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M Dramé,
P O Lang,
J-L Novella,
D Narbey,
R Mahmoudi,
I Lanièce,
D Somme,
J-B Gauvain,
D Heitz,
T Voisin, B de Wazières,
R Gonthier,
J Ankri,
O Saint-Jean,
C Jeandel,
P Couturier,
F Blanchard,
D Jolly
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ABSTRACT: The objective of the study was to identify factors predictive of 6-month institutionalization or mortality in frail elderly patients after acute hospitalization.
A prospective cohort of elderly subjects 75 years and older was set up in nine French teaching hospitals. Data obtained from a comprehensive geriatric assessment were used in a Cox model to predict 6-month institutionalization or mortality. Institutionalization was defined as incident admission either to a nursing home or other long-term care facility during the follow-up period.
Crude institutionalization and death rates after 6 months of follow-up were 18% and 24%, respectively. Independent predictors of institutionalization were: living alone (HR=1.83; 95% CI=1.27-2.62) or a higher number of children (HR=0.86; 95% CI=0.78-0.96), balance problems (HR=1.72; 95% CI=1.19-2.47), malnutrition or risk thereof (HR=1.93; 95% CI=1.24-3.01), and dementia syndrome (HR=1.88; 95% CI=1.32-2.67). Factors found to be independently related to 6-month mortality were exclusively medical factors: malnutrition or risk thereof (HR=1.92; 95% CI=1.17-3.16), delirium (HR=1.80; 95% CI=1.24-2.62), and a high level of comorbidity (HR=1.62; 95% CI=1.09-2.40). Institutionalization (HR=1.92; 95% CI=1.37-2.71) and unplanned readmission (HR=4.47; 95% CI=3.16-2.71) within the follow-up period were also found as independent predictors.
The main factors predictive of 6-month outcome identified in this study are modifiable by global and multidisciplinary interventions. Their early identification and management would make it possible to modify frail elderly subjects' prognosis favorably.
Revue d Épidémiologie et de Santé Publique 05/2012; 60(3):189-96. · 0.78 Impact Factor
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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
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ABSTRACT: To evaluate the predictive ability of four clinical frailty indexes as regards one-year rapid cognitive decline (RCD - defined as the loss of at least 3 points on the MMSE score), and one-year institutional admission (IA) and mortality respectively; and to measure their agreement for identifying groups at risk of these severe outcomes.
One-year follow-up and multicentre study of old patients participating in the SAFEs cohort study. Setting: Nine university hospitals in France.
1,306 patients aged 75 or older (mean age 85±6 years; 65% female) hospitalized in medical divisions through an Emergency department.
Four frailty indexes (Winograd; Rockwood; Donini; and Schoevaerdts) reflecting the multidimensionality of the frailty concept, using an ordinal scoring system able to discriminate different grades of frailty, and constructed based on the accumulation of identified deficits after comprehensive geriatric assessment conducted during the first week of hospital stay, were used to categorize participants into three different grades of frailty: G1 - not frail; G2 - moderately frail; and G3 - severely frail. Comparisons between groups were performed using Fisher's exact test. Agreement between indexes was evaluated using Cohen's Kappa coefficient.
All patients were classified as frail by at least one of the four indexes. The Winograd and Rockwood indexes mainly classified subjects as G2 (85% and 96%), and the Donini and Schoevaerdts indexes mainly as G3 (71% and 67%). Among the SAFEs cohort population, 250, 1047 and 1,306 subjects were eligible for analyses of predictability for RCD, 1-year IA and 1-year mortality respectively. At 1 year, 84 subjects (34%) experienced RCD, 377 (36%) were admitted into an institutional setting, and 445 (34%) had died. With the Rockwood index, all subjects who experienced RCD were classified in G2; and in G2 and G3 when the Donini and Schoevaerdts indexes were used. No significant difference was found between frailty grade and RCD, whereas frailty grade was significantly associated with an increased risk of IA and death, whatever the frailty index considered. Agreement between the different indexes of frailty was poor with Kappa coefficients ranging from -0.02 to 0.15.
These findings confirm the poor clinimetric properties of these current indexes to measure frailty, underlining the fact that further work is needed to develop a better and more widely-accepted definition of frailty and therefore a better understanding of its pathophysiology.
The Journal of Nutrition Health and Aging 08/2011; 15(8):699-705. · 2.69 Impact Factor
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D Somme,
C Lazarovici,
M Dramé,
P Blanc,
P O Lang,
J B Gauvain,
T Voisin,
R Gonthier, B De Wazières,
C Jeandel,
P Couturier,
F Blanchard,
O Saint-Jean
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ABSTRACT: We studied the factors influencing the choice of admission to Geriatrics units, instead of other acute hospital units after an emergency visit. We report the results from a cohort of 1283 randomly selected patients aged >75 years hospitalized in emergency and representative of the French University hospital system. All patients underwent geriatric assessment. Baseline characteristics of patients admitted to Geriatrics and other units were compared. A center effect influencing the use of Geriatrics units during emergencies was also investigated. Admission to a Geriatrics unit during the acute care episode occurred in 499 cases (40.3%). By multivariate analysis, 4 factors were related to admission to a Geriatrics unit: cognitive disorder: odds ratio (OR)=1.79 (1.38-2.32) (95% confidence interval=95% CI); "failure to thrive" syndrome OR=1.54 (1.01-2.35), depression: OR=1.42 (1.12-1.83) or loss of Activities of Daily Living (ADL): OR=1.35 (1.04-1.75). The emergency volume of the hospital was inversely related to the use of Geriatrics units, with high variation that could be explained by other unstudied factors. In the French University Emergency Healthcare system, the "geriatrics patient" is defined by the existence of cognitive disorder, psychological symptoms or installed loss of autonomy. Nevertheless, considerable nation-wide variation was observed underlining the need to clarify and reinforce this discipline in the emergency healthcare system.
Archives of gerontology and geriatrics 03/2010; 52(1):40-5. · 1.36 Impact Factor
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M Dramé,
J L Novella,
P O Lang,
D Somme,
N Jovenin,
I Lanièce,
P Couturier,
D Heitz,
J B Gauvain,
T Voisin, B De Wazières,
R Gonthier,
J Ankri,
C Jeandel,
O Saint-Jean,
F Blanchard,
D Jolly
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ABSTRACT: To identify predictive factors for 2-year mortality in frail elderly patients after acute hospitalisation, and from these to derive and validate a Mortality Risk Index (MRI). A prospective cohort of elderly patients was set up in nine teaching hospitals. This cohort was randomly split up into a derivation cohort (DC) of 870 subjects and a validation cohort (VC) of 436 subjects. Data obtained from a Comprehensive Geriatric Assessment were used in a Cox model to predict 2-year mortality and to identify risk groups for mortality. A ROC analysis was performed to explore the validity of the MRI. Five factors were identified and weighted using hazard ratios to construct the MRI: age 85 or over (1 point), dependence for the ADL (1 point), delirium (2 points), malnutrition risk (2 points), and co-morbidity level (2 points for medium level, 3 points for high level). Three risk groups were identified according to the MRI. Mortality rates increased significantly across risk groups in both cohorts. In the DC, mortality rates were: 20.8% in the low-risk group, 49.6% in the medium-risk group, and 62.1% in the high-risk group. In the VC, mortality rates were respectively 21.7, 48.5, and 65.4%. The area under the ROC curve for overall score was statistically the same in the DC (0.72) as in the VC (0.71). The proposed MRI appears as a simple and easy-to-use tool developed from relevant geriatric variables. Its accuracy is good and the validation procedure gives a good stability of results.
European Journal of Epidemiology 11/2008; 23(12):783-91. · 4.71 Impact Factor
