Publications by authors named "P J Hulick"

Atypical diabetes with overlapping clinical features of type 1 (T1D) and type 2 (T2D) is common and challenging diagnostically and for implementing effective treatment. Here, we validate a recently reported genetic probability of type 1 diabetes (GenProb-T1D) from the UK Biobank (UKB) for differentiating type 1 diabetes and type 2 diabetes in a diabetes patient cohort from a healthcare system-based biobank in the USA. Among 3,363 diabetes patients, we confirmed the performance of GenProb-T1D in differentiating typical type 1 diabetes vs type 2 diabetes.

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Context: The present study builds on our prior work that demonstrated an association between pharmacogenetic interactions and 90-day readmission. Objective: Evaluate aggregate contribution of social determinants, comorbidity, and gene-x-drug interactions to moderate 90-day hospital readmission. Study Design and Analysis: Non-concurrent cohort study; Multivariable logistic regression Setting: Hospital/integrated healthcare delivery system in northern Illinois Population Studied: 19,999 adults tracked from 2010 through 2020 who underwent testing with a 13-gene pharmacogenetic panel Outcome Measure: 90-day hospital readmission (primary outcome) Results: Univariate logistic regression analyses demonstrated that strongest associations with 90 day hospital readmissions were the number of medications prescribed within 30 days of a first hospital admission that had Clinical Pharmacogenomics Implementation Consortium (CPIC) guidance (CPIC medications) (5+ CPIC medications, odds ratio (OR) = 7.

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Genomic and personalized medicine implementation efforts have largely centered on specialty care in tertiary health systems. There are few examples of fully integrated care systems that span the healthcare continuum. In 2014, NorthShore University HealthSystem launched the Center for Personalized Medicine to catalyze the delivery of personalized medicine.

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Article Synopsis
  • * This study analyzed data from nearly 42,000 diabetes patients to evaluate the effectiveness of two polygenic scores (PGSs) in distinguishing between classic T1D and T2D, finding that these scores performed well with a high C statistic of 0.91.
  • * The results suggested that using these PGSs can identify patients with atypical diabetes who may actually have T1D, with 23% of such patients showing a higher probability of T1D based on genetic assessments
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Cancer-associated thrombosis (CAT) is common and associated with mortality. We estimated CAT rate by cancer sites and inherited factors among cancer patients from the UK Biobank (N =70,406). The 12-month CAT rate after cancer diagnosis was 2.

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