Plasma and Urinary Biomarkers Improve Prediction of Mortality through 1 Year in Intensive Care Patients: An Analysis from FROG-ICU.
biomarkers
critically ill
intensive care units
mortality
prognosis
severity score
Journal
Journal of clinical medicine
ISSN: 2077-0383
Titre abrégé: J Clin Med
Pays: Switzerland
ID NLM: 101606588
Informations de publication
Date de publication:
06 May 2023
06 May 2023
Historique:
received:
14
04
2023
revised:
01
05
2023
accepted:
03
05
2023
medline:
13
5
2023
pubmed:
13
5
2023
entrez:
13
5
2023
Statut:
epublish
Résumé
This study aimed to assess the value of blood and urine biomarkers in addition to routine clinical variables in risk stratification of patients admitted to ICU. Multivariable prognostic models were developed in this post hoc analysis of the French and EuRopean Outcome ReGistry in Intensive Care Units study, a prospective observational study of patients admitted to ICUs. The study included 2087 patients consecutively admitted to the ICU who required invasive mechanical ventilation or a vasoactive agent for more than 24 h. The main outcome measures were in-ICU, in-hospital, and 1 year mortality. Models including only SAPS II or APACHE II scores had c-indexes for in-hospital and 1 year mortality of 0.64 and 0.65, and 0.63 and 0.61, respectively. The c-indexes for a model including age and estimated glomerular filtration rate were higher at 0.69 and 0.67, respectively. Models utilizing available clinical variables increased the c-index for in-hospital and 1 year mortality to 0.80 and 0.76, respectively. The addition of biomarkers and urine proteomic markers increased c-indexes to 0.83 and 0.78. The commonly used scores for risk stratification in ICU patients did not perform well in this study. Models including clinical variables and biomarkers had significantly higher predictive values.
Sections du résumé
BACKGROUND
BACKGROUND
This study aimed to assess the value of blood and urine biomarkers in addition to routine clinical variables in risk stratification of patients admitted to ICU.
METHODS
METHODS
Multivariable prognostic models were developed in this post hoc analysis of the French and EuRopean Outcome ReGistry in Intensive Care Units study, a prospective observational study of patients admitted to ICUs. The study included 2087 patients consecutively admitted to the ICU who required invasive mechanical ventilation or a vasoactive agent for more than 24 h. The main outcome measures were in-ICU, in-hospital, and 1 year mortality.
RESULTS
RESULTS
Models including only SAPS II or APACHE II scores had c-indexes for in-hospital and 1 year mortality of 0.64 and 0.65, and 0.63 and 0.61, respectively. The c-indexes for a model including age and estimated glomerular filtration rate were higher at 0.69 and 0.67, respectively. Models utilizing available clinical variables increased the c-index for in-hospital and 1 year mortality to 0.80 and 0.76, respectively. The addition of biomarkers and urine proteomic markers increased c-indexes to 0.83 and 0.78.
CONCLUSIONS
CONCLUSIONS
The commonly used scores for risk stratification in ICU patients did not perform well in this study. Models including clinical variables and biomarkers had significantly higher predictive values.
Identifiants
pubmed: 37176751
pii: jcm12093311
doi: 10.3390/jcm12093311
pmc: PMC10179283
pii:
doi:
Types de publication
Journal Article
Langues
eng
Références
J Am Coll Cardiol. 2018 Jul 10;72(2):173-182
pubmed: 29976291
ESC Heart Fail. 2020 Aug;7(4):1595-1604
pubmed: 32383555
Intensive Care Med. 2001 Jun;27(6):1005-11
pubmed: 11497132
Clin Chim Acta. 2015 Mar 30;443:57-70
pubmed: 25269091
Crit Care Med. 2008 May;36(5):1523-30
pubmed: 18434893
Crit Care. 2013 Oct 03;17(5):R219
pubmed: 24090280
Lancet Diabetes Endocrinol. 2020 Apr;8(4):301-312
pubmed: 32135136
Crit Care Med. 1998 Nov;26(11):1793-800
pubmed: 9824069
Eur Heart J. 2012 Sep;33(18):2342-50
pubmed: 22789915
Ann Emerg Med. 2007 Jul;50(1):34-41
pubmed: 17161501
Arterioscler Thromb Vasc Biol. 2008 Mar;28(3):433-40
pubmed: 18096829
Int J Cardiol. 2014 Sep;176(1):158-65
pubmed: 25065337
Am Heart J. 1956 Apr;51(4):533-41
pubmed: 13302128
Crit Care Med. 2016 Jun;44(6):e450
pubmed: 27182877
Crit Care Med. 1996 Dec;24(12):1962-7
pubmed: 8968262
Crit Care. 2020 Jan 9;24(1):10
pubmed: 31918764
Circ Heart Fail. 2018 Dec;11(12):e005582
pubmed: 30562100
Int J Biochem Cell Biol. 2021 Jan;130:105881
pubmed: 33181315
Crit Care. 2019 Nov 27;23(1):374
pubmed: 31775846
Endocr Pathol. 2008 Summer;19(2):92-6
pubmed: 18581271
Intensive Care Med. 2005 Oct;31(10):1306-15
pubmed: 16132895
Anaesthesia. 2003 Jul;58(7):637-42
pubmed: 12790812
Acute Crit Care. 2018 Nov;33(4):216-221
pubmed: 31723888
BMC Anesthesiol. 2015 Oct 12;15:143
pubmed: 26459405
Eur J Heart Fail. 2019 Jun;21(6):732-743
pubmed: 30843353
Circ Heart Fail. 2012 Jan;5(1):72-8
pubmed: 22016505
Intensive Care Med. 2000 Dec;26(12):1779-85
pubmed: 11271085
Crit Care. 2018 Jan 18;22(1):8
pubmed: 29347987
Ann Intern Med. 2006 Aug 15;145(4):247-54
pubmed: 16908915
Hepatology. 1990 Nov;12(5):1179-86
pubmed: 1699862
Crit Care Med. 1985 Oct;13(10):818-29
pubmed: 3928249
Int J Environ Res Public Health. 2023 Jan 31;20(3):
pubmed: 36767947
Crit Care. 2013 Apr 27;17(2):R81
pubmed: 23622086
Curr Cardiol Rep. 2020 May 19;22(6):41
pubmed: 32430626
Front Immunol. 2016 Dec 19;7:604
pubmed: 28066415
Sci Rep. 2017 Nov 28;7(1):16479
pubmed: 29184072
N Engl J Med. 2010 Mar 4;362(9):779-89
pubmed: 20200382
Intensive Care Med. 1996 Jul;22(7):707-10
pubmed: 8844239
Sci Rep. 2017 Dec 5;7(1):16915
pubmed: 29208969
JAMA. 1993 Dec 22-29;270(24):2957-63
pubmed: 8254858
Sci Rep. 2017 Jan 16;7:40524
pubmed: 28091613