Poor nutritional status of older subacute patients predicts clinical outcomes and mortality at 18 months of follow-up

Charlton, Karen E; Nichols, Claire; Bowden, Steven; Milosavljevic, Marianna; Lambert, Kelly; Barone, L; Mason, Michelle; Batterham, Marijka

doi:10.1038/ejcn.2012.130

Cited by 101 publications

(92 citation statements)

References 32 publications

(25 reference statements)

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“…15,20,[22][23][24] However, the majority of these studies do not conduct any regression analysis 15,[22][23][24] and only measure in-hospital mortality. 15,23,24 One of these studies performes both regression analyses and measures long term mortality.…”

Section: Discussionmentioning

confidence: 99%

“…15,23,24 One of these studies performes both regression analyses and measures long term mortality. 20 This Australian study (n = 476) adjust the analyses for major disease classifications at admission and reports a hazard ratio for death in the malnourished group of 3.4 (1.07-10.87) after 18 months. 20 However, this retrospective study includes only individuals that had survived 12 months.…”

Section: Discussionmentioning

confidence: 99%

“…20 This Australian study (n = 476) adjust the analyses for major disease classifications at admission and reports a hazard ratio for death in the malnourished group of 3.4 (1.07-10.87) after 18 months. 20 However, this retrospective study includes only individuals that had survived 12 months. This introduces bias and hinders a direct comparison with our cohort, where a substantial mortality was noticed the first year of follow-up.…”

Section: Discussionmentioning

confidence: 99%

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Nutritional status predicts preterm death in older people: A prospective cohort study

et al. 2014

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

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Nutritional status predicts preterm death in older people: A prospective cohort study

et al. 2014

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“…An additional 35-39 % have been categorised as at risk of malnutrition. Malnutrition increases the risk of falls, osteoporosis, fractures, chronic disease, prolonged hospitalisation, and increased complications, all of which heighten the risk of mortality (5)(6)(7). Meals on Wheels (MOW), Australia, is a non-for-profit organization that provides both hot and frozen meals to frail older people, as well as younger people living with disabilities.…”

Section: Introductionmentioning

confidence: 99%

“It could probably help someone else but not me”: A feasibility study of a snack programme offered to meals on wheels clients

Charlton

Walton

Moon

et al. 2012

J Nutr Health Aging

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Objectives Community-based services, such as Meals on Wheels (MOW), allow older adults to remain in their homes for as long as possible. Many MOW recipients experience decreased appetite that limits intake at mealtimes. This pilot study aimed to determine the feasibility of providing high protein high energy snacks to improve nutrient intakes of MOW clients in a regional centre of New South Wales, Australia.Participants A convenience sample of 12 MOW clients.Intervention Participants received snacks five times a week, in addition to their usual MOW order, for four weeks.Measurements Nutritional status was assessed using the Mini Nutritional Assessment tool. Pre-post changes in dietary intake were assessed using a diet history and food frequency questionnaire. Qualitative interviews conducted in clients' homes were digitally recorded, transcribed verbatim, and themes identified.Results Post-intervention, there was a trend for an increased energy (mean = +415kJ (SD=1477)/day) and protein (+7.2 (±14.06) g/day) intake. MNA scores significantly increased (P= 0.036) and proportion of respondents categorised as 'malnourished' or 'at risk of malnutrition' decreased from 17% to 8%, and 67% to 25%, respectively (P Conclusion Provision of an additional daily mid-meal snack may be a useful addition to existing MOW services, for improved energy and protein intakes. However, not all MOW clients at risk of malnutrition perceived the snacks to be beneficial to them. Keywordsprobably, help, someone, wheels, else, but, not, me, programme, clients, offered, could, meals, feasibility, study, snack

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“…The presence of malnutrition adversely affects clinical outcomes and indicates a need to target this population (3) . Many factors alter nutritional status (4) ; therefore, it is difficult to estimate the optimal approach to nutritional assessment.…”

mentioning

confidence: 99%

Ten-year all-cause mortality in hospitalized non-surgical patients based on nutritional status screening

Kissova¹,

Rosenberger²,

Goboova³

et al. 2015

Public Health Nutr.

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Objective: Malnutrition is common in patients admitted to hospital due to acute illness and contributes to negative patient outcomes. In Slovakia there is a lack of relevant data on malnutrition in hospitalized patients, particularly based on chronic co-morbidity and survival. The aim of the present study was to explore the prevalence of malnutrition in hospitalized chronic patients, its relationship to co-morbidity and its impact on 10-year survival. Design: Retrospective cohort study. Setting: Nutritional status was estimated by Subjective Global Assessment (SGA), BMI and serum albumin level. Survival was assessed from the National Insurance Registry over a 10-year period. The association between nutritional status measured by SGA and 10-year survival controlling for age, gender, BMI and serum albumin was analysed using Cox regression. Subjects: Data were taken from the medical records of 202 consecutively admitted chronic patients. Results: Median age was 63·5 years; 55·4 % were males; median BMI was 25·9 kg/m 2 ; median serum albumin level was 39·0 g/l. Based on SGA evaluation, 38·1 % did not have sufficient nutritional status (SGA classification B and C). Malnutrition was more common in patients who were older (P = 0·023), with lower BMI (P < 0·001), who had gastrointestinal (P = 0·049) and oncologic co-morbidity (P = 0·021) and lower albumin level (P = 0·049). In-hospital mortality was 3 %, but during the following 10 years 52 % died. Cox regression analysis controlling for age, gender, BMI and serum albumin showed that SGA was an independent predictor of death (hazard ratio = 1·55; 95 % CI 1·04, 2·32; P = 0·031). Conclusions: SGA is a simple screening tool that can be routinely used in hospitalized Slovak medical patients to predict the risk of death. Improving patient nutrition could thus reduce mortality.

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Poor nutritional status of older subacute patients predicts clinical outcomes and mortality at 18 months of follow-up

Cited by 101 publications

References 32 publications

Nutritional status predicts preterm death in older people: A prospective cohort study

Nutritional status predicts preterm death in older people: A prospective cohort study

“It could probably help someone else but not me”: A feasibility study of a snack programme offered to meals on wheels clients

Ten-year all-cause mortality in hospitalized non-surgical patients based on nutritional status screening

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