Evidence map›Paper›PMID 36248366›Full record

ReviewFrontiers in surgery2022

Treatment of unruptured middle cerebral artery aneurysms: Systematic review in an attempt to perform a network meta-analysis.

Ignacio Arrese, Sergio García-García, Santiago Cepeda, Rosario Sarabia

Open access · goldAbstract readReview
In one paragraph

Review in Frontiers in surgery, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.4field-weighted citation impact, top 38% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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.

2 · The registry

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.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed, 3 citations in OpenAlex.

  1. Review
  2. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors at 1 institution in 1 country.

Ignacio ArreseNeurosurgery Department, Hospital Universitario Río Hortega, Valladolid, Spain.
Sergio García-GarcíaNeurosurgery Department, Hospital Universitario Río Hortega, Valladolid, Spain.
Santiago CepedaNeurosurgery Department, Hospital Universitario Río Hortega, Valladolid, Spain.
Rosario SarabiaNeurosurgery Department, Hospital Universitario Río Hortega, Valladolid, Spain.
Hospital Universitario Río Hortega · ES

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: Open surgical clipping has been generally considered the best treatment option for unruptured middle cerebral artery aneurysms (uMCAAs). However, this type of aneurysm is being treated endovascularly with the appearance of new devices. We have carried out a systematic review of randomized and quasi-experimental studies to conduct a network meta-analysis (NMA) to assess the safety and efficacy of the different treatment methods currently used in uMCAAs. Methods: The literature was searched by using PubMed and Google Scholar databases. Eligibility criteria were randomized or quasi-experimental studies including at least five cases per arm and reporting duration of follow-up and number of lost cases. The end points were: angiographic success, final neurological outcome, and the need for retreatments. Results: We could only analyze four quasi-experimental studies with 398 uMCAAs. All of them compared clipping vs. coiling. Clipping showed better results than coiling in all analyzed end points. We could not conduct the proposed NMA because of the absence of randomized or quasi-experimental studies. Instead, a systematic review is further discussed. Conclusions: There is an urgent need for comparative studies on the treatment of uMCAAs.

Indexed as

aneurysmendovascularnetwork meta-analysissurgerysystematic reviewunruptured

Identifiers

PMID36248366
PMCPMC9554213
OpenAlexW4297328971

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.