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Purpose Frailty is a valuable predictor for outcome in elderly ICU patients, and has been suggested to be used in various decision-making processes prior to and during an ICU admission. There are many instruments developed to assess frailty, but few of them can be used in emergency situations. In this setting the clinical frailty scale (CFS) is frequently used. The present study is a sub-study within a larger outcome study of elderly ICU patients in Europe (the VIP-2 study) in order to document the reliability of the CFS. Materials and methods From the VIP-2 study, 129 ICUs in 20 countries participated in this sub-study. The patients were acute admissions ≥ 80 years of age and frailty was assessed at admission by two independent observers using the CFS. Information was obtained from the patient, if not feasible, from the family/caregivers or from hospital files. The profession of the rater and source of data were recorded along with the score. Interrater variability was calculated using linear weighted kappa analysis. Results 1923 pairs of assessors were included and background data of patients were similar to the whole cohort ( n = 3920). We found a very high inter-rater agreement (weighted kappa 0.86), also in subgroup analyses. The agreement when comparing information from family or hospital records was better than using only direct patient information, and pairs of raters from same profession performed better than from different professions. Conclusions Overall, we documented a high reliability using CFS in this setting. This frailty score could be used more frequently in elderly ICU patients in order to create a more holistic and realistic impression of the patient´s condition prior to ICU admission.
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Flaattenetal. Ann. Intensive Care (2021) 11:22
Reliability oftheClinical Frailty Scale invery
elderly ICU patients: aprospective European
Hans Flaatten1* , Bertrand Guidet2, Finn H. Andersen3,4, Antonio Artigas5, Maurizio Cecconi6,
Ariane Boumendil7, Muhammed Elhadi8, Jesper Fjølner9, Michael Joannidis10, Christian Jung11,
Susannah Leaver12, Brian Marsh13, Rui Moreno14, Sandra Oeyen15, Yuriy Nalapko16, Joerg C. Schefold17,
Wojciech Szczeklik18, Sten Walther19, Ximena Watson20, Tilemachos Zafeiridis21 and Dylan W. de Lange22 on
behalf of the VIP2 Study Group
Purpose: Frailty is a valuable predictor for outcome in elderly ICU patients, and has been suggested to be used in
various decision-making processes prior to and during an ICU admission. There are many instruments developed
to assess frailty, but few of them can be used in emergency situations. In this setting the clinical frailty scale (CFS) is
frequently used. The present study is a sub-study within a larger outcome study of elderly ICU patients in Europe (the
VIP-2 study) in order to document the reliability of the CFS.
Materials and methods: From the VIP-2 study, 129 ICUs in 20 countries participated in this sub-study. The patients
were acute admissions 80 years of age and frailty was assessed at admission by two independent observers using
the CFS. Information was obtained from the patient, if not feasible, from the family/caregivers or from hospital files.
The profession of the rater and source of data were recorded along with the score. Interrater variability was calculated
using linear weighted kappa analysis.
Results: 1923 pairs of assessors were included and background data of patients were similar to the whole cohort
(n = 3920). We found a very high inter-rater agreement (weighted kappa 0.86), also in subgroup analyses. The agree-
ment when comparing information from family or hospital records was better than using only direct patient informa-
tion, and pairs of raters from same profession performed better than from different professions.
Conclusions: Overall, we documented a high reliability using CFS in this setting. This frailty score could be used more
frequently in elderly ICU patients in order to create a more holistic and realistic impression of the patient´s condition
prior to ICU admission.
Keywords: Clinical frailty scale, Inter-rater variability, Intensive care, Octogenarians
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Frailty assessment is increasingly used in critically ill
elderly patients and has in many studies been shown
to correlate with outcomes [13]. Frailty assessment
has recently been suggested as one of several ele-
ments that could theoretically considered for decision
to admit patients to the ICU during the present pan-
demic [4], although firm evidence for its use is lacking.
Open Access
1 Department of Anaesthesia and Intensive Care, Dep of Clinical Medicine,
Haukeland University Hospital Bergen Norway, University of Bergen,
5019 Bergen, Norway
Full list of author information is available at the end of the article
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Flaattenetal. Ann. Intensive Care (2021) 11:22
Traditionally, frailty assessments are performed within
the context of a comprehensive geriatric assessment and
require active participation from the patient [5].Under-
standably,this is not feasible in mostacutely admittedor
critical ill patients, and hence other methods have been
developed to overcome this problem. One of the most
frequently used tool for frailty assessments in this set-
ting is the Clinical Frailty Scale (CFS) [6] developed from
the large Canadian studies of frailty that established the
cumulative deficit approach to frailty. e CFS has since
increasingly been used in intensive care as well as in
other emergency settings and was found in a recent sys-
tematic review to be the most frequent instrument used
to assess frailty in ICU patients, but is only properly vali-
dated in patients 65years [7].
As in any assessment method, the psychometric prop-
erties of the test are important. Regarding the CFS, the
original publication [6] established construct validity by
comparing it with the frailty index [8]. Inter-rater reli-
ability of the CFS has been tested in a limited number
of patients in three studies [911] and the feasibility was
clinically demonstrated in the VIP1 study where CFS was
collected in 99.8% of the 5187 patients included [1]. As a
pre-defined sub-study nested within the VIP2 study [12]
we additionally planned to perform a large international
assessment of CFS reliability.
Interrater variability may vary for several reasons: indi-
vidual differences in how to use the CFS, the rater’s pro-
fession and experience, and the source of information
necessary to perform a frailty score. Our hypothesis is
that the CFS, being intuitive to perform, may vary little
with the rater’s profession and source of available infor-
mation to perform the score.
e main aim of this study was to document inter-rater
reliability within a large prospective observation study
and assess the results of the score being derived from dif-
ferent raters and dissimilar information source, and in
addition study potential variances between countries.
Study design andsetting
e observational VIP-2 study was performed in acute
ICU admissions of patients 80years, and its primary
aim was to describe the influence and interaction of sev-
eral geriatric syndromes: frailty, co-morbidity, the activity
of daily life, and cognition on many different outcomes.
e study was performed over 12months in 2018–2019
and included 3920 patients from 22 countries. More
details and results can be found in the original publica-
tion [12]. Units could voluntarily sign up additionally to
participate in a pre-defined sub-study of the inter-rater
variability of CFS. e English version of CFS was used
except for France and Switzerland using a validated ver-
sion in French [13].
Clinical Frailty Scale (CFS)
e CFS was used to assess frailty in all recruited patients
as it presented prior to the acute event and admission
to the ICU. e CFS is a pictographic scale from 1–9
describing nine different grades of frailty with a short text
attached [6]. Patients with scores from 1 to 3 are con-
sidered not frail, 4 is pre-frail or vulnerable, and 5 to 9
are considered to be frail. No specific training, except a
written explanation of the use of the CFS, was given to
the participating units where many, but not all units had
prior experience with using it.
Assessment performed bydierent raters
In this study, two different study personnel from the
ICU independently and blinded for each other results,
assessed the patient at admission (first 24h in the ICU)
using the CFS with input from patients if possible, if not
from care-givers or the medical and nursing hospital
notes. e second rater was free to use sources of input
and was not constrained to use the same as rater 1. e
CFS score was noted for assessor 1 and 2 with informa-
tion about the profession of the assessor: ICU nurse, ICU
physician, dedicated study person, or other. Furthermore,
they documented the kind of information that was used
to perform the score. ese data were then recorded in
the electronic case record form (CRF) for the VIP-2 study
by the local study investigator.
e assessors were named Rater 1 and Rater 2. In the
analysis of data, the CFS rating was considered as an
ordinal variable, and the occupation of the assessors
were grouped as ICU nurse; ICU physician; research
staff or other. e main source where the information
was obtained was classified into 4 groups: (a) from the
patient; (b) from family/care-givers; (c) from hospital
records; and (d); another source, and they could only
choose one option.
Registration andethics
is pre-defined sub-study was registered on Clinical identifier NCT03370692 at the same time as
the main study. e main study was approved by ethical
committees in all participating countries by institutional
research boards, for details see the VIP-2 study main
paper [12]. Since this study involved health profession-
als (raters) in some countries, this sub-study had to go
through an independent review, and the rater then had to
give informed consent to participate.
Page 3 of 7
Flaattenetal. Ann. Intensive Care (2021) 11:22
Statistical analyses
A statistical analysis plan was discussed in the VIP2 study
group and was decided to adopt to the guidelines for
reporting of reliability and agreement studies (GRAAS)
[14], see Additional file1.
Data were analysed using SPSS version 25.0 (IBM,
Armonk, NY USA) and with MedCalc 19.0 (http://www.
medca Ostend, Belgium). e inter-rater reliabil-
ity was assessed using linear weighted kappa in order to
minimise outlier ratings and with intraclass correlation
coefficient where raters for each subject were selected at
random and with a one-way random effects model. We
first analysed the inter-rater variability using all pairs
then compared raters from different professions, infor-
mation sources and participating countries. In the manu-
script, we further use the accepted grouping of weighted
kappa: Poor: 0–0.2, Fair (0.21–0.4), Moderate (0.41–0.6),
good (0.61–0.8) and very good (0.81–1.0) [14, 15].
20 countries and 129 ICUs contributed to the inter-rater
study that included 1923 pairs of raters, and hence two
independent CFS assessments. is represented 49.1% of
the whole VIP-2 study population, and patients’ details
compared to patients not studied are given in Table1.
Overall the number of completed CFS in the VIP-2
study was 99.6%, higher than activity of daily life score
(ADL): 88.6% or cognition (IQCODE): 76.0%, showing
very high compliance with this score. e profession of
rater 1 and rater 2 were most often ICU physicians fol-
lowed by ICU nurses, and the source of information for
the rating was most often the family/care-givers (Fig.1).
e mean CFS from rater 1 and 2 was 4.18 (± 1,764) and
4.25 (± 1.76), respectively. Since the “other” group of
raters and information sources were few and not speci-
fied, we have excluded these from further analysis.
e 9 different pairs of raters with regard to the profes-
sion are given in Table2. e weighted kappa for all pairs
was 0.86 (95% CI 0.84–0.87).
e intraclass correlation coefficient (absolute agree-
ment) was 0.93 for single measures and 0.96 for average
measures, and the weighted kappa for all measures was
0.86 (95% CI 0.84–0.87) (Table3). Worth noting is the
distribution of scores of 4 and 5 in Table3. A notewor-
thy number of rater one and two have scores above and
below these values. Among rater one, 30 of 402 (7.4%)
scored one or more CFS classes above 4 and by rater two
in 65 of 407 (16%) patients demonstrating some difficulty
of judging vulnerable from frail patients.
e results in Table 4 demonstrate the variability
between pairs from different professions and less vari-
ability when similar source for information was used for
both pairs. e best results were obtained when both
raters were either nurses or physicians, and mixed pairs
of assessors performed slightly worse. Likewise, there are
better results when information does not come from the
patients. ere is also a good performance of the CFS
across countries, but the three countries with the least
number of pairs included performed less well than the
others, although most countries were overall classified as
very good (weighted kappa 0.80).
We also performed a sensitivity analysis looking at two
subgroups according to rater 1: frail (CFS > 4) versus non-
frail (CFS < 5). In the frail the kappa was 0.70 (95% CI
0.66–0.74) compared to 0.76 (95% CI 0.74–0.79).
In this large prospective study on frailty assessment in
the ICU using the CFS, we found the overall agreement
of inter-rater variability in patients > 80years to be very
good. We revealed, however, distinct variations between
groups of raters and between countries. e agreement
between obtaining CFS from hospital records or family
Table 1 Details of VIP-2 patients studied compared
tothose notstudied
The CFS is the value from Rater 1, and the % relates to the column (within the
SOFA sequential organ failure assessment, CFS clinical frailty scale, IQCODE
informant questionnaire on cognitive decline in the elderly, ADL activity of daily
living, CPS Co-morbidity and Polypharmacy score
Included Not included
Number 1923 1997
Age (median IQR) year 84 (81–87) 84 (81–87)
Male sex (%) 53.8% 53.3%
ICU LOS (median IQR) days 4 (1.96–8.89) 4 (1.71–7.12)
SOFA score (median IQR) 6 (4–9) 6 (4–9)
CFS fit (1–3) 789 (41%) 754 (38.1%)
CFS vulnerable (CFS 4) 407 (21.1%) 384 (19.4%)
CFS frail (CFS 5–9) 732 (37.8%) 840 (42.5%)
IQCODE (median, IQR) 3.25 (3–3.75) 3.19 (3–3.56)
Katz ADL score (mean) 4.8
score (mean and 95% CI 10.6 (10.4–10.9)
Admission groups (%)
Acute respiratory failure 22.8 25.3
Emergency surgery 15.4 12.3
Sepsis 14.5 13.0
Acute circulatory failure 13.8 13.8
Respiratory and circulatory 10.7 12.2
Trauma 6.1 4.6
Cerebral failure 5.8 4.0
Other 10.4 13.0
Page 4 of 7
Flaattenetal. Ann. Intensive Care (2021) 11:22
was nearly identical but was lower when the patients were
used as the primary source of information.
Frailty is important in order to understand critical ill
patients, particularly in advanced age [16], and most
studies have demonstrated a close link between frailty
and survival. Hence, knowledge of frailty status could be
important when issues such as ICU triage and limitation
of life-sustaining therapy are discussed. Recent guidelines
10,0 %
20,0 %
30,0 %
40,0 %
50,0 %
60,0 %
70,0 %
Profession ICU
ICUnurse Research
Source Patients Care-giver Hospital
record s
Raters profession andsourceofinformation
Rater1 Rater2
Fig. 1 Raters profession and source of information in the two groups
Table 2 Distribution ofpairs ofRater 1 versusRater 2
a Missing pairs in 4 patients
Profession ofraters Rater 1
Rater 2aICU nurse ICU physician Research sta
ICU nurse 57 309 126
ICU physician 162 785 120
Research staff 46 96 138
Table 3 Intraclass variance Rater 1 (CFS1) andRater 2(CFS2); weighted kappa (linear) 0.86 (0.84–0.87)
1 2 3 4 5 6 7 8 9 Sum %
176 3 0 1 1 0 0 0 0 81 (3.5%)
2 0 71 0 0 0 0 0 0 196 (14.0%)
3 2 40 403 25 7 2 0 1 0 480 (25.0%)
4 1 4 54 313 22 7 1 0 0 402 (20.9%)
5 0 0 10 58 163 28 2 0 1 262 (13.6%)
6 0 0 5 5 43 177 17 2 0 249 (12.9%)
7 0 0 0 1 2 44 126 8 0 181 (9.4%)
80001031346 2 65 (3.4%)
90000000077 (0.4%)
Sum % 94 (4.9%) 202 (10.5%) 493 (25.6%) 407 (21.2%) 240 (12.5%) 261 (13.6%) 159 (8.3%) 57 (3.0%) 10 (0.5%) 1923
Page 5 of 7
Flaattenetal. Ann. Intensive Care (2021) 11:22
propose the use of frailty assessment as a part of the tri-
age process to be used with COVID-19 [17]. However,
use of frailty in triage setting has its limitations, and is
at present not confirmed in prospective studies. How-
ever, use of CFS would be effective in analysing the clini-
cal decision-making process of an ICU team. ere are
several methods to assess frailty, and CFS is frequently
used in clinical studies with ICU patients [2] as well as
in emergency admission [18] and is also used in routine
clinical use in intensive care units outside study settings
Using an instrument such as a frailty score requires
knowledge about its performance and with special atten-
tion to reliability and construct validity [20]. Of interest
is also its ability to predict risk for death, where CFS have
been found to perform well. is was recently confirmed
in the VIP-2 study, where CFS alone had similar predic-
tive value for 30-day mortality as a model incorporating
cognition and functional disability [12], again providing
good criterion validity.
e aim of the present study was to document several
unanswered questions using CFS. What is the inter-rater
variability when analysing more heterogeneous groups
of raters using a various source of data for the score?
Both aspects are important properties of a clinical test
or score. e variation of a score in the same patient
between two raters is the inter-rater variability. Overall,
our data proves a very high degree of agreement between
raters with a weighted kappa of 0.86. Since we had a large
number of pairs to study, we could study results in sub-
groups, both between raters from different professions,
the source of information as well as performance across
countries. ere seems to be better agreement when the
raters are from the same profession; physicians or nurses.
When the raters are from different professions the agree-
ment is slightly less. We also provide data showing that
obtaining information from family members and care-
givers or from written records in order to classify CFS
is in fact, better compared to the information obtained
from the patient. is may have a simple explanation that
many elderly patients, although seemingly awake and
co-operable, may not perform at their best at the time
of ICU admission. Hence important information may
not be revealed for the rater. We have found that it can
be a problem to differentiate between CFS 4 and 5. is
could be important since 5 is the first stage on the frail
part of the CFS and 4 is borderline. Recently the CFS was
upgraded to version 2.0 and a more detailed guideline
in how to understand and use the different levels in the
scale have been published [21].
Our study is in line with three recent studies of the
inter-rater variability of the CFS. All studies are from
single countries with a smaller number of pairs included,
and only the overall inter-rater variability was reported.
In a study from Canada involving two ICUs [8], different
assessors from a research coordinator, an occupational
therapist, and a geriatric resident, performed CFS scores
in 150 newly admitted ICU patients. ey reported no
significant differences between the three raters using
Spearman’s rank correlation coefficient. In a more recent
study from six ICUs in Wales and Scotland, 101 patients
were studied with two independent CFS assessments of
frailty by assessors from medical or nursing backgrounds
[7]. ey found a good agreement with a weighted kappa
of 0.74 between raters, and also that agreement differed
slightly depending on the assessor’s background.
A more recent study comparing CFS scored in 158
adult ICU patients scored by geriatricians and intensiv-
ists reported however a poor agreement between raters
[9]. e authors suggest that these two groups have a
different conception of how frailty presents in critical ill
patients as an explanation for this result.
Our study has its limitation: this was not a controlled
trial with regard to the choice of profession and source
of data used and may have been at the centres’ discre-
tion. We also have no information about the clinical
experience of the raters nor their age. e study has also
strengths. It has a very large sample size of nearly 2000
pairs of raters, with at least three important sources of
variation: the profession of raters, source of information,
and country.
Table 4 Weighted kappa in subgroups (physicians
andnurses) and8 countries ( 100 pairs)
Group profession NWeighted
kappa 95% CI
ICU physician/ICU physician 785 0.87 0.85 to 0.89
ICU nurse/ICU nurse 57 0.92 0.87 to 0.97
Research staff/research staff 276 0.84 0.80 to 0.87
ICU nurse/ICU physician 162 0.77 0.71 to 0.83
ICU physician/ICU nurse 309 0.80 0.77 to 0.84
Group: information source
Patient/patient 394 0.85 0.82–0.88
Family/family 818 0.89 0.87–0.90
Hospital records/hospital records 187 0.89 0.85–0.92
Group: countries
England 397 0.90 0.87 to 0.97
France 257 0.81 0.78 to 0.85
Spain 186 0.89 0.85 to 0.93
Poland 163 0.89 0.85 to 0.92
Greece 133 0.89 0.85 to 0.94
Germany 125 0.81 0.75 to 0.86
Norway 110 0.71 0.63 to 0.78
Portugal 106 0.82 0.76 to 0.89
Page 6 of 7
Flaattenetal. Ann. Intensive Care (2021) 11:22
In very elderly ICU patients, the CFS has a high compli-
ance rate and exhibits high overall inter-rater agreement
with a weighted kappa analysis of 0.86. Furthermore,
there are minor variations in performance across dif-
ferent health care professionals, countries and source of
data. We found the best agreement using raters from the
same health care professionals, but with no difference
between pair of nurses or physicians. To determine CFS,
caution should be used to rely on the elderly ICU patients
as the sole source of information.
Frailty assessment should be routine in the critical ill
elderly patients, and the CFS is a good instrument in this
respect, and will give a more holistic impression of the
patient´s condition prior to admission.
Supplementary Information
The online version contains supplementary material available at https ://doi.
org/10.1186/s1361 3-021-00815 -7.
Additional le1. Guideline for reporting of reliability and agreement
studies (GRAAS).
Additional le2. List of local investigators.
CFS: Clinical frailty scale; VIP: Very old intensive care patients; ADL: Activity of
daily life; IQCODE: Informant questionnaire on cognitive decline in the elderly;
GRAAS: Guidelines for reporting of reliability and agreement studies.
The study was endorsed by the European Society of Intensive Care Medicine
Authors’ contributions
HF, BG, DDL designed the study and wrote the study protocol. AM provided
geriatric expertise in designing the protocol. HF and AB performed the
statistical analysis. JF was responsible for data management and the electronic
CRF; HF drafted the first manuscript, and the writing group (BG, DDL, CJ and
HF) discussed and finalised the manuscript. The rest of the authors were
country coordinators and hence were responsible for data retrieval and have
participated reading and commenting the final draft of the manuscript. The
VIP-2-study collaborators from all individual ICUs are listed in Additional file 2.
Free support for running the electronic database and was granted from
University of Aarhus, Denmark. Financial support for creation of the e-CRF
and maintenance of the database was possible from a grant (open project
support) by Western Health region in Norway 2018 who also funded the par-
ticipating Norwegian ICUs. DRC Ile de France and URC Est helped conducting
VIP-2 in France.
Availability of data and materials
Data are embedded in the main database, and as such cannot be opened for
general inspection. The main author can at request give an extract from the
database for each pair of raters with necessary information about the inter-
rater agreement.
Ethics approval and consent to participate
The VIP2 study that includes this cohort of patients received ethical approval
from all participating countries, as revealed in the original publication [12].
Briefly this included informed consent at admission in some countries, and
this was not necessary in others because of the observational nature of the
study. Some countries did require informed consent from raters, since they
were in fact considered as “test persons” and this was approved when neces-
sary. Ethical approval from Norway (the country of the PI) had the number
2018/87/REK sør-øst D.
Consent for publication
Not applicable.
Competeing interests
JCS declares that the Dept. of Intensive Care Medicine Bern has/had research
and/or development/consulting contracts with (full disclosure): Orion Corpo-
ration, Abbott Nutrition International, B. Braun Medical AG, CSEM SA, Edwards
Lifesciences Services GmbH/SA, Kenta Biotech Ltd, Maquet Critical Care AB,
Omnicare Clinical Research AG, and Nestlé. Educational grants were received
from Fresenius Kabi; GSK; MSD; Lilly; Baxter; Astellas; AstraZeneca; B. Braun
Medical AG, CSL Behring, Maquet, Novartis, Covidien, Nycomed, Pierre Fabre
Pharma (Roba Pharma); Pfizer, Orion Pharma. The money went into depart-
mental funds. No personal financial gain applies. All other authors do not have
any conflict of interest to declare related to this manuscript.
Author details
1 Department of Anaesthesia and Intensive Care, Dep of Clinical Medi-
cine, Haukeland University Hospital Bergen Norway, University of Bergen,
5019 Bergen, Norway. 2 Sorbonne Université, INSERM, Institut Pierre Louis
D’Epidémiologie Et de Santé Publique, Saint Antoine Hospital, AP-HP, Hôpital
Saint-Antoine, Service de Réanimation, 75012 Paris, France. 3 Department
of Anaesthesia and Intensive Care, Ålesund Hospital, Ålesund, Norway. 4 Dep
of Circulation and Medical Imaging, NTNU, Trondheim, Norway. 5 Deparment
of Intensive Care Medicine, CIBER Enfermedades Respiratorias, Corpora-
cion Sanitaria Universitaria Parc Tauli, Autonomous University of Barcelona,
Sabadell, Spain. 6 Department of Anesthesia and Intensive Care Medicine,
Humanitas Clinical and Research Center–IRCCS, Via Alessandro Manzoni 56,
20089 Rozzano, MI, Italy. 7 AP-HP, Hôpital Saint-Antoine, Service de Réanima-
tion, 75012 Paris, France. 8 Faculty of Medicine, University of Tripoli, Tripoli,
Libya. 9 Department of Intensive Care, Aarhus University Hospital, Aarhus,
Denmark. 10 Division of Intensive Care and Emergency Medicine, Department
of Internal Medicine, Medical University Innsbruck, Innsbruck, Austria. 11 Divi-
sion of Cardiology, Pulmonology and Vascular Medicine, University Hospital
Düsseldorf, Heinrich-Heine- University, Düsseldorf, Germany. 12 Research Lead
Critical Care Directorate St George’s Hospital, London, UK. 13 Mater Misericor-
diae University Hospital, Dublin, Ireland. 14 Faculdade de Ciências Médicas de
Lisboa (Nova Médical School), Unidade de Cuidados Intensivos Neurocríticos
E Trauma. Hospital de São José, Centro Hospitalar Universitário de Lisboa Cen-
tral, Lisbon, Portugal. 15 Department of Intensive Care 1K12IC, Ghent University
Hospital, Ghent, Belgium. 16 European Wellness International, ICU, Luhansk,
Ukraine. 17 Department of Intensive Care Medicine, Inselspital, Universitätsspi-
tal, University of Bern, Bern, Switzerland. 18 Intensive Care and Perioperative
Medicine Division, Jagiellonian University Medical College, Kraków, Poland.
19 Heart Center, Linkoping University Hospital, Linkoping, Sweden. 20 ICU,
St George’s University Hospital, London, UK. 21 Intensive Care Unit General
Hospital of Larissa, Larissa, Greece. 22 Department of Intensive Care Medicine,
Dutch Poisons Information Center (DPIC), University Medical Center, University
Utrecht, Utrecht, The Netherlands.
Received: 10 November 2020 Accepted: 27 January 2021
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... Because of its subjective nature, inter-rater variability could exist. In recent published studies by Flaatten et al. and Surkan et al., a fair interrater reliability of the CFS was found if assessed by ICU-personnel and geriatricians [37][38][39]. However, in times of a pandemic when physicians or nurses with minimal experience in geriatric care are needed to assess these patients and use the CFS, we expect a higher interrater variability due to the subjective nature of this instrument. ...
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Background A variety of prediction models concerning COVID-19 have been proposed since onset of the pandemic, but to this date no gold standard exists. Mortality rates show a sharp increase with advancing age but with the large heterogeneity of this population in terms of comorbidities, vulnerability and disabilities, identifying risk factors is difficult. Therefore, we aimed to research the multidimensional concept of frailty, measured by the Acute Presenting Older Patient (APOP)-screener, as a risk factor for in-hospital mortality in older COVID-19 patients. Methods All consecutive patients of 70 years or older, with a PCR confirmed COVID-19 infection and a completed APOP-score, presenting at the Emergency Department (ED) of the Jeroen Bosch Hospital, the Netherlands, between February 27th 2020 and February 1st 2021 were retrospectively included. We gathered baseline characteristics and scored the CCI and CFS from patient records. The primary outcome was in-hospital mortality. Results A total of 292 patients met the inclusion criteria. Approximately half of the patients were considered frail by the APOP or CFS. 127 patients (43.5%) scored frail on the CFS, 158 (54.1%) scored high risk on the APOP-screener. 79 patients (27.1%) died during their hospital admission. The APOP-screener showed a significantly elevated risk of in-hospital mortality when patients scored both high risk of functional and evidence of cognitive impairment (OR 2.24, 95% 1.18–4.25). Significant elevation of in-hospital mortality was found for the high CCI-scores (≥ 5)(OR 1.78, 95% 1.02–3.11), but not for the highest CFS category (5–9, frail) (OR 1.35, 95% 0.75–2.47). The discriminatory performance of the APOP, CFS and CCI were comparable (AUC resp. 0.59 (0.52–0.66), 0.54 (0.46–0.62) and 0.58 (0.51–0.65)). Conclusion Although the elevated risk for in-hospital mortality found for the most frail patients as scored by the APOP, this instrument has poor discriminatory value. Additionally, the CFS did not show significance in predicting in-hospital mortality and had a poor discriminatory value as well. Therefore, treatment decisions based on frailty or comorbidities alone should be made with caution. Approaching the heterogeneity of the older population by adding frailty as assessed by the APOP-score to existing prediction models may enhance the predictive value of these models.
... The CFS is a clinician judgement-based frailty tool that evaluates specific domains including comorbidity, function, and cognition to generate a frailty score ranging from 1 (very fit) to 9 (terminally ill) [26]. The tool's interrater reliability is strong (weighted kappa 0.86) [27]. ...
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Background: Published studies suggest physical recovery from the COVID-19 is complex, with many individuals experiencing persistent symptoms. There is a paucity of data investigating the longer-term trajectory of physical recovery from COVID-19. Methods: A prospective longitudinal design was utilised to investigate the impact COVID-19 has on physical functioning at 10-weeks (T1), 6-months (T2) and 1-year (T3) post-hospital discharge. Objective measures of recovery included 6-Minute Walk Test Distance (6MWTD), frailty (Clinical Frailty Scale), quantification of falls following hospital-discharge, return to work status and exercise levels. Subjective markers included symptoms (COVID-19-Specific Patient Concerns Assessment), fatigue (Chalder Fatigue Score) and health-related quality of life (HrQOL) [Short-Form-36 Health Survey Questionnaire (SF-36-II)]. Univariate analysis was performed using t-test, Wilcoxon rank-sum, and Chi-squared test, paired analysis using one-way analysis of variance and Krustal Wallis testing and correlation analysis with Spearman correlation tests. Results: Sixty-one subjects participated. Assessments were conducted at a median of 55 days(T1), 242 days(T2), and 430 days(T3) following hospital-discharge. 6MWTD improved significantly overtime (F = 10.3, p < 0.001) from 365(209)m at T1 to 447(85)m at T3, however remained below population norms and with no associated improvement in perceived exertion. Approximately half (n = 27(51%)) had returned to pre-diagnosis exercise levels at T3. At least one concern/symptom was reported by 74%, 59% and 64% participants at T1, T2 and T3 respectively. Fatigue was the most frequently reported symptom at T1(40%) and T2(49%), while issues with memory/concentration was the most frequently reported at T3(49%). SF-36 scores did not change in any domain over the study period, and scores remained lower than population norms in the domains of physical functioning, energy/vitality, role limitations due to physical problems and general health. Return-to-work rates are low, with 55% of participants returning to work in some capacity, and 31% of participants don't feel back to full-health at 1-year following infection. Conclusion: Hospitalised COVID-19 survivors report persistent symptoms, particularly fatigue and breathlessness, low HrQOL scores, sub-optimal exercise levels and continued work absenteeism 1-year following infection, despite some objective recovery of physical functioning. Further research is warranted to explore rehabilitation goals and strategies to optimise patient outcomes during recovery from COVID-19. Clinical message: Hospitalised COVID-19 survivors report significant ongoing rehabilitation concerns 1-year following infection, despite objective recovery of physical functioning. Our findings suggest those who returned to exercise within 1-year may have less fatigue and breathlessness. The impact of exercise, and other rehabilitative strategies on physical functioning outcomes following COVID-19 should be investigated in future research.
... This highlights the need for frailty screening measures that assess a broad range of domains but are simple and time-efficient enough to be readily employed in clinical practice. Potential examples are the MFI-5 shown to have prognostic value in older adults undergoing surgery for CRC [38,39] and the CSHA-CFS which is quick to perform, requires limited training of staff and has been shown to have good inter-observer reliability [40,41]. ...
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Introduction Frailty is a complex multifactorial syndrome characterised by a significant increase in vulnerability and worsened health outcomes. Despite a range of proposed frailty screening measures, the prevalence and prognostic value of frailty in patients undergoing surgery for colorectal cancer is not clear. Aim The aim of this present review was to examine the use of commonly employed frailty screening measures in patients undergoing surgery for colorectal cancer. Methods A systematic search of PubMed and Medline was carried out to identify studies reporting the use of frailty screening tools or measures in patients undergoing surgery for colorectal cancer. The screening measure used and prevalence of frailty within the population were recorded. Outcomes of interest were the incidence of post-operative complications, 30-day mortality and overall survival. Results Of the 15 studies included ( n = 97, 898 patients), 9 studies were retrospective and included patients aged 70 years or older ( n = 96, 120 patients). 5 of 12 studies reported that frailty was independently associated with the incidence of post-operative complications. There was also evidence that frailty was independently associated with 30-day mortality (1 of 4 studies, n = 9, 252 patients) and long-term survival (2 of 3 studies, n = 1, 420 patients). Conclusions Frailty was common in patients with colorectal cancer and the assessment of frailty may have prognostic value in patients undergoing surgery. However, the basis of the relationship between frailty and post-operative outcomes is not clear and merits further study.
Seasonal or continuous resource constraints are evident in many healthcare systems and necessitate restrictions on admissions to intensive care units (ICUs). When the demand for ICU beds exceeds capacity, patients who are expected to benefit most are prioritised for admission and continuation of intensive care. In addition to survival, the benefit of intensive care in old patients strongly depends on the quality of life that can be achieved after discharge. In this chapter, we will discuss the challenges of predicting outcome for this patient population as well as the medical and ethical issues which may arise during triage.
Comprehensive Geriatric Assessment (CGA) is defined as “A multimodal, multidisciplinary process which identifies medical, social, functional needs, and the development of an integrated/coordinated care plan to meet those needs”. CGA is associated with lower mortality, less institutionalization and can prevent decline of functional autonomy. The main limits of CGA are that it is time-consuming and it requires many actors. In emergency context, CGA could be adapted to be pragmatic and achievable by non-geriatricians. In Intensive Care Unit (ICU) and especially after ICU discharge, CGA could improve prognosis of old patient and should be further developed in the future.
Learning objectives of this chapter is to review existent risk score applicable to the very old patient. Problems, challenges and ongoing developments are discussed, with particular emphasis on the importance of previous health status over the presence and degree of physiological derangements in this particular population when developing or applying one of these methods.
Introduction The prevalence and complications of biliary disease increase with age. Frailty has been associated with adverse outcomes in the hospital setting. We describe the prevalence of frailty in older patients hospitalised with benign biliary disease and its association with duration of hospital stay, and 90-day and 1-year mortality. Methods We performed a retrospective cohort study of patients aged 75 years and over admitted with acute biliary disease between 17 September 2014 and 20 March 2017. Clinical Frailty Scale (CFS) score was recorded on admission. Results We included 200 patients with a median age of 82 (75–99) years, 60% were female; 154 (77%) were independent for personal activities of daily living (ADLs) and 99 (49.5%) for instrumental ADLs. Cholecystitis was the most common diagnosis (43%) followed by cholangitis (36%) and pancreatitis (21%). Ninety-nine patients were non frail (NF; CFS 1–4) and 101 were frail (F; CFS 5–9). Some 104 patients received medical treatment only. Surgery was more common in NF patients (11% vs F 2%), percutaneous drainage more frequently performed in F patients (15% vs NF 5%) and endoscopic cholangiopancreatography was similar in both groups (F 32% vs NF 31%). Frailty was associated with worse clinical outcomes in F vs NF: functional deconditioning (34% vs 11%), increased care level (19% vs 3%), length of stay (12 vs 7 days), 90-day mortality (8% vs 3%) and 1-year mortality (48% vs 24%). Conclusions Half of patients in our cohort were frail and spent longer in hospital, were less likely to undergo surgery and were less likely to remain alive at 1 year after discharge.
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Background: The Clinical Frailty Scale (CFS) is increasingly used for clinical decision making in acute care but little is known about frailty after COVID-19. Objectives: To investigate frailty and the CFS for post-COVID-19 follow-up. Methods: This prospective multicentre cohort study included COVID-19 survivors aged ≥50 years presenting for a follow-up visit ≥3 months after the acute illness. Nine centres retrospectively collected pre-COVID-19 CFS and prospectively CFS at follow-up. Three centres completed the Frailty Index (FI), the short physical performance battery (SPPB), 30 s sit-to-stand test and handgrip strength measurements. Mixed effect logistic regression models accounting for repeated measurements and potential confounders were used to investigate factors associated with post-COVID-19 CFS. Criterion and construct validity were determined by correlating the CFS to other concurrently assessed frailty measurements and measures of respiratory impairment, respectively. Results: Of the 288 participants 65% were men, mean (SD) age was 65.1 (9) years. Median (IQR) CFS at follow-up was 3 (2-3), 21% were vulnerable or frail (CFS ≥4). The CFS was responsive to change, correlated with the FI (r=0.69, p<0.001), the SPPB score (r=-0.48, p<0.001) (criterion validity) and with the St George's Respiratory Questionnaire score (r=0.59, p<0.001), forced vital capacity %-predicted (r=-0.25, p<0.001), 6 min walk distance (r=-0.39, p<0.001) and modified Medical Research Council (mMRC) (r=0.59, p<0.001). Dyspnoea was significantly associated with a higher odds for vulnerability/frailty (per one mMRC adjusted OR 2.01 (95% CI 1.13 to 3.58), p=0.02). Conclusions: The CFS significantly increases with COVID-19, and dyspnoea is an important risk factor for post-COVID-19 frailty and should be addressed thoroughly.
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The key idea behind the Clinical Frailty Scale (CFS) is that, as people age, they are more likely to have things wrong with them. Those things they have wrong (health deficits) can, as they accumulate, erode their ability to do the high order functions which define their overall health. These high order functions include being able to: think and do as they please; look after themselves; interact with other people; and move about without falling. The Clinical Frailty Scale brings that information together in one place. This paper is a guide for people new to the Clinical Frailty Scale. It also introduces an updated version (CFS version 2.0), with revised level names (e.g., "vulnerable" becomes "living with very mild frailty") and minor edits to level descriptions. The key points discussed are that the Clinical Frailty Scale assays the baseline state, it is not widely validated in younger people or those with stable single-system disabilities, and it requires clinical judgement. The Clinical Frailty Scale is now commonly used as a triage tool to make important clinical decisions such as allocating scarce health care resources for COVID-19 management; therefore, it is important that the scale is used appropriately.
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Background: The Clinical Frailty Scale (CFS) is a commonly used frailty measure in intensive care unit (ICU) settings. We are interested in the test characteristics, especially interrater reliability, of the CFS in ICU by comparing the scores of intensivists to geriatricians. Methods: We conducted a prospective cohort study on a convenience sample of newly admitted patients to an ICU in Edmonton, Canada. An intensivist and a resident in Geriatric Medicine (GM) independently assigned a CFS score on 158 adults within 72 hours of admission. A specialist in Geriatric Medicine assigned a CFS score independently of 20 of the 158 patients to assess agreement between the two raters trained in geriatrics. Predictive validity was captured using mortality and length of stay. Results: Agreement on CFS score was fair for intensivists vs. GM resident (kappa 0.32) and for intensivists vs. GM specialist (0.29), but substantial for GM resident vs. staff (0.79). Despite this, the CFS remained prognostically relevant, regardless of rater background. Frailty (CFS ≥ 5) as assessed by either intensivist or GM resident was a strong predictor of in-hospital mortality (odds ratio [OR] 3.6; 95% CI, 1.6-8.4, p = .003 and OR 3.0; 95% CI 1.3-6.9; p = .01, respectively). Frailty was also positively correlated with age, illness severity measured by APACHE II score, and length of hospital stay. Conclusions: The interrater reliability of the CFS in ICU settings is fair for intensivists vs. geriatricians.
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The devastating pandemic that has stricken the worldwide population induced an unprecedented influx of patients in ICUs, raising ethical concerns not only surrounding triage and withdrawal of life support decisions, but also regarding family visits and quality of end-of-life support. These ingredients are liable to shake up our ethical principles, sharpen our ethical dilemmas, and lead to situations of major caregiver sufferings. Proposals have been made to rationalize triage policies in conjunction with ethical justifications. However, whatever the angle of approach, imbalance between utilitarian and individual ethics leads to unsolvable discomforts that caregivers will need to overcome. With this in mind, we aimed to point out some critical ethical choices with which ICU caregivers have been confronted during the Covid-19 pandemic and to underline their limits. The formalized strategies integrating the relevant tools of ethical reflection were disseminated without deviating from usual practices, leaving to intensivists the ultimate choice of decision.
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Background: Very old critical ill patients are a rapid expanding group. To better understand the magnitude of the challenges involved in intensive care practice for an ageing population and discuss a rational allocation of resources, healthcare practitioners need a reliable evaluation of frailty. In order to promote the adequate use of the Clinical Frailty Scale (CFS) in a wider panel of countries, we aimed to develop, validate and characterise a French (FR) version from the original English (EN) CFS. Methods: We included participants recruited prospectively for the observational "The very old intensive care patient: A multinational prospective observation study" (VIP Study) at Geneva University Hospitals (FR speaking hospital). A FR version of the CFS was obtained by translation (EN- > FR) and back translation (FR- > EN). The final CFS-FR was then evaluated twice on the same participants with at least a 2-week interval by FR-speaking doctors and nurses. Results: Inter-rater reliability was 0.87 (95%CI: 0.76-0.93) between doctors for the original CFS version and 0.76 (95%CI: 0.57-0.87) between nurses for the FR version. Inter-rater variability between doctor and nurse was 0.75 (95%CI: 0.56-0.87) for the original version, and 0.73 (95%CI: 0.52-0.85) for the FR version. Test-retest (stability) with the original vs the FR version was 0.86 (95%CI: 0.72-0.93) for doctors and 0.87 (95%CI: 0.76-0.93) for nurses. Differences between the evaluations of the CFS-EN and CSF-FR were not different from 0, with a mean difference of 0.06 (95%CI -0.24, 0.36) for the EN version and - 0.03 (95%CI -0.47, 0.41) for the FR version. Average original version ratings were slightly lower than FR version ratings, though this difference did not reach significance: -0.29 (95%CI -0.54, 0.04). Conclusion: In this prospective cohort of very old intensive care participants we developed and tested the basic psychometric properties (internal consistency, reproducibility) of a French version of the CFS. This manuscript provides clinically meaningful psychometric properties that have not been previously reported in any other language, including in the original EN version. The French cultural adaptation of this CFS has adequate psychometric properties for doctors or nurses to evaluate frailty in very old intensive care patients.
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Early identification of frailty through targeted screening can facilitate the delivery of comprehensive geriatric assessment (CGA) and may improve outcomes for older inpatients. As several instruments are available, we aimed to investigate which is the most accurate and reliable in the Emergency Department (ED). We compared the ability of three validated, short, frailty screening instruments to identify frailty in a large University Hospital ED. Consecutive patients aged ≥70 attending ED were screened using the Clinical Frailty Scale (CFS), Identification of Seniors at Risk Tool (ISAR), and the Programme on Research for Integrating Services for the Maintenance of Autonomy 7 item questionnaire (PRISMA-7). An independent CGA using a battery of assessments determined each patient’s frailty status. Of the 280 patients screened, complete data were available for 265, with a median age of 79 (interquartile ±9); 54% were female. The median CFS score was 4/9 (±2), ISAR 3/6 (±2), and PRISMA-7 was 3/7 (±3). Based upon the CGA, 58% were frail and the most accurate instrument for separating frail from non-frail was the PRISMA-7 (AUC 0.88; 95% CI:0.83–0.93) followed by the CFS (AUC 0.83; 95% CI:0.77–0.88), and the ISAR (AUC 0.78; 95% CI:0.71–0.84). The PRISMA-7 was statistically significantly more accurate than the ISAR (p = 0.008) but not the CFS (p = 0.15). Screening for frailty in the ED with a selection of short screening instruments, but particularly the PRISMA-7, is reliable and accurate.
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Purpose of the Review Frailty as a concept has been developed a lot during the last 25 years. From its start in geriatrics, its usefulness has also been demonstrated in most other clinical specialties including anesthesia, surgery, and intensive care. Several tools have been found useful to characterize frailty status: frailty phenotype, clinical frailty scale, or specific scores for surgical patients. The purpose of this review is to discuss how frailty interactive with acute critical illness and may alter ICU outcomes, particularly in the old patients. Recent Findings Frailty has in many studies been found to have a substantial impact on most outcome parameters in ICU patients, mainly mortality, but also as non-mortality outcomes. Risk ratio for mortality in frail versus non-frail ICU patients is significantly increased. Frailty affects several important body functions like the endocrine system and brain, muscular, and immune functions. In the ICU, these impaired body functions add to the traditional acute vital organ dysfunctions, well described in the ICU patient. This combination of reduced body function in patients that in addition develops a critical illness is the most likely cause of not only increased short-term but also long-term mortality found in frail ICU patients. Summary This review summarizes current tools to identify frailty and summarizes recent findings of the prognostic role of frailty in the ICU.
Background: A threshold Clinical Frailty Scale (CFS) of 5 (indicating mild frailty) has been proposed to guide ICU admission for UK patients with coronavirus disease 2019 (COVID-19) pneumonia. However, the impact of frailty on mortality with (non-COVID-19) pneumonia in critical illness is unknown. We examined the triage utility of the CFS in patients with pneumonia requiring ICU. Methods: We conducted a retrospective cohort study of adult patients admitted with pneumonia to 170 ICUs in Australia and New Zealand from January 1, 2018 to September 31, 2019. We classified patients as: non-frail (CFS 1-4) frail (CFS 5-8), mild/moderately frail (CFS 5-6),and severe/very severely frail (CFS 7-8). We evaluated mortality (primary outcome) adjusting for site, age, sex, mechanical ventilation, pneumonia type and illness severity. We also compared the proportion of ICU bed-days occupied between frailty categories. Results: 1852/5607 (33%) patients were classified as frail, including1291/3056 (42%) of patients aged >65 yr, who would potentially be excluded from ICU admission under UK-based COVID-19 triage guidelines. Only severe/very severe frailty scores were associated with mortality (adjusted odds ratio [aOR] for CFS=7: 3.2; 95% confidence interval [CI]: 1.3-7.8; CFS=8 [aOR: 7.2; 95% CI: 2.6-20.0]). These patients accounted for 7% of ICU bed days. Vulnerability (CFS=4) and mild frailty (CFS=5) were associated with a similar mortality risk (CFS=4 [OR: 1.6; 95% CI: 0.7-3.8]; CFS=5 [OR: 1.6; 95% CI: 0.7-3.9]). Conclusions: Patients with severe and very severe frailty account for relatively few ICU bed days as a result of pneumonia, whilst adjusted mortality analysis indicated little difference in risk between patients in vulnerable, mild, and moderate frailty categories. These data do not support CFS ≥5 to guide ICU admission for pneumonia.
Purpose Premorbid conditions affect prognosis of acutely-ill aged patients. Several lines of evidence suggest geriatric syndromes need to be assessed but little is known on their relative effect on the 30-day survival after ICU admission. The primary aim of this study was to describe the prevalence of frailty, cognition decline and activity of daily life in addition to the presence of comorbidity and polypharmacy and to assess their influence on 30-day survival. Methods Prospective cohort study with 242 ICUs from 22 countries. Patients 80 years or above acutely admitted over a six months period to an ICU between May 2018 and May 2019 were included. In addition to common patients’ characteristics and disease severity, we collected information on specific geriatric syndromes as potential predictive factors for 30-day survival, frailty (Clinical Frailty scale) with a CFS > 4 defining frail patients, cognitive impairment (informant questionnaire on cognitive decline in the elderly (IQCODE) with IQCODE ≥ 3.5 defining cognitive decline, and disability (measured the activity of daily life with the Katz index) with ADL ≤ 4 defining disability. A Principal Component Analysis to identify co-linearity between geriatric syndromes was performed and from this a multivariable model was built with all geriatric information or only one: CFS, IQCODE or ADL. Akaike’s information criterion across imputations was used to evaluate the goodness of fit of our models. Results We included 3920 patients with a median age of 84 years (IQR: 81–87), 53.3% males). 80% received at least one organ support. The median ICU length of stay was 3.88 days (IQR: 1.83–8). The ICU and 30-day survival were 72.5% and 61.2% respectively. The geriatric conditions were median (IQR): CFS: 4 (3–6); IQCODE: 3.19 (3–3.69); ADL: 6 (4–6); Comorbidity and Polypharmacy score (CPS): 10 (7–14). CFS, ADL and IQCODE were closely correlated. The multivariable analysis identified predictors of 1-month mortality (HR; 95% CI): Age (per 1 year increase): 1.02 (1.–1.03, p = 0.01), ICU admission diagnosis, sequential organ failure assessment score (SOFA) (per point): 1.15 (1.14–1.17, p < 0.0001) and CFS (per point): 1.1 (1.05–1.15, p < 0.001). CFS remained an independent factor after inclusion of life-sustaining treatment limitation in the model. Conclusion We confirm that frailty assessment using the CFS is able to predict short-term mortality in elderly patients admitted to ICU. Other geriatric syndromes do not add improvement to the prediction model. Since CFS is easy to measure, it should be routinely collected for all elderly ICU patients in particular in connection to advance care plans, and should be used in decision making.
Purpose: Frailty is a common condition among critically ill patients. Usually evaluated in a mixed population of medical, cardiac and surgical patients, we aimed to assess the impact of frailty on short- and long-term mortality exclusively in critically ill older medical patients. Materials and methods: We included 285 patients aged≥70 years admitted to ICU (2009-2017). Comorbidities, severity scores, treatment intensity and complications were recorded. Pre-hospital frailty, measured by Clinical Frailty Scale (CFS), was defined as a score ≥ 5 according to this scale. Results: Prevalence of frailty (CFS ≥ 5) of 18.6%. Frail patients were more likely to be female (64.2% vs. 35.6%, p < .001) or suffer from heart failure (17% vs. 6%,p = .021). Apache II score was higher in frail than in non-frail patients (27.4 ± 7.1 vs. 24.8 ± 8.6,p = .041). Age, comorbidities, treatment intensity, complications, and ICU and hospital length of stay were similar between frail and non-frail patients. Life-sustaining treatment limitation was more frequent in frail patients (47.2% vs. 20.7%,p < .001). Except for ICU mortality, frailty was an independent predictor of short- and long-term mortality after adjustment for sociodemographic, comorbidities, severity scores, treatment intensity and complications. Conclusions: Frailty (CFS ≥ 5) was independently associated with short- and long-term mortality in older patients admitted to ICU exclusively due to a medical reason.
Demand for critical care among older patients is increasing in many countries. Assessment of frailty may inform discussions and decision making, but acute illness and reliance on proxies for history‐taking pose particular challenges in patients who are critically ill. Our aim was to investigate the inter‐rater reliability of the Clinical Frailty Scale for assessing frailty in patients admitted to critical care. We conducted a prospective, multi‐centre study comparing assessments of frailty by staff from medical, nursing and physiotherapy backgrounds. Each assessment was made independently by two assessors after review of clinical notes and interview with an individual who maintained close contact with the patient. Frailty was defined as a Clinical Frailty Scale rating > 4. We made 202 assessments in 101 patients (median (IQR [range]) age 69 (65–75 [60–80]) years, median (IQR [range]) Acute Physiology and Chronic Health Evaluation II score 19 (15–23 [7–33])). Fifty‐two (51%) of the included patients were able to participate in the interview; 35 patients (35%) were considered frail. Linear weighted kappa was 0.74 (95%CI 0.67–0.80) indicating a good level of agreement between assessors. However, frailty rating differed by at least one category in 47 (47%) cases. Factors independently associated with higher frailty ratings were: female sex; higher Acute Physiology and Chronic Health Evaluation II score; higher category of pre‐hospital dependence; and the assessor having a medical background. We identified a good level of agreement in frailty assessment using the Clinical Frailty Scale, supporting its use in clinical care, but identified factors independently associated with higher ratings which could indicate personal bias.