pyPheWAS: A Phenome-Disease Association Tool for Electronic Medical Record Analysis

Kerley, Cailey I.; Chaganti, Shikha; Nguyen, Tin Q; Bermúdez, Camilo; Cutting, Laurie E.; Beason‐Held, Lori L.; Lasko, Thomas A.; Landman, Bennett A.

doi:10.1007/s12021-021-09553-4

Cited by 15 publications

(18 citation statements)

References 35 publications

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“…The PheDAS method 16,22 was used to determine significant differences in the prevalence of reported health codes between the participants with dementia (AD or VaD) and respective control groups. Subjects were matched 1: n for the dementia:control participants based on maximum age (age at diagnosis for AD and VaD; age at last follow‐up visit for CN), sex, and follow‐up length of medical records.…”

Section: Methodsmentioning

confidence: 99%

Health Conditions Associated with Alzheimer's Disease and Vascular Dementia

Beason‐Held

Kerley

Chaganti

et al. 2023

Annals of Neurology

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Objective: We examined medical records to determine health conditions associated with dementia at varied intervals prior to dementia diagnosis in participants from the Baltimore Longitudinal Study of Aging (BLSA). Methods: Data were available for 347 Alzheimer's disease (AD), 76 vascular dementia (VaD), and 811 control participants without dementia. Logistic regressions were performed associating International Classification of Diseases, 9th Revision (ICD-9) health codes with dementia status across all time points, at 5 and 1 year(s) prior to dementia diagnosis, and at the year of diagnosis, controlling for age, sex, and follow-up length of the medical record. Results: In AD, the earliest and most consistent associations across all time points included depression, erectile dysfunction, gait abnormalities, hearing loss, and nervous and musculoskeletal symptoms. Cardiomegaly, urinary incontinence, non-epithelial skin cancer, and pneumonia were not significant until 1 year before dementia diagnosis. In VaD, the earliest and most consistent associations across all time points included abnormal electrocardiogram (EKG), cardiac dysrhythmias, cerebrovascular disease, non-epithelial skin cancer, depression, and hearing loss. Atrial fibrillation, occlusion of cerebral arteries, essential tremor, and abnormal reflexes were not significant until 1 year before dementia diagnosis. Interpretation: These findings suggest that some health conditions are associated with future dementia beginning at least 5 years before dementia diagnosis and are consistently seen over time, while others only reach significance closer to the date of diagnosis. These results also show that there are both shared and distinctive health conditions associated with AD and VaD. These results reinforce the need for medical intervention and treatment to lessen the impact of health comorbidities in the aging population.

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Section: Methodsmentioning

confidence: 99%

Health Conditions Associated with Alzheimer's Disease and Vascular Dementia

Beason‐Held

Kerley

Chaganti

et al. 2023

Annals of Neurology

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“…We analyzed the ICD signature of patients with PC compared with the control group by performing a binary PheWAS to identify comorbidities associated with each patient group. We used the pyPheWAS toolkit, an open-source Python package 40 …”

Section: Methodsmentioning

confidence: 99%

Structured deep embedding model to generate composite clinical indices from electronic health records for early detection of pancreatic cancer

et al. 2023

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“…pyPheWAS Explorer is available in open source as part of the pyPheWAS Python package 11 (version 4.1+), available at https://github.com/MASILab/pyPheWAS . The Explorer consists of a JavaScript and D3 23 front-end, with a Python Flask 24 server back-end.…”

Section: Methodsmentioning

confidence: 99%

pyPheWAS Explorer: a visualization tool for exploratory analysis of phenome-disease associations

et al. 2023

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Objective To enable interactive visualization of phenome-wide association studies (PheWAS) on electronic health records (EHR). Materials and Methods Current PheWAS technologies require familiarity with command-line interfaces and lack end-to-end data visualizations. pyPheWAS Explorer allows users to examine group variables, test assumptions, design PheWAS models, and evaluate results in a streamlined graphical interface. Results A cohort of attention deficit hyperactivity disorder (ADHD) subjects and matched non-ADHD controls is examined. pyPheWAS Explorer is used to build a PheWAS model including sex and deprivation index as covariates, and the Explorer’s result visualization for this model reveals known ADHD comorbidities. Discussion pyPheWAS Explorer may be used to rapidly investigate potentially novel EHR associations. Broader applications include deployment for clinical experts and preliminary exploration tools for institutional EHR repositories. Conclusion pyPheWAS Explorer provides a seamless graphical interface for designing, executing, and analyzing PheWAS experiments, emphasizing exploratory analysis of regression types and covariate selection.

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pyPheWAS: A Phenome-Disease Association Tool for Electronic Medical Record Analysis

Cited by 15 publications

References 35 publications

Health Conditions Associated with Alzheimer's Disease and Vascular Dementia

Health Conditions Associated with Alzheimer's Disease and Vascular Dementia

Structured deep embedding model to generate composite clinical indices from electronic health records for early detection of pancreatic cancer

pyPheWAS Explorer: a visualization tool for exploratory analysis of phenome-disease associations

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