6 research outputs found

    Malnutrition and its impact on cost of hospitalization, length of stay, readmission and 3-year mortality

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    Background &amp; aims The confounding effect of disease on the outcomes of malnutrition using diagnosis-related groups (DRG) has never been studied in a multidisciplinary setting. This study aims to determine the impact of malnutrition on hospitalisation outcomes, controlling for DRG. Methods Subjective Global Assessment was used to assess the nutritional status of 818 patients within 48 hours of admission. Prospective data were collected on cost of hospitalisation, length of stay (LOS), readmission and mortality up to 3 years post-discharged using National Death Register data. Mixed model analysis and conditional logistic regression matching by DRG were carried out to evaluate the association between nutritional status and outcomes, with the results adjusted for gender, age and race. Results Malnourished patients (29%) had longer hospital stays (6.9±7.3 days vs. 4.6±5.6 days, p<0.001) and were more likely to be readmitted within 15 days (adjusted relative risk = 1.9, 95%CI 1.1–3.2, p=0.025). Within a DRG, the mean difference between actual cost of hospitalisation and the average cost for malnourished patients was greater than well-nourished patients (p=0.014). Mortality was higher in malnourished patients at 1 year (34% vs. 4.1 %), 2 years (42.6% vs. 6.7%) and 3 years (48.5% vs. 9.9%); p<0.001 for all. Overall, malnutrition was a significant predictor of mortality (adjusted hazard ratio = 4.4, 95%CI 3.3-6.0, p<0.001). Conclusions Malnutrition was evident in up to one third of inpatients and led to poor hospitalisation outcomes, even after matching for DRG. Strategies to prevent and treat malnutrition in the hospital and post-discharge are needed

    Irregular meal timing is associated with Helicobacter pylori infection and gastritis

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    Background Helicobacter pylori (HP) is associated with chronic gastritis and gastric cancer, and more than half of the world’s population is chronically infected. The aim of this retrospective study was to investigate whether an irregular meal pattern is associated with increased risk of gastritis and HP infection. Methods The study involved 323 subjects, divided into three groups: subjects with HP infection and gastritis, with gastritis, and a control group. Subjects were interviewed on eating habits and meal timing. Multivariate logistic regression was used to compare groups. Adjusted odds ratios (OR) were derived controlling for gender, age, stress and probiotic consumption. Results Subjects who deviated from their regular meals by 2 hours or more had a significantly higher incidence of HP infection with gastritis (adjusted OR= 13.3, 95% CI 5.3–33.3, p<0.001) and gastritis (adjusted OR=6.1, 95% CI 2.5–15.0, p<0.001). Subjects who deviated their meals by 2 hours or more, twice or more per week, had an adjusted OR of 6.3 and 3.5 of acquiring HP infection with gastritis (95% CI 2.6–15.2, p<0.001) and gastritis (95% CI 1.5–8.5, p<0.001) respectively. Conclusion Frequent deviation in meal timing over a prolonged period appears associated with increased risk of developing HP infection and gastritis

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    Background & aims\ud \ud The confounding effect of disease on the outcomes of malnutrition using diagnosis-related groups (DRG) has never been studied in a multidisciplinary setting. This study aims to determine the impact of malnutrition on hospitalisation outcomes, controlling for DRG.\ud \ud Methods\ud \ud Subjective Global Assessment was used to assess the nutritional status of 818 patients within 48 hours of admission. Prospective data were collected on cost of hospitalisation, length of stay (LOS), readmission and mortality up to 3 years post-discharged using National Death Register data. Mixed model analysis and conditional logistic regression matching by DRG were carried out to evaluate the association between nutritional status and outcomes, with the results adjusted for gender, age and race.\ud \ud Results\ud \ud Malnourished patients (29%) had longer hospital stays (6.9±7.3 days vs. 4.6±5.6 days, p<0.001) and were more likely to be readmitted within 15 days (adjusted relative risk = 1.9, 95%CI 1.1–3.2, p=0.025). Within a DRG, the mean difference between actual cost of hospitalisation and the average cost for malnourished patients was greater than well-nourished patients (p=0.014). Mortality was higher in malnourished patients at 1 year (34% vs. 4.1 %), 2 years (42.6% vs. 6.7%) and 3 years (48.5% vs. 9.9%); p<0.001 for all. Overall, malnutrition was a significant predictor of mortality (adjusted hazard ratio = 4.4, 95%CI 3.3-6.0, p<0.001).\ud \ud Conclusions\ud \ud Malnutrition was evident in up to one third of inpatients and led to poor hospitalisation outcomes, even after matching for DRG. Strategies to prevent and treat malnutrition in the hospital and post-discharge are needed

    Development and validation of 3-minute nutrition screening (3-minNS) tool for acute hospital patients in Singapore

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    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

    Assessing differences in utility scores: a comparison of four widely used preference-based instruments.

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    OBJECTIVES: To characterize the differences in utility scores (dUTY) among four commonly used preference-based Health-Related Quality of Life instruments, to evaluate the potential impact of these differences on cost-utility analyses (CUA), and to determine if sociodemographic/clinical factors influenced the magnitude of these differences. METHODS: Consenting adult Chinese, Malay and Indian subjects in Singapore were interviewed using Singapore English, Chinese, Malay or Tamil versions of the EQ-5D, Health Utilities Index Mark 2 (HUI2) and Mark 3 (HUI3), and SF-6D. Agreement between instruments was assessed using Bland-Altman (BA) plots. Changes in incremental cost-utility ratio (ICUR) from dUTY were investigated using eight hypothetical decision trees. The influence of sociodemographic/clinical factors on dUTY between instrument pairs was studied using multiple linear regression (MLR) models for English-speaking subjects (circumventing structural zero issues). RESULTS: In 667 subjects (median age 48 years, 59% female), median utility scores ranged from 0.80 (95% confidence interval [CI] 0.80, 0.85) for the EQ-5D to 0.89 (95% CI 0.88, 0.89) for the SF-6D. BA plots: Mean differences (95% CI) exceeded the clinically important difference (CID) of 0.04 for four of six pairwise comparisons, with the exception of the HUI2/EQ-5D (0.03, CI: 0.02, 0.04) and SF-6D/HUI2 (0.02, CI: 0.006, 0.02). Decision trees: The ICER ranged from $94,661/QALY (quality-adjusted life-year; 6.3% difference from base case) to 100,693 dollars/QALY (0.3% difference from base case). MLR: Chronic medical conditions, marital status, and Family Functioning Measures scores significantly (P-value < 0.05) influenced dUTY for several instrument pairs. CONCLUSION: Although CIDs in utility measurements were present for different preference-based instruments, the impact of these differences on CUA appeared relatively minor. Chronic medical conditions, marital status, and family functioning influenced the magnitude of these differences

    The association of body mass index with health-related quality of life: an exploratory study in a multiethnic Asian population.

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    OBJECTIVES: To evaluate the association between body mass index (BMI) and health-related quality of life (HRQoL) in a multiethnic Asian population in Singapore, and to explore if the World Health Organization (WHO) recommendation of alternative BMI cutoffs for Asians could be further strengthened by evidence of higher risk of impaired HRQoL using these criteria. METHODS: Consenting English, Chinese, Malay and Tamil-speaking primary care patients (age >or= 21 years) were interviewed using English/their respective mother tongue versions of the EQ-5D/EQ-VAS, Health Utilities Index (HUI2 & HUI3) and the SF-6D. We first evaluated the relationship between BMI and HRQoL (overall and individual attributes for each instrument) using multiple linear/logistic regression (where appropriate) to adjust for factors known to affect HRQoL. We next reorganized BMI into five categories (reflecting the differences in cutoffs between International/Asian classifications) and evaluated if median HRQoL scores were significantly different across these categories. RESULTS: Among 411 participants [response rate: 87%; median age: 51 years; obese: 19% (International); 33% (Asian)], after adjusting for sociodemographic and other factors, a tendency for underweight and obese subjects to report lower overall HRQoL scores was observed for most instruments. At the individual attribute level, obese subjects reported significantly lower HUI2 pain scores (regression coefficient: -0.035, P = 0.029) and greater odds of reporting problems for SF-6D role-limitations (odds ratio: 2.9, P = 0.005). Median overall HRQoL scores were not significantly different across the five BMI categories. CONCLUSION: Consistent with available studies, obese subjects reported worse HRQoL than normal-weight subjects. That underweight subjects also reported worse HRQoL is interesting and requires confirmation. HRQoL was similar in Asians using either WHO criteria
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