Outcomes of the first 54 pediatric patients on long-term home parenteral nutrition from a single Brazilian center

Objectives: Data on multidisciplinary programs dedicated to home parenteral nutrition (HPN) in Latin America are limited. This study describes the results of the first multidisciplinary pediatric intestinal rehabilitation program for HPN at a public tertiary hospital in Brazil. Methods: We retrospectively reviewed patients aged 0–18 years with intestinal failure (IF) who required parenteral nutrition (PN) for >60 days between January/2014 and December/2020. Results: Fifty-four patients were discharged on HPN (15 achieved enteral autonomy, 34 continued on HPN at the end of the study, 1 underwent intestinal transplantation, and 4 died). The median (IQR) age at the study endpoint of patients who achieved enteral autonomy was 14.1 (9.7–19) versus 34.7 (20.4–53.9) months in those who did not achieve enteral autonomy. Overall prevalence of catheter-related thrombosis was 66.7% and catheterrelated bloodstream infection rate was 0.39/1000 catheter-days. Intestinal failure-associated liver disease (IFALD) was present in 24% of all patients; none of the patients who achieved enteral autonomy had IFALD. All patients showed significant improvement in anthropometric parameters during the HPN period. The sociodemographic characteristics of the patients’ family members were mothers less than 20 years old (7.5%), schooling time more than 10 years (55.5%), and household income between 1 and 3 times the minimum wage (64.8%). The 5-year survival rate for HPN is 90%, and 27.7% of patients achieve enteral autonomy. Conclusion: The treatment of pediatric patients with IF followed by a multidisciplinary pediatric intestinal rehabilitation program with HPN is feasible and safe in the Brazilian public health system

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear understanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5,6,7 vast areas of the tropics remain understudied.8,9,10,11 In the American tropics, Amazonia stands out as the world's most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepresented in biodiversity databases.13,14,15 To worsen this situation, human-induced modifications16,17 may eliminate pieces of the Amazon's biodiversity puzzle before we can use them to understand how ecological communities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple organism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region's vulnerability to environmental change. 15%–18% of the most neglected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lost

Development and validation of the MMCD score to predict kidney replacement therapy in COVID-19 patients

Abstract Background Acute kidney injury (AKI) is frequently associated with COVID-19, and the need for kidney replacement therapy (KRT) is considered an indicator of disease severity. This study aimed to develop a prognostic score for predicting the need for KRT in hospitalised COVID-19 patients, and to assess the incidence of AKI and KRT requirement. Methods This study is part of a multicentre cohort, the Brazilian COVID-19 Registry. A total of 5212 adult COVID-19 patients were included between March/2020 and September/2020. Variable selection was performed using generalised additive models (GAM), and least absolute shrinkage and selection operator (LASSO) regression was used for score derivation. Accuracy was assessed using the area under the receiver operating characteristic curve (AUC-ROC). Results The median age of the model-derivation cohort was 59 (IQR 47–70) years, 54.5% were men, 34.3% required ICU admission, 20.9% evolved with AKI, 9.3% required KRT, and 15.1% died during hospitalisation. The temporal validation cohort had similar age, sex, ICU admission, AKI, required KRT distribution and in-hospital mortality. The geographic validation cohort had similar age and sex; however, this cohort had higher rates of ICU admission, AKI, need for KRT and in-hospital mortality. Four predictors of the need for KRT were identified using GAM: need for mechanical ventilation, male sex, higher creatinine at hospital presentation and diabetes. The MMCD score had excellent discrimination in derivation (AUROC 0.929, 95% CI 0.918–0.939) and validation (temporal AUROC 0.927, 95% CI 0.911–0.941; geographic AUROC 0.819, 95% CI 0.792–0.845) cohorts and good overall performance (Brier score: 0.057, 0.056 and 0.122, respectively). The score is implemented in a freely available online risk calculator ( https://www.mmcdscore.com/ ). Conclusions The use of the MMCD score to predict the need for KRT may assist healthcare workers in identifying hospitalised COVID-19 patients who may require more intensive monitoring, and can be useful for resource allocation