Tritordeum breads are well tolerated with preference over gluten-free breads in non-celiac wheat-sensitive patients and its consumption induce changes in gut bacteria

[Backgound] The ingestion of wheat and other cereals are related to several gut disorders. The specific components responsible for non-celiac wheat-sensitivity (NCWS) may include gluten and other compounds. Tritordeum is a new cereal derived from crossing durum wheat with a wild barley species, which differs from bread wheat in its gluten composition. In the present work, we examined the response of NCWS patients to tritordeum bread Gastrointestinal symptoms as well as tritordeum acceptability, gluten immunogenic peptides excretion, and the composition and structure of the intestinal microbiota were evaluated.[Results] Gastrointestinal symptoms of the subjects showed no significant change between the gluten-free bread and the tritordeum bread. Participating subjects rated tritordeum bread higher than the gluten-free bread. Analysis of the bacterial gut microbiota indicated that tritordeum consumption does not alter the global structure and composition of the intestinal microbiota, and only a few changes in some butyrate-producing bacteria were observed. [Conclusions] All the results derived from acceptability, biochemical and microbiological tests suggest that tritordeum may be tolerated by a sub-set of NCWS sufferers who do not require strict exclusion of gluten from their diet. © 2020 Society of Chemical Industry.This research was funded by Junta de Andalucía, Consejería de Conocimiento, Investigación y Universidad, project AT-5985 and the European Regional Development Fund (FEDER)

Predicting the length of mechanical ventilation in acute respiratory disease syndrome using machine learning: The PIONEER Study

Background: The ability to predict a long duration of mechanical ventilation (MV) by clinicians is very limited. We assessed the value of machine learning (ML) for early prediction of the duration of MV > 14 days in patients with moderate-to-severe acute respiratory distress syndrome (ARDS). Methods: This is a development, testing, and external validation study using data from 1173 patients on MV ≥ 3 days with moderate-to-severe ARDS. We first developed and tested prediction models in 920 ARDS patients using relevant features captured at the time of moderate/severe ARDS diagnosis, at 24 h and 72 h after diagnosis with logistic regression, and Multilayer Perceptron, Support Vector Machine, and Random Forest ML techniques. For external validation, we used an independent cohort of 253 patients on MV ≥ 3 days with moderate/severe ARDS. Results: A total of 441 patients (48%) from the derivation cohort (n = 920) and 100 patients (40%) from the validation cohort (n = 253) were mechanically ventilated for >14 days [median 14 days (IQR 8–25) vs. 13 days (IQR 7–21), respectively]. The best early prediction model was obtained with data collected at 72 h after moderate/severe ARDS diagnosis. Multilayer Perceptron risk modeling identified major prognostic factors for the duration of MV > 14 days, including PaO2/FiO2, PaCO2, pH, and positive end-expiratory pressure. Predictions of the duration of MV > 14 days showed modest discrimination [AUC 0.71 (95%CI 0.65–0.76)]. Conclusions: Prolonged MV duration in moderate/severe ARDS patients remains difficult to predict early even with ML techniques such as Multilayer Perceptron and using data at 72 h of diagnosis. More research is needed to identify markers for predicting the length of MV. This study was registered on 14 August 2023 at ClinicalTrials.gov (NCT NCT05993377)