Children with acute food protein-induced enterocolitis syndrome from Spain and Italy usually tolerate all other food groups.

Acute food protein-induced enterocolitis syndrome ('FPIES') is a potentially severe type of non IgE-mediated food allergy affecting mainly infants usually when foods are introduced [1]. Acute FPIES triggered by multiple unrelated foods ('multiple food FPIES') has been reported in up to two thirds of patients, particularly in the USA [2,3]. FPIES reactions are often traumatic experiences for parents and weaning leads to significant anxiety, as there is no test to identify safe new foods. This has led to complex weaning recommendations in children with FPIES in an attempt to support parents [4]. However, evidence suggests that multiple food FPIES is rare in other regions, such as Southern Europe [5,6], which questions the applicability of such weaning advice in this population. Studies including a detailed dietary history in children with FPIES are lacking

Case-Control Analysis of the Impact of Anemia on Quality of Life in Patients with Cancer: A Qca Study Analysis

The impact of anemia on the quality of life (QoL) in cancer patients has been studied previously; however, the cut-off point used to define anemia differed among studies, thus providing inconsistent results. Therefore, we analysed the clinical impact of anemia on QoL using the same cut-off point for hemoglobin level to define anemia as that used in ESMO clinical practice guidelines. This post-hoc analysis aimed to determine the impact of anemia on QoL in cancer patients through the European Organization for Research and Treatment of Cancer Quality of life questionnaire version 3.0 (EORTC QLQ-C30) and Euro QoL 5-dimension 3-level (EQ-5D-3L) questionnaire. We found that cancer patients with anemia had significantly worse QoL in clinical terms. In addition, anemic patients had more pronounced symptoms than those in non-anemic patients. Anemia is a common condition in cancer patients and is associated with a wide variety of symptoms that impair quality of life (QoL). However, exactly how anemia affects QoL in cancer patients is unclear because of the inconsistencies in its definition in previous reports. We aimed to examine the clinical impact of anemia on the QoL of cancer patients using specific questionnaires. We performed a post-hoc analysis of a multicenter, prospective, case-control study. We included patients with cancer with (cases) or without (controls) anemia. Participants completed the European Organization for Research and Treatment of Cancer Quality of Life questionnaire version 3.0 (EORTC QLQ-C30) and Euro QoL 5-dimension 3-level (EQ-5D-3L) questionnaire. Statistically significant and clinically relevant differences in the global health status were examined. From 2015 to 2018, 365 patients were included (90 cases and 275 controls). We found minimally important differences in global health status according to the EORTC QLQ-C30 questionnaire (case vs. controls: 45.6 vs. 58%, respectively; mean difference: -12.4, p < 0.001). Regarding symptoms, cancer patients with anemia had more pronounced symptoms in six out of nine scales in comparison with those without anemia. In conclusion, cancer patients with anemia had a worse QoL both clinically and statistically

Clustering COVID-19 ARDS patients through the first days of ICU admission. An analysis of the CIBERESUCICOVID Cohort

Background Acute respiratory distress syndrome (ARDS) can be classified into sub-phenotypes according to different inflammatory/clinical status. Prognostic enrichment was achieved by grouping patients into hypoinflammatory or hyperinflammatory sub-phenotypes, even though the time of analysis may change the classification according to treatment response or disease evolution. We aimed to evaluate when patients can be clustered in more than 1 group, and how they may change the clustering of patients using data of baseline or day 3, and the prognosis of patients according to their evolution by changing or not the cluster.Methods Multicenter, observational prospective, and retrospective study of patients admitted due to ARDS related to COVID-19 infection in Spain. Patients were grouped according to a clustering mixed-type data algorithm (k-prototypes) using continuous and categorical readily available variables at baseline and day 3.Results Of 6205 patients, 3743 (60%) were included in the study. According to silhouette analysis, patients were grouped in two clusters. At baseline, 1402 (37%) patients were included in cluster 1 and 2341(63%) in cluster 2. On day 3, 1557(42%) patients were included in cluster 1 and 2086 (57%) in cluster 2. The patients included in cluster 2 were older and more frequently hypertensive and had a higher prevalence of shock, organ dysfunction, inflammatory biomarkers, and worst respiratory indexes at both time points. The 90-day mortality was higher in cluster 2 at both clustering processes (43.8% [n = 1025] versus 27.3% [n = 383] at baseline, and 49% [n = 1023] versus 20.6% [n = 321] on day 3). Four hundred and fifty-eight (33%) patients clustered in the first group were clustered in the second group on day 3. In contrast, 638 (27%) patients clustered in the second group were clustered in the first group on day 3.Conclusions During the first days, patients can be clustered into two groups and the process of clustering patients may change as they continue to evolve. This means that despite a vast majority of patients remaining in the same cluster, a minority reaching 33% of patients analyzed may be re-categorized into different clusters based on their progress. Such changes can significantly impact their prognosis