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Meta-analyses
Nutritional support after hospital discharge improves long-term
mortality in malnourished adult medical patients: Systematic review
and meta-analysis
Nina Kaegi-Braun
a
,
1
, Fiona Kilchoer
b
,
1
, Saranda Dragusha
c
,
1
, Carla Gressies
a
,
Montserrat Faessli
b
, Filomena Gomes
d
,
e
, Nicolaas E. Deutz
f
, Zeno Stanga
g
,
Beat Mueller
a
, Philipp Schuetz
a
,
*
a
Medical University Department, Clinic for Endocrinology/Metabolism/Clinical Nutrition, Kantonsspital Aarau, Aarau and Medical Faculty of the University
of Basel, Switzerland
b
Medical Faculty of the University of Basel, Switzerland
c
Medical Faculty of the Universit
a Della Svizzera Italiana, Switzerland
d
The New York Academy of Sciences, New York, NY, USA
e
NOVA Medical School, Universidade NOVA de Lisboa, Lisboa, Portugal
f
Center for Translational Research in Aging &Longevity, Department of Health &Kinesiology, Texas A&M University, College Station, TX, USA
g
Division of Diabetology, Endocrinology, Nutritional Medicine, &Metabolism, University Hospital Inselspital Bern, University of Bern, Bern, Switzerland
article info
Article history:
Received 2 May 2022
Accepted 21 September 2022
Key words:
Malnutrition
Outpatient
Post-discharge
Nutritional support
Nutritional therapy
summary
Background &aims: In patients with malnutrition there is an increased long-term risk for mortality
beyond the preciding hospital stay. We investigated the effects of postdischarge nutritional support in
the outpatient setting on all-cause mortality in the populaton of malnourished medical patients in a
systematic review of randomized controlled trials.
Methods: We searched MEDLINE and EMBASE, from inception to December 21, 2022. Randomized-
controlled trials investigating nutritional support in medical patients following hospital discharge vs.
control group (usual care, placebo and no nutritional support) were included. Data were independently
extracted by two authors and were pooled using random effects model. Our primary outcome was all
cause-mortality up to 12-months (end of intervention) of hospital discharge.
Results: We included 14 randomized-controlled trials with a total of 2438 participants and mostly mod-
erate trial quality. Compared to the control group, patients receiving outpatient nutritional support had
lower mortality (13 trials, odds ratio [OR] 0.63, 95% confidence interval [CI] 0.48 to 0.84, p ¼0.0 01, I
2
¼1%).
Nutritional support was also associated with a significant increase in the mean daily intake of energy
(568 kcal, 95% CI 24 to 1,113, p ¼0.04), proteins (24 g, 95% CI 7 to 41), p ¼0.005) and body weight (1.1 kg, 95%
CI 0.6 to 1.7), p <0.001). No differences were found on hospital readmissions and handgrip strength.
Conclusions: This meta-analysis of randomized-controlled trials with mostly moderate trial quality
suggests that nutritional support in the outpatient setting significantly increases nutritional intake as
well as body weight, and importantly improves survival. Further large-scale and high-quality inter-
vention trials are needed to confirm these findings.
©2022 Elsevier Ltd and European Society for Clinical Nutrition and Metabolism. All rights reserved.
1. Introduction
Disease-related malnutrition (DRM) is a syndrome associated
with increased morbidity, disability, short- and long-term mortal-
ity, impaired recovery from illness, and cost of care [1,2]. The
findings of numerous randomized-controlled trials document that
nutritional care in the hospital setting improves survival and
clinical outcomes [3e5]. For this reason, current international
*Corresponding author. University Department of Medicine, Kantonsspital
Aarau, Tellstrasse, CH-5001, Aarau, Switzerland. Fax: þ41 (0)62 838 4100.
E-mail address: schuetzph@gmail.com (P. Schuetz).
1
Equally contributing first authors.
Contents lists available at ScienceDirect
Clinical Nutrition
journal homepage: http://www.elsevier.com/locate/clnu
https://doi.org/10.1016/j.clnu.2022.09.011
0261-5614/©2022 Elsevier Ltd and European Society for Clinical Nutrition and Metabolism. All rights reserved.
Clinical Nutrition 41 (2022) 2431e2441
guidelines recommend a proactive screening of patients at hospital
admission followed by individualized nutritional support during
the hospital stay in patients at risk [6,7].
However, malnutrition not only influences hospital outcomes,
but also impacts long-term prognosis of patients. In fact, long-term
mortality associated with malnutrition is very high in multimorbid
medical patients [2,8]. A recent follow-up study of patients
included in the EFFORT trial [4] reported a substantial increase in 5-
year mortality risk related to more severe malnutrition, increasing
from approximately 50%e60% with a nutritional risk screening
(NRS 2002) score increase from 3 to 5 [2]. Nevertheless, the effects
of in-hospital nutritional support, which was stopped at hospital
discharge, did not show a legacy effect beyond 6 months [8].
While there has been strong research data regarding the
inhospital setting and short-term mortality, it remains unclear at
present whether continued nutritional support after hospital
discharge positively impacts survival in the long run. Some soci-
eties, for example the British Association for Parenteral and Enteral
Nutrition recommend to identify and consecutely treat patients
with malnutrition in the community setting [9]. However, due to
the paucity of conclusive evidence regarding long-term benefitof
outpatient nutrition, lack of resources and financial aspects,
nutritional support is often discontinued after discharge in clinical
practice without continuation in the community setting.
Herein, our aim was to investigate the association between post-
discharge nutritional support and clinical outcomes in hospitalized
medical patients at risk of malnutrition by doing a systematic
search and meta-analysis.
2. Methods
The methodology used for this meta-analysis followed a pre-
specified Cochrane protocol [10] and the Preferred Reporting Items
for Systematic Reviews and Meta-analyses (PRISMA) reporting
guidelines [11].
2.1. Data sources and searches
The literature searches were conducted in MEDLINE and EMBASE
databases. The last update was done in December 21st, 2021 and one
additionalstudywasidentifiedand includedforanalysisin January 2022.
An example of the search strategy used in MEDLINE is provided
in the eMethods in the Supplement. In addition, we searched bib-
liographies of review articles and the ClinicalTrials.gov registry for
ongoing or unpublished trials. There were no language restrictions.
2.2. Study selection
We included RCTs investigating the effect of nutritional in-
terventions in malnourished or nutritionally at-risk adult patients
in the community setting after a hospitalization on medical wards.
The patients in the included RCTs were aged 18 years or older
and discharged home from a medical ward after they have been
identified as malnourished or at risk for malnutrition during
hospitalization.
Varios methods for malnutrition screening or assessment of
nutritional status were considered for inclusion, such as low body
mass index (BMI), significant weight loss in recent months, a vali-
dated nutritional assessment or screening tool (e.g., Mini-
Nutritional Assessment (MNA), NRS-2002, Subjective Global
Assessment (SGA), Patient-Generated SGA (PG-SGA)). We only
included patients who were initially hospitalized in an acute care
institution on general medical wards or wards of any other medical
speciality (e.g., gastro-enterology, cardiology, pneumology, general
internal medicine, infectious diseases, nephrology, oncology).
We did not include trials focusing on surgical patients, intensive
care unit patients or patients under palliative care. If trials were
reporting results of mixed medical/surgical populations, we only
included those studies with at least 75% medical patients. If there
was no information about the distribution of medical/surgical pa-
tients we excluded the study. Focusing only on patients living at
home post hospital discharge, we also excluded trials carried in
nursing homes or long-term care facilities settings.
2.3. Types of interventions
Studies were eligible for inclusion if the intervention consisted
of any type of nutritional support such as: (a) dietary advice (in-
dividual dietary counselling to reach nutritional targets delivered
by dieticians through at-home visits or via telephone) (b) food
fortification (e.g. with protein powders), (c) oral nutrition supple-
ments (e.g. ready-to-drink-liquid, sip-feed), (d) snacks between
meals and (e) enteral tube feeding or anycombination of (a)-(e). We
did not include any trials with parenteral nutrition interventions,
neither in combination with other nutritional support nor exclu-
sively. Supplementation of specific vitamins (e.g. vitamin D) or
other micronutrients as well as hormonal therapies (e.g. testos-
terone) were not included in our analysis.
Interventions were initiated either during hospitalization or
after discharge and had to continue at least 2 weeks in the com-
munity setting.
Control group procedures were: (a) no nutritional support, (b)
usual care (nutritional management at the discretion of the treating
physician) or (c) placebo treatment.
In sensitivity analyses we stratified trials by the prespecified
subgroups setting, type and duration of intervention, as well as age
and admission diagnosis. There was a lack of trials with additional
physical activity and grading of malnutrition status, therefore, the
preplanned analysis was not possible. An exploratory subgroup
analysis on sex and protein content of the nutritional intervention
was implemented. Subgroup analysis was taken into consideration
if the amount of trials included in a subgroup were 3.
2.4. Outcomes
Our primary endpoint was all-cause mortality defined as death
from any cause at the end of the intervention (up to 1 year after
randomization). Secondary outcomes included non-elective read-
mission rates, hand grip strength as a functional outcome, changes
in anthropometric measurements (weight change, BMI), daily en-
ergy (kcal), and protein (g) intake. Additionally, we assessed
adverse events.
2.5. Data extraction and quality assessment
Each abstract was screened by two reviewers independently and
relevant data of studies meeting the inclusion criteria were
extracted by means of a standardized data extraction template.
Discrepancies were resolved through consensus or recourse to a
third review author. The reviewers also assessed risk for bias using
the criteria recommended by Cochrane Collaboration [10].
We tested two-sided with a significance level of
a
¼0.05. Re-
view Manager version 5.4 (from the Cochrane Collaboration)
generated the figures and calculations.
2.6. Statistical analysis
2.6.1. Data synthesis and analysis
We expressed dichotomous data as odds ratios (ORs) or risk
ratios (RRs) with 95% confidence intervals (CIs). Continuous data
N. Kaegi-Braun, F. Kilchoer, S. Dragusha et al. Clinical Nutrition 41 (2022) 2431e2441
2432
Table 1
Overview of included studies.
Source Country Journal Amount of
randomized
patients
Ward Patient
population
Setting of
intervention
Type of intervention Control
Gazzotti, C.,
2003 [17]
Belgium Age and Ageing 80 Geriatric 75 years, admitted for
acute conditions,
informed consent, at
risk of undernutrition
based on their initial
MNA score between 17
and 23.5
inhospital and
community
200 ml sweet or salty
sip feed twice daily
(500 kcal, 21 g protein
per day) throughout
hospitalization and
convalescence
usual care
Edington, J.,
2004 [23]
United Kingdom Clinical nutrition 100 Undefined >65 years, to be
discharged from
hospital with either (i) a
BMI <20 kg/m
2
, or (ii)
BMI >20 but <25 kg/m
2
with documented
evidence of weight loss
of 10% of their body
weight in the 6 months
prior to the study
period or 5% in the 3
months prior to the
study, score 7 on the
Abbreviated Mental
Test
community different types of ONS usual care
Price, R., 2005
[18]
United Kingdom Gerontology 136 medical and geriatric BMI 24 kg/m
2
and
triceps skin fold
thickness (TSF) or mid-
arm muscle
circumference (MAMC)
below the 10th centile
and/or a weight loss
65% during hospital
stay, aged 75 years
community 2 servings of ONS/day
for 8 weeks
usual care
Feldblum, I.,
2010 [24]
Israel The American
Geriatrics Society
259 internal medicine 65 years, at
nutritional risk (MNA
less than 10), weight
loss of more than 10%
during the 6 months
before the study period
inhospital and
community
Dietary advice during
hospitalization and
post discharge, food
supplements, vitamins
and minerals if
necessary
usual care or
dietary advice once
during
hospitalization
Neelemaat, F.,
2011 [20]
Netherlands Journal of the
American Medical
Directors Association
210 general internal
medicine,
rheumatology,
gastroenterology,
dermatology,
nephrology,
orthopedics,
traumatology, and
vascular surgery
60 years of age,
expected length of
hospital admission >2
days, BMI of 20 kg/m
2
or lower and/or, 5% or
more unintentional
weight loss in the
previous month and/or
10% or more
unintentional weight
loss in the previous 6
months.
inhospital and
community
energy- and protein
enriched diet, two
additional servings of
ONS, calcium-
usual care
vitamin D supplement,
telephone counseling
by a dietitian for 3
months after discharge
(continued on next page)
N. Kaegi-Braun, F. Kilchoer, S. Dragusha et al. Clinical Nutrition 41 (2022) 2431e2441
2433
Table 1 (continued )
Source Country Journal Amount of
randomized
patients
Ward Patient
population
Setting of
intervention
Type of intervention Control
Beck, A. M.,
2013 [25]
Denmark Clinical Rehabilitation 152 Geriatric 65 years, at
nutritional risk
according to the level 1
screen in NRS 2002,
hospitalized for 2
days, BMI <20.5 kg/m
2
;
and/or weight loss
within the last 3
months; and/or a
reduced dietary intake
in the last week; and/or
serious ill (e.g. in
intensive therapy)
community three GP visits post
discharge plus three
visits of a dietician for
dietary counselling
three GP visits post
discharge, without
dietician
Beck A., 2015
[26]
Denmark Clinical rehabilitation 71 geriatric/orthopedic
ward
at nutritional risk,
receiving nutritional
support at the wards,
were planned to be
discharged to their
private home
community discharge Liaison-Team
in cooperation with a
dietician
- three home visits to
implement a
nutritional care plan
(dietary counselling,
subscription of ONS)
discharge Liaison-
Team without a
dietician
Deutz, N. E.,
2016 [3] and
Matheson,
M. E.,
2020*
16
USA Clinical nutrition 652 internal medicine >65 years, recent
hospital admission,
primary diagnosis of
CHF, AMI, PNA, or
COPD, SGA class of B or
C
inhospital and
community
2 servings/day of high
protein ONS (HP-HMB)
2 servings/day of
placebo
supplement
Bonilla-
Palomas, J. L.,
2016 [28]
Spain Archives of Medical
Research
120 Undefined >18 years, hospitalized
for acute heart failure,
either decompensated
chronic heart failure or
new onset heart failure,
also presenting
malnutrition (MNA
score)
inhospital and
community
diet optimization,
specific
recommendations and
nutritional supplement
prescriptions
usual care
Andersson, J.,
2017 [21]
Norway J Nutr Health Aging 115 rehabilitation >18 years,
undernourished or at
risk of disease-related
malnutrition (>3 points
using the NRS 2002),
and residing in the
capital Oslo or the
nearby municipalities
of Asker or Bærum,
communicate in
Norwegian and to
provide written
informed consent
community Dietary advice,
individual nutritional
plan, three telephone
calls and one home visit
for nutritional
counselling
no nutritional
support after
discharge
Sharma, Y.,
2017 [19]
Australia QJM: An International
Journal of Medicine
148 acute medical >60 years,
malnourished by PG-
SGA (classes B and C)
inhospital and
community
individualized nutrition
care plan plus monthly
post-discharge
telehealth follow-up
usual care
N. Kaegi-Braun, F. Kilchoer, S. Dragusha et al. Clinical Nutrition 41 (2022) 2431e2441
2434
was expressed as mean differences (MDs) with 95% CIs and data
were pooled using random effects model.
Missing data was imputed following the Cochrane Handbook
[10], whenever possible and reasonable: we used the median to
estimate the mean in trials with more than 25 patients [12]. When
the variance was not given, it was estimated with the 95% CI [10,12].
To approximate the SD for the change in an outcome, we calculated
the mean from baseline and follow-up, when nothing else was
applicable.
2.6.2. Assessment of heterogeneity and publication bias
We identified heterogeneity (inconsistency) through visual in-
spection of the forest plots and considered the I
2
statistic, to assess
the impact of heterogeneity on the meta-analysis [13]. An I
2
statistic
of 50% or more indicates a substantial level of heterogeneity [14].
We used visual inspection of funnel plots to assess publication
bias. Owing to several possible explanations for funnel plot asym-
metry, we interpreted these results carefully [15].
3. Results
3.1. Systematic literature search
Our systematic literature search identified 293 titles and ab-
stracts of potentially eligible studies from electronic databases and
56 additional records through contact with experts, systematic
reviews/meta-analyses and handsearching of literature. After
duplicate removal, 310 records were screened, and 83 full texts
were assessed for eligibility. Of these, 14 trials with a total of 2438
randomized and 2330 analysed patients were included in the final
meta-analysis. A flow chart is displayed ineFig. 3 in the Supplement.
Most included RCTs were single-centre and included heteroge-
neous adult medical or mixed medical/surgical inpatients. Studies
were conducted between 2004 and December 2021 in different,
mostly European, countries. Interventions were mainly oral feeding
strategies and dietary advice. None of the included studies per-
formed enteral tube feeding nor other, not pre-defined, in-
terventions (such as exercise). Control group patients were mostly
treated based on usual care. Only one trial used a placebo-
controlled intervention. Additional characteristics of included
RCTs are shown in Table 1.
3.2. Risk of bias assessment
There was a low or unclear risk of bias in most trials except for
performance bias because blinding of participants and personnel
regarding the nutritional interventions was not done in most
studies (eFigs. 1 and 2).
3.3. Primary outcome
Out of 14 included studies, 13 trials reported all-cause mortality
within 12 months while one study [16] analyzied only secondary
outcomes of a previous included trial [3]. The mortality in the
different RCTs varied from 0.9% to 34.2%. In the overall analysis,
there were 108/1060 (10.2%) deaths in the intervention group
compared to 170/1164 (14.6%) in the control group (OR 0.63, 95%CI
0.48 to 0.84, p ¼0.001). We found low heterogeneity among trials
(I
2
¼1%, p ¼0.44) (Fig. 1).
The time of outcome measurement was different among the
trials. The range of the observation period was 60 dayse360 days. If
there were multiple time points of mortality assessment, we
collected the mortality rate as close to a 180 days observation
period as possible. Mortality rates were shown at follow-up at 60
Yang, P. H.,
2019 [22]
Taiwan International Journal of
Environmental
Research and Public
Health
82 medical >65 years, primary
diagnosis of pneumonia
by a physician, and
malnutrition status
indicated by BMI
<18.5 kg/m
2
or MNA-SF
score 7
inhospital and
community
individualized
nutritional intervention
program
usual care
Munk, T., 2021
[27]
Denmark Clinical nutrition 207 oncology,
gastroenterology,
cardiology, medical
50 years, NRS3,
inhospital nutritional
support, ability to read,
hear and understand,
discharge to own home,
cognitively intact
inhospital and
community
individual dietary
counselling and an
individualized
nutritional plan from a
research assistant,
hand-out nutritional
information material,
food package, goodie
bag, electronical
communication to
municipality
usual care
Blondal, B.S.,
2021 [51]
Iceland Clinical Nutrition
ESPEN
106 geriatric 65 y, community
dwelling, discharge
home, risk for
malnutrition, living in
Reykjavik, MMSE20
community dietary counselling,
free supplemental
energy- and protein-
rich foods, ONS
usual care
MNA: Mini Nutritional Assessment, BMI: body mass index, ONS: oral nutritional supplement, NRS 2002: Nutritional Risk Screening 2002, GP: general practitioner, CHF: congestive heart failure, AMI: acute myocardial infarction,
PNA: pneumonia, COPD: chronic obstructive pulmonary disease, SGA: Subjective Global Assessment, HP-HMB: high-protein beta-hydroxy-beta-methylbutyrate, PG-SGA: Patient Generated Subjective Global Assessment, MNA-
SF: Mini Nutritional Assessment eShort Form, ESPEN: European Society for Clinical Nutrition and Metabolism, MMSE: Mini-Mental State Exam.
*
subgroup analysis.
N. Kaegi-Braun, F. Kilchoer, S. Dragusha et al. Clinical Nutrition 41 (2022) 2431e2441
2435
days [17], 84 days [18 ], 90 days [3,19e21], 180 days [22e27] and 360
days [28].
3.4. Secondary outcomes
3.4.1. Readmission rate
A total of 10 RCTs reported non-elective hospital readmissions
during a follow-up of 60 days [17], 3 months [3,18], 6 months
[19,22,25,26], or 12 months [28]. Two trials reported the read-
mission rates for one disease only (pneumonia [22], heart failure
[28]). We included those trials in our readmission-analysis without
any limitations. There was no significant difference in readmission
rate between intervention and control (RR 0.89, 95% CI 0.74 to 1.07,
p¼0.22) (eFig. 4). The heterogeneity was moderate I
2
¼56%.
3.4.2. Functional outcome
A total of 4 RCTs reported functional outcome with measure-
ment of hand grip strength at 3 months [16,19,25,26]after
discharge (eFig. 5). There was no significant difference in handgrip
strength between intervention and control group patients (MD
0.03, 95% CI -1.08 to 1.15, p ¼0.95). Heterogeneity was moderate
(I
2
¼62%).
One trial [20] reported the change in functional outcome only.
Other trials [18,23] performed measurements but did not provide
exact numbers.
3.4.3. Body weight, BMI and nutritional intake
A total of 9 RCTs reported a body weight change from baseline
measurements until follow-up at 60 days [17], 3 months
[18e20,25e27] and 6 months [23,24]. Compared with the control
group, the nutritional intervention was associated with a signifi-
cant increase in body weight change (MD of weight change 1.14 kg,
95% CI 0.58 to 1.70, p <0.0001) at the time of outcome measure-
ment (Fig. 2). Patients in the nutritional intervention group
increased their weight an average of 1.17 kg, while the control
group had an average weight loss of 0.11 kg during the observa-
tion period. Heterogeneity was low (I
2
¼25%).
A total of 7 RCTs reported daily protein intake at 60 days [17], 3
months [25e27] or 6 months [22,29] after discharge. There was a
significant increase in protein intake in the nutritional intervention
group (MD 24.26 g per day, 95% CI 7.18 to 41.34, p ¼0.005)
Fig. 1. Forest plot comparing nutritional intervention and control for mortality. A Mantel-Haenszel random-effects model was used. Squares indicate mean values, with the size of
squares reflecting the weigth and the lines indicating 95% Cis. Diamonds indicate pooled estimates, with horizontal points of the diamonds indicating 95% CIs.
Fig. 2. Forest plot comparing nutritional intervention and control for change in body weight. A Mantel-Haenszel random-effects model was used. Squares indicate mean values,
with the size of squares reflecting the weigth and the lines indicating 95% Cis. Diamonds indicate pooled estimates, with horizontal points of the diamonds indicating 95% CIs.
N. Kaegi-Braun, F. Kilchoer, S. Dragusha et al. Clinical Nutrition 41 (2022) 2431e2441
2436
compared with the control group (Fig. 3). The average protein
consumption per day among the patients in the nutritional inter-
vention group was 74 g and 49 g in the control group. Heteroge-
neity was high (I
2
¼98%). Fig. 4
There was a significant difference in 6 trials reporting energy
intake at follow-up (at 60 days [17], 3 months [25e27], or 6 months
[22,29] after discharge) in the intervention group compared to the
control group (MD 568.06 kcals per day, 95% CI 23.56 to 1112.57,
p¼0.04) (eFig. 6). The average energy consumption per day among
the patients in the nutritional intervention was 1838 kcal and
1270 kcal in the control group. We imputed total energy intake in
the intervention group of one trial [17], because they reported the
energy intake from the ONS separately.
Furthermore 3 trials showed no significant change in BMI (MD
0.18, 95% CI -0.75 to 1.11, I
2
¼68%, p ¼0.71) in the nutritional
intervention group compared to the control group after 3 months
[19] and 6 months [22,23] with moderate heterogeneity (I
2
¼68%)
(eFig. 7).
Only three trials [3,17,18] reported adverse outcomes in corre-
lation with the consumption of ONS (eTable 1 in the Supplement).
3.5. Sensitivity analyses
Table 2 provides an overview of the subgroup analysis.
3.5.1. Mortality
Regarding the effect of outpatient nutritional support on mor-
tality, there were only minor differences between the subgroups.
Three studies included patients with specific admission diagnosis
(cardiac and/or pulmonary). Compared to no specific admission
diagnosis in the remaining 10 studies (OR 0.83, 95% CI 0.59 to 1.18,
I
2
¼0%, p ¼0.30), these patient group showed a pronounced
benefit from nutritional support (OR 0.43, 95% CI 0.28 to 0.68,
I
2
¼0%, p ¼0.0003) with a significant p-value for subgroup dif-
ference 0.03.
4. Discussion
This systematic review and meta-analysis of RCTs investigating
the association of outpatient nutritional support with clinical out-
comes has three key findings. First, post-discharge nutritional
support in medical patients at nutritional risk reduced long-term
mortality by 37%. Second, there were significant and clinical rele-
vant effects on further secondary outcome such as body weight
change, protein intake and energy intake, respectively. And third,
there were some significant effects in subgroup analyses stratified
for patients characteristics and type of nutritional intervention.
Most of the recently published literature about nutritional in-
terventions for malnourished patients include meta-analyses from
mixed health care settings (in- and outpatient) [30] or meta-
analyses focusing on inhospital interventions [5,31]. Today, there
is conclusive evidence that inhospital nutritional support improves
survival. However, until now, the evidence on the management of
DRM after hospitalisation in the outpatient setting has been
limited, especially in regard to mortality benefit. Published in 2016,
a meta-analysis of 4 RCTs with similar inclusion criteria than the
Fig. 3. Forest plot comparing nutritional intervention and control for protein intake. A Mantel-Haenszel random-effects model was used. Squares indicate mean values, with the
size of squares reflecting the weigth and the lines indicating.
Fig. 4. Forest plot comparing nutritional intervention and control for caloric intake. A Mantel-Haenszel random-effects model was used. Squares indicate mean values, with the size
of squares reflecting the weigth and the lines indicating.
N. Kaegi-Braun, F. Kilchoer, S. Dragusha et al. Clinical Nutrition 41 (2022) 2431e2441
2437
Table 2
Outcomes overall and in subgroups.
Mortality Non-elective
readmissions
Body weight
change [kg]
Weight at
follow up [kg]
BMI-change Function
(hand grip strength)
Daily
protein intake [g]
Daily energy intake [kcal]
OR (95%CI) RR (95%CI) Mean difference
(95%CI)
Mean difference
(95%CI)
Mean difference
(95%CI)
Mean difference
(95%CI)
Mean difference
(95%CI)
Mean difference
(95%CI)
Overall population
Intervention, events/total (%)
or mean (No)
108/1060 (10.2%) 273/823 (33.2%) 1.17 (457) 61.2 (307) 0.37 (118) 20.15 (330) 74.0 (346) 1838.4 (317)
Control, events/total, (%)
or mean (No)
170/1164 (14.6%) 299/820 (36.5%) 0.11 (486) 60.0 (294) 0.45 (101) 20.15 (312) 49.5 (380) 1270.4 (351)
Overall estimate 0.63 (0.48, 0.84) 0.89 (0.74, 1.07) 1.14 (0.58, 1.70) 0.52 (2.36, 1.33) 0.18 (0.75, 1.11) 0.03 (1.08, 1.15) 24.26 (7.18, 41.34) 568.06 (23.56, 1112.57)
Heterogeneity, Test for overall effect I2 ¼1%, p ¼0.001 I2 ¼56%, p ¼0.22 I2 ¼25%, p <0.0001 I2 ¼33%, p ¼0.58 I2 ¼68%, p ¼0.71 I2 ¼62%, p ¼0.95 I2 ¼98%, p ¼0.005 I2 ¼99%, p ¼0.04
Stratification by start of intervention
Start during hospitalisation 0.57 (0.37, 0.86) 0.78 (0.52, 1.15) 0.87 (0.12, 1.61) NA NA NA 13.18 (4.98, 31.35) NA
Start after hospitalisation 0.87 (0.54, 1.39) 0.95 (0.77, 1.17) 1.44 (0.65, 2.23) NA NA NA 32.78 (7.18, 41.34) NA
Test for subgroup differences I2 ¼42.8%, p ¼0.19 I2 ¼0%, p ¼0.38 I2 ¼7.1%, p ¼0.30 NA NA NA I2 ¼15.5%, p ¼0.28 NA
Stratification by type of intervention
Dietary advice ±ONS 0.63 (0.42, 0.94) 0.78 (0.56, 1.10) 1.32 (0.52, 2.12) NA NA NA NA NA
ONS 0.68 (0.42, 1.08) 0.99 (0.91, 1.09) 0.90 (0.02, 1.82) NA NA NA NA NA
Test for subgroup differences I2 ¼0%, p ¼0.81 I2 ¼42.7%, p ¼0.19 I2 ¼0%, p ¼0.50 NA NA NA NA NA
Stratification by duration
of intervention
60 days 0.77 (0.41, 1.44) 0.91 (0.55, 1.51) 0.61 (0.02, 1.24) NA NA NA NA NA
>60 days 0.63 (0.44, 0.90) 0.85 (0.66, 1.10) 1.62 (0.86, 2.38) NA NA NA NA NA
Test for subgroup differences I2 ¼0%, p ¼0.57 I2 ¼0%, p ¼0.81 I2 ¼75.0%, p ¼0.05 NA NA NA NA NA
Stratification by age
Mean age <80 years 0.67 (0.42, 1.09) 0.90 (0.70, 1.17) 1.35 (0.38, 2.32) 1.19 (3.58, 1.20) NA NA 13.20 (-4.16, 30.55) 349.48 (49.39, 748.36)
Mean age >80 years 0.64 (0.38, 1.07) 0.84 (0.61, 1.16) 1.00 (0.27, 1.72) 0.81 (3.77, 5.38) NA NA 32.77 (145, 64.09) 779.87 (252.54, 1812.29)
Test for subgroup differences I2 ¼0%, p ¼0.88 I2 ¼0%, p ¼0.73 I2 ¼0%, p ¼0.57 I2 ¼0%, p ¼0.45 NA NA I2 ¼12.9%, p ¼0.28 I2 ¼0%, p ¼0.45
Stratification by sex
<60% female 0.71 (0.50, 1.01) 0.97 (0.85, 1.10) 0.61 (0.03, 1.19) NA NA NA NA NA
>60% female 0.56 (0.31, 0.88) 0.78 (0.49, 1.25) 1.87 (1.09, 2.66) NA NA NA NA NA
Test for subgroup differences I2 ¼0%, p ¼0.50 I2 ¼0%, 0.38 I2 ¼84.4%, p ¼0.001 NA NA NA NA NA
Stratification by admission diagnosis
Cardial ±pulmonary disease 0.43 (0.28, 0.68) 0.58 (0.25, 1.31) NA NA NA NA NA NA
No specific diagnosis 0.83 (0.59, 1.18) 0.94 (0.75, 1.16) NA NA NA NA NA NA
Test for subgroup differences I2 ¼80.0%, p ¼0.03 I2 ¼20.3%, p ¼0.26 NA NA NA NA NA NA
Stratification by individualized
goals for energy intake
Individualized kcal-goals 0.60 (0.41, 0.90) 0.85 (0.66, 1.10) 1.12 (0.37, 1.87) NA NA NA NA NA
Non-individualized kcal-goals 0.75 (0.45, 1.25) 0.94 (0.74, 1.21) 1.25 (0.34, 2.16) NA NA NA NA NA
Test for subgroup differences I2 ¼0%, p ¼0.53 I2 ¼0%, p ¼0.58 I2 ¼0%, p ¼0.83 NA NA NA NA NA
Amount of protein in the nutritional intervention
High-protein nutritional intervention 0.49 (0.28, 0.86) 0.77 (0.48, 1.23) NA NA NA NA NA NA
Low-protein nutritional intervention 0.78 (0.51, 1.20) 0.87 (0.64, 1.17) NA NA NA NA NA NA
Test for subgroup differences I2 ¼38.3%, p ¼0.20 I2 ¼0%, p ¼0.67 NA NA NA NA NA NA
OR: Odd Ratio, CI: Confidence Interval, ONS: oral nutritional supplement, NA: not applicable.
N. Kaegi-Braun, F. Kilchoer, S. Dragusha et al. Clinical Nutrition 41 (2022) 2431e2441
2438
ones of our analysis found no significant mortality benefit[32],
probably due to low number of trials and therefore little power.
Another meta-analysis from 2013 investigating outpatient nutri-
tional support in mixed surgical and medical populations, also did
not find a significant mortality reduction [33]. To our knowledge,
this is the largest and, thus, most powerful meta-analysis including
14 RCTs and the first showing that continued outpatient or post-
discharge nutritional support leads to reduced all-cause mortality
within one year. Our study population was more than three times
larger than in the above mentioned analyses and the quality of
nutrition supplements and individualized therapy has improved
significantly during the recent years. These could be possible ex-
planations for our new and more positive findings. We included
trials with different patient populations and different nutritional
interventions resulting in a high external validity.
Additionally, we found that outpatient nutritional therapy was
associated with increased weight gain and nutritional intake,
which could be seen as proof of concept regarding the nutritional
support intervention. These findings are in line with several other
meta-analyses and reviews from different patient populations
[32e40]. Interestingly, there was no difference in regard to func-
tional improvements measured by handgrip strength. However,
another meta-analysis from 2012, focusing on patients with chronic
obstructive lung disease, found a positive effect of nutritional in-
terventions on handgrip strength, even though the interventions
resulted in lower mean difference of nutritional intake than in our
trial [36]. Moreover, the combination of nutritional support and
physical activity may improve functional outcomes, as shown in a
former meta-analysis of Wright et al. [41].
In case of readmission rates, there was no significant effect of
nutritional interventions and there was moderate heterogeneity,
probably arising from different durations of intervention and
different diagnoses at admission. An meta-analysis from 2013 re-
ported a significant reduction of readmission rate [42]. However,
comparability is limited because they included only trials with ONS
and also patients from the community setting without a preceeding
hospitalisation and from any nutritional state. The investigation of
readmission rates and other quality outcomes are important and do
have economic implications for health care systems. There is evi-
dence for the cost-effectiveness of inhospital nutritional support
interventions [43], while there is still a lack of similar studies for the
outpatient malnutrition management.
Furthermore, there is need to determine which specific patient
group benefit most from nutritional support. In a subgroup anal-
ysis, we found a pronounced survival benefit in patients with car-
diopulmonary diseases. Hence, the underlying disease might play a
role in the extent of the response to nutritional intervention.
Similarly to our findings, subanalyses of one of the largest RCT from
the inhospital setting, showed strong survival benefit of nutritional
support interventions in patients with chronic heart disease [44],
but also for other diseases such as chronic kidney disease [45],
cancer [46], pulmonary infections [47] and frailty [48]. Additionally,
RCTs with >60% women resulted in a higher weight gain than RCTs
with <60% women, but heterogeneity was high. Still patient- or
disease-specific nutritional treatment algorithms could be of in-
terest for further nutritional research. Also, stronger effect of
nutritional interventions on body weight change was found in RCTs
with >60 days duration. This is in line with a recent analysis which
included only hospital-initiated intervention and even found a
significant difference in mortality risk [49]. Even though not sig-
nificant, results tended to be favorable in the RCTs providing higher
levels of protein and with individualized nutritional requirements,
so characteristics of the nutritional intervention, such as protein
content and quality, individualization and duration of the inter-
vention are considered to be of further interest as well.
5. Limitations
The main limitation of this analysis is the relatively limited
number of trials and patients, reducing the power of our findings,
especially for subgroups. For many outcomes, heterogeneity was
high among trials and we were not able to create more homoge-
nous subgroups due to low number of eligible studies. Further
search updates including the ongoing trials can be considered in
perspective to update this meta-analysis (eTable 2).
According to the GRADE methodology [50], the quality of evi-
dence was low to very low for most outcomes except for mortality,
weight change, and protein intake where it was moderate. Yet, the
risk of bias analysis showed mostly high risk in performance bias
due to type of intervention and a mixed distribution for detection
and attrition bias.
6. Conclusions
This meta-analysis of randomized-controlled trials with mostly
moderate trial quality suggests that continued outpatient or post-
discharge nutritional support significantly increases protein and
energy intake as well as body weight, and improves long-term
survival. Further large-scale and high-quality intervention trials
are needed to confirm these findings and answers further questions
regarding the optimal target population, about duration and quality
of nutritional interventions as well as about their cost-
effectiveness.
Funding
This study was supported in part by the Swiss National Science
Foundation (SNSF Professorship, PP00P3_150531 / 1) and the
Research Council of the Kantonsspital Aarau (1410.000.044).
Author Contributions
NK, FG, and PS wrote the initial protocol. FK, SD, MF, CG and NK
performed the data extraction and performed the statistical ana-
lyses. FK, SD, NK, CG and PS drafted the manuscript; all authors
amended and commented on the manuscript and approved the
final version. PS oversaw the study and acts as guarantor.
Conflict of interest
PS has received research support from Nestl
e Health Science and
Abbott Nutrition and ND received support from Abbott Nutrition
for research and lectures. All other authors confirm that they do not
have a conflict of interest associated with this manuscript.
Appendix A. Supplementary data
Supplementary data to this article can be found online at
https://doi.org/10.1016/j.clnu.2022.09.011.
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