Evidence map›Paper›PMID 39085721›Full record

ArticleNeurosurgical review2024

A mathematical model to predict "low-lying" posterior communicating artery aneurysms in neurosurgical practice.

Qianquan Ma, Lei Liu, Zhihao Song, Hongbo Wen, Kaihuan Li, Jingqi Chen, Weixin Zhang, Tao Huang, Yufeng Xu, Haoyu Li and 2 more

Abstract read
In one paragraph

Article in Neurosurgical review, 2024. 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
–field-weighted citation impact
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.

  1. Article
  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

12 authors.

Qianquan Ma *Department of Neurosurgery, Peking University Third Hospital, Peking University, Beijing, China.
Lei Liu *School of Mathematics and Statistics, Central South University, Changsha, Hunan, China.
Zhihao Song *Department of Neurosurgery, Xiangya Hospital, Central South University, Changsha, Hunan, China.
Hongbo WenDepartment of Neurosurgery, Yiyang Central Hospital, Yiyang, Hunan, China.
Kaihuan LiDepartment of Neurosurgery, Yiyang Central Hospital, Yiyang, Hunan, China.
Jingqi ChenDepartment of Neurosurgery, Yiyang Central Hospital, Yiyang, Hunan, China.
Weixin ZhangDepartment of Neurosurgery, Yiyang Central Hospital, Yiyang, Hunan, China.
Tao HuangDepartment of Neurosurgery, Yiyang Central Hospital, Yiyang, Hunan, China.
Yufeng XuSchool of Mathematics and Statistics, Central South University, Changsha, Hunan, China.
Haoyu LiDepartment of Neurosurgery, Xiangya Hospital, Central South University, Changsha, Hunan, China.
Ting LeiDepartment of Neurosurgery, Sanbo Brain Hospital, Capital medical university, Beijing, China.
Xuezhi SunDepartment of Neurosurgery, Yiyang Central Hospital, Yiyang, Hunan, China. sunxuezhi@163.com.

Funding

Clinical Medical Technology Innovation Guide Project of Hunan Province 2021SK52603
6 · The paper itself

Abstract

"Low-lying" posterior communicating artery (PCoA) aneurysms require great attention in surgical clipping due to their distinct anatomical characteristics. In this study, we propose an easy method to immediately recognize "low-lying" PCoA aneurysms in neurosurgical practice. A total of 89 cases with "low-lying" PCoA aneurysms were retrospectively analyzed. All patients underwent preoperative digital subtraction angiography (DSA) examinations and microsurgical clipping. Cases were classified into the "low-lying" and regular groups based on intraoperative findings. The distance- and angle-relevant parameters that reflected the relative location of the aneurysms and tortuosity of the internal carotid artery were measured using 3D-DSA images. The data were sequentially integrated into a mathematical analysis to obtain the prediction model. Finally, we proposed a novel mathematical formula to preoperatively predict the existence of "low-lying" PCoA aneurysms with great accuracy. Neurosurgeons might benefit from this model, which enables them to directly identify "low-lying" PCoA aneurysms and make appropriate surgical decisions accordingly.

Indexed as

Angiography, Digital SubtractionIntracranial AneurysmNeurosurgical ProceduresAdultAgedCarotid Artery, InternalCerebral AngiographyFemaleHumansMaleMiddle AgedModels, TheoreticalRetrospective StudiesAnterior clinoid processAnterior petroclinoid Fold“low-lying” PCoA aneurysmsPcoAPredict model

Identifiers

PMID39085721
PMCPMC11291602

What Socratic 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 Socratic graph.