Clustering Analysis of Geriatric and Acute Characteristics in a Cohort of Very Old Patients on Admission to ICU

Overview

Journal Intensive Care Med

Specialty Critical Care

Date 2022 Sep 2

PMID 36056194

Authors

Oded Mousai

Lola Tafoureau

Tamar Yovell

Hans Flaatten

Bertrand Guidet

Christian Jung

Dylan de Lange

Susannah Leaver

Wojciech Szczeklik

Jesper Fjolner

Peter Vernon van Heerden

Leo Joskowicz

Michael Beil

Gal Hyams

Sigal Sviri

Affiliations

Soon will be listed here.

Abstract

Purpose: The biological and functional heterogeneity in very old patients constitutes a major challenge to prognostication and patient management in intensive care units (ICUs). In addition to the characteristics of acute diseases, geriatric conditions such as frailty, multimorbidity, cognitive impairment and functional disabilities were shown to influence outcome in that population. The goal of this study was to identify new and robust phenotypes based on the combination of these features to facilitate early outcome prediction.

Methods: Patients aged 80 years old or older with and without limitations of life-sustaining treatment and with complete data were recruited from the VIP2 study for phenotyping and from the COVIP study for external validation. The sequential organ failure assessment (SOFA) score and its sub-scores taken on admission to ICU as well as demographic and geriatric patient characteristics were subjected to clustering analysis. Phenotypes were identified after repeated bootstrapping and clustering runs.

Results: In patients from the VIP2 study without limitations of life-sustaining treatment (n = 1977), ICU mortality was 12% and 30-day mortality 19%. Seven phenotypes with distinct profiles of acute and geriatric characteristics were identified in that cohort. Phenotype-specific mortality within 30 days ranged from 3 to 57%. Among the patients assigned to a phenotype with pronounced geriatric features and high SOFA scores, 50% died in ICU and 57% within 30 days. Mortality differences between phenotypes were confirmed in the COVIP study cohort (n = 280).

Conclusions: Phenotyping of very old patients on admission to ICU revealed new phenotypes with different mortality and potential need for anticipatory intervention.

Citing Articles

The (un)surprising resilience of octogenarians in intensive care.

Beil M, Jacobs J, Guidet B Intensive Care Med. 2025; 51(1):140-142.

PMID: 39774860 DOI: 10.1007/s00134-024-07766-0.

Role of age as eligibility criterion for ECMO in patients with ARDS: meta-regression analysis.

Tonetti T, Di Staso R, Bambini L, Bordini M, DAlbo R, Nocera D Crit Care. 2024; 28(1):278.

PMID: 39192302 PMC: 11348734. DOI: 10.1186/s13054-024-05074-z.

Prognosticating the outcome of intensive care in older patients-a narrative review.

Beil M, Moreno R, Fronczek J, Kogan Y, Moreno R, Flaatten H Ann Intensive Care. 2024; 14(1):97.

PMID: 38907141 PMC: 11192712. DOI: 10.1186/s13613-024-01330-1.

Critical care beyond organ support: the importance of geriatric rehabilitation.

Jacobs J, Rahamim A, Beil M, Guidet B, Vallet H, Flaatten H Ann Intensive Care. 2024; 14(1):71.

PMID: 38727919 PMC: 11087448. DOI: 10.1186/s13613-024-01306-1.

Development and Validation of Multimodal Models to Predict the 30-Day Mortality of ICU Patients Based on Clinical Parameters and Chest X-Rays.

Lin J, Yang J, Yin M, Tang Y, Chen L, Xu C J Imaging Inform Med. 2024; 37(4):1312-1322.

PMID: 38448758 PMC: 11300735. DOI: 10.1007/s10278-024-01066-1.

References

Beard J, Jotheeswaran A, Cesari M, Araujo de Carvalho I . The structure and predictive value of intrinsic capacity in a longitudinal study of ageing. BMJ Open. 2019; 9(11):e026119. PMC: 6830681. DOI: 10.1136/bmjopen-2018-026119. View

Flaatten H, de Lange D, Artigas A, Bin D, Moreno R, Christensen S . The status of intensive care medicine research and a future agenda for very old patients in the ICU. Intensive Care Med. 2017; 43(9):1319-1328. DOI: 10.1007/s00134-017-4718-z. View

Theou O, Brothers T, Mitnitski A, Rockwood K . Operationalization of frailty using eight commonly used scales and comparison of their ability to predict all-cause mortality. J Am Geriatr Soc. 2013; 61(9):1537-51. DOI: 10.1111/jgs.12420. View

Flaatten H, de Lange D, Morandi A, Andersen F, Artigas A, Bertolini G . 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(12):1820-1828. DOI: 10.1007/s00134-017-4940-8. View

Chong E, Chan M, Tan H, Lim W . COVID-19: Use of the Clinical Frailty Scale for Critical Care Decisions. J Am Geriatr Soc. 2020; 68(6):E30-E32. PMC: 7267651. DOI: 10.1111/jgs.16528. View

Fronczek J, Polok K, de Lange D, Jung C, Beil M, Rhodes A . Relationship between the Clinical Frailty Scale and short-term mortality in patients ≥ 80 years old acutely admitted to the ICU: a prospective cohort study. Crit Care. 2021; 25(1):231. PMC: 8247215. DOI: 10.1186/s13054-021-03632-3. View

Castela Forte J, Perner A, van der Horst I . The use of clustering algorithms in critical care research to unravel patient heterogeneity. Intensive Care Med. 2019; 45(7):1025-1028. DOI: 10.1007/s00134-019-05631-z. View

Whitty C, MacEwen C, Goddard A, Alderson D, Marshall M, Calderwood C . Rising to the challenge of multimorbidity. BMJ. 2020; 368:l6964. PMC: 7190283. DOI: 10.1136/bmj.l6964. View

Marcucci M, Franchi C, Nobili A, Mannucci P, Ardoino I . Defining Aging Phenotypes and Related Outcomes: Clues to Recognize Frailty in Hospitalized Older Patients. J Gerontol A Biol Sci Med Sci. 2017; 72(3):395-402. DOI: 10.1093/gerona/glw188. View

10.

Castela Forte J, Yeshmagambetova G, van der Grinten M, Hiemstra B, Kaufmann T, Eck R . Identifying and characterizing high-risk clusters in a heterogeneous ICU population with deep embedded clustering. Sci Rep. 2021; 11(1):12109. PMC: 8187398. DOI: 10.1038/s41598-021-91297-x. View

11.

Knaus W, Marks R . New Phenotypes for Sepsis: The Promise and Problem of Applying Machine Learning and Artificial Intelligence in Clinical Research. JAMA. 2019; 321(20):1981-1982. DOI: 10.1001/jama.2019.5794. View

12.

Bian J, Lyu T, Loiacono A, Viramontes T, Lipori G, Guo Y . Assessing the practice of data quality evaluation in a national clinical data research network through a systematic scoping review in the era of real-world data. J Am Med Inform Assoc. 2020; 27(12):1999-2010. PMC: 7727392. DOI: 10.1093/jamia/ocaa245. View

13.

Reddy K, Sinha P, OKane C, Gordon A, Calfee C, McAuley D . Subphenotypes in critical care: translation into clinical practice. Lancet Respir Med. 2020; 8(6):631-643. DOI: 10.1016/S2213-2600(20)30124-7. View

14.

Geri G, Vignon P, Aubry A, Fedou A, Charron C, Silva S . Cardiovascular clusters in septic shock combining clinical and echocardiographic parameters: a post hoc analysis. Intensive Care Med. 2019; 45(5):657-667. DOI: 10.1007/s00134-019-05596-z. View

15.

Azoulay E, Zafrani L, Mirouse A, Lengline E, Darmon M, Chevret S . Clinical phenotypes of critically ill COVID-19 patients. Intensive Care Med. 2020; 46(8):1651-1652. PMC: 8830032. DOI: 10.1007/s00134-020-06120-4. View

16.

Seymour C, Kennedy J, Wang S, Chang C, Elliott C, Xu Z . Derivation, Validation, and Potential Treatment Implications of Novel Clinical Phenotypes for Sepsis. JAMA. 2019; 321(20):2003-2017. PMC: 6537818. DOI: 10.1001/jama.2019.5791. View

17.

Rodriguez A, Ruiz-Botella M, Martin-Loeches I, Jimenez Herrera M, Sole-Violan J, Gomez J . Deploying unsupervised clustering analysis to derive clinical phenotypes and risk factors associated with mortality risk in 2022 critically ill patients with COVID-19 in Spain. Crit Care. 2021; 25(1):63. PMC: 7883885. DOI: 10.1186/s13054-021-03487-8. View

18.

Guidet B, de Lange D, Boumendil A, Leaver S, Watson X, Boulanger C . 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. 2019; 46(1):57-69. PMC: 7223711. DOI: 10.1007/s00134-019-05853-1. View

19.

Guidet B, Flaatten H, Boumendil A, Morandi A, Andersen F, Artigas A . Withholding or withdrawing of life-sustaining therapy in older adults (≥ 80 years) admitted to the intensive care unit. Intensive Care Med. 2018; 44(7):1027-1038. DOI: 10.1007/s00134-018-5196-7. View

20.

Jung C, Flaatten H, Fjolner J, Bruno R, Wernly B, Artigas A . The impact of frailty on survival in elderly intensive care patients with COVID-19: the COVIP study. Crit Care. 2021; 25(1):149. PMC: 8054503. DOI: 10.1186/s13054-021-03551-3. View