Evidence map›Paper›PMID 39548256›Full record

ArticleScientific reports2024

Prognostic value of morphology and hemodynamics in moyamoya disease for long-term outcomes and disease progression.

Long Ma, Peicong Ge, Chaofan Zeng, Chenglong Liu, Zihan Yin, Xiaolong Ya, Yuanren Zhai, Qiheng He, Junsheng Li, Xun Ye and 5 more

Abstract read
In one paragraph

Article in Scientific reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing 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

8 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
  4. Article
  5. Review
  6. Article
  7. Cerebrovascular morphology: Insights into normal variations, aging effects and disease implications.Journal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and Metabolism · 2025
    Review
  8. 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

15 authors.

Long MaDepartment of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, 100070, China.
Peicong GeChina National Clinical Research Center for Neurological Diseases, Beijing, China. gepeicong@163.com.
Chaofan ZengDepartment of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, 100070, China.
Chenglong LiuDepartment of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, 100070, China.
Zihan YinDepartment of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, 100070, China.
Xiaolong YaDepartment of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, 100070, China.
Yuanren ZhaiDepartment of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, 100070, China.
Qiheng HeDepartment of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, 100070, China.
Junsheng LiDepartment of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, 100070, China.
Xun YeDepartment of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, 100070, China.
Qian ZhangDepartment of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, 100070, China.
Rong WangDepartment of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, 100070, China.
Dong ZhangDepartment of Neurosurgery, Beijing Hospital, Beijing, China.
Yan ZhangDepartment of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, 100070, China.
Jizong ZhaoDepartment of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, 100070, China. zhaojizong@bjtth.org.

Funding

National Key Research and Development Program of China 2021YFC2500502National Natural Science Foundation of China 82301451
6 · The paper itself

Abstract

To explore the relationship between morphological and hemodynamic parameters, baseline characteristics, and long-term outcomes in patients with moyamoya disease (MMD) using a computational fluid dynamics model. We retrospectively reviewed 129 patients at Beijing Tiantan hospital between July 2020 and December 2021. Perioperative clinical variables and Suzuki stage were recorded. Logistic regression analysis was employed to identify the risk factors for unfavorable long-term outcomes. The association between morphological, CT perfusion parameters, hemodynamic parameters and the Suzuki stage, clinical variables of MMD was also analyzed. Patients with high relative Wall Shear Stress (rWSS) were older and had more cases with higher Suzuki stage and worse follow-up mRS scores (p < 0.05). High rWSS at the terminal ICA and diabetes mellitus were identified as independent predictors of unfavorable long-term outcomes [OR = 3.039(1.191-7.754), p = 0.020; OR = 3.164(1.141-8.723), p = 0.027, respectively]. ROC analysis demonstrated that predictive models incorporating rWSS improved AUC values, with the highest AUC in Model 2 (AUC = 0.889). High rWSS was significantly associated with future TIA and stroke events (p = 0.032). We speculated that high rWSS and diabetes mellitus were independent risk factors for unfavorable long-term outcomes in patients with MMD. rWSS and morphological parameters are crucial for predicting MMD progression and understanding its pathogenesis.

Indexed as

Disease ProgressionHemodynamicsMoyamoya DiseaseAdultFemaleHumansMaleMiddle AgedPrognosisRetrospective StudiesRisk FactorsComputational fluid dynamicsCT perfusionHemodynamicMorphologyMoyamoya diseasePrognosisWall shear stress

Identifiers

PMID39548256
PMCPMC11568140

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