Development and validation of 3-Minute Nutrition Screening (3-MinNS) tool for acute hospital patients in Singapore

It is important to detect and treat malnutrition in hospital patients so as to improve clinical outcome and reduce hospital stay. The aim of this study was to develop and validate a nutrition screening tool with a simple and quick scoring system for acute hospital patients in Singapore. In this study, 818 newly admitted patients aged above 18 years old were screened using five parameters that contribute to the risk of malnutrition. A dietitian blinded to the nutrition screening score assessed the same patients using the reference standard, Subjective Global Assessment (SGA) within 48 hours. The sensitivity and specificity were established using the Receiver Operator Characteristics (ROC) curve and the best cutoff scores determined. The nutrition parameter with the largest Area Under the ROC Curve (AUC) was chosen as the final screening tool, which was named 3-Minute Nutrition Screening (3-MinNS). The combination of the parameters weight loss, intake and muscle wastage (3-MinNS), gave the largest AUC when compared with SGA. Using 3-MinNS, the best cutoff point to identify malnourished patients is three (sensitivity 86%, specificity 83%). The cutoff score to identify subjects at risk of severe malnutrition is five (sensitivity 93%, specificity 86%). 3-Minute Nutrition Screening is a valid, simple and rapid tool to identify patients at risk of malnutrition in Singapore acute hospital patients. It is able to differentiate patients at risk of moderate malnutrition and severe malnutrition for prioritization and management purposes.

Validity and reliability of 3-minute nutrition screening (3-MinNS)performed by nurses on oncology and surgical patients

Background Nutrition screening is usually administered by nurses. However, most studies on nutrition screening tools have not used nurses to validate the tools. The 3-Minute Nutrition Screening (3-MinNS) assesses weight loss, dietary intake and muscle wastage, with the composite score of each used to determine risk of malnutrition. The aim of the study was to determine the validity and reliability of 3-MinNS administered by nurses, who are the intended assessors. Methods In this cross sectional study, three ward-based nurses screened 121 patients aged 21 years and over using 3-MinNS in three wards within 24 hours of admission. A dietitian then assessed the patients’ nutritional status using Subjective Global Assessment within 48 hours of admission, whilst blinded to the results of the screening. To assess the reliability of 3-MinNS, 37 patients screened by the first nurse were re-screened by a second nurse within 24 hours, who was blinded to the results of the first nurse. The sensitivity, specificity and best cutoff score for 3-MinNS were determined using the Receiver Operator Characteristics Curve. Results The best cutoff score to identify all patients at risk of malnutrition using 3-MinNS was three, with sensitivity of 89% and specificity of 88%. This cutoff point also identified all (100%) severely malnourished patients. There was strong correlation between 3-MinNS and SGA (r=0.78, p<0.001). The agreement between two nurses conducting the 3-MinNS tool was 78.3%. Conclusion 3-Minute Nutrition Screening is a valid and reliable tool for nurses to identify patients at risk of malnutrition.

Prognostic validity of 3-Minute Nutrition Screening (3-MinNS) in predicting length of hospital stay, readmission, cost of hospitalisation and mortality : a cohort study

Background: It is important to identify patients who are at risk of malnutrition upon hospital admission as malnutrition results in poor outcomes such as longer length of hospital stay, readmission, hospitalisation cost and mortality. The aim of this study was to determine the prognostic validity of 3-Minute Nutrition Screening (3-MinNS) in predicting hospital outcomes in patients admitted to an acute tertiary hospital through a list of diagnosis-related groups (DRG). Methods: In this study, 818 adult patients were screened for risk of malnutrition using 3-MinNS within 24 hours of admission. Mortality data was collected from the National Registry with other hospitalisation outcomes retrieved from electronic hospital records. The results were adjusted for age, gender and ethnicity, and matched for DRG. Results: Patients identified to be at risk of malnutrition (37%) using 3-MinNS had significant positive association with longer length of hospital stay (6.6 ± 7.1 days vs. 4.5 ± 5.5 days, p<0.001), higher hospitalisation cost (S$4540 ± 7190 vs. S$3630 ± 4961, p<0.001) and increased mortality rate at 1 year (27.8% vs. 3.9%), 2 years (33.8% vs. 7.2%) and 3 years (39.1% vs. 10.5%); p<0.001 for all. Conclusions: The 3-MinNS is able to predict clinical outcomes and can be used to screen newly admitted patients for nutrition risk so that appropriate nutrition assessment and early nutritional intervention can be initiated.

Validity and reliability of nutrition screening administered by nurses

Background: Nutrition screening is usually administered by nurses. However, most studies on nutrition screening tools have not used nurses to validate the tools. The 3-Minute Nutrition Screening (3-MinNS) assesses weight loss, dietary intake and muscle wastage, with the composite score of each used to determine risk of malnutrition. The aim of the study was to determine the validity and reliability of 3-MinNS administered by nurses, who are the intended assessors. Methods: In this cross sectional study, three ward-based nurses screened 121 patients aged 21 years and over using 3-MinNS in three wards within 24 hours of admission. A dietitian then assessed the patients’ nutritional status using Subjective Global Assessment within 48 hours of admission, whilst blinded to the results of the screening. To assess the reliability of 3-MinNS, 37 patients screened by the first nurse were re-screened by a second nurse within 24 hours, who was blinded to the results of the first nurse. The sensitivity, specificity and best cutoff score for 3-MinNS were determined using the Receiver Operator Characteristics Curve. Results: The best cutoff score to identify all patients at risk of malnutrition using 3-MinNS was three, with sensitivity of 89% and specificity of 88%. This cutoff point also identified all (100%) severely malnourished patients. There was strong correlation between 3-MinNS and SGA (r=0.78, p<0.001). The agreement between two nurses conducting the 3-MinNS tool was 78.3%. Conclusion: 3-Minute Nutrition Screening is a valid and reliable tool for nurses to identify patients at risk of malnutrition.

Malnutrition in hospitalised patients and clinical outcomes : a missed opportunity?

This research programme has resulted in 5 published papers in international peer-reviewed journals and contributed to better outcomes for patients. It has provided clear evidence that the adverse outcomes of malnutrition are not just a consequence of the disease process, and lead to substantial increases in length of hospital stay, readmission rate, mortality and hospitalisation cost when compared with well-nourished patients of similar diagnoses and complexities. The research programme led to the development and validation of a new nutrition screening tool called 3-Minute Nutrition Screening (3-MinNS). It has also implemented quality improvement initiatives which proved successful in improving the compliance to 3-MinNS and ensuring referral of malnourished or 'at risk' patients to dietitians. Finally, this research programme has provided an effective method for following up malnourished patients post-discharge, which resulted in improved nutritional status and quality of life.

Improving the performance of nutrition screening through a series of quality improvement initiatives

Background Nutrition screening identifies patients at risk of malnutrition to facilitate early nutritional intervention. Studies have reported incompletion and error rates of 30-90% for a range of commonly used screening tools. This study aims to investigate the incompletion and error rates of 3-Minute Nutrition Screening (3-MinNS) and the effect of quality improvement initiatives in improving the overall performance of the screening tool and the referral process for at risk patients. Methods Annual audits were carried out from 2008-2013 on 4467 patients. Value Stream Mapping, Plan-Do-Check-Act cycle and Root Cause Analysis were used in this study to identify gaps and determine the best intervention. The intervention included 1) implementing a nutrition screening protocol, 2) nutrition screening training, 3) nurse empowerment for online dietetics referral of at-risk cases, 4) closed-loop feedback system and 5) removing a component of 3-MinNS that caused the most error without compromising its sensitivity and specificity. Results Nutrition screening error rates were 33% and 31%, with 5% and 8% blank or missing forms, in 2008 and 2009 respectively. For patients at risk of malnutrition, referral to dietetics took up to 7.5 days, with 10% not referred at all. After intervention, the latter decreased to 7% (2010), 4% (2011) and 3% (2012 and 2013), and the mean turnaround time from screening to referral was reduced significantly from 4.3 ± 1.8 days to 0.3 ± 0.4 days (p < 0.001). Error rates were reduced to 25% (2010), 15% (2011), 7% (2012) and 5% (2013) and percentage of blank or missing forms reduced to and remained at 1%. Conclusion Quality improvement initiatives are effective in reducing the incompletion and error rates of nutrition screening, and led to sustainable improvements in the referral process of patients at nutritional risk.

A new low temperature synthesis route of fraipontite (Zn,Al)3(Si,Al)2O5(OH)4

A low temperature synthesis method based on the decomposition of urea at 90°C in water has been developed to synthesise fraipontite. This material is characterised by a basal reflection 001 at 7.44 Å. The trioctahedral nature of the fraipontite is shown by the presence of a 06l band around 1.54 Å, while a minor band around 1.51 Å indicates some cation ordering between Zn and Al resulting in Al-rich areas with a more dioctahedral nature. TEM and IR indicate that no separate kaolinite phase is present. An increase in the Al content however, did result in the formation of some SiO2 in the form of quartz. Minor impurities of carbonate salts were observed during the synthesis caused by to the formation of CO32- during the decomposition of urea.