Nutrition Screening Tools and the Prediction of Clinical Outcomes among Chinese Hospitalized Gastrointestinal Disease Patients

The Relationship between Nutritional Risk and the Most Common Chronic Diseases in Hospitalized Geriatric Population from Central Poland

The aim of this study was to assess the relationship between Nutrition Risk Screening 2002 (NRS-2002) and the prevalence of concomitant chronic diseases among hospitalized older adults. This study included 2122 consecutively hospitalized older participants with an average age of 82 years. The criteria to participate were the ability to communicate and give consent. In multivariate design, the prevalence of nutritional risk with at least 3 points in the NRS-2002 score was associated with the presence of stroke, atrial fibrillation, dementia and pressure ulcers. Patients with arterial hypertension, lipid disorders, osteoarthritis and urine incontinence had a significantly lower (better) NRS-2002 score. The explanation of the inverse relationship between some disorders and nutritional risk may be their occurrence in relatively earlier age and the relationship with body mass index. In conclusion, the study revealed which medical conditions coexist with the increased nutritional risk in a “real-world” hospitalized geriatric population. The hospital admission of an older subject with stroke, atrial fibrillation, dementia or pressure ulcers should primarily draw attention to the nutritional risk of the patient.

Spatial distribution of various forms of malnutrition among reproductive age women in Nepal: A Bayesian geoadditive quantile regression approach

Addressing both the under-and over-nutritional status of women is an eminent challenge for developing countries like Nepal. This paper examined a critical analysis of factors associated with various forms of malnutrition using Bayesian geoadditive quantile regression approach and assessed spatial variations of malnutrition among Nepalese women using Asian cut-off values. Data drawn from the 2016 Nepal Demographic and Health Survey was utilized to assess the spatial distributions of underweight, overweight and obesity at the provincial level. Spatial and nonlinear components were estimated using Markov random fields and Bayesian P-splines, respectively. The analysis of 4,338 women confirmed that women living in extremely urbanized areas and in Province 1, Province 3, and Province 4 were more likely to be overweight/obese. Similarly, the likelihood of being underweight was prominently high among women residing in rural municipality and women residing in Province 2 and Province 7. Women from the richest and richer quintiles, and with primary education were more likely to be obese. Furthermore, currently-working women and women having access to protected water source were less likely to be obese while improved toilet and access to electricity facility were associated with obesity. Women with access to newspaper and radio were less prone to obesity. Inconsistent distribution of under- and over-nutrition existed in Nepal, given that the high prevalence of overweight/obesity among women living in metropolitan and undernutrition among rural women. Specific intervention measures, addressing location-specific nutrition issues are urgent. Rigorous implementation of strategies incorporated in the national nutrition plan is called for to curb the burden of overweight/obesity. Involving mass media to promote healthier lifestyle and nutritious food could be advantageous at the population level, especially in rural municipalities.

Nutrition Risk Assessed by STRONGkids Predicts Longer Hospital Stay in a Pediatric Cohort: A Survival Analysis

BACKGROUND

We evaluated the impact of Screening Tool for Risk on Nutritional Status and Growth (STRONGkids) classification in time to discharge and verify whether the nutrition risk assessed by this method is an independent predictor of hospital length of stay (LOS) in pediatric inpatients.

METHODS

A cohort study was conducted in a Brazilian hospital from February 2014 to July 2018. The outcome in the survivor analysis was hospital discharge. Kaplan-Meier curves were used to estimate the cumulative survival time according to STRONGkids categories. Multivariable Cox proportional hazard models were fitted, and the adjusted hazard ratio (aHR), with respective 95% CI, was used to measure the strength of association. The discriminatory ability of STRONGkids was verified by a receiver operating characteristic curve RESULTS: A total 641 patients were included in the study: 54.9% males, median age of 2.8 years. The frequencies of low, moderate, and high nutrition risk were 15.6%, 63.7%, and 20.7%, respectively. The mean LOS was 5.9 days. Survival curves differed significantly according to nutrition-risk categories. Patients classified as high risk had a 52% less chance of hospital discharge when compared with low-risk patients (aHR: 0.48; 95% CI, 0.35-0.65). STRONGkids score ≥ 3 showed the best discriminatory power to identify LOS. From this score, there was a significant increase in the days of hospitalization.

CONCLUSION

The nutrition risk assessed by STRONGkids independently predicts LOS in pediatric patients. For this outcome, patients with 3 points (moderate risk) should be treated with the same priority as those with high risk.

Comparison of nutritional screening tools to assess nutritional risk and predict clinical outcomes in Mexican patients with digestive diseases

BACKGROUND

The prevalence of malnutrition remains high in hospitals but no "gold standard" has been established to identify nutritional risks adequately. The Nutrition Risk Screening-2002 (NRS-2002), Subjective Global Assessment (SGA), and Controlling Nutritional Status Index (CONUT) are widely used screening tools, but their efficacy has not yet been compared in Mexican patients. Here, we aimed to compare the efficacy of these tools in identifying nutritional risks within the first 48 h of admission in a group of patients with gastrointestinal diseases.

METHODS

This was a cross-sectional study of 196 patients. The results of the screening tools, length of hospital stay, serum albumin and cholesterol concentrations, lymphocyte counts, age, body mass index (BMI), complications, and mortality were analyzed. Kappa (κ) statistics were applied to determine the degree of agreement between tools. The performances of the screening tools in predicting complications and mortality were assessed using binary logistic regression.

RESULTS

The NRS-2002, SGA, and CONUT tools identified nutritional risk in 67, 74, and 51% of the patients, respectively. The observed agreements between tools were: NRS2002/SGA, κ = 0.53; CONUT/NRS-2002, κ = 0.42; and SGA/CONUT, κ = 0.36. Within age groups, the best agreement was found in those aged 51-65 years (κ = 0.68). CONUT and length of stay were both predictive for the number of complications. The number of complications and serum cholesterol concentrations were predictive for mortality.

CONCLUSIONS

The proportion of patients identified as having nutritional risk was high using all three screening tools. SGA, NRS-2002, and CONUT had similar capacities for screening risk, but the best agreement was observed between NRS-2002 and SGA. Only CONUT predicted complications, but none of these tools performed well in predicting mortality.