scholarly journals Urinary Arsenic and Cadmium Associations with Findings from Cranial MRI in American Indians: Data from the Strong Heart Study

2020 ◽  
Vol 128 (12) ◽  
pp. 127009
Author(s):  
Astrid Suchy-Dicey ◽  
Carolyn Noonan ◽  
Ekaterina Burduli ◽  
Farrah J. Mateen ◽  
W.T. Longstreth ◽  
...  
2017 ◽  
Vol 48 (1-2) ◽  
pp. 39-47 ◽  
Author(s):  
Astrid M. Suchy-Dicey ◽  
Dean K. Shibata ◽  
Tara M. Madhyastha ◽  
Thomas J. Grabowski ◽  
W.T. Longstreth Jr. ◽  
...  

Background: The Cerebrovascular Disease and its Consequences in American Indians study conducted cranial MRI examination of surviving participants of the Strong Heart Study, a longitudinal cohort of elderly American Indians. Methods: Of the 1,033 recruited participants, some were unable to complete the MRI (n = 22), some scans were unusable due to participant motion or technical errors (n = 13), and one community withdrew consent after data collection (n = 209), leaving 789 interpretable MRI scan images. Six image sequences were obtained in contiguous slices on 1.5T scanners. Neuroradiologists graded white matter hyperintensities (WMH), sulci, and ventricles on a 0- to 9-point scale, and recorded the presence of infarcts and hemorrhages. Intracranial, brain, hippocampal, and WMH volumes were estimated by automated image processing. Results: The median scores for graded measures were 2 (WMH) and 3 (sulci, ventricles). About one-third of participants had lacunar (20%) or other infarcts (13%); few had hemorrhages (5.7%). Findings of cortical atrophy were also prevalent. Statistical analyses indicated significant associations between older age and findings of vascular injury and atrophy; male gender was associated with findings of cortical atrophy. Conclusions: Vascular brain injury is the likely explanation in this elderly American Indian population for brain infarcts, hemorrhages, WMH grade, and WMH volume. Although vascular brain injury may play a role in other findings, independent degenerative other disease processes may underlie abnormal sulcal widening, ventricular enlargement, hippocampal volume, and total brain volume. Further examination of risk factors and outcomes with these findings may expand the understanding of neurological conditions in this understudied population.


Diabetes Care ◽  
2002 ◽  
Vol 25 (1) ◽  
pp. 49-54 ◽  
Author(s):  
E. T. Lee ◽  
T. K. Welty ◽  
L. D. Cowan ◽  
W. Wang ◽  
D. A. Rhoades ◽  
...  

2008 ◽  
Vol 108 (5) ◽  
pp. 794-802 ◽  
Author(s):  
Sigal Eilat-Adar ◽  
Jiaqiong Xu ◽  
Uri Goldbourt ◽  
Ellie Zephier ◽  
Barbara V. Howard ◽  
...  

2009 ◽  
Vol 170 (5) ◽  
pp. 632-639 ◽  
Author(s):  
A. M. Fretts ◽  
B. V. Howard ◽  
A. M. Kriska ◽  
N. L. Smith ◽  
T. Lumley ◽  
...  

Circulation ◽  
2013 ◽  
Vol 127 (suppl_12) ◽  
Author(s):  
Ying Zhang ◽  
Wenyu Wang ◽  
Elisa T Lee ◽  
Thomas K Welty ◽  
Jorge R Kizer ◽  
...  

Background— Stroke prediction models are valuable to physicians in evaluating the risk of their patients so that preventive interventions can be promoted. The Framingham Risk Profile is a widely used stroke prediction equation. However, the contributions of some common risk factors for stroke vary across populations and some risk factors are specific to certain populations. For example, albuminuria is an important risk factor in American Indians (AIs), which is not included in the Framingham equation. The objective of the current study is to develop stroke prediction equations using routinely collected variables in AIs, a population with high rates of diabetes and stroke. Methods— The data used in the analysis are from 4507 stroke free participants at enrollment in the Strong Heart Study (SHS), the largest population-based longitudinal study of cardiovascular disease (CVD) and its risk factors in AIs in Arizona, Oklahoma, and South/North Dakota. As of December 2008, 379/4507 (8.4%) participants suffered a first stroke during an average follow-up of 17 years. Baseline potential risk factors were included in the Cox proportional-hazard models to develop gender-specific prediction equations. Backward selection was used to choose the predictors. Model performance was assessed using Harrell’s C statistics based on bootstrapping methods. Results— Baseline age, untreated systolic blood pressure, treated diastolic blood pressure, HDL-C, current smoking, diabetes, macro-albuminuria, and history of CVD are significant predictors for incident stroke among women. Most of these predictors except HDL-C were also in the prediction equation for men. The equations provided good discrimination ability, as indicated by a C statistic of 0.72 for men and 0.73 for women. Conclusions— Predicted risk of stroke in 10 years can be provided for physicians and their patients. Then appropriate intervention can be implemented. The stroke prediction equations from SHS can be applied to other AIs as well as other ethnic groups with high rates of diabetes and albuminuria.


Author(s):  
Clemma J. Muller ◽  
Carolyn J. Noonan ◽  
Richard F. MacLehose ◽  
Julie A. Stoner ◽  
Elisa T. Lee ◽  
...  

GeroScience ◽  
2019 ◽  
Vol 41 (3) ◽  
pp. 351-361 ◽  
Author(s):  
Pooja Subedi ◽  
Stefano Nembrini ◽  
Qiang An ◽  
Yun Zhu ◽  
Hao Peng ◽  
...  

Diabetologia ◽  
1998 ◽  
Vol 41 (9) ◽  
pp. 1002-1009 ◽  
Author(s):  
A. Fagot-Campagna ◽  
R. G. Nelson ◽  
W. C. Knowler ◽  
D. J. Pettitt ◽  
D. C. Robbins ◽  
...  

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