Subtopic Deep Dive
Pediatric Moyamoya Disease Epidemiology
Research Guide
What is Pediatric Moyamoya Disease Epidemiology?
Pediatric Moyamoya Disease Epidemiology examines the incidence, prevalence, progression patterns, and syndromic associations of Moyamoya disease specifically in children across diverse populations.
This subtopic analyzes epidemiological data from large cohorts, revealing higher incidence in East Asian children compared to other groups. Key studies report prevalence rates in Japan and progression risks in pediatric cases (Kuriyama et al., 2007; 440 citations; Seung-Ki Kim et al., 2010; 211 citations). It tracks associations with neurofibromatosis and neurocognitive outcomes.
Why It Matters
Epidemiological insights guide early screening in high-risk pediatric populations, such as East Asian children, reducing stroke incidence through timely surgical intervention (Seung-Ki Kim et al., 2010). They inform prognosis models for unilateral cases progressing bilaterally, aiding family counseling (Smith and Scott, 2008). Population studies enable targeted public health strategies in regions with varying incidence (Kuriyama et al., 2007).
Key Research Challenges
Low Incidence Variability
Rare disease status complicates global incidence comparisons due to small sample sizes and diagnostic underreporting. Japanese prevalence surveys highlight East Asian bias (Kuriyama et al., 2007; 440 citations). Cross-population studies are needed for accurate rates.
Progression Prediction Gaps
Predicting bilateral progression from unilateral pediatric cases remains inconsistent despite clinical factors. Smith and Scott (2008; 138 citations) identified imaging predictors in 88 cases. Long-term tracking is challenged by loss to follow-up.
Syndromic Association Uncertainty
Linking Moyamoya to syndromes like neurofibromatosis lacks causal clarity in children. Genetic analyses show population-specific RNF213 variants (Wu et al., 2012; 136 citations). Phenotypic overlap hinders epidemiological distinction.
Essential Papers
Guidelines for Diagnosis and Treatment of Moyamoya Disease (Spontaneous Occlusion of the Circle of Willis)
Research Committee on the Pathology and Treatment of Spontaneous Occlusion of the Circle of Willis, Health Labour Sciences Research Grant for Research on Measures for Intractable Diseases · 2012 · Neurologia medico-chirurgica · 951 citations
Moyamoya Disease: Epidemiology, Clinical Features, and Diagnosis
Jong Seung Kim · 2016 · Journal of Stroke · 464 citations
Moyamoya disease (MMD) is a chronic, occlusive cerebrovascular disease characterized by progressive stenosis at the terminal portion of the internal carotid artery and an abnormal vascular network ...
Prevalence and Clinicoepidemiological Features of Moyamoya Disease in Japan
Shinichi Kuriyama, Yasuko Kusaka, Miki Fujimura et al. · 2007 · Stroke · 440 citations
Background and Purpose— The objectives of the present study were to estimate an annual number of patients with moyamoya disease in Japan and to describe the clinicoepidemiological features of the d...
Moyamoya Disease: Treatment and Outcomes
Tackeun Kim, Chang Wan Oh, Jae Seung Bang et al. · 2016 · Journal of Stroke · 231 citations
Although the pathogenesis of moyamoya disease (MMD) has not been fully elucidated, the effectiveness of surgical revascularization in preventing stroke has been addressed by many studies. The main ...
Diagnostic Criteria for Moyamoya Disease - 2021 Revised Version
Satoshi Kuroda, Miki Fujimura, Jun Takahashi et al. · 2022 · Neurologia medico-chirurgica · 223 citations
In this report, we, the Research Committee on Moyamoya Disease (Spontaneous Occlusion of the circle of Willis), describe in detail the changes in the new "Diagnostic Criteria 2021" for moyamoya dis...
Pediatric moyamoya disease: An analysis of 410 consecutive cases
Seung‐Ki Kim, Byung‐Kyu Cho, Ji Hoon Phi et al. · 2010 · Annals of Neurology · 211 citations
Abstract Objective Moyamoya disease (MMD) is a cerebrovascular occlusive disease of the bilateral internal carotid arteries that causes a compensatory abnormal vascular network at the base of brain...
2021 Japanese Guidelines for the Management of Moyamoya Disease: Guidelines from the Research Committee on Moyamoya Disease and Japan Stroke Society
Miki Fujimura, Teiji Tominaga, Satoshi Kuroda et al. · 2022 · Neurologia medico-chirurgica · 207 citations
Reading Guide
Foundational Papers
Start with Kuriyama et al. (2007; 440 citations) for Japanese prevalence baseline, then Seung-Ki Kim et al. (2010; 211 citations) for largest pediatric cohort analysis establishing progression patterns.
Recent Advances
Study Smith and Scott (2008; 138 citations) for unilateral progression risks and Wu et al. (2012; 136 citations) for RNF213 genetics in non-Japanese populations.
Core Methods
Core techniques are questionnaire-based national surveys (Kuriyama et al., 2007), retrospective case series (Seung-Ki Kim et al., 2010), and imaging progression tracking (Smith and Scott, 2008).
How PapersFlow Helps You Research Pediatric Moyamoya Disease Epidemiology
Discover & Search
Research Agent uses searchPapers and exaSearch to find pediatric epidemiology papers like 'Pediatric moyamoya disease: An analysis of 410 consecutive cases' by Seung-Ki Kim et al. (2010), then citationGraph reveals connections to Kuriyama et al. (2007) prevalence data, and findSimilarPapers uncovers global incidence comparators.
Analyze & Verify
Analysis Agent employs readPaperContent on Seung-Ki Kim et al. (2010) to extract cohort statistics, verifyResponse with CoVe checks incidence claims against Kuriyama et al. (2007), and runPythonAnalysis performs GRADE grading on progression risks with pandas survival analysis from extracted data.
Synthesize & Write
Synthesis Agent detects gaps in pediatric progression models from Smith and Scott (2008), flags contradictions in incidence across populations, while Writing Agent uses latexEditText, latexSyncCitations for guideline drafts, and latexCompile generates formatted reports with exportMermaid for disease progression diagrams.
Use Cases
"Compare incidence rates of pediatric Moyamoya in Japan vs. other populations using statistical tests."
Research Agent → searchPapers('pediatric Moyamoya epidemiology incidence') → Analysis Agent → runPythonAnalysis(pandas t-test on Kuriyama 2007 and Seung-Ki Kim 2010 data) → outputs p-value table and matplotlib incidence plot.
"Draft LaTeX review on pediatric Moyamoya progression risks."
Synthesis Agent → gap detection on Smith and Scott 2008 → Writing Agent → latexEditText(structure review) → latexSyncCitations(Kuriyama 2007 et al.) → latexCompile → researcher gets compiled PDF with citations.
"Find code for analyzing Moyamoya genetic epidemiology from papers."
Research Agent → paperExtractUrls(Wu 2012 RNF213) → paperFindGithubRepo → githubRepoInspect → outputs Python scripts for variant frequency analysis from Han population data.
Automated Workflows
Deep Research workflow conducts systematic review of 50+ pediatric epidemiology papers, chaining searchPapers → citationGraph → GRADE grading for incidence meta-analysis. DeepScan applies 7-step verification to progression data from Seung-Ki Kim et al. (2010), with CoVe checkpoints on cohort claims. Theorizer generates hypotheses on syndromic links from genetic papers like Wu et al. (2012).
Frequently Asked Questions
What defines Pediatric Moyamoya Disease Epidemiology?
It covers incidence, prevalence, progression, and syndromic links in children, with Japanese annual patients estimated at thousands (Kuriyama et al., 2007).
What are key methods in this subtopic?
Methods include nationwide questionnaires for prevalence (Kuriyama et al., 2007) and retrospective analysis of consecutive pediatric cases (Seung-Ki Kim et al., 2010).
What are landmark papers?
Kuriyama et al. (2007; 440 citations) on Japanese prevalence; Seung-Ki Kim et al. (2010; 211 citations) on 410 pediatric cases.
What open problems exist?
Global incidence standardization, progression predictors beyond imaging (Smith and Scott, 2008), and syndromic genetic causality (Wu et al., 2012).
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