Critically ill elderly patients (≥ 90 years): Clinical characteristics, outcome and financial implications
Critically ill elderly patients ( 90 years): Clinical characteristics, outcome and financial implications
Pierrick Le Borgne 0 1 2 3
Quentin Maestraggi 2 3
Sophie Couraud 0 2 3
Franc? ois Lefebvre 2 3
Jean- Etienne Herbrecht 2 3
Alexandra Boivin 2 3
Baptiste Michard 2 3
Vincent Castelain 2 3
Georges Kaltenbach 2 3
Pascal Bilbault 0 1 2 3
Francis Schneider 2 3
0 Emergency Department, Hautepierre Hospital, University Hospital of Strasbourg , Strasbourg , France
1 INSERM (French National Institute of Health and Medical Research), UMR 1260, Regenerative NanoMedicine (RNM), FeA?deA?ration de MeA? decine Translationnelle (FMTS), University of Strasbourg, Strasbourg, France, 3 Medical Intensive Care Unit and UMR 1121, Hautepierre Hospital, University Hospital of Strasbourg, Strasbourg, France, 4 Department of Public Health, University Hospital of Strasbourg, Strasbourg, France, 5 Department of Geriatrics, University Hospital of Strasbourg , Strasbourg , France
2 Editor: Chiara Lazzeri , Azienda Ospedaliero Universitaria Careggi , ITALY
3 Abbreviations: ICU, intensive care unit; ED, Emergency Department; OR, odds ratio; SAPS II, Simplified Acute Physiology Score II; NIV , non-
Data Availability Statement: All relevant data are
within the paper.
Funding: The author(s) received no specific
funding for this work.
Competing interests: The authors have declared
that no competing interests exist.
In the study group of 317 stays: median age was 92 years (IQR: 91?94 years); most patients
were female (71.3%.). Acute respiratory failure (52.4%) was the main admission diagnosis;
mean SAPS II was 55.6?21.3; half the stays (49.2%) required mechanical ventilation
(duration: 7.2?8.8 days); withholding and withdrawing decisions were made for 33.4% of all
stays. ICU and hospital mortality rates were 35.7% and 42.6% respectively. Mechanical
ventilation (OR = 4.83, CI95%: 1.59?15.82) was an independent predictor of ICU mortality
whereas age was not (OR = 0.88, CI95%: 0.72?1.08). Social security reimbursement was
significantly lower in the study group compared with all other ICU stays, both per stay
(13,160 vs 22,092 Euros, p< 0.01) and per day of stay (p = 0.03).
invasive ventilation; RRT, renal replacement
Among critically ill elderly patients ( 90 years), chronological age was not an independent
factor of ICU mortality. ICU care-related costs in this population should not be considered as
a limiting factor for ICU admission.
According to the US Census Bureau, more than 1.87 million adults are 90 years or older (29%
increase from 2000) [
]. As the population ages, intensive care units (ICUs) are confronted
with increasing demand, with elderly patients now representing up to 20?30% of all
Firstly, studies suggest that physicians select patients based on chronological age albeit with
considerable variations among centers [3?4]. Secondly, the geriatric specificities of these
patients are not totally understood, and physicians' knowledge concerning prognosis is not
optimal. The initial triage process prior to ICU admission should be based on patient benefit,
not determined solely by prognosis and comorbidities, but also accompanied by a functional
approach and quality-of-life perspective. Most ICU studies focus on 30-day mortality, whereas
6-month or 1-year mortality seems more appropriate [
]. When a very old patient leaves the
ICU alive, the rehabilitation process appears far more complex. Key factors contributing to a
good recovery include frailty and comorbidity management [6?7].
Several questions remain open, such as the controversial benefit of ICU care for elderly
]. Both ICU and in-hospital mortality rates remain high in critically ill elderly
patients, with a large difference in outcome depending mainly on the motive for admission.
Thus, surgical patients have a satisfactory outcome in contrast to medical patients who are at
higher risk of death [9?10]. Moreover, many patients die soon after ICU discharge and few
have a good recovery one year after discharge. The long-term recovery of functional status
seems low, only one quarter return to baseline levels after 12 months [
End-of-life issues are critical in this population. Ambiguous directives make the
management of such patients complex, highlighting the significance of proactively addressing goals
In the current austere economic climate, cost-effectiveness considerations may also be
included in medical decisions [
]. Concerning elderly patients, very few studies have
addressed this particular implication [
]. It also appears that elderly patients receive less
treatment in the ICU even after adjustment for severity of illness [
]. There are no current
guidelines to assist the decision-making process, which leads to heterogeneity of practices [
The main objective of this study was to determine the clinical characteristics and outcome
in elderly patients ( 90 years). In addition, we wanted to determine independent predictors
of ICU mortality. Lastly, a particular focus was laid on medico-economic implications.
Our hospital is a teaching hospital with 2,200 beds, 179,000 stays, 70,000 patients in the
Emergency Department (ED) and approximately 1,000 ICU admissions each year. In France, the
development of out-of-hospital medical care allows direct ICU admission (from home or
nursing home) for critically ill patients.
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The present study was a monocentric and retrospective analysis of collected data of all
patients 90 years admitted to a 30-bed medical ICU (mean duration of stay: 9 days) between
January 2000 and December 2015. If a patient was admitted to the ICU several times, this was
considered as multiple stays and data were analyzed for each stay.
For each patient, we collected demographic information including age, sex, motive for
admission and disposition at hospital discharge. The existence of a fatal disease was reflected by the
McCabe score and the functional status was evaluated by the Knaus classification [17?18].
Otherwise, we used the Charslon comorbidity index, which has been shown to predict the
one-year mortality [
]. Clinical data encompassed the primary diagnosis, the comorbidities,
the need for ventilation and organ support (catecholamines, renal replacement therapy), the
length of ICU and hospital stay, the discharge information as well as occurrence of
withholding or withdrawing life support. A long-term survival follow-up was obtained for all patients
by direct contact with them, their relatives or their general practitioner.
Severity of illness was assessed using the Simplified Acute Physiology Score II (SAPS II)
]. ICU and in-hospital outcomes were analyzed and compared with those of all other ICU
patients (< 90 years) during the study period and the French general population ( 90 years)
]. Sub-group analysis was performed in order to compare clinical characteristics and ICU
procedures, firstly, between ICU survivors and non-survivors and, secondly, according to
three consecutive periods (2000?2004, 2005?2009, 2010?2015).
Finally, we studied medico-economic data and activity tarification. In our healthcare
system, care-payers reimburse ICU stays to hospitals according to annual tariff rates fixed by law.
The all-inclusive price includes both a basic rate according to homogeneous disease-stay fare
(or case-mix fare) and a daily, but fixed, supplement related to the intensity of care whatever
the disease treated. During the study period tariffs were stable or slightly increasing for a given
case-mix from 2000 to 2010, but were progressively decreasing from 2011 to 2015 thanks to a
policy of improving care-related costs. There was no specific adjustment for age in this
reimbursement from the social security budget in relation to either part of the tariff.
This study was approved by the institution's ethics review board (reference: AMK/BG/2015/
The descriptive analysis of the qualitative variables gives the frequency of each value and the
cumulative frequency, and that of the quantitative variables, gives location parameters (mean,
median, first and third quartiles), and dispersion parameters (standard deviation, variance,
range and interquartile range). Normality of the distributions was checked using the
ShapiroWilk or Kolmogorov-Smirnov test. The Kaplan-Meier method was used to determine survival
rates. Comparisons between qualitative variables were made using Chi-squared test or Fisher's
exact test. Comparisons between quantitative and qualitative variables were made using the
Student's t-test (or ANOVA) or Wilcoxon's test (or Kruskall-Wallis test). To estimate the
independent predictors of ICU mortality, logistic regressions were performed. Multivariate
analyses were done using variables statistically significant in bivariate analyses (p<0.1) and with
age. A stepwise regression based on the AIC was performed with backward selection (and with
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age always included in the model). The significance level was set at 5%. All analyses were made
with R 3.2.2 software.
During the study period a total of 16,210 stays were completed in our ICU. In 317 stays the
patient was 90 years or older (1.96%) with 22 multiple stays (6.9%). Median age was 92 years,
(IQR: 91?94) and the proportion of females was 71.3%. Most patients (39.8%) were admitted
from the ED and about one third directly from home or nursing home by out-of-hospital
services. Acute respiratory failure (52.4%) was the most frequent cause of admission followed by
sepsis (11.4%). Mean ICU length of stay (LOS) was 7.0?8.0 days. Clinical characteristics of the
study population can be consulted in Table 1.
Almost half the study population (49.2%) underwent mechanical ventilation (MV) for an
average of 7.2?8.8 days; 38.8% of all patients had exclusive non-invasive ventilation (NIV) for 2.9?
2.6 days. Catecholamine support was applied in 47.6% of ICU stays and in 6.9% of stays a renal
replacement therapy (RRT) was necessary. The decision to withhold or withdraw treatments
was made for 33.4% of all stays, on average after 5.3 days (SD: 9.0 days) after ICU admission.
ICU non-survivors had more MV and catecholamines (p<0.01) but less NIV (p = 0.02).
Withholding and withdrawing therapy were used mainly in the non-survivors group (p<0.01), but
later after admission than in survivors (6.1 vs. 1.9 days, p = 0.01). The list of ICU procedures is
available in Table 2.
Clinical course and outcome
ICU mortality was 35.7% and in-hospital-mortality was 42.6% in the study population. ICU
survivors and non-survivors did not differ significantly in terms of comorbidities. Non-survivors
had higher severity, as illustrated by SAPS II (71.7 vs. 46.7, p<0.01). Patients admitted from the
ED were more likely to survive the ICU stay (p = 0.03), contrary to patients admitted directly
from home (p = 0.04) and respiratory failure was linked to better ICU outcome (p<0.01). There
was no difference in terms of ICU LOS between survivors and non-survivors (p = 0.43).
Mechanical ventilation (OR = 4.83, CI95%: 1.59?15.82) and SAPS II (OR = 1.09, CI95%:
1.05?1.12) were independent predictors of ICU mortality in univariate and multivariate
analysis. Withhholding and Withdrawing therapy (OR = 202.25, CI95%: 50.3?1145.2) and
bacteremia were also associated with worse outcome. Other variables such as RRT, catecholamines,
NIV and age (OR = 0.88, CI95%: 0.72?1.08) did not differ between ICU survivors and
nonsurvivors (Table 3).
Most survivors were discharged to medical wards (45.7%) and geriatrics (14.8%). 90-day,
6-month and 1-year mortality were 47.3%, 55.8% and 69.7% respectively. We compared the
study population with French population-based data of the same age group (Fig 1).
Evolution of practices
We divided the study time into three periods (2000?2004, 2005?2009, 2010?2015) in order to
compare patients characterictics, ICU procedures and survival. The proportion of elderly
patients did not change over the time of the study (p = 0.26), nor did the ICU LOS (p = 0.76)
and most procedures (S1 and S2 Tables); whereas severity and LOS increased significantly in
younger patients from 2000 to 2015. However, we noticed a progressive increase in advanced
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a more than one diagnosis is possible.
ICU: intensive care unit, Me: mean, Md: median, IQR: interquartile range (25?75), SD: standard derivation, SAPS II: simplified acute physiology score, LOS: Length of
Pearson's Chi-squared test.
Fisher's Exact Test.
?? Wilcoxon rank sum test.
PLOS ONE | https://doi.org/10.1371/journal.pone.0198360
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n = 204
n = 113
ICU: intensive care unit, MV: mechanical ventilation, NIV: non-invasive ventilation, RRT: renal replacement therapy. Me: mean, Md: median, IQR: interquartile range
(25?75), SD: standard deviation.
Pearson's Chi-squared test.
Fisher's Exact Test.
?? Wilcoxon rank sum test.
end of life instructions which almost doubled from 2000 to 2015. Survival rates among elderly
patients remained similar in all three periods (p = 0.27) (S1 Fig), while mortality in younger
patients significantly decreased (data not shown).
We compared the financing of ICU stays by care-payers in the study population with a control
group of all other stays of patients aged less than 90 years (n = 15,893) admitted to the ICU
during the same period. The elderly population had a higher SAPS II score (p<0.01), but the
ICU LOS was similar in both groups (p = 0.07). Social security reimbursement was
significantly lower in the study group, both per stay (13,160 vs. 22,092 Euros, p<0.01) and per day of
stay (3,305 vs. 4,332 Euros, p = 0.03). Over the previously defined study periods, we saw a
divergence in the LOS and social security compensation between the study group and the
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control group. From 2000 to 2015, severity, LOS and reimbursements remained stable in the
study population whereas in younger patients all three increased significantly (Tables 4 and 5).
Most countries are now faced with the growing challenge related to global population ageing.
In our region with good bed availability, ICU physicians have been admitting very old patients
for a long time. Poor availability of ICU beds will require unbiased triage guidelines and it
should ideally use different tools than in younger patients [
]. In this context, our data
underscore two significant points: firstly, life expectancy of patients over 90 years old admitted
to the ICU is limited to 3 years and secondly, the financial burden of critical care for these
elderly patients is?on average?not on the increase compared with younger patients.
Fig 1. Survival from ICU admission. Kaplan-Meier survival curve of the study population in comparison with the
French general poplation of similar age. Mortality data for the latter were obtained from INED . ICU: intensive
care unit. INED: institut national d'e?tudes de?mographiques. Absolute Excess Risk test.
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Our study showed a high ICU and in-hospital mortality. Hwabejire et al. [
] analyzed 474
trauma nonagenarians, with lower in-hospital mortality (9.5%) but higher 1-year mortality
(40.5%). Becker et al. [
] examined 372 patients, the ICU and in-hospital mortality being
18.3% and 30.9% respectively. Other studies with elderly patients (mostly done with
patients 80 years) demonstrated ICU mortality rates ranging from 15% to 50% [
comparison, in-hospital mortality in younger ICU populations (45?65 years) ranges from 20% to
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]. The comparability between all these studies is limited by the fact that outcome is
dependent on the patient's profile (medical or surgical, planned or unplanned admission) [
The fact that we had mainly medical and unplanned patients could explain our high mortality
rate (likely leading to lower ICU costs); which is also being related to our liberal admission
policy. Whereas age is identified as an independent risk factor for ICU mortality in non-selected
populations, comorbidities, frailty and severity of illness appear to be more important risk
factors than age itself in an elderly population [
ICU physicians also suggest that end-of-life decisions are not adequately weighed in this
population with a poor short-term outcome [
]. We have observed an increasing number of
end-of-life decisions over time in our study, which may explain why the ICU length of stay did
not increase in the study population ( 90 years), yet it increased in younger patients. In fact,
a high proportion of deaths in critically ill elderly patients follow a withdrawal of
life-sustaining therapy. Furthermore, it is fundamental to assess the patient's opinion, especially as the
elderly are often reluctant to undergo life-sustaining treatments [
]. A recent study reported
that only 13% had been asked about their willingness to be admitted to the ICU [
Studies focused on very elderly patients ( 90 years) admitted to ICUs are scarce. Becker
et al. [
] have detected age, the need for vasopressors and renal impairment as independent
factors of bad outcome within the ICU, while elective surgery did not negatively impact
outcome. In our study, chronological age was not per se a factor of bad prognosis and this was
stable throughout the study period. In contrast, the need for MV was independently associated
with poor prognosis. The influence of NIV on outcome in our study population remains
unclear, since it looked protective only in univariate analysis. Given the fact that it can easily
be performed elsewhere than in the ICU, our data suggest it be used without limit.
Most elderly patients are treated in ICUs at heavy costs, in cooperation if necessary with
organ specialists. Few of them are visited by a geriatrician despite recent data suggesting a
need of such involvement [
]. The holistic approach of geriatricians could lead to better
decision-making, help in the triage process and remain a key factor in post-ICU care. Specific
geriatric ICUs are exceedingly rare [
]. Combining a multidimensional and interdisciplinary
approach to coordinate treatments with the recovery process could be an efficient way of
treating approximatively half the nonagenarians studied who did not require respiratory support.
Limited resources, costs and controversial benefit are currently the main reasons for the
debate regarding ICU access for elderly patients [8,13?14]. It has been demonstrated that these
patients receive lower treatment intensity and less life-sustaining treatment than younger
patients even after adjustment for severity of illness [
]. Overall, in our study, the total
amount of money dedicated to elderly patients is significantly lower than that for younger
patients. This data suggests that elderly patients undergoing intensive care do not constitute a
heavier healthcare burden. Thus, in our economic model, cost of stay cannot be considered as
an obstacle to admission in ICUs. Our results suggest that ICU costs have to be studied in line
with a close to 0% life expectancy 3 years after ICU admission. Appropriateness of care should
be the main priority, as it is for younger patients in which a 3-year life expectancy is not an
obstacle to ICU care. These are several reasons why guidelines need to be published with a
view to clarifying admission criteria for elderly patients [
Our results should be interpreted with caution on account of several limitations. Firstly,
our single-center study provides findings that may not be transposable to settings where ICU
availability is different. Secondly, our follow-up did not provide insights into functional status
after discharge and assessment of frailty which is now used to evaluate outcome [6?7]. Thirdly,
there is no estimate of costs associated with overall hospital stay nor post-hospital healthcare
utilisation, which may be significant in this very old population. Finally, further studies on
long-term outcome are needed [
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Critically ill elderly patients ( 90 years) constitute a fast-expanding subgroup proposed for
ICU admission. Until now, some physicians have been reluctant to admit them, mostly
because of high in-hospital mortality; however prognosis is not as poor as often perceived. Our
data suggests that chronological age is not a viable exclusion criterion for ICU admission, but
rather that elderly patients should benefit of equitable access to ICUs. The present study adds
to our understanding that there is no real financing issue regarding ICU care in patients over
90 years old.
S1 Table. Comparison of general characteristics of the study population according to the
three consecutive periods of the study.
S2 Table. Comparison of ICU procedures according to the three consecutive periods of the
S1 Fig. Kaplan-Meier survival curves for the three periods of the study.
We thank Dr C. Brunhuber for her English proofreading of the manuscript.
Conceptualization: Pierrick Le Borgne, Sophie Couraud, Georges Kaltenbach, Pascal Bilbault,
Data curation: Quentin Maestraggi, Sophie Couraud, Franc?ois Lefebvre.
Formal analysis: Pierrick Le Borgne, Sophie Couraud, Franc?ois Lefebvre, Baptiste Michard,
Investigation: Pierrick Le Borgne, Alexandra Boivin, Francis Schneider.
Methodology: Pierrick Le Borgne, Quentin Maestraggi, Franc?ois Lefebvre, Alexandra Boivin,
Pascal Bilbault, Francis Schneider.
Project administration: Jean-Etienne Herbrecht, Francis Schneider.
Resources: Pierrick Le Borgne.
Software: Jean-Etienne Herbrecht.
Supervision: Pierrick Le Borgne, Quentin Maestraggi, Sophie Couraud, Franc?ois Lefebvre,
Jean-Etienne Herbrecht, Alexandra Boivin, Baptiste Michard, Vincent Castelain, Georges
Kaltenbach, Francis Schneider.
Validation: Pierrick Le Borgne, Quentin Maestraggi, Sophie Couraud, Franc?ois Lefebvre,
Jean-Etienne Herbrecht, Alexandra Boivin, Baptiste Michard, Vincent Castelain, Georges
Kaltenbach, Francis Schneider.
Visualization: Pierrick Le Borgne, Alexandra Boivin, Francis Schneider.
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Writing ? original draft: Pierrick Le Borgne, Sophie Couraud, Pascal Bilbault, Francis
Writing ? review & editing: Pierrick Le Borgne, Baptiste Michard, Vincent Castelain, Georges
Kaltenbach, Pascal Bilbault, Francis Schneider.
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