Hot topic in geriatric medicine
Risk factors for adverse drug events in hospitalized elderly patients: A geriatric score

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Abstract

Objective

To propose a score to evaluate the risk of ADEs in hospitalized elderly patients.

Design

This score was developed on the basis of the IMEPAG study.

Setting

In France, in the greater Paris area in 16 geriatric rehabilitation centres.

Participants

All individuals aged 65 years or older who experienced an ADE during the 4 weeks of the study period.

Measurements

ADEs were detected using a standardized checklist. Separate multivariable models were constructed using any occurrence of an ADE as the outcome with stepwise logistic regression. Significant variables were included to compute the ADE risk score. The score was validated by resampling technique (bootstrap).

Results

During the study, on 526 hospitalized patients, 152 had at least one ADE (mean age 83.6 ± 7.9 years). Risk factors included in the final score were: number of medications (if  7), the presence of antipsychotic treatment and recent anticoagulant. The number of drugs taken was the strongest predictor of ADEs. The final score was between zero and 34, with an ADE risk of 12% for a score  6, 28% for a score of 7–12, 35% for a score of 13–18 and 52% for a score > 18. The area under the ROC curve was 0.70 (95% CI, 0.65–0.74).

Conclusion

We have developed and validated a simple and practical score to detect the risk of ADEs in elderly hospitalized patients. We have also proposed a classification of risk of the drugs most frequently associated with ADEs.

Introduction

Adverse drug events (ADEs) represent a major public health problem in the aged. The World Health Organization (WHO) defines an adverse drug event (ADE) as a detrimental response to a medication that is undesired and unintended, excluding therapeutic failure, poisoning, and intentional overdose [1]. In the United States, the number of reported ADEs increased by 160% between 1998 and 2005 [2] with an increase in fatal ADEs of 170%. Despite concerns that ADEs represent an important medical problem in the elderly, the predictive factors are still poorly understood. Risk factors reported to be independently associated with ADEs have included advancing age, sex, comorbidities, multiple drug regimens, inappropriate use of medication, poor cognitive function and anticoagulants [3]. Factors such as frailty, renal insufficiency, malnutrition or heart failure have also been mentioned. However, there is currently no consensus on which factors have the greatest impact. On the other hand, most studies have focused on the prevalence and risk analyses of inappropriate drug use in the elderly population using the Beers criteria [4], [5].

As strategies for preventing and reducing the effects of ADEs in the elderly are developed, an important component will be identifying high risk patients. Strategies to systematically detect and prevent ADEs are not always put to practice. One strategy for preventing in hospital ADEs may be to identify high risk elderly patients so that physicians can include the patient's level of risk when deciding upon the drug monitoring strategy. The aim of our study was to propose a specific score to evaluate the risk of ADEs in the elderly.

Because another score (the GerontoNet ADR risk score) [6] was recently proposed by a European group of geriatricians, it was interesting to compare the two scores.

Section snippets

Methods

To investigate this issue, a score was developed based on data from the IMEPAG study. The IMEPAG study was described in detail elsewhere [7] and its principal features are briefly described below.

Results

Sixteen geriatric centres participated in the study and 576 patients (mean age: 83.6 ± 7.9 years) were consecutively included. The mean number of drugs taken at inclusion was 9.4 ± 4.24 per patient; the median was nine (IQR: 6–12).

The most prevalent chronic diseases in the IMEPAG study were: cardiovascular (n = 412; 72%), musculoskeletal (n = 276; 48%), gastrointestinal (n = 207; 36%), genitourinary (n = 168; 29%), neurological (n = 150; 26%), ophthalmologic (n = 126; 22%), respiratory (n = 122; 21%), dementia (n

Discussion

The number of medications, antipsychotic treatment and a recent anticoagulant were identified as risk factors for ADE in our study. The most frequently involved drugs were antipsychotics, antihypertensives, anticoagulants, and analgesics. This confirms several other studies in elderly inpatients. Our score was validated by booststrapping (internal validation) and seems to be simple and easy to use in clinical practice. Discrimination of the risk score between those with low from those with

Comparison with the GerontoNet score

Recently, the GerontoNet ADR risk score was proposed by a European group of geriatricians [6]. The variables included in this score are: ≥ 4 comorbid conditions, heart failure, liver disease, number of drugs, previous adverse drug reaction (ADR) and renal failure (glomerular filtration rate less than 60 mL/min). The GerontoNet score is between 0 and 10, with an ADR risk in the validation study of 4.2–4.5% for a score of 0 to 3; 7% for a score of 4 to 5; 11.5% for a score of 6 to 7 and 28% for a

Number of drugs

The most powerful predictor of an ADE in our score is the use of seven or more drugs like in the GerontoNet ADR risk score [6]. Many studies have shown that the only significant predictor for ADE with multivariate analysis was the number of drugs. Indeed, the number of drugs taken, whatever the type of drug, could be a predictor of ADE. For Davies et al. [12], each additional drug multiplies the risk of an ADE by 1.14. It is important to note that the incidence of ADE increases with each

Comorbid conditions and age

In addition to the number of drugs, the presence of four or more comorbid conditions was a variable in the final score in the study by Onder et al. [6]. Comorbidity has been found to be the principal ADE risk factor in many other studies. In our study, the number of diseases or the number of comorbidities was not an independent risk factor because it was correlated with the number of medications. In practice, the number of prescribed drugs could be a useful measurement of comorbidity [16]. In

Anticoagulants

Recent anticoagulant treatment (< 3 months) was associated with the risk of ADEs in our study. In the study by Hanlon et al. [17], the main ADE risk factors in frail elderly persons after a hospital stay were the number of medications and warfarin use. The study by Gurwitz et al. [13] also found that anticoagulant use was a risk factor for all ADEs as well as preventable ADEs. Although warfarin presents safety concerns for patients, it is still often associated with severe ADEs. In a study on

In practice

Patients with a high ADE risk score and taking anticoagulants or antipsychotics should be carefully evaluated for ways of reducing their ADE risk, such as the possibility of safely reducing the number of medications to less than seven, if they are taking more than that number.The distribution of drugs associated with an ADE in our study (Table 2) is very similar to the drug groups which cause preventable admissions to hospital [25]. These treatments are frequently co-prescribed in the elderly,

Strengths and limitations

This study has the advantage of being a prospective and multicentric trial with 16 participating centres. Moreover the assessment of ADEs was standardized and reviewed weekly by investigators. Third, the results of the study were analysed by a multidisciplinary team of physicians and pharmacists.

Our study was limited by the size of the patient population and the resulting number of ADEs and preventable ADEs restricting our ability to identify risk factors. Another limitation is that our

Conclusion

Elderly patients with a high ADE geriatric score should be considered at risk and clinicians should critically review their drug regimens during hospitalization to identify unnecessary or inappropriate medications that could be discontinued. We have developed and validated a score to help clinicians identify elderly adults at a greater risk of ADE and therefore, who could be more closely monitored. Clinicians who care for elderly patients with multiple prescriptions, antipsychotics or recent

Disclosure of interest

The authors declare that they have no conflicts of interest concerning this article.

References (27)

  • J. Doucet et al.

    Preventable and non-preventable risk factors for adverse drug events related to hospital admissions in the elderly. A prospective study

    Clin Drug Invest

    (2002)
  • Dictionnaire Vidal 2005. OVP: Vidal ed. Paris,...
  • F.E. Harrell et al.

    Multivariate prognostic models: issues in developing models, evaluating, assumptions and adequacy, and measuring and reducing errors

    Stat Med

    (1996)
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