postoperative details—were examined. The study population was analyzed using machine learning techniques such as the MRMR algorithm for feature selection, and the LASSO method was employed to construct linear predictive models based on these features. Results: The study cohort had a mean age of 54 years, with 26 female and 24 male patients. Temporary clipping of main vessels was performed in 96% of procedures, with a mean duration of 3.74 min. Postoperatively, the mean Intensive Care Unit (ICU) stay was 7.28 days, with 14% mortality at 30 days and 4% within the first week. At the six-month follow-up, 63% of discharged

FAQs

What problem does the proposed AcoA prognostic score address?

It targets prediction of patient outcomes after microsurgical clipping for ruptured AcoA aneurysms, where aSAH carries high mortality and rebleeding risk.

How were machine learning methods used in the study?

The study applied MRMR for feature selection and used LASSO to construct linear predictive models for Glasgow outcome score at discharge and at 6-month follow-up.

Which factors were reported as significant predictors of outcomes?

Preoperative factors including BNI score, Vasograde, and preoperative cerebral edema correlated with outcomes; intraoperative bleeding and prolonged temporary clipping durations (over 3 minutes) were also highlighted as important considerations.

Aug 5, 2026

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