Associated Risks to the Treatment of Unruptured Intracranial Aneurysms (MARTA) Score: Development and External Validation.

Background And Objectives Unruptured intracranial aneurysms (UIAs) are increasingly detected and require careful management to prevent rupture. No externally validated score currently predicts procedural risk to guide treatment decisions. We developed and validated 2 predictive scores for complications after endovascular treatment (EVT) or neurosurgical treatment (NT) of UIA using routinely collected clinical and aneurysmal features.Methods We conducted a multicenter retrospective study including patients with UIA treated with EVT or NT across 15 neurovascular centers (2014-2024). Predictive models were built using multivariable logistic regression, with variables derived from Delphi consensus. The primary outcome was a composite safety end point: new neurological deficits, modified Rankin Scale (mRS) worsening (≥1 point or mRS 2-5 within 30 days), or procedural death. Internal validation used bootstrapping, and external validation was performed temporally and institutionally. Model performance was assessed using area under the receiver operating characteristic curve (AUROC) and calibration. Final scores, named Morbidity and Mortality Associated Risk in the Treatment of UIAs (MARTA)-EVT and MARTA-NT, were compared with existing models identified through systematic review.Results Among 2647 patients (1907 EVT and 740 NT), procedural complications occurred in 6.3% (EVT) and 12.8% (NT). Independent predictors included age, baseline mRS, aneurysm location, size, morphology, and procedural factors. MARTA-EVT (AUROC = 0.68, 95% CI = 0.57-0.78) and MARTA-NT (AUROC = 0.65, 95% CI = 0.54-0.77) showed moderate discrimination and good calibration. MARTA-EVT outperformed existing models; MARTA-NT performed similarly to SAFETEA. Predictive models are available open-source: https://martascoreapp.shinyapps.io/martascoreapp/.Conclusion MARTA-EVT and MARTA-NT are validated tools for predicting procedural risks in UIA treatment and may support patient counseling and clinical decision making.

Authors

Publication Details

Journal
Open Access CRIS of the University of Bern
Published
2026-01-14
DOI
https://doi.org/10.48620/94085
Primary Topic
Intracranial Aneurysms: Treatment and Complications
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Associated Risks to the Treatment of Unruptured Intracranial Aneurysms (MARTA) Score: Development and External Validation.

Ammad A. Baig, Andrea Salcuni, Matthias Gmeiner, Thomas Petutschnigg et al.
Open Access CRIS of the University of Bern
Intracranial Aneurysms: Treatment and Complications
article

Associated Risks to the Treatment of Unruptured Intracranial Aneurysms (MARTA) Score: Development and External Validation.

Ammad A. Baig, Andrea Salcuni, Matthias Gmeiner, Thomas Petutschnigg, Marta de Dios Lascuevas, Manuel Requena, Eytan Raz, Haydn Hoffman, Fady T. Charbel, Peter Vajkoczy, Vinay Jaikumar, N. Velinov, Adriano Bonura, Elia Manfrini, Ryan C. Ransom, Nicolas Khattar, Nico Stroh-Holly, Amina Sanchin, Francesco Diana, Vittorio Civelli, Michele Romoli, Fuat Arikan, Adam S Arthur, Bin Xu, David Hernandez, Erez Nossek, Hamzah Saei, Adnan H Siddiqui, Jan-Karl Burkhardt, Christopher M Nickele, Giuseppe Lanzino, Andreas Raabe, Charlotte Chung, Alejandro Tomasello, Ameer E Hassan, Pascal Jabbour, Simone Peschillo
article en

Abstract

Background And Objectives Unruptured intracranial aneurysms (UIAs) are increasingly detected and require careful management to prevent rupture. No externally validated score currently predicts procedural risk to guide treatment decisions. We developed and validated 2 predictive scores for complications after endovascular treatment (EVT) or neurosurgical treatment (NT) of UIA using routinely collected clinical and aneurysmal features.Methods We conducted a multicenter retrospective study including patients with UIA treated with EVT or NT across 15 neurovascular centers (2014-2024). Predictive models were built using multivariable logistic regression, with variables derived from Delphi consensus. The primary outcome was a composite safety end point: new neurological deficits, modified Rankin Scale (mRS) worsening (≥1 point or mRS 2-5 within 30 days), or procedural death. Internal validation used bootstrapping, and external validation was performed temporally and institutionally. Model performance was assessed using area under the receiver operating characteristic curve (AUROC) and calibration. Final scores, named Morbidity and Mortality Associated Risk in the Treatment of UIAs (MARTA)-EVT and MARTA-NT, were compared with existing models identified through systematic review.Results Among 2647 patients (1907 EVT and 740 NT), procedural complications occurred in 6.3% (EVT) and 12.8% (NT). Independent predictors included age, baseline mRS, aneurysm location, size, morphology, and procedural factors. MARTA-EVT (AUROC = 0.68, 95% CI = 0.57-0.78) and MARTA-NT (AUROC = 0.65, 95% CI = 0.54-0.77) showed moderate discrimination and good calibration. MARTA-EVT outperformed existing models; MARTA-NT performed similarly to SAFETEA. Predictive models are available open-source: https://martascoreapp.shinyapps.io/martascoreapp/.Conclusion MARTA-EVT and MARTA-NT are validated tools for predicting procedural risks in UIA treatment and may support patient counseling and clinical decision making.

Open Access CRIS of the University of Bern
Peace, Justice and strong institutions
Openalex Percentile: Top 77%
Intracranial Aneurysms: Treatment and Complications
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.