Original Article
Geriatrics index of comorbidity was the most accurate predictor of death in geriatric hospital among six comorbidity scores

https://doi.org/10.1016/j.jclinepi.2009.11.013Get rights and content

Abstract

Objectives

To compare the abilities of six validated comorbidity indices (Charlson index, cumulative illness rating scale [CIRS], index of coexistent diseases, Kaplan scale, geriatrics index of comorbidity [GIC], and chronic disease score) to predict adverse hospitalization outcomes (death during hospitalization, length of stay, and institutionalization).

Study Design and Setting

Prospective cohort of 444 elderly inpatients (mean age 85.3) was randomly selected from Geneva geriatric hospital.

Results

In univariate analyses, GIC was the best predictor for all outcomes. The risk of death was 30 times higher and the risk of prolonged hospitalization and being institutionalized was eight to nine times higher in patients with scores of class 3 or 4. In adjusted logistic regression models, GIC remained the best predictor of death during hospitalization. Higher GIC scores accounted for 25% of the variance of this outcome, with mortality rates differing by a factor of four between the highest and the lowest scores. CIRS was a strong predictor of a prolonged hospital stay and institutionalization, accounting for 10% of the variance of these outcomes.

Conclusion

GIC was the most accurate predictor of death during hospitalization. CIRS could be used to select elderly patients at admission as an indicator of improvement at discharge.

Introduction

Elderly patients often suffer from multiple chronic conditions that individually and jointly affect their quality of life, use of health services, morbidity, and mortality [1]. Several indices have been proposed to quantify comorbidity in adults. However, only some of them are valid and reliable for use as a measure of comorbidity in applied clinical research [2] or in elderly patients [3], [4]: (1) The Charlson comorbidity index (CCI) is the most extensively studied comorbidity index (CI) for predicting mortality. It is a weighted index that takes into account the number and severity of comorbid conditions [5]. This index was created to enhance the prediction of 1-year mortality in a cohort of medical young patients, but it has been used to predict other health outcomes, such as functional status. It gives a highest weight for conditions that are not frequent (i.e., AIDS) in the elderly; and for other conditions, so frequent in elderly patients (i.e., dementia) the weight is lower, (2) the cumulative illness rating scale (CIRS) addresses all relevant physiological systems rather than being based on specific diagnoses and consists of two parts: the CI and the severity index [6]. The advantage of this scale built for geriatrics patients is that it assesses the severity of diseases according to their impact of disability, (3) The index of coexisting disease (ICED) was developed to predict in-hospital postoperative complications and 1-year health-related quality of life of patients who underwent total hip replacement surgery. This index has a 2-dimensional structure, measuring disease severity and disability, which can be useful when considering mortality and disability as the outcomes of interest [7]. A major limitation of the ICED is that it requires medical records and highly trained reviewers who must follow complex decision rules in creating the index, (4) The Kaplan index was developed specifically for use in diabetes research [8], (5) the geriatrics index of comorbidity (GIC) takes into account the number and severity of diseases, but although it was built for geriatric patients, it has the peculiarity of not including disability [9], and (6) the chronic disease score (CDS) is an alternative CI based on the drugs taken by the patient rather than clinical diagnoses [10].

These tools were initially validated in institutionalized elderly patients in a retrospective manner. A previous study examined the prognostic value of the CCI in predicting a 3-year mortality and functional decline in patients receiving long-term care from 88 residential care facilities in Quebec, Canada (291 dependent elderly adults with a mean age of 83.3 years). The CCI performed well in predicting both outcomes [11]. The CIRS is significantly associated with mortality, acute hospitalization, medication usage, laboratory test results, and functional disability among frail elderly institutionalized patients [6]. Recently, Di Bari et al. [12] showed that these measures of comorbidity (CCI, ICED, GIC, and CDS) predicted death and disability in basic activities of daily life in 688 Italian community dwellers with a mean age of 74 years. However, the value, relevance, and pertinence of these CIs as predictors of hospitalization adverse outcomes in the very elderly remain unknown.

In this prospective study, we compared the performance of these six validated and widely used CIs in predicting adverse hospitalization outcomes in the elderly, including death during the hospitalization period, a prolonged hospital stay, and institutionalization. The study population was derived from a study cohort of very elderly, acutely ill geriatric inpatients.

Section snippets

Patients and data collection

We carried out a prospective study in a 300-bed geriatric hospital (HOGER) of the University Hospitals of Geneva, Switzerland, for acute illness. Patients and data collection have been described elsewhere [13]. Briefly, patients were recruited by clinically trained staff. All patients older than 75 years and consecutively admitted on selected days between January 2004 and December 2005 were included. We selected a random sample of patients for each day, using a computer-generated randomization

Results

We included 444 patients in this study (mean age 85.3 ± 6.7, 74% women). Table 1 summarizes frequency distribution of patients according to each comorbidity score.

As there were no patients in the ICED classes 1 and 2, we considered only classes 3 and 4, providing binary data for the analyses. Likewise, only 2% of the patients were classified as class 1 by the GIC, allowing us to combine classes 1 and 2 for the analysis.

For the other four indices, the distribution was almost equal among the four

Discussion

One of the main strengths of this study was the comprehensive and detailed assessment of the presence and extent of comorbidities: the same medical doctor scored the six CIs for all patients to ensure a high accuracy of scoring. The prospective collection of comorbidity data allowed better control over the quality of the data needed to quantify comorbidity. We carried out, for the first time, a prospective study comparing the use of six CIs—the most widely used and validated in elderly

Acknowledgments

The authors thank the teams of Mrs. O. Baumer, L. Humblot, and M. Cos for their technical assistance. This work was supported by grant 3200B0-102069 from the Swiss National Science Foundation.

References (30)

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No author received any consultancy fees or has any company holdings or patents. There are no conflicts of interest.

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