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The Journals of Gerontology Series A: Biological Sciences and Medical Sciences 59:M1068-M1075 (2004)
© 2004 The Gerontological Society of America

Measuring Medical Burden Using CIRS in Older Veterans Enrolled in UPBEAT, a Psychogeriatric Treatment Program: A Pilot Study

Ritesh Mistry1,2,7,, Izabella Gokhman3, Roshan Bastani4,5, Robert Gould6, Elvira Jimenez1,7, Annette Maxwell4,5, Charles McDermott7, Joel Rosansky7, William Van Stone8, Lissy Jarvik1,7 and the UPBEAT Collaborative Group

1 Department of Psychiatry and Biobehavioral Sciences, and Neuropsychiatric Institute and Hospital, University of California, Los Angeles.
2 Department of Community Health Sciences, School of Public Health, University of California, Los Angeles.
3 Department of Psychiatry, Charles Drew University, Los Angeles, California.
4 Department of Health Services, School of Public Health, University of California, Los Angeles.
5 Jonsson Comprehensive Cancer Center, University of California, Los Angeles.
6 Department of Statistics, University of California, Los Angeles.
7 Department of Veterans Affairs, Greater Los Angeles Healthcare System, California.
8 Department of Veterans Affairs, Central Office, Washington, District of Columbia.

Address correspondence to Ritesh Mistry, MPH, c/o Lissy Jarvik, MD, PhD, 760 Westwood Blvd., Los Angeles, CA 90095-1759. E-mail: riteshm{at}ucla.edu


   Abstract
Top
 Abstract
Methods
 Results
 Discussion
 Appendix
 References
 
Background. A quantitative measure of medical burden is needed to assess medical comorbidities in psychogeriatric patients. The Cumulative Illness Rating Scale (CIRS) is the most widely used instrument for measuring medical burden in psychogeriatric research. Many clinicians, however, are discouraged by the requirement to project the persistence of acute conditions and therefore do not use the scale. The goal of this pilot study was to determine whether the inclusion of acute medical conditions undermines the usefulness of the CIRS. No such comparison was found in the existing literature.

Methods. Included in this study were 95 patients previously enrolled in the Unified Psychogeriatric Biopsychosocial Evaluation and Treatment (UPBEAT) demonstration program. All were male veterans of the U.S. armed forces who were admitted to acute medical or surgical inpatient units and who had positive screening results for anxiety, depression, or alcohol abuse. Two types of retrospective CIRS ratings were made for each patient: one included (CIRS-IP) and the other excluded (CIRS-PH) acute conditions. For each type of rating (CIRS-IP and CIRS-PH), 7 CIRS scores were computed according to methods reported in the literature. Survival time during 24 months of follow-up was used as a measure of health outcome indicating medical burden.

Results. With 1 exception, CIRS-IP and corresponding CIRS-PH scores were highly correlated (.70 < r <.99; p <.001). And, for 5 of 7 scores, both CIRS-IP and CIRS-PH were significantly associated with survival time (p <.05).

Conclusions. Results suggest that the CIRS can be used as an indicator of medical burden even with the inclusion of acute conditions. If replicated, these findings may increase CIRS use and thus aid the effort to encourage clinicians working with psychogeriatric patients to use standardized instruments to document medical burden.

THE frequent coexistence of psychiatric and medical disorders has been well documented for geriatric patients (1–5), even if the reasons are not always clear. In addition, chronic physical illness is recognized as a poor prognostic factor for depression and other psychiatric disorders (6–8). Furthermore, medical and surgical patients with psychiatric comorbidities, especially depression, have been reported to have a higher mortality rate, longer hospital stays, more postoperative complications, and an overall decrease in physical well-being and social functioning (3,6,9–11).

The Cumulative Illness Rating Scale [CIRS (12) and its geriatric version, CIRS-G (13)], one of several scales (14–16) that rate medical burden (or illness severity), has been widely used, including in patients with cancer, heart disease, depression, suicide, and dementia. Studies have reported results in outpatients, inpatients, community-dwelling and nursing home residents, and even in the examination of tissues at autopsy (15,17–32).

Although the CIRS is the most frequently used scale in geriatric psychiatry, few clinicians have incorporated it, or any other validated rating scale that measures medical burden, into their routine clinical practice. Furthermore, even when the CIRS has been used, generally in the setting of research or demonstration projects, not all raters followed instructions (13,33) to exclude from their ratings acute medical conditions not expected to persist chronically.

We encountered this discrepancy among CIRS raters in the Unified Psychogeriatric Biopsychosocial Evaluation and Treatment (UPBEAT) demonstration program (described in detail elsewhere [9,11,34–37)]. Raters often voiced dissatisfaction with the requirement to project future chronic medical burden, and it was unclear how many raters had actually deviated from the protocol and included acute conditions when scoring the CIRS. This uncertainty prompted us to consider the effects of including and excluding acute conditions on the relationship between CIRS scores and health outcome (using mortality as the outcome measure) in the pilot study described below.


   METHODS
Top
 Abstract
 Methods
Results
 Discussion
 Appendix
 References
 
Participants
The participants constitute a convenience sample of 100 UPBEAT Care patients drawn from the Greater Los Angeles Veterans Affairs Health Care System, West Los Angeles, California, one of the 9 participating UPBEAT sites. Details concerning the UPBEAT sample are provided elsewhere (9,11,34,36,37). The patients had been admitted to acute medical or surgical inpatient units between 1995 and 1998 and had positive screening results for symptoms of anxiety, depression [Mental Health Inventory (38) subscales: Anxiety: ≥ 17; Depression: ≥ 7], or alcohol abuse [Alcohol Use Disorder Identification Test (39): ≥ 16]. Patients were excluded from the program if they were unlikely to benefit from the UPBEAT psychogeriatric intervention because they were already receiving the treatment they needed (e.g., they had psychiatric appointments in the preceding or subsequent 6 months), were unlikely to survive the 24-month follow-up period (e.g., they were receiving hospice care), or were unlikely to maintain contact throughout the study (e.g., they resided outside the catchment area). Four of the 100 patients died during the UPBEAT enrollment hospitalization and were excluded from the current pilot study for that reason. In addition, the only woman in the group was excluded to maintain sample homogeneity.

The remaining 95 men were aged 68.4 years (SD [standard deviation] = 6.4) on average (range, 60 to 88 years) at the time of UPBEAT enrollment. Most (83.1%) were retired or unemployed; 37.9% were married, 30.6% were divorced or separated, 22.1% were single or never married, and 9.5% were widowed; and 59% had a high school diploma or fewer years of education. All participants were veterans of the United States armed forces. The convenience sample for this pilot study was similar to the total national UPBEAT Care sample (n = 814) in terms of demographic characteristics except for race (38.9% white and 50.5% black in the current study, compared with 68.4% white and 20.6% black in the national UPBEAT Care sample) (36). All participants gave informed consent.

Measures
Cumulative Illness Rating Scale (CIRS).-- One clinician (I.G.) did a retrospective chart review between 1 and 4 years after the enrollment episode and provided 2 sets of CIRS ratings for each of the 95 patients: an inpatient rating (CIRS-IP), which included both acute and chronic conditions, and a posthospitalization rating (CIRS-PH), which included only chronic conditions, as described in the Manual of Guidelines for Scoring the Cumulative Illness Rating Scale for Geriatrics (33). Both ratings were based on medical records describing patients' conditions as of the day of enrollment into the UPBEAT program. For most patients, both ratings were done on the same day. The ratings were used to calculate 7 summary scores reported in the literature (13,18,21,29). A total of 14 summary scores (7 for CIRS-IP and 7 for CIRS-PH) were calculated for each study participant. The CIRS and procedures describing the calculation of summary scores are presented in the Appendix.

Mortality and survival time.-- Mortality and survival time were used as proxies for overall physical health. Mortality was ascertained at the end of the 24-month period. Survival time was measured as the number of days patients survived between the date of UPBEAT enrollment and the end of the 24-month follow-up.

Statistical Analyses
We used Cox proportional hazards regression to estimate the association of CIRS summary scores (which were standardized using z-score transformation) with days of survival (40). In addition, we used logistic regression to estimate the association of the standardized CIRS summary scores with mortality (alive or dead) at the 24-month follow-up. Each model contained as predictors 1 of the 7 standardized CIRS summary scores and age at UPBEAT enrollment.

We used paired t tests to identify significant differences in means between each CIRS-IP and CIRS-PH summary score, and Spearman's rank-order method to calculate correlations between CIRS-IP and CIRS-PH scores.


   RESULTS
Top
 Abstract
 Methods
 Results
Discussion
 Appendix
 References
 
Age-adjusted Cox proportional hazards regressions showed that for 5 of the 7 CIRS summary scores, both CIRS-IP and CIRS-PH were significantly associated with the number of days of survival (Table 1). Two summary scores that were not significantly associated with survival time were the severity index (SV) and the number of severe categories (#SV). The SV was significantly associated with survival time for CIRS-PH, but not CIRS-IP, and neither #SV-IP nor #SV-PH was significantly associated with survival time. Logistic regression analyses showed similar patterns of associations between CIRS-IP and CIRS-PH summary scores and mortality (data not shown); that is, those CIRS-IP and CIRS-PH scores that were significantly associated with survival days were also associated with mortality.


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  		Table 1. Age-Adjusted* Associations Between Days of Survival and Each Z-Transformed Inpatient (CIRS-IP) as Well as Posthospitalization (CIRS-PH) CIRS Summary Score: Cox Proportional Hazards Regression (N = 95).

 
Means for CIRS-IP were greater than those for CIRS-PH for 5 of the 7 summary scores (Figure 1), and 4 of these 5 were significantly associated with survival time and mortality at the 24-month follow-up for both CIRS-IP and CIRS-PH. The exception was that SV-PH was significantly associated with survival time but SV-IP was not (Table 1).



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  		Figure 1. Means with 95% confidence intervals for Cumulative Illness rating Scale (CIRS)-Inpatient and CIRS-Posthospitalization summary scores (n = 95). Unshaded bars = CIRS-Inpatient (CIRS-IP); shaded bars = CIRS-Posthospitalization (CIRS-PH). *Significant difference in mean scores (paired t test, p <.001). TSC = total score; SV = severity index; CM = comorbidity index; #SV = number of severe categories; #EX = number of extremely severe categories

 
The CIRS-IP scores were highly correlated with corresponding CIRS-PH scores (Table 2). The number of extremely severe categories (#EX) showed the lowest correlation between CIRS-IP and CIRS-PH ratings, yet both were significantly associated with survival time and mortality (Table 1).


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  		Table 2. Spearman Rank Correlations Between CIRS Inpatient (CIRS-IP) and Corresponding Posthospitalization (CIRS-PH) Sumary Scores (N = 95).

 
Seventy-five of the 95 participants survived throughout the 24-month follow-up period (i.e., at least 731 days). The remaining 20 patients lived for an average of 268 ± 200 days (median, 238; range, 25 to 627).


   DISCUSSION
Top
 Abstract
 Methods
 Results
 Discussion
Appendix
 References
 
The results of the current pilot study suggest that the CIRS can be a useful indicator of medical burden as measured by survival time (and mortality) during a 24-month period, even with the inclusion of acute conditions. This is supported by the facts that CIRS-IP and CIRS-PH scores were generally highly correlated and most CIRS-IP and CIRS-PH scores were significantly associated with both survival time and mortality.

It was not our goal to determine whether one summary score is better or worse than another in terms of measuring medical burden. We report findings with respect to the 7 CIRS summary scores found in the literature (Table 3) to determine whether the inclusion of acute medical conditions in CIRS ratings influenced measurement of medical burden based on the various ways used to summarize the CIRS ratings. It is possible, perhaps even likely, that different summary scores will be optimal for different patient groups and for answering different questions such as those concerning daily functioning, treatment effects, rehabilitation efficiency, and mortality.


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  		Table 3. Summary of Results of Studies Relating CIRS Scores to Health Outcome.

 
CIRS-IP ratings provide an advantage over CIRS-PH ratings because including acute conditions from which the patient suffers at the time the CIRS ratings are made is simpler, for the rater, than projecting the chronic sequelae of the acute conditions. In addition, it is less time consuming.

How do our results compare with those reported in the literature? We found no other studies comparing the effect of inclusion and exclusion of acute medical conditions on the usefulness of the CIRS.

However, we did identify the opportunity to evaluate studies that report more than 1 summary score. Because some summary scores are based on ratings along a 5-point scale (TSC and SV) and others are based on collapsing these ratings (CM1, CM2, CM3, #SV, and #EX, hereafter designated as scores based on "binary ratings"), we could determine whether both types of scoring methods provide useful information on medical burden. A search of the literature from 1992 to 2002 revealed 10 studies (13,18,21,23,25,27–30,32) that report summary scores based on both the 5-point Likert-type rating scale and binary ratings. Table 3 summarizes 7 of the 10 studies. Two studies (30,32) reporting on patients with dementia were not included, because we excluded persons with dementia from our current sample, and a third study (13) was excluded because it used neither survival–mortality nor functional independence as health outcomes. The 7 remaining studies contained considerable variability in medical burden, with some of the study participants being much sicker than those in the current study and others much less so (Table 4). Some studies reported psychiatric comorbidities (27,28), whereas others did not. And outcome measures varied from survival or mortality (18,28,29) to functional independence (21,23,25,27). The investigators also used different versions of the CIRS (Table 4). And yet, by and large, both the summary scores based on the 5-point Likert-type ratings and those based on binary ratings were significantly related to outcome measures (Tables 3 and 4).


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  		Table 4. Studies Reporting at Least 2 Types of CIRS Summary Scores*.

 
We found that most of the scores based on binary ratings (4 of the 5) were associated with survival time and mortality, suggesting that binary ratings may be another way to make the scale more user friendly. Binary ratings would require less time and could produce fewer errors of judgment by overcoming the difficulty in distinguishing adjacent degrees of illness severity along the 5-point Likert-type rating scale. Thus, Miller and Towers (33) indicate that it is "easier to rate the severity of medical problems within a category [organ system] by defining ‘mild’ and ‘extremely severe’ first, ... and subsequently ‘moderate’ and ‘severe’" (p. 3). When using the binary ratings, clinicians would not have to make the finer judgments, and may, therefore, be more willing to include the CIRS when evaluating their patients. However, further research is needed to determine whether binary ratings done without 5-point ratings are as useful as suggested by collapsing the 5-point ratings, as we did in the current study and as reported in the literature.

In addition to being user friendly, CM2, CM3, and #EX offer an advantage over TSC and SV by minimizing the possibility of under-representing serious medical problems. For example, Miller and colleagues (13) state that "a patient with end-stage cardiac failure could be very seriously impaired, but would score a maximum of 4 in the [cardiac] category of the CIRS(G)" (p. 246). If such a patient had no other impairments, TSC would be 4, far below the average indicating (incorrectly) low overall illness severity, whereas CM2, CM3, and #EX would indicate the serious illness. Indeed, TSC, unlike #EX, which is a score based on binary ratings, failed to predict survival in the lung cancer study cited in Table 4 (29). It must be noted, however, that making only binary ratings instead of those on a 5-point scale precludes the computation of the TSC and SV.

Clearly more data are needed, including CIRS ratings obtained during a hospital admission rather than retrospectively. More data are also needed to evaluate various modifications of the CIRS itself. For example, could removing the psychiatric category be advantageous for psychogeriatricians and others who include standardized measures of psychiatric disorders in their assessment? Does this modification improve the ability of the CIRS to measure nonpsychiatric medical burden? These are just two examples of questions awaiting answers, which will be important for research (particularly with regard to medical and psychiatric comorbidities) and clinical care.

Limitations
First, we used a convenience sample of limited size consisting of only male veterans older than 60 years admitted to acute medical or surgical inpatient services at a single Veterans Affairs hospital who had positive screening results for symptoms of depression, anxiety, or alcohol abuse at the time of admission. Second, we excluded patients with dementia and other known mental health problems and patients not expected to be available throughout the 24-month follow-up period. Therefore, our findings cannot be generalized to other groups. Furthermore, rater bias could have influenced the results because a single rater performed both CIRS-IP and CIRS-PH ratings retrospectively, and most of the time, on the same day.

Although there is some indirect support in the literature and in the current study for the validity of CIRS scores based on binary ratings, studies that directly examine ratings made in a binary manner (which are not collapsed forms of ratings made along the 5-point scale) are required to establish their validity.

Conclusions
Our results suggest that the CIRS can measure medical burden in acutely hospitalized medical or surgical inpatients with symptoms of depression, anxiety, or alcohol abuse, even when acute medical conditions are included in the ratings. Because we could find no reports in the literature comparing ratings that included and excluded acute conditions, further research is needed on representative samples of geriatric patients with medical and psychiatric comorbidities who are followed prospectively. We hope that the findings of this pilot study will lead to research on simplifying the CIRS while increasing consistency in the use of the scale. The results of such research could facilitate more widespread use of the CIRS, not only in research but also among clinicians who work with psychogeriatric patients but do not record their patients' medical burdens in a quantitative way.


   APPENDIX
Top
 Abstract
 Methods
 Results
 Discussion
 Appendix
References
 
Scoring Instructions for the UPBEAT CIRS [CIRS-Modified (18)].-- Degree of Impairment in Each Organ System Is Rated as Follows:

0 – None, no impairment to organ system
1 – Mild impairment, which does not interfere with normal activity; treatment may or may not be required
2 – Moderate impairment, which interferes with normal activity; "first line" therapy is needed
3 – Severe impairment, significantly disabling problem
4 – Extremely severe impairment, life-threatening problem; immediate treatment required or of no avail; end-organ failure

Rated Organ Systems (Categories):

  1. Cardiac (heart only)
  2. Hypertension (affected organs are scored separately)
  3. Vascular (blood vessels; blood cells; lymphatic, marrow, spleen)
  4. Respiratory (lungs, bronchi, trachea)
  5. Eye-Ear-Nose-Throat (includes larynx)
  6. Upper Gastrointestinal (esophagus, stomach, duodenum, pancreas)
  7. Lower Gastrointestinal (large and small intestines; includes hernias)
  8. Hepatic (liver, gall bladder, biliary tree)
  9. Renal (kidneys only)
  10. Other Genitourinary (bladder, prostate, urinary tract, genitals)
  11. Musculoskeletal/Integumentary
  12. Neurological (brain, spinal cord, peripheral nerves; does not include dementia and psychiatric disorders)
  13. Endocrine/Metabolic (includes hormonal imbalances; morbid obesity, breast pathology, blood chemistry abnormalities; infections; intoxications)

Note: The original CIRS (12) includes Hypertension under Vascular, and includes Psychiatric, for a total of 13 categories. The CIRS-G (13) includes Hypertension under Vascular, and includes Psychiatric, but removes Hematopoetic from Vascular as a separate category, for a total of 14 categories. The CIRS-Modified (18) includes Hematopoetic under Vascular, and includes Psychiatric for a total of 14 categories. However, Parmelee and colleagues (18) exclude Psychiatric from their analyses (even though they list it as a category), for a total of 13 categories.

Summary Scores.-- Scores Based on a 5-Point Likert-Type Rating Scale:

  1. TSC = Total score: sum of rating across 13 categories
  2. SV = Severity index: TSC divided by the number of mild or worse ratings across all 13 categories.

Scores Based on Binary Ratings Derived From Collapsing Ratings Made on the 5-Point Likert-Type Scale:

  1. CM1 = Comorbidity index 1: number of mild or worse ratings across all 13 categories
  2. CM2 = Comorbidity index 2: number of moderate or worse ratings across all 13 categories
  3. CM3 = Comorbidity index 3: number of severe or extremely severe ratings across all 13 categories
  4. #SV = Number of severe ratings
  5. #EX = Number of extremely severe ratings.


   Acknowledgments
 
The opinions herein are those of the authors and not the Department of Veterans Affairs. The Department of Veterans Affairs provided financial support for the UPBEAT program. The authors thank all those at the Department of Veterans Affairs Greater Los Angeles Healthcare System, West Los Angeles UPBEAT site, who contributed their efforts to this project. They also thank Coen A. Bernaards, PhD, from UCLA Jonsson Comprehensive Cancer Center, Los Angeles, California, for assistance in statistical matters.

Received April 30, 2003

Accepted May 19, 2003


   References
Top
 Abstract
 Methods
 Results
 Discussion
 Appendix
 References
 

  1. Jarvik LF. The impact of immediate life situations on depression: illness and losses. In: Breslau LD, Haug MR, eds. Depression and Aging: Causes, Care, and Consequences. New York: Springer; 1983:114–120.
  2. Thomas C, Kelman HR, Kennedy GJ, Ahn C, Yang CY. Depressive symptoms and mortality in elderly persons. J Gerontol. 1992;47:S80-S87.
  3. Draper E, Luscombe G. The effects of physical health upon the outcome of admission to an acute psychogeriatrics ward. Australasian J Ageing. 1999;18:134-139.
  4. Borson S, Bartels SJ, Colenda CC, Gottlieb GL, Meyers B. Geriatric mental health services research: strategic plan for an aging population. Report of the Health Services Work Group of the American Association for Geriatric Psychiatry. Am J Geriatr Psychiatry. 2001;9:191-204.[Medline]
  5. Hansen MS, Fink P, Frydenberg M, Oxhoj ML, Sondergaard L, Eriksen M. Mental disorders in medical inpatients and the association to severity of illness, self-rated physical disability, and health perception. Psychosomatics. 2001;42:41-47.[Abstract/Free Full Text]
  6. Schulz R, Beach SR, Ives DG, Martire LM, Ariyo AA, Kop WJ. Association between depression and mortality in older adults: the Cardiovascular Health Study. Arch Intern Med. 2000;160:1761-1768.[Abstract/Free Full Text]
  7. Jackson-Triche ME, Greer Sullivan J, Wells KB, Rogers W, Camp P, Mazel R. Depression and health-related quality of life in ethnic minorities seeking care in general medical settings. J Affect Disord. 2000;58:89-97.[Medline]
  8. Blazer DG, Hybels CF, Pieper CF. The association of depression and mortality in elderly persons: a case for multiple, independent pathways. J Gerontol Med Sci. 2001;56A:M505-M509.
  9. Druss BG, Rohrbaugh RM, Rosenheck RA. Depressive symptoms and health costs in older medical patients. Am J Psychiatry. 1999;156:477-479.[Abstract/Free Full Text]
  10. Koenig HG, George LK, Larson DB, McCullough ME, Branch PS, Kuchibhatla M. Depressive symptoms and nine-year survival of 1,001 male veterans hospitalized with medical illness. Am J Geriatr Psychiatry. 1999;7:124-131.[Medline]
  11. Lavretsky H, Bastani R, Gould R, et al. Predictors of two-year mortality in a prospective "UPBEAT" study of elderly veterans with comorbid medical and psychiatric symptoms. Am J Geriatr Psychiatry. 2002;10:458-468.[Medline]
  12. Linn BS, Linn MW, Gurel L. Cumulative illness rating scale. J Am Geriatr Soc. 1968;16:622-626.[Medline]
  13. Miller MD, Paradis CF, Houck PR, et al. Rating chronic medical illness burden in geropsychiatric practice and research: application of the Cumulative Illness Rating Scale. Psychiatry Res. 1992;41:237-248.[Medline]
  14. Charlson M, Szatrowski TP, Peterson J, Gold J. Validation of a combined comorbidity index. J Clin Epidemiol. 1994;47:1245-1251.[Medline]
  15. Rochon PA, Katz JN, Morrow LA, et al. Comorbid illness is associated with survival and length of hospital stay in patients with chronic disability. A prospective comparison of three comorbidity indices. Med Care. 1996;34:1093-1101.[Medline]
  16. Harboun M, Ankri J. Comorbidity indexes: review of the literature and application to the elderly population. Rev Epidemiol Sante Publique. 2001;49:287-298.[Medline]
  17. Conwell Y, Forbes NT, Cox C, Caine ED. Validation of a measure of physical illness burden at autopsy: the Cumulative Illness Rating Scale. J Am Geriatr Soc. 1993;41:38-41.[Medline]
  18. Parmelee PA, Thuras PD, Katz IR, Lawton MP. Validation of the Cumulative Illness Rating Scale in a geriatric residential population. J Am Geriatr Soc. 1995;43:130-137.[Medline]
  19. Miller MD, Paradis CF, Houck PR, et al. Chronic medical illness in patients with recurrent major depression. Am J Geriatr Psychiatry. 1996;4:281-290.
  20. Alexopoulos GS, Meyers BS, Young RC, Kakuma T, Silbersweig D, Charlson M. Clinically defined vascular depression. Am J Psychiatry. 1997;154:562-565.[Abstract]
  21. Extermann M, Overcash J, Lyman GH, Parr J, Balducci L. Comorbidity and functional status are independent in older cancer patients. J Clin Oncol. 1998;16:1582-1587.[Abstract/Free Full Text]
  22. Steffens DC, O'Connor CM, Jiang WJ, et al. The effect of major depression on functional status in patients with coronary artery disease. J Am Geriatr Soc. 1999;47:319-322.[Medline]
  23. Di Libero F, Fargnoli M, Pittiglio S, Mascio M, Giaquinto S. Comorbidity and rehabilitation. Arch Gerontol Geriatr. 2001;32:15-22.[Medline]
  24. Katz IR, Curyto KJ, TenHave T, Mossey J, Sands L, Kallan MJ. Validating the diagnosis of delirium and evaluating its association with deterioration over a one-year period. Am J Geriatr Psychiatry. 2001;9:148-159.[Medline]
  25. Giaquinto S, Palma E, Maiolo I, et al. Importance and evaluation of comorbidity in rehabilitation. Disabil Rehabil. 2001;23:296-299.[Medline]
  26. Shmuely Y, Baumgarten M, Rovner B, Berlin J. Predictors of improvement in health-related quality of life among elderly patients with depression. Int Psychogeriatr. 2001;13:63-73.[Medline]
  27. Patrick L, Knoefel F, Gaskowski P, Rexroth D. Medical comorbidity and rehabilitation efficiency in geriatric inpatients. J Am Geriatr Soc. 2001;49:1471-1477.[Medline]
  28. Waern M, Rubenowitz E, Runeson B, Skoog I, Wilhelmson K, Allebeck P. Burden of illness and suicide in elderly people: case-control study. BMJ. 2002;324:1355-1357.[Abstract/Free Full Text]
  29. Firat S, Byhardt RW, Gore E. Comorbidity and Karnofksy performance score are independent prognostic factors in Stage III non-small-cell lung cancer: an institutional analysis of patients treated on four RTOG studies. Int J Radiat Oncol Biol Phys. 2002;54:357-364.[Medline]
  30. Doraiswamy PM, Leon J, Cummings JL, Marin D, Neumann PJ. Prevalence and impact of medical comorbidity in Alzheimer's disease. J Gerontol Med Sci. 2002;57A:M173-M177.
  31. Lyness JM, Caine ED, King DA, Conwell Y, Duberstein PR, Cox C. Depressive disorders and symptoms in older primary care patients: one-year outcomes. Am J Geriatr Psychiatry. 2002;10:275-282.[Medline]
  32. Colombo M, Vitali S, Cairati M, et al. Wanderers: features, findings, issues. Arch Gerontol Geriatr. 2001; 99–106.
  33. Miller MD, Towers A. A Manual of Guidelines for Scoring the Cumulative Illness Rating Scale for Geriatrics (CIRS-G). Pittsburgh, PA: University of Pittsburgh; 1991.
  34. Karel MJ, Lynch B, Moye J. Patterns of lifetime alcohol use in a clinical sample of older male veterans. Clin Gerontol. 2000;22:55-71.
  35. Moye J, Rosansky JS, Llorente M, Jarvik LF. Engaging patients in treatment: lessons learned from the UPBEAT program. Annals Long Term Care. 2001;9:61-67.
  36. Kominski G, Andersen R, Bastani R, et al. UPBEAT: the impact of a psychogeriatric intervention in VA medical centers. Unified psychogeriatric biopsychosocial evaluation and treatment. Med Care. 2001;39:500-512.[Medline]
  37. Mistry R, Rosansky J, McGuire J, McDermott C, Jarvik L. Social isolation predicts re-hospitalization in a group of older American veterans enrolled in the UPBEAT program. Int J Geriatr Psychiatry. 2001;16:950-959.[Medline]
  38. Veit CT, Ware JE. The structure of psychological distress and well-being in general population. J Consult Clin Psychol. 1997;51:730-742.
  39. Allen JP, Litten RZ, Fertig JB, Babor T. A review of research on the Alcohol Use Disorders Identification Test (AUDIT). Alcohol Clin Exp Res. 1997;21:613-619.[Medline]
  40. Cox DR, Oakes D. Analysis of survival data. Monographs on Statistics and Applied Probability. New York: Chapman and Hall; 1984.




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