The management of patients with inflammatory bowel disease-associated spondyloarthritis: Italian Group for the Study of Inflammatory Bowel Disease (IG-IBD) and Italian Society of Rheumatology (SIR) recommendations based on a pseudo-Delphi consensus.

Spondyloarthritis (SpA) is the most frequent extraintestinal manifestation in patients with inflammatory bowel diseases (IBD). When IBD and spondyloarthritis coexist, musculoskeletal and intestinal disease features should be considered when planning a therapeutic strategy. Treatment options for IBD and SpA have expanded enormously over the last few years, but randomized controlled trials with specific endpoints focused on SpA are not available in the IBD setting. To address this important clinical topic, the Italian Group for the Study of Inflammatory Bowel Disease (IG-IBD) and the Italian Society of Rheumatology (SIR) jointly planned to draw updated therapeutic recommendations for IBD-associated SpA using a pseudo-Delphi method. This document presents the official recommendations of IG-IBD and SIR on the management of IBD-associated SpA in the form of 34 statements and 4 therapeutic algorithms. It is intended to be a reference guide for gastroenterologists and rheumatologists dealing with IBD-associated SpA.

The Role of Selected Psychological Factors in Healthy-Sustainable Food Consumption Behaviors during the COVID-19 Pandemic.

The COVID-19 pandemic and the consequent precautions and dispositions adopted have triggered substantial changes in daily health-related behaviors, including food consumption habits. The psychological impact of the pandemic has been considered one of the factors affecting this transition and requiring consideration when targeting healthy-sustainable behavior preservation. The present study describes the results of a survey conducted on a convenience sample of Italian residents (n = 2272) during the first phases of pandemic. The aim was to explore the daily nutritional choices and behaviors and their transformations that occurred along with the associations with psychological factors (i.e., subjective well-being, and depression, anxiety and stress symptoms). An indicator for healthy-sustainable transition (HST index) was constructed and revealed diffused transformation in dietary habits, with a large segment of the sample adopting healthier and more sustainable dietary behaviors and others showing reduced healthy-sustainable food choices. Informative relationships with the psychological variables were then found from the correlational and regression analyses. Lower levels of anxiety, depression and stress symptomatology and higher perceived subjective well-being were significantly associated with healthier-sustainable food consumption behaviors. These findings shed light on the crucial areas to be considered in future institutional interventions, ultimately ensuring favorable conditions for both healthy diet behaviors and sustainable food consumption choices.

Predicting elderly patient length of stay in hospital and community care using a series of conditional Coxian phase-type distributions, further conditioned on a survival tree.

Increasing demand on hospital resources by an ageing population is impacting significantly on the number of beds available and, in turn, the length of time that elderly patients must wait for a bed before being admitted to hospital. This research presents a new methodology that models patient pathways and allows the accurate prediction of patient length of stay in hospital, using a phase-type survival tree to cluster patients based on their covariates and length of stay in hospital. A type of Markov model, called the conditional Coxian phase-type distribution is then implemented, with the probability density function for the time spent at a particular stage of care, for example, the first community discharge, conditioned on the length of stay experienced at the previous stage, namely the initial hospital admission. This component of the methodology is subsequently applied to each cohort of patients over a number of hospital and community stages in order to build up the profile of patient readmissions and associated timescales for each cohort. It is then possible to invert the methodology, so that the length of stay for an observation representing a new patient admission may be estimated at each stage of care, based on the assigned cohort at the initial hospital stage. This approach provides hospital managers with an accurate understanding of the rates with which different groups of patients move between hospital and community care, which may be used to reduce the negative effects of bed-blocking and the premature discharge of patients without a required period of convalescence. This has the benefit of assisting hospital managers with the effective allocation of vital healthcare resources. The approach presented is different to previous research in that it allows the inclusion of patient covariate information into the methodology describing patient transitions between hospital and community care stages in an aggregate Markov process. A data set containing hospital readmission data for elderly patients from the Abruzzo region of Italy is used as a case study in the application of the presented methodology.