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Published in: BMC Geriatrics 1/2022

Open Access 01-12-2022 | Care | Research article

Premorbid functional status as an outcome predictor in intensive care patients aged over 85 years

Authors: Laura Pietiläinen, Minna Bäcklund, Johanna Hästbacka, Matti Reinikainen

Published in: BMC Geriatrics | Issue 1/2022

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Abstract

Background

Poor premorbid functional status (PFS) is associated with mortality after intensive care unit (ICU) admission in patients aged 80 years or older. In the subgroup of very old ICU patients, the ability to recover from critical illness varies irrespective of age. To assess the predictive ability of PFS also among the patients aged 85 or older we set out the current study.

Methods

In this nationwide observational registry study based on the Finnish Intensive Care Consortium database, we analysed data of patients aged 85 years or over treated in ICUs between May 2012 and December 2015. We defined PFS as good for patients who had been independent in activities of daily living (ADL) and able to climb stairs and as poor for those who were dependent on help or unable to climb stairs.
To assess patients’ functional outcome one year after ICU admission, we created a functional status score (FSS) based on how many out of five physical activities (getting out of bed, moving indoors, dressing, climbing stairs, and walking 400 m) the patient could manage. We also assessed the patients’ ability to return to their previous type of accommodation.

Results

Overall, 2037 (3.3% of all adult ICU patients) patients were 85 years old or older. The average age of the study population was 87 years. Data on PFS were available for 1446 (71.0%) patients (good for 48.8% and poor for 51.2%). The one-year mortalities of patients with good and those with poor PFS were 29.2% and 50.1%, respectively, p < 0.001. Poor PFS increased the probability of death within 12 months, adjusted odds ratio (OR), 2.15; 95% confidence interval (CI) 1.68–2.76, p < 0.001. For 69.5% of survivors, the FSS one year after ICU admission was unchanged or higher than their premorbid FSS and 84.2% of patients living at home before ICU admission still lived at home.

Conclusions

Poor PFS doubled the odds of death within one year. For most survivors, functional status was comparable to the premorbid status.
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Literature
1.
go back to reference Haas LEM, Ferishta BR, van Dijjk D, de Lange DW, de Keizer NF. Outcomes of intensive care patients over 90 years old, a 11-year national observational study. J Am Geriatr Soc. 2020;68:1828–32.CrossRef Haas LEM, Ferishta BR, van Dijjk D, de Lange DW, de Keizer NF. Outcomes of intensive care patients over 90 years old, a 11-year national observational study. J Am Geriatr Soc. 2020;68:1828–32.CrossRef
2.
go back to reference Garrouste-Orgeas M, Ruckly S, Grégoire C, Dumesnil A-S, Pommier C, Jamali S, et al. Treatment intensity and outcome of nonagenarians selected for admission in ICUs: a multicenter study of the Outcomerea Research Group. Ann Intensive Care. 2016;6:31.CrossRef Garrouste-Orgeas M, Ruckly S, Grégoire C, Dumesnil A-S, Pommier C, Jamali S, et al. Treatment intensity and outcome of nonagenarians selected for admission in ICUs: a multicenter study of the Outcomerea Research Group. Ann Intensive Care. 2016;6:31.CrossRef
3.
go back to reference Heyland D, Cook D, Bagshaw SM, Garland A, Stelfox HT, Mehta S, et al. The very elderly admitted to ICU: a quality finish? Crit Care Med. 2015;43:1352–60.CrossRef Heyland D, Cook D, Bagshaw SM, Garland A, Stelfox HT, Mehta S, et al. The very elderly admitted to ICU: a quality finish? Crit Care Med. 2015;43:1352–60.CrossRef
4.
go back to reference Reinikainen M, Uusaro A, Niskanen M, Ruokonen E. Intensive care of the elderly in Finland. Acta Anaesthesiol Scand. 2007;51:522–9.CrossRef Reinikainen M, Uusaro A, Niskanen M, Ruokonen E. Intensive care of the elderly in Finland. Acta Anaesthesiol Scand. 2007;51:522–9.CrossRef
5.
go back to reference Garrouste-Orgeas M, Timsit J-F, Montuclard L, Colvez A, Gattolliat O, Philippart F, et al. Decision-making process, outcome, and 1-year quality of life of octogenarians referred for intensive care unit admission. Intensive Care Med. 2006;32:1045–51.CrossRef Garrouste-Orgeas M, Timsit J-F, Montuclard L, Colvez A, Gattolliat O, Philippart F, et al. Decision-making process, outcome, and 1-year quality of life of octogenarians referred for intensive care unit admission. Intensive Care Med. 2006;32:1045–51.CrossRef
6.
go back to reference Boumendil A, Angus DC, Guitonneau A-L, Menn AM, Ginsburg C, Takun K, et al. Variability of intensive care admission decisions for the very elderly. PLoS One. 2012;7:e34387.CrossRef Boumendil A, Angus DC, Guitonneau A-L, Menn AM, Ginsburg C, Takun K, et al. Variability of intensive care admission decisions for the very elderly. PLoS One. 2012;7:e34387.CrossRef
7.
go back to reference Knaus WA, Draper EA, Wagner DP. APACHE II: a severity of disease classification system. Crit Care Med. 1985;13:818–29.CrossRef Knaus WA, Draper EA, Wagner DP. APACHE II: a severity of disease classification system. Crit Care Med. 1985;13:818–29.CrossRef
8.
go back to reference Le Gall JRJ, Lemeshow SS, Saulnier FF. A new Simplified Acute Physiology Score (SAPS II) based on a European/North American multicenter study. JAMA. 1993;270:2957–63.CrossRef Le Gall JRJ, Lemeshow SS, Saulnier FF. A new Simplified Acute Physiology Score (SAPS II) based on a European/North American multicenter study. JAMA. 1993;270:2957–63.CrossRef
9.
go back to reference de Rooij SE, Govers A, Korevaar JC, Abu-Hanna A, Levi M, de Jonge E. Short-term and long-term mortality in very elderly patients admitted to an intensive care unit. Intensive Care Med. 2006;32:1039–44.CrossRef de Rooij SE, Govers A, Korevaar JC, Abu-Hanna A, Levi M, de Jonge E. Short-term and long-term mortality in very elderly patients admitted to an intensive care unit. Intensive Care Med. 2006;32:1039–44.CrossRef
10.
go back to reference Kaarlola A, Tallgren M, Pettilä V. Long-term survival, quality of life, and quality-adjusted life-years among critically ill elderly patients. Crit Care Med. 2006;34:2120–6.CrossRef Kaarlola A, Tallgren M, Pettilä V. Long-term survival, quality of life, and quality-adjusted life-years among critically ill elderly patients. Crit Care Med. 2006;34:2120–6.CrossRef
11.
go back to reference Sacanella E, Perez-Castejon JM, Nicolas JM, Masanés F, Navarro M, Castro P, et al. Mortality in healthy elderly patients after ICU admission. Intensive Care Med. 2009;35:550–5.CrossRef Sacanella E, Perez-Castejon JM, Nicolas JM, Masanés F, Navarro M, Castro P, et al. Mortality in healthy elderly patients after ICU admission. Intensive Care Med. 2009;35:550–5.CrossRef
12.
go back to reference Flaatten H, de Lange DW, Morandi A, Andersen FH, Artigas A, Bertolini G, et al. The impact of frailty on ICU and 30-day mortality and the level of care in very elderly patients (≥ 80 years). Intensive Care Med. 2017;43:1820–8.CrossRef Flaatten H, de Lange DW, Morandi A, Andersen FH, Artigas A, Bertolini G, et al. The impact of frailty on ICU and 30-day mortality and the level of care in very elderly patients (≥ 80 years). Intensive Care Med. 2017;43:1820–8.CrossRef
13.
go back to reference Guidet B, De Lange DW, Boumendil A, Leaver S, Watson X, Boulanger C, Szczeklik W, et al. The contribution of frailty, cognition, activity of daily life and comorbidities on outcome in acutely admitted patients over 80 years in European ICUs: the VIP2 study. Intensive Care Med. 2020;46:57–69.CrossRef Guidet B, De Lange DW, Boumendil A, Leaver S, Watson X, Boulanger C, Szczeklik W, et al. The contribution of frailty, cognition, activity of daily life and comorbidities on outcome in acutely admitted patients over 80 years in European ICUs: the VIP2 study. Intensive Care Med. 2020;46:57–69.CrossRef
14.
go back to reference Montgomery C, Zuege D, Rolfson D, Opgenorth D, Hudson D, Stelfox HT, et al. Implementation of population-level screening for frailty among patients admitted to adult intensive care in Alberta. Canada Can J Anesth. 2019;66:1310–9.CrossRef Montgomery C, Zuege D, Rolfson D, Opgenorth D, Hudson D, Stelfox HT, et al. Implementation of population-level screening for frailty among patients admitted to adult intensive care in Alberta. Canada Can J Anesth. 2019;66:1310–9.CrossRef
15.
go back to reference Muscedere J, Waters B, Varambally A, Bagshaw SM, Boyd JG, Maslove D, et al. The impact of frailty on intensive care unit outcomes: a systematic review and meta-analysis. Intensive Care Med. 2017;43:1105–22.CrossRef Muscedere J, Waters B, Varambally A, Bagshaw SM, Boyd JG, Maslove D, et al. The impact of frailty on intensive care unit outcomes: a systematic review and meta-analysis. Intensive Care Med. 2017;43:1105–22.CrossRef
16.
go back to reference De Geer L, Fredrikson M, Tibblin A. Frailty predicts 30-day mortality in intensive care patients: A prospective prediction study. Eur J Anaesthesiol. 2020;37:1058–65.CrossRef De Geer L, Fredrikson M, Tibblin A. Frailty predicts 30-day mortality in intensive care patients: A prospective prediction study. Eur J Anaesthesiol. 2020;37:1058–65.CrossRef
17.
go back to reference Pietiläinen L, Hästbacka J, Bäcklund M, Parviainen I, Pettilä V, Reinikainen M. Premorbid functional status as a predictor of 1-year mortality and functional status in intensive care patients aged 80 years or older. Intensive Care Med. 2018;44:1221–9.CrossRef Pietiläinen L, Hästbacka J, Bäcklund M, Parviainen I, Pettilä V, Reinikainen M. Premorbid functional status as a predictor of 1-year mortality and functional status in intensive care patients aged 80 years or older. Intensive Care Med. 2018;44:1221–9.CrossRef
18.
go back to reference Reinikainen M, Mussalo P, Hovilehto S, Uusaro A, Varpula T, Kari A, et al. Association of automated data collection and data completeness with outcome of intensive care. A new customised model for outcome prediction. Acta Anaesthesiol Scand. 2012;56:1114–22.CrossRef Reinikainen M, Mussalo P, Hovilehto S, Uusaro A, Varpula T, Kari A, et al. Association of automated data collection and data completeness with outcome of intensive care. A new customised model for outcome prediction. Acta Anaesthesiol Scand. 2012;56:1114–22.CrossRef
19.
go back to reference Vincent JL, Moreno R, Takala J, Willatts S, De Mendonça A, Bruining H, et al. The SOFA (Sepsis-related Organ Failure Assessment) score to describe organ dysfunction/failure. On behalf of the Working Group on Sepsis-Related Problems of the European Society of Intensive Care Medicine. Intensive Care Med. 1996;22:707–10.CrossRef Vincent JL, Moreno R, Takala J, Willatts S, De Mendonça A, Bruining H, et al. The SOFA (Sepsis-related Organ Failure Assessment) score to describe organ dysfunction/failure. On behalf of the Working Group on Sepsis-Related Problems of the European Society of Intensive Care Medicine. Intensive Care Med. 1996;22:707–10.CrossRef
20.
go back to reference Vincent JL, de Mendonça A, Cantraine F, Moreno R, Takala J, Suter PM, et al. Use of the SOFA score to assess the incidence of organ dysfunction/failure in intensive care units: results of a multicenter, prospective study. Working group on “sepsis-related problems” of the European Society of Intensive Care Medicine. Crit Care Med. 1998;26:1793–800.CrossRef Vincent JL, de Mendonça A, Cantraine F, Moreno R, Takala J, Suter PM, et al. Use of the SOFA score to assess the incidence of organ dysfunction/failure in intensive care units: results of a multicenter, prospective study. Working group on “sepsis-related problems” of the European Society of Intensive Care Medicine. Crit Care Med. 1998;26:1793–800.CrossRef
21.
go back to reference Keene AR, Cullen DJ. Therapeutic Intervention Scoring System: update 1983. Crit Care Med. 1983;11:1–3.CrossRef Keene AR, Cullen DJ. Therapeutic Intervention Scoring System: update 1983. Crit Care Med. 1983;11:1–3.CrossRef
22.
go back to reference Oken M, Creech R, Tormey D, Horton J, Davis TE, McFadden ET, et al. Toxicity and response criteria of the Eastern Cooperative Oncology Group. Am J Clin Oncol. 1982;5:649–55.CrossRef Oken M, Creech R, Tormey D, Horton J, Davis TE, McFadden ET, et al. Toxicity and response criteria of the Eastern Cooperative Oncology Group. Am J Clin Oncol. 1982;5:649–55.CrossRef
23.
go back to reference Tiainen K, Raitanen J, Vaara E, Hervonen A, Jylhä M. Longitudinal changes in mobility among nonagenarians: the Vitality 90+ Study. BMC Geriatr. 2015;15:124.CrossRef Tiainen K, Raitanen J, Vaara E, Hervonen A, Jylhä M. Longitudinal changes in mobility among nonagenarians: the Vitality 90+ Study. BMC Geriatr. 2015;15:124.CrossRef
24.
go back to reference Lisko I, Tiainen K, Raitanen J, Jylhävä J, Hurme M, Hervonen A, et al. Body Mass Index and Waist Circumference as Predictors of Disability in Nonagenarians: The Vitality 90+ Study. J Gerontol A Biol Sci Med Sci. 2017;72:1569–74.CrossRef Lisko I, Tiainen K, Raitanen J, Jylhävä J, Hurme M, Hervonen A, et al. Body Mass Index and Waist Circumference as Predictors of Disability in Nonagenarians: The Vitality 90+ Study. J Gerontol A Biol Sci Med Sci. 2017;72:1569–74.CrossRef
25.
go back to reference Liu H, Li G, Cumberland WG, Wu T. Testing statistical significance of the area under a receiving operating characteristics curve for repeated measures design with bootstrapping. Journal of Data Science. 2005;3:257–78.CrossRef Liu H, Li G, Cumberland WG, Wu T. Testing statistical significance of the area under a receiving operating characteristics curve for repeated measures design with bootstrapping. Journal of Data Science. 2005;3:257–78.CrossRef
26.
go back to reference Guidet B, Leblanc G, Simon T, Woimant M, Quenot JP, Ganansia O, et al. Effect of systematic intensive care unit triage on long-term mortality among critically ill elderly patients in France: A randomized clinical trial. JAMA. 2017;318:1450–9.CrossRef Guidet B, Leblanc G, Simon T, Woimant M, Quenot JP, Ganansia O, et al. Effect of systematic intensive care unit triage on long-term mortality among critically ill elderly patients in France: A randomized clinical trial. JAMA. 2017;318:1450–9.CrossRef
27.
go back to reference Ball IM, Bagshaw SM, Burns KE, Cook DJ, Day AG, Dodek PM, et al. A clinical prediction tool for hospital mortality in critically ill elderly patients. J Crit Care. 2016;35:206–12.CrossRef Ball IM, Bagshaw SM, Burns KE, Cook DJ, Day AG, Dodek PM, et al. A clinical prediction tool for hospital mortality in critically ill elderly patients. J Crit Care. 2016;35:206–12.CrossRef
28.
go back to reference Andersen FH, Flaatten H, Klepstad P, Follestad T, Strand K, Krüger AJ, et al. Long-term outcomes after ICU admission triage in octogenarians. Crit Care Med. 2016;45:e363–71.CrossRef Andersen FH, Flaatten H, Klepstad P, Follestad T, Strand K, Krüger AJ, et al. Long-term outcomes after ICU admission triage in octogenarians. Crit Care Med. 2016;45:e363–71.CrossRef
29.
go back to reference Heyland DK, Stelfox HT, Garland A, Cook D, Dodek P, Kutsogiannis J, et al. Predicting performance status 1 year after critical illness in patients 80 years or older: Development of a multivariable clinical prediction model. Crit Care Med. 2016;44:1718–26.CrossRef Heyland DK, Stelfox HT, Garland A, Cook D, Dodek P, Kutsogiannis J, et al. Predicting performance status 1 year after critical illness in patients 80 years or older: Development of a multivariable clinical prediction model. Crit Care Med. 2016;44:1718–26.CrossRef
30.
go back to reference Rockwood K, Song X, MacKnight C, Bergman H, Hogan DB, McDowell I, et al. A global clinical measure of fitness and frailty in elderly people. Can Med Assoc J. 2005;173:489–95.CrossRef Rockwood K, Song X, MacKnight C, Bergman H, Hogan DB, McDowell I, et al. A global clinical measure of fitness and frailty in elderly people. Can Med Assoc J. 2005;173:489–95.CrossRef
31.
go back to reference Zhang XM, Chen D, Xie XH, Zhang JE, Zeng Y, Cheng ASK. Sarcopenia as a predictor of mortality among the critically ill in an intensive care unit: a systematic review and meta-analysis. BMC Geriatr. 2021;21:339.CrossRef Zhang XM, Chen D, Xie XH, Zhang JE, Zeng Y, Cheng ASK. Sarcopenia as a predictor of mortality among the critically ill in an intensive care unit: a systematic review and meta-analysis. BMC Geriatr. 2021;21:339.CrossRef
32.
go back to reference Hoogendijk EO, van der Noordt M, Onwuteaka-Philipsen BD, Deeg DJH, Huisman M, Enroth L, et al. Sex differences in healthy life expectancy among nonagenarians: A multistate survival model using data from the vitality 90+ study. Exp Gerontol. 2019;116:80–5.CrossRef Hoogendijk EO, van der Noordt M, Onwuteaka-Philipsen BD, Deeg DJH, Huisman M, Enroth L, et al. Sex differences in healthy life expectancy among nonagenarians: A multistate survival model using data from the vitality 90+ study. Exp Gerontol. 2019;116:80–5.CrossRef
33.
go back to reference Heyland DK, Garland A, Bagshaw SM, Cook D, Rockwood K, Stelfox HT, et al. Recovery after critical illness in patients aged 80 years or older: a multi-center prospective observational cohort study. Intensive Care Med. 2015;41:1911–20.CrossRef Heyland DK, Garland A, Bagshaw SM, Cook D, Rockwood K, Stelfox HT, et al. Recovery after critical illness in patients aged 80 years or older: a multi-center prospective observational cohort study. Intensive Care Med. 2015;41:1911–20.CrossRef
34.
go back to reference Guidet B, Flaatten H, Boumendil A, Morandi A, Andersen FH, Artigas A, et al. Withholding or withdrawing of life sustaining therapy in very elderly patients (≥ 80 years) admitted to the intensive care unit. Intensive Care Med. 2018;44:1027–38.CrossRef Guidet B, Flaatten H, Boumendil A, Morandi A, Andersen FH, Artigas A, et al. Withholding or withdrawing of life sustaining therapy in very elderly patients (≥ 80 years) admitted to the intensive care unit. Intensive Care Med. 2018;44:1027–38.CrossRef
35.
go back to reference Adamski J, Weigl W, Lahtinen P, Reinikainen M, Kaminski T, Pietiläinen L, et al. Intensive care patient survival after limiting life-sustaining treatment—The FINNEOL national cohort study. Acta Anaesthesiol Scand. 2020;64:1144–53.CrossRef Adamski J, Weigl W, Lahtinen P, Reinikainen M, Kaminski T, Pietiläinen L, et al. Intensive care patient survival after limiting life-sustaining treatment—The FINNEOL national cohort study. Acta Anaesthesiol Scand. 2020;64:1144–53.CrossRef
Metadata
Title
Premorbid functional status as an outcome predictor in intensive care patients aged over 85 years
Authors
Laura Pietiläinen
Minna Bäcklund
Johanna Hästbacka
Matti Reinikainen
Publication date
01-12-2022
Publisher
BioMed Central
Keyword
Care
Published in
BMC Geriatrics / Issue 1/2022
Electronic ISSN: 1471-2318
DOI
https://doi.org/10.1186/s12877-021-02746-1

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