Medicine (RMH) - Research Publications

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Start date: 2020 × End date: 2020 × Author: Maier, Andrea × Author: Lim, Wen ×

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    Prevalence of malnutrition comparing the GLIM criteria, ESPEN definition and MST malnutrition risk in geriatric rehabilitation patients: RESORT
    Clark, AB ; Reijnierse, EM ; Lim, WK ; Maier, AB (CHURCHILL LIVINGSTONE, 2020-11)
    BACKGROUND & AIMS: The Global Leadership Initiative on Malnutrition (GLIM) has developed new criteria for the diagnosis of malnutrition. This study aimed 1) to determine and compare malnutrition prevalence and risk using the GLIM criteria, European Society for Clinical Nutrition and Metabolism (ESPEN) definition of malnutrition and the Malnutrition Screening Tool (MST) in patients admitted to subacute geriatric rehabilitation wards, 2) to explore the agreement of malnutrition prevalence determined by each definition, and 3) to determine the accuracy of the MST against the GLIM criteria and ESPEN definition as references. METHODS: Geriatric rehabilitation patients (n = 444) from the observational, longitudinal REStORing health of acutely unwell adulTs (RESORT) cohort in Melbourne, Australia were included. The GLIM criteria, ESPEN definition and MST were applied. Accuracy was determined by the sensitivity, specificity and Area Under the Curve (AUC). RESULTS: According to the GLIM criteria, the overall prevalence of malnutrition was 52.0%. The ESPEN definition diagnosed 12.6% of patients as malnourished and the MST identified 44.4% of patients at risk for malnutrition. Agreement was low; 7% of patients were malnourished and at risk for malnutrition according to all three definitions. The accuracy of the MST compared to the GLIM criteria was fair (sensitivity 56.7%, specificity 69.0%) and sufficient (AUC 0.63); MST compared to the ESPEN definition was fair (sensitivity 60.7%, specificity 58.0%) and poor (AUC 0.59). CONCLUSIONS: According to the GLIM criteria, half of geriatric rehabilitation patients were malnourished, whereas the prevalence was much lower applying the ESPEN definition. This highlights the need for further studies to determine diagnostic accuracy of the GLIM criteria compared to pre-existing validated tools.
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    A study protocol for the development of a multivariable model predicting 6- and 12-month mortality for people with dementia living in residential aged care facilities (RACFs) in Australia.
    Bicknell, R ; Lim, WK ; Maier, AB ; LoGiuidice, D (Springer Science and Business Media LLC, 2020)
    BACKGROUND: For residential aged care facility (RACF) residents with dementia, lack of prognostic guidance presents a significant challenge for end of life care planning. In an attempt to address this issue, models have been developed to assess mortality risk for people with advanced dementia, predominantly using long-term care minimum data set (MDS) information from the USA. A limitation of these models is that the information contained within the MDS used for model development was not collected for the purpose of identifying prognostic factors. The models developed using MDS data have had relatively modest ability to discriminate mortality risk and are difficult to apply outside the MDS setting. This study will aim to develop a model to estimate 6- and 12-month mortality risk for people with dementia from prognostic indicators recorded during usual clinical care provided in RACFs in Australia. METHODS: A secondary analysis will be conducted for a cohort of people with dementia from RACFs participating in a cluster-randomized trial of a palliative care education intervention (IMPETUS-D). Ten prognostic indicator variables were identified based on a literature review of clinical features associated with increased mortality for people with dementia living in RACFs. Variables will be extracted from RACF files at baseline and mortality measured at 6 and 12 months after baseline data collection. A multivariable logistic regression model will be developed for 6- and 12-month mortality outcome measures using backwards elimination with a fractional polynomial approach for continuous variables. Internal validation will be undertaken using bootstrapping methods. Discrimination of the model for 6- and 12-month mortality will be presented as receiver operating curves with c statistics. Calibration curves will be presented comparing observed and predicted event rates for each decile of risk as well as flexible calibration curves derived using loess-based functions. DISCUSSION: The model developed in this study aims to improve clinical assessment of mortality risk for people with dementia living in RACFs in Australia. Further external validation in different populations will be required before the model could be developed into a tool to assist with clinical decision-making in the future.