Analysis on Nutritional Risk Screening and Influencing Factors of Hospitalized Patients in Central Urban Area

Rational nutritional support shall be based on nutritional screening and nutritional assessment. This study is aimed to explore nutritional risk screening and its influencing factors of hospitalized patients in central urban area. It is helpful for the early detection of problems in nutritional supports, nutrition management and the implementation of intervention measures, which will contribute a lot to improving the patient＇s poor clinical outcome. A total of three tertiary medical institutions were enrolled in this study. From October 2015 to June 2016, 1202 hospitalized patients aged ≥18 years were enrolled in Nutrition Risk Screening 2002（NRS2002） for nutritional risk screening, including 8 cases who refused to participate, 5 cases of same-day surgery and 5 cases of coma. A single-factor chi-square test was performed on 312 patients with nutritional risk and 872 hospitalized patients without nutritional risk. Logistic regression analysis was performed with univariate analysis（P〈0.05）, to investigate the incidence of nutritional risk and influencing factors. The incidence of nutritional risk was 26.35% in the inpatients, 25.90% in male and 26.84% in female, respectively. The single-factor analysis showed that the age ≥60, sleeping disorder, fasting, intraoperative bleeding, the surgery in recent month, digestive diseases, metabolic diseases and endocrine system diseases had significant effects on nutritional risk（P〈0.05）. Having considered the above-mentioned factors as independent variables and nutritional risk（Y=1, N=0） as dependent variable, logistic regression analysis revealed that the age ≥60, fasting, sleeping disorders, the surgery in recent month and digestive diseases are hazardous factors for nutritional risk. Nutritional risk exists in hospitalized patients in central urban areas. Nutritional risk screening should be conducted for inpatients. Nutritional intervention programs should be formulated in consideration of those influencing factors, which enable to reduce the nutritional risk and to promote the rehabilitation of inpatients.

Preliminary study on nutritional diet management in the prevention and treatment of COVID-19 in China

Through the painstaking efforts,the situation of epidemic prevention and control is now developing in a positive direction.Nutritional Diet health management is an important part of health management.The main objective of nutritional diet health management is to improve the clinical outcomes,quality of life and cost-effectiveness ratio of patients with COVID-19 through standardized nutritional support,nutritional diet supplement and medical nutritional diet therapy,for the benefit of patients with COVID-19.

“Timing of percutaneous endoscopic gastrostomy tube placement in post-stroke patients does not impact mortality,complications,or outcomes”:Commentary

In this commentary,we summarize some of the key points of the original paper“Timing of percutaneous endoscopic gastrostomy tube placement in post-stroke patients does not impact mortality,complications,or outcomes”and offer support for the proposed results.Specifically,we address how early percutaneous endoscopic gastrostomy(PEG)tube placement may reduce hospital length of stay and costs.We also discuss topics related to the article including PEG weaning and post-stroke nutritional formulation.However,we note that concerns purported by previous studies that early PEG placement may worsen outcomes are not fully addressed,and further research is needed.

A Simple Geospatial Nutrient Budget Model for Assessing Forest Harvest Sustainability across Nova Scotia, Canada

A geospatial GIS-linked spreadsheet model (Nutrient Budget Model—Nova Scotia: NBM-NS) was developed for Nova Scotia to assess the long-term sustainability of forest harvest scenarios as constrained by primary nutrient inputs and outputs due to atmospheric deposition, soil weathering, and leaching. Harvest scenarios refer to user-defined stand-specific removal rates of bole wood, bark, branches, and foliage, based on current or projected forest inventories. These scenarios are evaluated within the context of existing data layers for current climate (mean annual precipitation and air temperatures), atmospheric deposition (N, S, Ca, Mg, K), and soil/substrate types, supplemented by species-specific look-up tables containing expected biomass fractions and nutrient concentrations. This article introduces this model to assess relative site quality and limiting nutrients for red spruce and sugar maple across Nova Scotia. This is followed by an output comparison involving 25 spruce plantations whereby NBM-NS determinations derived using “default” soil survey data are compared with those derived using plantation-specific soil data. Model output shows that (i) Ca and N are the main growth-limiting nutrients across Nova Scotia, (ii) currently projected plantation yields are generally not sustainable on sites underlain by slowly weathering soils, (iii) current soil base cation contents are generally lower than what is reported in historic soil survey reports, and (iv) model results are expected to vary within the context of changing climate, acid deposition levels, and data accuracy.

Dietary counseling based on artificial intelligence for patients with nonalcoholic fatty liver disease

BACKGROUND About 25%of the general population in Japan are reported to have nonalcoholic fatty liver disease(NAFLD).NAFLD and nonalcoholic steatohepatitis carry a risk of progressing further to hepatocellular carcinoma.The primary treatment for NAFLD is dietary therapy.Dietary counseling plays an essential role in dietary therapy.Although artificial intelligence(AI)-based nutrition management software applications have been developed and put into practical use in recent years,the majority focus on weight loss or muscle strengthening,and no software has been developed for patient use in clinical practice.AIM To examine whether effective dietary counseling is possible using AI-based nutrition management software.METHODS NAFLD patients who had been assessed using an AI-based nutrition management software application(Calomeal)that automatically analyzed images of meals photographed by patients and agreed to receive dietary counseling were given dietary counseling.Blood biochemistry tests were performed before(baseline)and 6 mo after(6M follow-up)dietary counseling.After the dietary counseling,the patients were asked to complete a questionnaire survey.RESULTS A total of 29 patients diagnosed with NAFLD between August 2020 and March 2022 were included.There were significant decreases in liver enzyme and triglyceride levels at the 6M follow-up compared to baseline.The food analysis capability of the AI used by Calomeal in this study was 75.1%.Patient satisfaction with the AIbased dietary counselling was high.CONCLUSION AI-based nutrition management appeared to raise awareness of dietary habits among NAFLD patients.However,it did not directly alleviate the burden of registered dietitians,and improvements are much anticipated.

Current situation,consensus and controversy of perioperative nutrition management in pancreatic surgery:A narrative review

Pancreatic surgery contains several major procedures of pancreatectomy.Surgical trauma,severe complications and preoperative nutritional disorders will affect postoperative recovery and clinical outcomes of patients.Perioperative whole-course nutrition management focus on rational nutritional care from admission to discharge even post-hospital follow-up,including preoperative nutritional screening,perioperative nutrition assessment and intervention.The whole-course strategy has been validated in some other fields by RCTs and is also seemed to be suitable for pancreatic surgery.However,few high-grade evidences have been published and controversy still exists.This review aims to reflect the current situation,consensus and controversy of perioperative nutrition management in pancreatic surgery,expecting to provide necessary guidance for clinical research and practice.