ArticleWorld neurosurgery: X2024
The impact of selection bias in the treatment for ruptured anterior communicating artery aneurysms: different results or different patients?
Article in World neurosurgery: X, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper, 1 of them a synthesis that pooled it.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
1 citing paper in PubMed, 1 synthesis or guideline pooled it.
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Anterior communicating artery is one of the most frequent locations for the development of intracranial aneurysm. The availability and advances of different treatments modalities allows for case-specific selection, but potentially impacts our ability to assess equipoise among them. Objective: Investigate and compare clinical and morphological variables among surgical and endovascular treatment groups with ruptured anterior communicating artery aneurysms. Methods: Data from patients from a single university hospital treated for ruptured anterior communicating aneurysms after multidisciplinary discussion in a period from January 2009 to January 2020 were retrospectively reviewed. Demographics, clinical status, aneurysm morphologic features and in-hospital complications were registered for each treatment (endovascular coiling vs. microsurgical clipping). Clinical assessment was made from outpatient evaluation at 1-year follow-up. Results: A total of 119 patients was obtained adding surgical ( Conclusions: Despite similar clinical outcomes and rate of complications, morphological differences highlight the presence of a selection bias and high heterogeneity, which hampers inferential analysis when comparing both techniques.
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