Publications by authors named "F Kenneth Freedman"

Background: Bariatric surgery has been shown to cause a negative impact on oral health, as reflected by postsurgical increase of caries-related dental interventions.

Objectives: The aim of this study was to compare dental intervention rates after Roux-en-Y gastric bypass (RYGB) and sleeve gastrectomy (SG).

Setting: Nationwide and register-based (Sweden).

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Objective: The impact of weight loss surgery on oral health is not clear. The aim of the present study was to investigate its impact on the risk for dental interventions.

Materials And Methods: All adults who underwent metabolic surgery in Sweden between January 1, 2009 and December 31, 2018 were identified in the Scandinavian Obesity Surgery Registry (SOReg; n = 53,643).

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In the UK, different dietary systems are used to calculate protein or tyrosine/phenylalanine intake in the dietary management of hereditary tyrosinaemia, HTI, II and III (HT), with no systematic evidence comparing the merits and inadequacies of each. This study aimed to examine the current UK dietary practices in all HTs and, using Delphi methodology, to reach consensus agreement about the best dietary management system. Over 12 months, five meetings were held with UK paediatric and adult dietitians working in inherited metabolic disorders (IMDs) managing HTs.

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Introduction: There is little practical guidance about suitable food choices for higher natural protein tolerances in patients with phenylketonuria (PKU). This is particularly important to consider with the introduction of adjunct pharmaceutical treatments that may improve protein tolerance. Aim: To develop a set of guidelines for the introduction of higher protein foods into the diets of patients with PKU who tolerate >10 g/day of protein.

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Smoke impacts from large wildfires are mounting, and the projection is for more such events in the future as the one experienced October 2017 in Northern California, and subsequently in 2018 and 2020. Further, the evidence is growing about the health impacts from these events which are also difficult to simulate. Therefore, we simulated air quality conditions using a suite of remotely-sensed data, surface observational data, chemical transport modeling with WRF-CMAQ, one data fusion, and three machine learning methods to arrive at datasets useful to air quality and health impact analyses.

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