Publications by authors named "J E Sanchez"

Background: The impact of referral type and socioeconomic status on completion of the bariatric surgery process is not well understood.

Objectives: This study aims to 1) describe how sociodemographic characteristics influence referral type and 2) identify predictors of completion of surgery.

Setting: Large multihospital health care system, including a large academic medical center.

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High-energy nuclear collisions create a quark-gluon plasma, whose initial condition and subsequent expansion vary from event to event, impacting the distribution of the eventwise average transverse momentum [P([p_{T}])]. Disentangling the contributions from fluctuations in the nuclear overlap size (geometrical component) and other sources at a fixed size (intrinsic component) remains a challenge. This problem is addressed by measuring the mean, variance, and skewness of P([p_{T}]) in ^{208}Pb+^{208}Pb and ^{129}Xe+^{129}Xe collisions at sqrt[s_{NN}]=5.

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Atopic dermatitis (AD) is a disease that significantly impacts the quality of life of patients. Although there are multiple evidence-based guidelines, they are usually aimed at providing recommendations to AD specialists rather than primary care physicians (PCPs). The aim of this study was to construct a consensus document for PCPs, with the aim of presenting evidence-based recommendations that allow general practitioners, family physicians, pediatricians, internists and emergency physicians to provide appropriate care to AD patients, facilitating their diagnosis, management, and avoiding delays that can deteriorate patients' f quality of life.

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Background: Prior studies have shown differences in the genetic etiology and clinical presentation of Alzheimer's Disease across populations. For example, for multiple genetic loci associated with AD, effect sizes can vary drastically between individuals of different ancestral backgrounds. Few investigations into differences in epigenetic features like DNA methylation have been conducted in AD, particularly in diverse individuals.

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Background: Polygenic Risk Scores (PRS) are important in predicting disease risk and are usually rely on markers selected by thresholding p-values from genome-wide association studies (GWAS). In traditional approaches, one single model is built to calculate risk scores, employing effect size to determine additive risk. However, this traditional method overlooks potential interactions between genetic loci resulting in reduced prediction power.

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