Socioeconomic and demographic disparities of moyamoya disease in the United States

Ghaffari-Rafi, Arash; Ghaffari-Rafi, Shadeh; Leon-Rojas, Jose

doi:10.1016/j.clineuro.2020.105719

Cited by 28 publications

(27 citation statements)

References 47 publications

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“…In this paper, the top ten factors of feature importance of the three models all indicated that hemorrhagic stroke as the initial symptom of moyamoya disease patients may be closely related to Suzuki rating, with aneurysm or not, hospitalization times, residence and age of onset. In conclusion, multiple factors determine the initial symptoms of patients with moyamoya disease, Suzuki rating, with aneurysm or not, hospitalization times, residence, age of onset and other risk factors may be important risk factors for hemorrhagic stroke, which is similar to some reports [19] .…”

Section: Feature Importance Of Modelssupporting

confidence: 83%

Machine learning models of ischemia/hemorrhage in moyamoya disease and analysis of its risk factors

Chen

Luo

2021

Clinical Neurology and Neurosurgery

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Section: Feature Importance Of Modelssupporting

confidence: 83%

Machine learning models of ischemia/hemorrhage in moyamoya disease and analysis of its risk factors

Chen

Luo

2021

Clinical Neurology and Neurosurgery

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“…In this nationwide population-based study, we calculated the incidence and prevalence of MMD in mainland China as 0.59 (95% CI 0.49 to 0.68) and 1.01 (95% CI 0.81 to 1.21) per 100 000 person-years, respectively. These estimates indicate that the rates of MMD in China were greater than those in the United States 12 and Europe, 14 22 but lower than recent values from other East Asian countries such as Japan 7 and South Korea. 9 10 Our results confirm that MMD is relatively common in East Asian populations, which may result from the distinct genetic background.…”

Section: Discussionmentioning

confidence: 73%

“…Patients with MMD were identified by diagnostic code or diagnostic text, based on International Classification of Diseases, 10th Revision code I67.5, 12 14 and medical terms in Chinese and English including MMD, spontaneous occlusion of the circle of Willis, abnormal vascular network at the base of the brain, moyamoya vessels and MMD. To avoid missing patients, we constructed a relatively loose algorithm using fuzzy string matching to extract all potential MMD patients in the database.…”

Section: Methodsmentioning

confidence: 99%

Incidence and prevalence of moyamoya disease in urban China: a nationwide retrospective cohort study

et al. 2021

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Background and objectiveMoyamoya disease (MMD) is an increasingly recognised cause of stroke, mainly described in East Asia. China is the largest nation in Asia, but few studies reported the epidemiology of MMD, especially at a national level. We aimed to estimate the incidence and prevalence of MMD in China.MethodsWe performed a population-based study using data from the national databases of Urban Basic Medical Insurance between 2013 and 2016, covering approximately 0.50 billion individuals. MMD cases were identified by diagnostic code (International Classification of Diseases, 10th Revision I67.5) or related diagnostic text.ResultsA total of 1987 MMD patients (mean age 44.45±14.30 years, female-to-male ratio 1.12) were identified, representing a national crude incidence of 0.59 (95% CI: 0.49 to 0.68) and a prevalence of 1.01 (95% CI: 0.81 to 1.21) per 100 000 person-years in 2016. Rates were higher in females than in males for the incidence (0.66 vs 0.52) and prevalence (1.05 vs 0.90). And the age-specific rates showed a bimodal distribution, with the highest peak in middle-aged group and the second peak in child group.ConclusionsOur results confirm that MMD is relatively common in East Asians, but the rates in China were lower than those in other East Asian countries such as Japan and Korea. The unique epidemiological features, including a relatively weak female predominance and a shift in the highest peak of incidence from children to adults, revealed new sight into MMD. Further research is expected to explore the potential pathogenesis of MMD.

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“…Disease morbidity and mortality has long been linked to socioeconomic status, yet no investigations have examined such an association with IIH incidence in the US (13,49,50). Between 2003 and 2016, patients in the lowest income quartile were found to have an incidence of 1.56 (1.47 to 1.82), significantly larger (0.44, 95% CI 0.33 to 0.53, p = 0.00024) than the 1.21 (1.01 to 1.36) of middle/high-income patients.…”

Section: Patient Incomementioning

confidence: 99%

“…Notably, there is impetus to better define IIH's distribution among the subsets of society, especially when considering the burden imposed on patients—as 68–98% suffer from headaches, whereas roughly half experience sustained vision loss and 8–10% bi- or monocular blindness ( 2 , 4 , 8 – 12 ). Moreover, epidemiology not only provides a conduit for risk-factor identification and by extension etiology elucidation but also aids legislators in addressing community needs ( 13 ).…”

Section: Introductionmentioning

confidence: 99%

Idiopathic Intracranial Hypertension in the United States: Demographic and Socioeconomic Disparities

Ghaffari-Rafi

Mehdizadeh

et al. 2020

Front. Neurol.

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Background: Obesity's risk increases for low-income, female, young, and Black patients. By extrapolation, idiopathic intracranial hypertension (IIH)-a disease associated with body mass index-would potentially display socioeconomic and demographic disparities. Methods: IIH incidence (per 100,000) was investigated with respect to sex, age, income, residence, and race/ethnicity, by querying the largest United States (US) healthcare administrative dataset (1997-2016), the National (Nationwide) Inpatient Sample. Results: Annual national incidence (with 25th and 75th quartiles) for IIH was 1.15 (0.91, 1.44). Females had an incidence of 1.97 (1.48, 2.48), larger (p = 0.0000038) than males at 0.36 (0.26, 0.38). Regarding age, largest incidence was among those 18-44 years old at 2.47 (1.84, 2.73). Low-income patients had an incidence of 1.56 (1.47, 1.82), larger (p = 0.00024) than the 1.21 (1.01, 1.36) of the middle/high. No differences (χ 2 = 4.67, p = 0.097) were appreciated between urban (1.44; 1.40, 1.61), suburban (1.30; 1.09, 1.40), or rural (1.46; 1.40, 1.48) communities. For race/ethnicity (χ 2 = 57, p = 2.57 × 10 −12), incidence was largest for Blacks (2.05; 1.76, 2.74), followed by Whites (1.04; 0.79, 1.41), Hispanics (0.67; 0.57, 0.94), and Asian/Pacific Islanders (0.16; 0.11, 0.19). Year-to-year, incidence rose for all strata subsets except Asian/Pacific Islanders (τ = −0.84, p = 0.00000068). Conclusion: IIH demonstrates several sociodemographic disparities. Specifically, incidences are larger for those low-income, Black, 18-44 years old, or female, while annually increasing for all subsets, except Asian/Pacific Islanders. Hence, IIH differentially afflicts the US population, yielding in healthcare inequalities.

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Socioeconomic and demographic disparities of moyamoya disease in the United States

Cited by 28 publications

References 47 publications

Machine learning models of ischemia/hemorrhage in moyamoya disease and analysis of its risk factors

Machine learning models of ischemia/hemorrhage in moyamoya disease and analysis of its risk factors

Incidence and prevalence of moyamoya disease in urban China: a nationwide retrospective cohort study

Idiopathic Intracranial Hypertension in the United States: Demographic and Socioeconomic Disparities

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