TY - JOUR
T1 - Cumulative Prognostic Score Predicting Mortality in Patients Older Than 80 Years Admitted to the ICU
AU - the VIP1 study group
AU - de Lange, Dylan W.
AU - Brinkman, Sylvia
AU - Flaatten, Hans
AU - Boumendil, Ariane
AU - Morandi, Alessandro
AU - Andersen, Finn H.
AU - Artigas, Antonio
AU - Bertolini, Guido
AU - Cecconi, Maurizio
AU - Christensen, Steffen
AU - Faraldi, Loredana
AU - Fjølner, Jesper
AU - Jung, Christian
AU - Marsh, Brian
AU - Moreno, Rui
AU - Oeyen, Sandra
AU - Öhman, Christina Agvald
AU - Bollen Pinto, Bernardo
AU - de Smet, Anne Marie G.A.
AU - Soliman, Ivo W.
AU - Szczeklik, Wojciech
AU - Valentin, Andreas
AU - Watson, Ximena
AU - Zafeiridis, Tilemachos
AU - Guidet, Bertrand
AU - Schmutz, René
AU - Wimmer, Franz
AU - Eller, Philipp
AU - Joannidis, Michael
AU - De Buysscher, Pieter
AU - De Neve, Nikolaas
AU - Swinnen, Walter
AU - Abraham, Paul
AU - Hergafi, Leila
AU - Schefold, Joerg C.
AU - Biskup, Ewelina
AU - Piza, Petr
AU - Taliadoros, Ioannis
AU - Dey, Nilanjan
AU - Sølling, Christoffer
AU - Rasmussen, Bodil Steen
AU - Forceville, Xavier
AU - Besch, Guillaume
AU - Mentec, Herve
AU - Michel, Philippe
AU - Mateu, Philippe
AU - Michel, Philippe
AU - Vettoretti, Lucie
AU - Bourenne, Jeremy
AU - Faulkner, Maria
N1 - Publisher Copyright:
© 2019 The Authors. Journal of the American Geriatrics Society published by Wiley Periodicals, Inc. on behalf of The American Geriatrics Society.
PY - 2019/6/1
Y1 - 2019/6/1
N2 - OBJECTIVES: To develop a scoring system model that predicts mortality within 30 days of admission of patients older than 80 years admitted to intensive care units (ICUs). DESIGN: Prospective cohort study. SETTING: A total of 306 ICUs from 24 European countries. PARTICIPANTS: Older adults admitted to European ICUs (N = 3730; median age = 84 years [interquartile range = 81-87 y]; 51.8% male). MEASUREMENTS: Overall, 24 variables available during ICU admission were included as potential predictive variables. Multivariable logistic regression was used to identify independent predictors of 30-day mortality. Model sensitivity, specificity, and accuracy were evaluated with receiver operating characteristic curves. RESULTS: The 30-day-mortality was 1562 (41.9%). In multivariable analysis, these variables were selected as independent predictors of mortality: age, sex, ICU admission diagnosis, Clinical Frailty Scale, Sequential Organ Failure Score, invasive mechanical ventilation, and renal replacement therapy. The discrimination, accuracy, and calibration of the model were good: the area under the curve for a score of 10 or higher was.80, and the Brier score was.18. At a cut point of 10 or higher (75% of all patients), the model predicts 30-day mortality in 91.1% of all patients who die. CONCLUSION: A predictive model of cumulative events predicts 30-day mortality in patients older than 80 years admitted to ICUs. Future studies should include other potential predictor variables including functional status, presence of advance care plans, and assessment of each patient's decision-making capacity.
AB - OBJECTIVES: To develop a scoring system model that predicts mortality within 30 days of admission of patients older than 80 years admitted to intensive care units (ICUs). DESIGN: Prospective cohort study. SETTING: A total of 306 ICUs from 24 European countries. PARTICIPANTS: Older adults admitted to European ICUs (N = 3730; median age = 84 years [interquartile range = 81-87 y]; 51.8% male). MEASUREMENTS: Overall, 24 variables available during ICU admission were included as potential predictive variables. Multivariable logistic regression was used to identify independent predictors of 30-day mortality. Model sensitivity, specificity, and accuracy were evaluated with receiver operating characteristic curves. RESULTS: The 30-day-mortality was 1562 (41.9%). In multivariable analysis, these variables were selected as independent predictors of mortality: age, sex, ICU admission diagnosis, Clinical Frailty Scale, Sequential Organ Failure Score, invasive mechanical ventilation, and renal replacement therapy. The discrimination, accuracy, and calibration of the model were good: the area under the curve for a score of 10 or higher was.80, and the Brier score was.18. At a cut point of 10 or higher (75% of all patients), the model predicts 30-day mortality in 91.1% of all patients who die. CONCLUSION: A predictive model of cumulative events predicts 30-day mortality in patients older than 80 years admitted to ICUs. Future studies should include other potential predictor variables including functional status, presence of advance care plans, and assessment of each patient's decision-making capacity.
KW - critical care
KW - model
KW - older adults
KW - predict
KW - prognosis
UR - http://www.scopus.com/inward/record.url?scp=85064492544&partnerID=8YFLogxK
U2 - 10.1111/jgs.15888
DO - 10.1111/jgs.15888
M3 - Article
C2 - 30977911
AN - SCOPUS:85064492544
SN - 0002-8614
VL - 67
SP - 1263
EP - 1267
JO - Journal of the American Geriatrics Society
JF - Journal of the American Geriatrics Society
IS - 6
ER -