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Depressive Symptoms as a Predictor of 6-Month Outcomes and Services Utilization in Elderly Medical Inpatients
Christophe J. Büla, MD;
Vincent Wietlisbach, BA;
Bernard Burnand, MD;
Bertrand Yersin, MD
Arch Intern Med. 2001;161:2609-2615.
ABSTRACT
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Background Depressive symptoms have been associated with higher mortality in hospitalized
elderly persons, but few data are available associating depressive symptoms
with other outcomes.
Objective To determine the association between depressive symptoms and the risk
of hospital readmission, nursing home admission, and death as well as inpatient
services utilization during a 6-month follow-up period in a cohort of elderly
medical inpatients.
Methods We enrolled 401 patients, 75 years and older, admitted to the internal
medicine service of an academic hospital in Lausanne, Switzerland. Data on
demographic, medical, physical, social, and mental status were collected on
admission. Depressive symptoms were defined as a score of 6 or higher on the
Geriatric Depression Scale short form. Follow-up data were gathered from the
centralized billing system (hospital and nursing home admissions) and from
proxies (in cases of death).
Results In bivariate analysis, depressive symptoms were associated with an increased
risk of hospital readmission, nursing home placement, and death. After adjustment
for demographic, socioeconomic, and functional status and comorbidity, depressive
symptoms remained associated with an increased risk of hospital readmission
(adjusted hazard ratio, 1.50; 95% confidence interval, 1.03-2.17; P = .03). In addition, depressive symptoms were associated with increased
average costs of both acute and rehabilitation services, resulting in higher
overall costs of inpatient services. ($175.70 vs $126.00; P<.001). This association remained after adjusting for differences
in functional status, comorbidity, and living situation, although it was just
short of statistical significance (P = .07).
Conclusions Elderly medical inpatients with depressive symptoms were more likely
than those without to be readmitted and had higher inpatient services utilization
during the follow-up period, independent of functional and health status.
These results emphasize the need for interventions directed at improving management
of depressive symptoms, given the low recognition and treatment rates of this
problem in elderly populations.
INTRODUCTION
DEPRESSION is frequently encountered in hospitalized elderly persons.1-6
In these persons, several studies have found an independent association between
depressive symptoms and mortality,7-11
as well as functional decline.12 For example,
in a study of elderly medical inpatients, subjects who scored 6 or higher
on the Geriatric Depression Scale (GDS) had a 34% higher mortality (95% confidence
interval [CI], 3%-73%) during a 3-year follow-up.8
While the association between depressive symptoms at hospital admission and
mortality has been well studied in this setting, few studies looked specifically
at other potential effects of depressive symptoms, such as subsequent hospital
readmission or nursing home admission.13-16
Similarly, whereas the association between depressive symptoms and increased
health services utilization is well described for community-dwelling elderly,17 similar data are sparse for inpatients.14-15
In a study of inappropriate hospital utilization among elderly medical inpatients,
depressive symptoms were associated with an increased likelihood of spending
inappropriate days in the hospital.18
The objective of the present study was to investigate the relationship
between depressive symptoms and 6-month outcomes as well as services utilization
in a cohort of elderly medical inpatients. Specifically, we wanted to test
the hypothesis that depressive symptoms are associated with an increased risk
of hospital readmission, permanent nursing home admission, and death within
6 months of an index hospitalization in an acute care setting. In addition,
we hypothesized that depressive symptoms would be associated with an increased
overall utilization of inpatient services (hospital, rehabilitation, short-
and long-term nursing home) during the follow-up period.
PATIENTS AND METHODS
STUDY POPULATION AND SETTING
Participants were patients enrolled in a larger study on functional
assessment in the acute care setting. The sample selection process has been
described previously.3 Briefly, eligible participants
were alternate patients 75 years or older admitted to the internal medicine
service of an academic medical center in French-speaking Switzerland over
a 6-month period. From the original 649 patients, 135 (20.8%) were not included
because they (1) stayed less than 24 hours in the hospital (n = 10), (2) were
transferred from a regional or out-of-state hospital for an elective procedure
(n = 32), (3) were already living in a nursing home (n = 43), or (4) had private
insurance (n = 50). These latter patients were not included because of the
inability to access administrative and follow-up data needed for the larger
study.
In addition, 106 patients (16.3 %) were excluded because of inability
to answer questions because of severe cognitive impairment (defined as the
inability to provide their name and date of birth, n = 29), aphasia or stroke
(n = 9), unstable medical condition (n = 20), terminal illness or coma (n
= 23), or other reasons (eg, language barrier) (n = 25). In addition, 7 patients
(1.1%) refused to participate in the study. Thus, a total of 401 patients
were eventually recruited. Excluded patients had a similar age and sex distribution,
but, as expected, were more likely to die during their hospital stay (25.0%
vs 5.0%; P<.005). The study was approved by the
institutional review board of the Faculty of Medicine, University of Lausanne,
Lausanne, Switzerland. Written informed consent for participation was obtained
from each patient.
BASELINE DATA COLLECTION
Patient interviews were conducted at the bedside by a trained research
nurse within 48 hours of admission. Demographic, socioeconomic, and health
data were collected. In addition, functional status was assessed using the
Katz basic activities of daily living (ADL) scale19
and the Lawton instrumental ADL scale20; cognitive
status was assessed using the Folstein Mini-Mental State Examination scale.21 Home care services were systematically contacted
to collect data on formal help received at home prior to hospitalization.
In addition, in-hospital basic ADL performance information was obtained from
the ward nurse in charge of the patient. The main admission diagnosis, Charlson
Comorbidity Index,22 and data on medication
prescribed at home were collected from the medical chart. Information on destination
after discharge was collected from the administrative files.
DEPRESSIVE SYMPTOMS ASSESSMENT
To assess the presence of depressive symptoms, we administered the GDS
short form (15 items).23-24 The
widely used cutoff number of 6 or more depressive symptoms was chosen to define
the presence of depressive symptoms. In previous studies, this cutoff has
been shown to have 85% to 88% sensitivity and 62% to 87% specificity.23, 25-26 Although a score
of 6 or higher is not equivalent to depression, it suggests mood problems
severe enough to warrant further evaluation and management. In addition, the
same cutoff has been used in other studies that showed an association between
depressive symptoms and an increased risk of mortality or significant functional
decline.7-8,27-28
FOLLOW-UP DATA COLLECTION
Data on utilization during the 6-month follow-up period were collected
from several sources. Subjects were systematically contacted. For those who
died during the study, the exact date of death was ascertained through contact
with a proxy whose name was registered at the baseline interview. If a proxy
was not available, the primary care physician was contacted, and, if necessary
and applicable, representatives of the in-home services or nursing home were
questioned. We were able to determine the place of living and vital status
(ie, alive vs dead) in all subjects. Data on hospital and nursing home date
of admission and discharge were gathered through the centralized, statewide,
billing office. This office bills for all hospital, rehabilitation, and nursing
home stays throughout the Canton of Vaud (Switzerland) for patients with basic
insurance coverage (72.4% of women and 51.2% of men 65 years or older in the
canton in 1993). To assess the validity of this database, we used data collected
on discharge destination immediately following the index hospitalization and
compared them with the data extracted from this database. There was a 96.9%
agreement ( = 0.94; P = .02). Data on nursing
home admission during the 6-month follow-up period were systematically correlated
with proxy information. No unexpected nursing admission was found. We excluded
29 patients (7.2%) from the analysis of hospital readmission because data
on their index hospitalization were missing in the billing database; however,
none had a nursing home admission.
Total costs related to inpatient services utilization were calculated
for each patient. The number of days spent at each level of care was multiplied
by the average daily cost billed to the insurance system ($630 for acute care,
$261 for rehabilitation care, $124 for nursing home care). All inpatient costs
were totaled and divided by the number of days the patient remained in the
study.
STATISTICAL ANALYSIS
Subjects were placed into 2 categories according to their GDS result:
with or without depressive symptoms. Kaplan-Meier survival curves were plotted
and tested for differences using the log-rank test. Risks of hospital readmission,
nursing home admission, and death were estimated from bivariate and multivariate
Cox proportional hazards regression using a stepwise procedure. In the analysis
of hospital readmission, 2 variables were added to demographic and socioeconomic
status and functional covariates: the length of the index hospitalization
and a dummy variable indicating whether the subject had been admitted in the
previous year. Statistical significance level for variables to enter and remain
in the model were set at P<.10 and P<.20, respectively. Multivariate analyses were performed with and
without the depressive symptoms variable forced into the model (no differences).
Death was a censoring event in all these analyses. For all models developed
in the study, no statistically significant departure from the proportional
hazard assumption occurred, based on the tests of Grambsch and Therneau.29
To eliminate the possible confounding effect on GDS results of an undetected
terminal disease at the time of the index hospitalization, we repeated the
analysis of permanent nursing home admission after exclusion of subjects who
died within the 6-month follow-up period. As a sensitivity analysis, we repeated
all the analyses using higher GDS scores (one at  8 and one at 10)
to define the presence of depressive symptoms.
Cost data were analyzed in bivariate and multivariate linear regression
analyses after logarithmic transformation to normalize data distribution.
We used a stepwise procedure with demographic, socioeconomic, and functional
status and medical data (admitting diagnosis and comorbidity) included in
the model. The final multivariate model was tested for the potential disproportionate
influence of outliers, (ie, patients with an extremely low or high daily cost).
We studied the residuals and used robust regression techniques to detect any
departure from linearity assumptions. None was found. Statistical analyses
were performed using Stata 6.0 (Stata Corp, College Station, Tex).
RESULTS
At baseline, participants ranged in age from 75 to 99 years (mean age,
82.4 years); 60.9% were women; 57.6% lived alone; and 54.1% had at least a
high school education. The most frequent admitting diagnoses were cardiovascular
disorders (39.4%), pulmonary disease (13.0%), and falls (11.0%). At the time
of admission, 64.6% had at least one comorbidity as measured by the Charlson
Comorbidity Index, and 13.2% had 3 or more. Dependency in one or more basic
and/or instrumental ADLs was reported by 38.9% and 86.3% of patients, respectively.
Abnormal MMSE scores (<24) were present in 32.2% of the patients. Overall,
90 (22.4%) of the 401 patients of the sample met or exceeded the GDS cutoff
score (6) for depressive symptoms.
Median length of stay was 8.0 days (mean, 10.3; range, 1-100). Overall,
20 patients (5.0%) died during the index stay. During the 6-month follow-up,
82 patients (21.5%) died, 137 (36.0%) were readmitted at least once to an
acute care hospital, and 36 (9.4%) were permanently admitted to a nursing
home. At 6-month follow-up, cross-sectional analysis showed that, compared
with subjects without depressive symptoms, those with depressive symptoms
were more frequently readmitted at least once (45.5% vs 34.2%; P = .02), were more frequently living in a nursing home (18.5% vs 6.3%; P = .002), and died more frequently (27.8% vs 18.3%; P = .05).
Kaplan-Meier estimations of survival without hospital readmission, survival
without permanent nursing home admission, and survival among patients with
and without depressive symptoms are given in Figure 1. In bivariate analysis using Cox proportional hazard analysis
(Table 1, Table 2, and Table 3),
patients with depressive symptoms were about 1.6 times more likely to be readmitted,
more than twice as likely to be permanently admitted to a nursing home, and
1.6 times more likely to die. Using multivariate stepwise analysis to adjust
for demographic, socioeconomic, and functional status and comorbidity (third
and fourth columns of Table 1, Table 2, and Table 3), we found that depressive symptoms remained independently
associated with an increased risk of hospital readmission (adjusted hazard
ratio [adj HR], 1.50; 95% CI, 1.03-2.17; P = .03).
Sensitivity analyses using higher GDS cutoff scores gave a similar result
for a cutoff of 8 or higher (adj HR, 1.60; 95% CI, 1.03-2.47; P = .04), but not for a cutoff of 10 or higher (adj HR, 1.31; 95% CI,
0.68-2.50; P = .42). This latter result is likely
explained by the very small proportion of patients (5.5%) with depressive
symptoms in the sample when using this higher cutoff.
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Figure 1. Kaplan-Meier curves are shown
for patients with depressive symptoms (defined as a Geriatric Depression Scale
[GDS] score23 of 6) and those without depressive
symptoms (defined as a GDS score of <6). A, Survival without hospital readmission
(P = .02, log-rank test); B, survival without permanent
nursing home admission (P = .03, log-rank test);
and C, overall survival (P = .06, log-rank test).
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Table 1. Results From Bivariate and Multivariate Cox Proportional Hazard
Regression Analysis Predicting 6-Month Risk of Hospital Readmission*
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Table 2. Results From Bivariate and Multivariate Cox Proportional Hazard
Regression Analysis Predicting 6-Month Risk of Permanent Nursing Home Admission*
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Table 3. Results From Bivariate and Multivariate Cox Proportional Hazard
Regression Analysis Predicting 6-Month Risk of Death*
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In addition, because previous studies have shown that the GDS might
not be appropriate for subjects with severe cognitive impairment,30 we repeated the analyses after excluding subjects
with an MMSE score lower than 16 (n = 30). Results were not modified except
for the analysis of permanent nursing home admission, in which the instrumental
ADL variable disappeared from the model. However, results for the abnormal
GDS variable were unchanged. Finally, the secondary analysis of permanent
nursing home admission after exclusion of the subjects who died during the
6-month follow-up provided the same independent predictors with the addition
of the abnormal GDS variable, although the relationship did not reach statistical
significance (adj HR, 1.73; 95% CI, 0.82-3.64; P
= .15).
Overall, mean (SD) inpatient services costs per day of follow-up were
significantly higher for subjects with depressive symptoms than for those
without ($175.70 [$182.40] vs $126.00 [$167.10], respectively; P<.001; Kruskall-Wallis rank sum test). Although the cost of all
types of inpatient services was increased (Figure 2), the difference was mostly due to average (SD) costs of
acute services ($140.90 [$180.60] for patients with depressive symptoms vs
$106.90 [$163.90] for those without; P = .03) and
rehabilitation services ($20.60 [$37.50] for those with symptoms vs $10.70
[$30.00] for those without; P = .007). The association
between overall costs and depressive symptoms remained after adjusting for
comorbidity, functional status, and living situation, although it fell just
short of statistical significance ( = .254; SE = 0.139; P = .07).
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Figure 2. Average costs per day of follow-up
and type of inpatient stay for subjects with depressive symptoms (Geriatric
Depression Scale [GDS] 6) vs without depressive symptoms (GDS,<6).
Long NHome indicates permanent nursing home placement; short NHome, short
stay in a nursing home.
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COMMENT
Our results point to 2 main findings that support and extend other research
that has demonstrated a strong relationship between depressive symptoms and
poor health outcomes. First, we found an increased likelihood for subjects
with depressive symptoms to be readmitted to the hospital within 6 months
of an index acute hospital admission. Second, we found a clear trend for these
subjects to have a higher utilization of inpatient services during the follow-up
period, resulting in higher costs. Unfortunately, we were unable to confirm
the increased risk of mortality associated with depressive symptoms, but this
is most likely owing to our limited follow-up period.
Three major mechanisms can be proposed to explain the link between depressive
symptoms and hospital readmission. First, a direct effect of depressive symptoms
on health is possible. For example, a meta-analytic review found a significant
association between depression and alteration in cellular immunity, potentially
resulting in a reduced capability to resist stressors.31-32
In other studies focusing on the relationship of depression to cardiovascular
diseases, depression has been associated with alteration in neuroendocrine
function, autonomic nervous system activity, and platelet reactivity.33
Alternatively, an indirect effect of depressive symptoms may be postulated.
Hospital readmission might be secondary to poor adherence to medical treatment
and recommendations, as found in previous studies.34-36
In addition, subjects with depressive symptoms might be more vulnerable when
facing an acute situation because of a poorer social support system. These
subjects will more likely end up in the hospital, while a nondepressed person
might be able to more efficiently mobilize social resources to avoid hospital
readmission. However, if that were the case, one would expect to find a significant
relationship between the presence of formal help provided prior to the index
hospital admission and hospital readmission outcome. This was not the case
in our study. Of interest, a previous study of the possible modifying effect
of social support on the relation between depression and mortality in older
adults also failed to demonstrate a substantial effect.37
A third hypothesis is that depressive symptoms as measured at baseline
were an indicator of some underlying but unrecognized clinical disease that
modified the readmission risk. Although complete risk adjustment is impossible,
we controlled for comorbidity and functional status in the multivariate model,
and the relationship was not affected.
Clearly, further studies are needed to clarify the exact mechanisms
linking depressive symptoms to adverse outcomes such as hospital readmission.
Nevertheless, our results add to the evidence supporting the need to further
test the effects of better detection and treatment of depressive symptoms
in elderly persons on a wide range of outcomes.38-40
Unfortunately, available evidence suggests no simple interventional strategy
to achieve better outcomes in elderly persons with depressive symptoms.41-42 For example, a recent randomized
trial of simple case finding for depression in elderly outpatients did not
result in any reduction in health care utilization during a 2-year follow-up
period.41 Achieving better results will likely
require more complex and intensive strategies, combining provider education
with psychosocial and/or antidepressant drug interventions targeted at patients
meeting appropriate criteria.
We were unable to confirm the hypothesized association between depressive
symptoms and permanent nursing home admission. Most likely this is because
of the limited number of subjects admitted to nursing homes in this population
during the study period. Nevertheless, results of the subgroup analysis restricted
to subjects who survived during the 6-month follow-up suggest a potential
independent effect that should be investigated with a larger sample.
Finally, we did not confirm the previously well-described association
between depressive symptoms and mortality. However, Kaplan-Meier survival
curves (eg, Figure 1C) strongly
suggest that the limited follow-up period was the main factor explaining this
negative result. Interestingly, the curves for subjects with and without depressive
symptoms begin to clearly separate at around 100 days, as previously found
in similar studies of elderly medical inpatients.8, 10
Several limitations to this study should be mentioned. First, as already
discussed, we had a short follow-up period that likely affected our results,
especially the analysis on mortality. Second, the use of the GDS to define
depressive symptoms might be criticized because it is primarily a screening
tool. However, the GDS has been widely used and has been shown to perform
adequately in studies of similar elderly patients who have a high prevalence
of somatic symptoms. Moreover, sensitivity analyses using higher GDS cutoffs
to increase its specificity gave consistent results. Third, depressive symptoms
were defined according to the GDS result measured at hospital admission, which
might not reflect baseline mood status. In addition, we do not have data on
GDS evolution over time. Fourth, because we did not have specific data on
the reasons for readmission, we were unable to investigate which proportion
would be inappropriate and preventable. Several studies of elderly inpatients
found similar readmission rates and identified 9% to 17% of these readmissions
to be preventable.43-44 Finally,
several mediating and confounding factors such as smoking status, alcohol
use, and severity of illness measures were not controlled for in the multivariate
model. However, health effects of alcohol use and smoking status in this elderly
population are partially accounted for in the admitting diagnosis and Charlson
Comorbidity Index. In addition, functional status measured at hospital admission
is likely to reflect to some extent the severity of illness at admission.
This study also has several strengths. We used an exhaustive database
on health care utilization and were able to adjust in the multivariate model
for comorbidity, functional status, and social support measures in addition
to the traditional health measures.
CONCLUSIONS
The relationship between depressive symptoms and undesirable health
outcomes such as hospital readmission is probably complex, but the low detection
and treatment rates for depression found in previous studies suggest that
improved detection and treatment of this condition might result in improved
outcomes. Such an approach needs to be tested in an interventional trial.
AUTHOR INFORMATION
Accepted for publication March 29, 2001.
This project was supported by Fonds de Performance grant 20-1994 from
the Public Health Service, Canton of Vaud, Lausanne, Switzerland (Dr Büla).
We are grateful to Nadine Corbaz for secretarial assistance and John
C. Beck, MD, for comments on the manuscript.
Corresponding author and reprints: Christophe J. Büla, MD, CUTR
Sylvana, Ch de Sylvana 10, 1066 Epalinges, Switzerland (e-mail:
Christophe.Bula{at}chuv.hospvd.ch).
From the Division of Geriatric Medicine (Dr Büla) and the Department
of Internal Medicine (Drs Büla and Yersin), Centre Hospitalier Universitaire
Vaudois; and the Institute of Social and Preventive Medicine, University of
Lausanne (Drs Wietlisbach and Burnand), Lausanne, Switzerland.
REFERENCES
| |
1. Gillick MR, Serrell NA, Gillick LS. Adverse consequences of hospitalization in the elderly. Soc Sci Med. 1982;16:1033-1038.
2. Büla CJ, Rubenstein LZ. Risks of hospitalization for elderly persons: a clinical overview. Clin Geriatr. 1995;3:17-30.
3. Pouget R, Yersin B, Wietlisbach V, Burnand B, Büla CJ. Depressed mood in a cohort of elderly medical inpatients: prevalence,
clinical correlates, and recognition rate. Aging (Milano). 2000;12:301-307.
PUBMED
4. Koenig HG, Meador KG, Cohen HJ, Blazer DG. Depression in elderly hospitalized patients with medical illness. Arch Intern Med. 1988;148:1929-1936.
ABSTRACT
5. Koenig HG, Goli V, Shelp F, Kudler HS, Cohen HJ, Blazer DG. Major depression in hospitalized medically ill older men: documentation,
management, and outcome. Int J Geriatr Psychiatry. 1992;7:25-34.
6. O'Riordan TG, Hayes JP, Shelley R, O'Neill D, Walsh B, Coakley D. The prevalence of depression in acute geriatric medical assessment
unit. Int J Geriatr Psychiatry. 1989;4:17-21.
7. Covinsky KE, Fortinsky RH, Palmer RM, Kresevic DM, Landefeld CS. Relation between symptoms of depression and health status outcomes
in acutely ill hospitalized older persons. Ann Intern Med. 1997;126:417-425.
FREE FULL TEXT
8. Covinsky KE, Kahana E, Chin MH, Palmer RM, Fortinsky RH, Landefeld CS. Depressive symptoms and 3-year mortality in older hospitalized medical
patients. Ann Intern Med. 1999;130:563-569.
FREE FULL TEXT
9. Roach MJ, Connors AF, Dawson NV, et al. Depressed mood and survival in seriously ill hospitalized adults. Arch Intern Med. 1998;158:397-404.
FREE FULL TEXT
10. Ganzini L, Smith DM, Fenn DS, Lee MA. Depression and mortality in medically ill older adults. J Am Geriatr Soc. 1997;45:307-312.
ISI
| PUBMED
11. Cole MG, Bellavance F. Depression in elderly medical inpatients: a meta-analysis of outcomes. CMAJ. 1997;157:1055-1060.
ABSTRACT
12. Dunham NC, Sager MA. Functional status, symptoms of depression, and the outcomes of hospitalization
in community-dwelling elderly patients. Arch Fam Med. 1994;3:676-681.
ABSTRACT
13. Callahan CM, Hui SL, Nienaber NA, Musick BS, Tierney WM. Longitudinal study of depression and health services use among elderly
primary care patients. J Am Geriatr Soc. 1994;42:833-838.
ISI
| PUBMED
14. Koenig HB, Shelp F, Goli V, Cohen HJ, Blazer DG. Survival and health care utilization in elderly medical inpatients
with major depression. J Am Geriatr Soc. 1989;37:599-606.
ISI
| PUBMED
15. Koenig HG, Kuchibhatla M. Use of health services by hospitalized medically ill depressed elderly
patients. Am J Psychiatry. 1998;155:871-877.
FREE FULL TEXT
16. Saravay SM, Pollack S, Steinberg MD, Weinschel B, Habert M. Four-year follow-up of the influence of psychological comorbidity on
medical rehospitalization. Am J Psychiatry. 1996;153:397-403.
FREE FULL TEXT
17. Unützer J, Patrick DL, Simon G, et al. Depressive symptoms and the cost of health services in HMO patients
aged 65 years and older. JAMA. 1997;277:1618-1623.
ABSTRACT
18. Ingold B, Yersin B, Wietlisbach V, Burnand B, Büla CJ. Characteristics associated with inappropriate hospital use in elderly
patients admitted to a general internal medicine service. Aging (Milano). 2000;12:430-438.
PUBMED
19. Katz S. Assessing self maintenance: activities of daily living, mobility, and
instrumental activities of daily living. J Am Geriatr Soc. 1983;31:721-727.
ISI
| PUBMED
20. Lawton MP, Brody EM. Assessment of older people: self maintaining and instrumental activities
of daily living. Gerontologist. 1969;9:179-186.
ISI
| PUBMED
21. Folstein MF, Folstein SE, McHugh PR. "Mini-Mental State": a practical method for grading the cognitive state
of patients for the clinician. J Psychiatr Res. 1975;12:189-198.
FULL TEXT
|
ISI
| PUBMED
22. Charlson ME, Pompei P, Ales KL, MacKenzie CR. A new method of classifying prognostic comorbidity in longitudinal
studies: development and validation. J Chronic Dis. 1987;40:373-383.
FULL TEXT
|
ISI
| PUBMED
23. Sheikh JI, Yesavage JA. Geriatric Depression Scale (GDS): recent evidence and development of
a shorter version. Clin Gerontol. 1986;5:165-173.
24. Yesavage JA, Brink TL, Rose TL, Huang V, Adey M, Lerier VO. Development and validation of the geriatric depression screening scale. J Psychiatr Res. 1982;17:37-49.
25. Gerety MB, Williams JW Jr, Mulrow CD, et al. Performance of case-finding tools for depression in the nursing home:
influence of clinical and functional characteristics and selection of optimal
threshold scores. J Am Geriatr Soc. 1994;42:1103-1109.
ISI
| PUBMED
26. Hoyl MT, Alessi CA, Harker JO, et al. Development and testing of a five-item version of the Geriatric Depression
Scale. J Am Geriatr Soc. 1999;47:873-878.
ISI
| PUBMED
27. Whooley MA, Browner WS. Association between depressive symptoms and mortality in older women. Arch Intern Med. 1998;158:2129-2135.
FREE FULL TEXT
28. Stuck AE, Walthert JM, Nikolaus T, Büla CJ, Hohmann C, Beck JC. Risk factors for functional status decline in community-living elderly
people: a systematic literature review. Soc Sci Med. 1999;48:445-469.
29. Grambsch PM, Therneau MT. Proportional hazard tests and diagnostics based on weight residuals. Biometrika. 1994;81:515-526.
FREE FULL TEXT
30. McGivney S, Mulvihill M, Taylor B. Validating the GDS depression screen in the nursing home. J Am Geriatr Soc. 1994;42:490-492.
ISI
| PUBMED
31. Bennett TB, Cohen S. Depression and immunity: a meta-analytic review. Psychol Bull. 1993;113:472-486.
FULL TEXT
|
ISI
| PUBMED
32. Burack JH, Barrett DC, Stall RD, Chesney MA, Ekstrand ML, Coates TJ. Depressive symptoms and CD4 lymphocyte decline among HIV-infected men. JAMA. 1993;270:2568-2573.
ABSTRACT
33. Musselman DL, Evans DL, Nemeroff CB. The relationship of depression to cardiovascular disease. Arch Gen Psychiatry. 1998;55:580-592.
FREE FULL TEXT
34. Carney RM, Freedland KE, Eisen SA, Rich MW, Jaffe AS. Major depression and medication adherence in elderly patients with
coronary artery disease. Health Psychol. 1995;14:88-90.
FULL TEXT
|
ISI
| PUBMED
35. Ziegelstein RC, Fauerbach JA, Stevens SS, Romanelli J, Richter DP, Bush DE. Patients with depression are less likely to follow recommendations
to reduce cardiac risk during recovery from a myocardial infarction. Arch Intern Med. 2000;160:1818-1823.
FREE FULL TEXT
36. Buist DS, LaCroix AZ, Black DM, et al. Inclusion of older women in randomized clinical trials: factors associated
with taking study medication in the Fracture Intervention Trial. J Am Geriatr Soc. 2000;48:1126-1131.
ISI
| PUBMED
37. Fuhrer R, Dufouil C, Antonucci TC, Shipley MJ, Helmer C, Dartigues JF. Psychological disorder and mortality in French older adults: do social
relations modify the association? Am J Epidemiol. 1999;149:116-126.
FREE FULL TEXT
38. Gallo JJ, Coyne JC. The challenge of depression in late life: bridging science and service
in primary care. JAMA. 2000;284:1570-1572.
FREE FULL TEXT
39. McCusker J, Cole MG, Keller E, Bellavance F, Berard A. Effectiveness of treatments of depression in older ambulatory patients. Arch Intern Med. 1998;158:705-712.
FREE FULL TEXT
40. Williams JW Jr, Barrett J, Oxman T, et al. Treatment of dysthymia and minor depression in primary care: a randomized
controlled trial in older adults. JAMA. 2000;284:1519-1526.
FREE FULL TEXT
41. Whooley MA, Stone B, Soghikian K. Randomized trial of case-finding for depression in elderly primary
care patients. J Gen Intern Med. 2000;15:293-300.
FULL TEXT
|
ISI
| PUBMED
42. Callahan CM, Hendrie HC, Dittus RS, Brater DC, Hui SL, Tierney WM. Improving treatment of late life depression in primary care: a randomized
clinical trial. J Am Geriatr Soc. 1994;42:839-846.
ISI
| PUBMED
|
