Baseline characteristics of participants (n = 1254).

<p>SD: standard deviation.</p><p>*: Use of benzodiazepines or antidepressants or neuroleptics.</p>†<p>: Inability to give the month and/or year.</p>‡<p>: Formal (i.e., health and/or social professional) or informal (i.e., family and/or friends).</p><p>Baseline characteristics of participants (n = 1254).</p

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).

<p>All models used low-risk level as reference value.</p><p>*: adjustment on place of life.</p>†<p>: Combinations described previously (Beauchet et al. J Emerg Med. 2013; 45: 739–45).</p>‡<p>: Defined by a number of drugs taken per day above 4.</p>§<p>: Living alone without using any formal or informal home services and social help.</p>¶<p>: In past 6 months.</p>#<p>: Inability to give the month and/or year.</p><p>Hazard ratio and p-value significant (i.e., <0.05) indicated in bold.</p><p>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).</p

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

<p>*: 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.</p

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).

<p>ROC: Receiver operating characteristic curve; PPV: Positive predictive value; NPV: Negative predictive value; LR+: Likelihood ration of positive test; LR-: Likelihood ration of negative test; TP: True positive; FP: False positive; TN: True negative; FN: False negative;</p><p>*: Only three best models (i.e., highest value of ROC) by level (i.e., Low, intermediate and high risk) are shown;</p>†<p>: Defined being in the highest tertile of length of hospital saty (i.e.,>13 days);</p>‡<p>: Defined by a number of drugs taken per day above 4;</p>§<p>: Living alone without using any formal or informal home services and social help;</p>¶<p>: during the past 6 months;</p>#<p>: Inability to give the month and/or year;</p><p>**: Only combination involving at least 10 participants were considered;</p>††<p>: Combinations described in previous published study (Beauchet et al. J Emerg Med. 2013; 45: 739–45).</p><p>Area under Receiver operating characteristic curve and prognostic values of brief geriatric assessment items and their combinations^{<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0110135#nt106" target="_blank">*</a>} for prolonged length of hospital stay^{<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0110135#nt107" target="_blank">†</a>} (n = 1254).</p

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).

<p>Model 1: Unadjusted model.</p><p>Model 2: Model adjusted on organ failure and place of life.</p><p>Model 3: Low risk of prolonged length of hospital stay used as reference, with adjustment on organ failure and place of life.</p><p>*: Combinations described previously (Beauchet et al. J Emerg Med. 2013; 45: 739–45).</p>†<p>: Defined by a number of drugs taken per day above 4.</p>‡<p>: Living alone without using any formal or informal home services and social help.</p>§<p>: In past 6 months.</p>¶<p>: Inability to give the month and/or year.</p><p>Hazard ratio and p-value significant (i.e., <0.05) indicated in bold.</p><p>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).</p

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

<p>Flow chart showing the selection of participants included in the analysis.</p

Uni- and multivariate logistic regression models showing the association between low-quality control of INR and Charlson Comorbidity Index ≥ 3 adjusted for clinical characteristics (n = 2164).

<p>Uni- and multivariate logistic regression models showing the association between low-quality control of INR and Charlson Comorbidity Index ≥ 3 adjusted for clinical characteristics (n = 2164).</p

Characteristics of patients according to low-quality control of INR (n = 2164).

<p>Characteristics of patients according to low-quality control of INR (n = 2164).</p

Comparison of baseline characteristics among breast cancer cases and oestrogen receptor status (n = 1,707).

<p>* Based on independent samples <i>t</i>-test or chi-square test with <i>P</i> significant <0·05.</p><p>Significant P-values (P<0·05) are indicated in bold.</p

Characteristics of patients (N = 217).

<p>Characteristics of patients (N = 217).</p