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2021 ◽  
Vol 17 (S6) ◽  
Author(s):  
Julie Murray ◽  
Hector Leonardo Gonzalez ◽  
Sarah Schwartz ◽  
Gail B. Rattinger ◽  
Yin Liu ◽  
...  

2021 ◽  
Vol 5 (Supplement_1) ◽  
pp. 646-647
Author(s):  
Karen Schliep ◽  
Zachary Shepelak ◽  
Nicolas Bitter ◽  
Ramkiran Gouripeddi ◽  
Truls Ostbye ◽  
...  

Abstract As dementia is widely under-detected, a predictive model using electronic health records (EHR) could provide a method for early screening to implement preventive strategies. There is limited research on using EHR to identify persons with Alzheimer’s disease (AD) and related dementias (RD). In a data-driven approach, we used all ICD-9 diagnosis and CPT procedure codes from statewide inpatient, ambulatory surgery, and Medicare records, in addition to age at baseline and gender, to detect AD/RD from the Cache County Study on Memory in Aging (1995–2009). After removing participants diagnosed with dementia at baseline (n=335), 3882 (82%) Cache County Study participants could be linked to inpatient, ambulatory surgery, and/or Medicare EHR records; 484 (12.5%) of these 3882 had incident all-cause dementia, with 308 (7.9%) having AD/AD comorbid with RD; and 176 (4.5%) having RD without AD. We removed participant’s ICD-9 codes occurring after first AD/RD diagnoses. EHR features (~2000) along with gold-standard diagnoses as class labels were then used to train and detect AD and/or RD using a Gradient Boosting Trees machine learning algorithm. Models evaluated with nested cross-validation yielded AUCs of 0.70 for all-cause dementia, 0.69 for AD/AD comorbid with RD, and 0.67 for RD without AD. Key factors detecting AD/RD included age at enrollment, cardiovascular, metabolic, and kidney disease, and sleep disturbances, with feature importance varying by record type and time frame prior to dementia onset. Our findings suggest that a patient’s health status up to 12 years prior may be useful in identifying individuals at-risk for dementia development.


2020 ◽  
Vol 28 (1) ◽  
pp. 64-71 ◽  
Author(s):  
Muhammad Haroon Burhanullah ◽  
JoAnn T. Tschanz ◽  
Matthew E. Peters ◽  
Jeannie-Marie Leoutsakos ◽  
Joshua Matyi ◽  
...  

2020 ◽  
Author(s):  
Ryan Taggart ◽  
◽  
Natalie Weed ◽  
Lily Wetterlin ◽  
Christopher Johnson
Keyword(s):  

Geosites ◽  
2019 ◽  
Vol 1 ◽  
pp. 1-6
Author(s):  
Lawrence Spangler

Ricks Spring is one of several major karst springs that discharge along the Logan River in the Bear River Range in Cache County, Utah. The spring is located along U.S. Highway 89 in Logan Canyon about 17 miles (27.4 kilometers) northeast of (up-canyon from) the city of Logan, at mile marker 477. It lies within Uinta-Wasatch-Cache National Forest at an elevation of 5880 feet (1792 meters). Situated at the base of a hillside, the spring is one of the largest and most scenic along the Logan River (figure 1). Water from the spring flows out of a large alcove, under Highway 89, and into the Logan River, about 150 feet (45 meters) from the spring. Pullouts on both sides of the highway provide parking for visitors to the spring, and a boardwalk crosses the spring run, which allows access to the rise pool in the alcove. Several signs at the spring provide information about its history and hydrology. Ricks Spring typically flows during the spring, summer, and fall months, but can have periods of no flow during the winter months, particularly during extended periods of cold weather. During these times, the water in the rise pit recedes to a small pool of standing water that can contain fish, which presumably originate from the nearby Logan River. During the last 10 years, cave divers have explored the conduit that feeds the spring for about 2300 feet (700 meters) into the mountainside.


Menopause ◽  
2019 ◽  
Vol 26 (12) ◽  
pp. 1366-1374 ◽  
Author(s):  
Joshua M. Matyi ◽  
Gail B. Rattinger ◽  
Sarah Schwartz ◽  
Mona Buhusi ◽  
JoAnn T. Tschanz

2019 ◽  
Vol 84 ◽  
pp. 242.e1-242.e6 ◽  
Author(s):  
Sage M. Wright ◽  
Samantha L. Jensen ◽  
Kristen L. Cockriel ◽  
Brian Davis ◽  
JoAnn T. Tschanz ◽  
...  

2019 ◽  
Vol 15 ◽  
pp. P834-P835
Author(s):  
Elizabeth K. Vernon ◽  
Gail B. Rattinger ◽  
Scott DeBerard ◽  
Jordan Kugler ◽  
JoAnn T. Tschanz

2019 ◽  
Vol 187 ◽  
pp. 119-128 ◽  
Author(s):  
Shuolei Chen ◽  
Keith M. Christensen ◽  
Shujuan Li
Keyword(s):  

2019 ◽  
Vol 15 ◽  
pp. P452-P452
Author(s):  
Kaitlyn E. Kauzor ◽  
Sarah Schwartz ◽  
Zach Tubbs ◽  
Alexandra G. Hammond ◽  
JoAnn T. Tschanz

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