OBJECTIVES: The aim of the study was, by early identification of deleterious prognostic factors that are open to remediation, to be in a position to assign elderly patients to different mortality risk groups to improve management. DESIGN: Prospective multicentre cohort. SETTING: Nine French teaching hospitals. PARTICIPANTS: One thousand three hundred and six (1 306) patients aged 75 and over, hospitalised after having passed through Emergency Department (ED). MEASUREMENTS: Patients were assessed using Comprehensive Geriatric Assessment (CGA) tools. A Cox survival analysis was performed to identify prognostic variables for six-week mortality. Receiver Operating Characteristics analysis was used to study the discriminant power of the model. A mortality risk score is proposed to define three risk groups for six-week mortality. RESULTS: Crude mortality rate after a six week follow-up was 10.6% (n=135). Prognostic factors identified were: malnutrition risk (HR=2.1; 95% CI: 1.1-3.8; p=.02), delirium (HR=1.7; 95% CI: 1.2-2.5; p=.006), and dependency: moderate dependency (HR=4.9; 95% CI: 1.5-16.5; p=.01) or severe dependency (HR=10.3; 95% CI: 3.2-33.1; p < .001). The discriminant power of the model was good: the c-statistic representing the area under the curve was 0.71 (95% IC: 0.67 - 0.75; p < .001). The six-week mortality rate increased significantly (p < .001) across the three risk groups: 1.1% (n=269; 95% CI=0.5-1.7) in the lowest risk group, 11.1% (n=854; 95% CI=9.4-12.9) in the intermediate risk group, and 22.4% (n=125; 95% CI=20.1-24.7) in the highest risk group. CONCLUSIONS: A simple score has been calculated (using only three variables from the CGA) and a practical schedule proposed to characterise patients according to the degree of mortality risk. Each of these three variables (malnutrition risk, delirium, and dependency) identified as independent prognostic factors can lead to a targeted therapeutic option to prevent early mortality.
OBJECTIVES: The aim of the study was, by early identification of deleterious prognostic factors that are open to remediation, to be in a position to assign elderly patients to different mortality risk groups to improve management. DESIGN: Prospective multicentre cohort. SETTING: Nine French teaching hospitals. PARTICIPANTS: One thousand three hundred and six (1 306) patients aged 75 and over, hospitalised after having passed through Emergency Department (ED). MEASUREMENTS: Patients were assessed using Comprehensive Geriatric Assessment (CGA) tools. A Cox survival analysis was performed to identify prognostic variables for six-week mortality. Receiver Operating Characteristics analysis was used to study the discriminant power of the model. A mortality risk score is proposed to define three risk groups for six-week mortality. RESULTS: Crude mortality rate after a six week follow-up was 10.6% (n=135). Prognostic factors identified were: malnutrition risk (HR=2.1; 95% CI: 1.1-3.8; p=.02), delirium (HR=1.7; 95% CI: 1.2-2.5; p=.006), and dependency: moderate dependency (HR=4.9; 95% CI: 1.5-16.5; p=.01) or severe dependency (HR=10.3; 95% CI: 3.2-33.1; p < .001). The discriminant power of the model was good: the c-statistic representing the area under the curve was 0.71 (95% IC: 0.67 - 0.75; p < .001). The six-week mortality rate increased significantly (p < .001) across the three risk groups: 1.1% (n=269; 95% CI=0.5-1.7) in the lowest risk group, 11.1% (n=854; 95% CI=9.4-12.9) in the intermediate risk group, and 22.4% (n=125; 95% CI=20.1-24.7) in the highest risk group. CONCLUSIONS: A simple score has been calculated (using only three variables from the CGA) and a practical schedule proposed to characterise patients according to the degree of mortality risk. Each of these three variables (malnutrition risk, delirium, and dependency) identified as independent prognostic factors can lead to a targeted therapeutic option to prevent early mortality.
Authors: M Dramé; J-L Novella; D Jolly; I Lanièce; D Somme; D Heitz; J-B Gauvain; T Voisin; B De Wazières; R Gonthier; C Jeandel; P Couturier; O Saint-Jean; J Ankri; F Blanchard; P-O Lang Journal: J Nutr Health Aging Date: 2011-08 Impact factor: 4.075
Authors: Bianca M Buurman; Ling Han; Terrence E Murphy; Evelyne A Gahbauer; Linda Leo-Summers; Heather G Allore; Thomas M Gill Journal: J Am Med Dir Assoc Date: 2015-11-24 Impact factor: 4.669
Authors: D Zekry; K H Krause; I Irminger-Finger; C E Graf; C Genet; A-M Vitale; J-P Michel; G Gold; F R Herrmann Journal: J Nutr Health Aging Date: 2012-03 Impact factor: 4.075
Authors: M Dramé; F Fierobe; P-O Lang; D Jolly; F Boyer; R Mahmoudi; D Somme; I Laniece; D Heitz; J-B Gauvain; T Voisin; B De Wazieres; R Gonthier; J Ankri; O Saint-Jean; P Couturier; C Jeandel; F Blanchard; J-L Novella Journal: J Nutr Health Aging Date: 2011-05 Impact factor: 4.075
Authors: S Gentile; O Lacroix; A C Durand; E Cretel; M Alazia; R Sambuc; S Bonin-Guillaume Journal: J Nutr Health Aging Date: 2013-04 Impact factor: 4.075