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Figure 1.

Flow chart showing the selection of participants included in the analysis.

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Table 1.

Baseline characteristics of participants (n = 1254).

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Table 2.

Area under Receiver operating characteristic curve and prognostic values of brief geriatric assessment items and their combinations* for prolonged length of hospital stay (n = 1254).

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Table 3.

Cox regression models showing the association between the length of hospital stay (dependent variable) and combinations of brief geriatric assessment items (independent variables) separated into three risk-levels (i.e., low risk, intermediate risk, and high risk of prolonged length of hospital stay) (n = 1254).

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Table 4.

Cox regression models showing the association between the length of hospital stay (dependent variable) and combinations of brief geriatric assessment items (independent variables) separated into three risk-levels (i.e., low risk, intermediate risk, and high risk of prolonged length of hospital stay) with separated models for reasons for admission to emergency department (n = 1254).

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Figure 2.

Kaplan-Meier estimates of the probability of discharge from acute care medical units among older inpatients (n = 12,054) using a priori* combinations of the 6 items of the brief geriatric assessment.

*: Combinations described previously (Beauchet et al. J Emerg Med. 2013; 45: 739–45). †: Defined by a number of drugs taken per day above 4. ‡: Living alone without using any formal or informal home services and social help. §: In past 6 months. ¶: Inability to give the month and/or year.

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Figure 3.

Kaplan-Meier estimates of the probability of discharge from acute care medical units among older inpatients (n = 12,054) using newly identified combinations of the 6 items of the brief geriatric assessment.

*: Defined by a number of drugs taken per day above 4. †: Living alone without using any formal or informal home services and social help. ‡: In past 6 months. §: Inability to give the month and/or year.

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