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Drug related problems in older adults living with dementia

  • Sirasa Ruangritchankul ,

    Roles Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Project administration, Validation, Visualization, Writing – original draft, Writing – review & editing

    sirasarama37@gmail.com

    Current address: Division of Geriatric Medicine, Department of Medicine, Faculty of Medicine, Ramathibodi Hospital, Mahidol University, Bangkok, Thailand

    Affiliations Centre for Health Services Research, Faculty of Medicine, The University of Queensland, Brisbane, QLD, Australia, Division of Geriatric Medicine, Department of Medicine, Faculty of Medicine, Ramathibodi Hospital, Mahidol University, Bangkok, Thailand

  • Nancye M. Peel,

    Roles Conceptualization, Data curation, Resources, Supervision, Writing – review & editing

    Affiliation Centre for Health Services Research, Faculty of Medicine, The University of Queensland, Brisbane, QLD, Australia

  • Leila Shafiee Hanjani,

    Roles Conceptualization, Writing – review & editing

    Affiliation Centre for Health Services Research, Faculty of Medicine, The University of Queensland, Brisbane, QLD, Australia

  • Leonard C. Gray

    Roles Conceptualization, Data curation, Resources, Software, Supervision, Writing – review & editing

    Affiliation Centre for Health Services Research, Faculty of Medicine, The University of Queensland, Brisbane, QLD, Australia

Drug related problems in older adults living with dementia

  • Sirasa Ruangritchankul, 
  • Nancye M. Peel, 
  • Leila Shafiee Hanjani, 
  • Leonard C. Gray
PLOS
x

Abstract

Background

Compared with those without dementia, older patients with dementia admitted to acute care settings are at higher risk for triad combination of polypharmacy (PP), potentially inappropriate medication (PIM), and drug-drug interaction (DDI), which may consequently result in detrimental health. The aims of this research were to assess risk factors associated with triad combination of PP, PIM and DDI among hospitalized older patients with dementia, and to assess prevalence and characteristics of PP, PIM and DDI in this population.

Methods

In this retrospective cross-sectional study, 416 older inpatients diagnosed with dementia and referred for specialist geriatric consultation at a tertiary hospital in Brisbane, Australia during 2006–2016 were enrolled. Patients were categorized into two groups according to their exposure to the combination of PP, PIM and DDI: ‘triad combination’ and ‘non-triad combination’. Data were collected using the interRAI Acute Care (AC) assessment instrument. Independent risk factors of exposure to the triad combination were evaluated using bivariate and multivariate logistic regression analyses.

Results

Overall, 181 (43.5%) were classified as triad combination group. The majority of the population took at least 1 PIM (56%) or experienced at least one potential DDI (76%). Over 75% of the participants were exposed to polypharmacy. The most common prescribed PIMs were antipsychotics, followed by benzodiazepines. The independent risk factors of the triad combination were the presence of atrial fibrillation diagnosis and higher medications use in cardiac therapy, psycholeptics and psychoanaleptics.

Conclusions

The exposure to triad combination of PP, PIM and DDI are common among people with dementia as a result of their vulnerable conditions and the greater risks of adverse events from medications use. This study identified the use of cardiac therapy, psycholeptics and psychoanaleptics as predictors of exposure to PP, PIM and DDI. Therefore, use of these medications should be carefully considered and closely monitored. Furthermore, comprehensive medication reviews to optimize medication prescribing should be initiated and continually implemented for this vulnerable population.

Introduction

During the recent decades, the increasing aging population and the great gains in life expectancy have resulted in raised prevalence of neurodegenerative diseases including dementia. Globally, the number of people affected by dementia was almost 50 million in 2017 and is projected to increase to 131.5 million by 2050 [1]. In Australia, the number of people living with dementia was 447,115 in 2019. In the next four decades, the number will over double to reach an estimated number of 1,076,129 by 2058 [2].

Dementia is a term used to describe clinical syndromes associated with irreversibly progressive deterioration of multiple higher cortical functions, including language, memory, calculation, comprehension, thinking, learning skills and appropriate judgment, leading to interfering with functional ability and daily life [3,4]. Due to the deterioration of cortical functions, especially in memory, people with dementia may take the medicine repeatedly or wrong medications, resulting in drug related problems (DRPs) and increased medication use. These problems have devastating effects on health outcomes, such as adverse drug events, morbidity and mortality. Dementia is the greatest risk factor of disability and premature mortality in Australian older people aged 65 years and older [5,6]. In 2017, dementia was the second-leading cause of death in Australia, just after coronary artery diseases [7]. The average survival time of people living with dementia has ranged from 3 to 13 years [8,9]. Finally, the economic impact of dementia has markedly been concerning. The estimated cost of dementia in Australia was over $15 billion in 2019 and is estimated to increase to over $36.8 billion by 2056 [6].

Dementia is usually associated with the development of three or more chronic diseases including hypertension, stroke, diabetes and coronary heart disease, resulting in increased health care needs and medication use [1016]. Dementia and demented-related complications are common causes for unplanned visits to acute care sectors and then contribute to adverse consequences including falls, superimposed delirium, frailty, malnutrition, increased mortality rate and longer hospital stay [1726]. In Australia, approximately 83,000 people with dementia are admitted to acute care settings each year [27]. In previous studies, between 15% to 40% of admitted patients were diagnosed with dementia, and they accounted for 10% of acute care bed days [2832]. With regard to medication use, people with dementia are more likely to take many medications for treatment of cognitive problems, psycho-behavioral symptoms and multiple comorbidities, compared with people without dementia [33,34]. Most geriatric patients with dementia usually consume a mean of five or more medications, commonly defined as polypharmacy (PP) [3539]. Although taking multiple medications may be necessary for the management of dementia and chronic diseases, the use of multiple medications can lead to greater risk of DRPs, including potentially inappropriate medications (PIMs), drug-drug interactions (DDIs), and adverse drug reactions (ADRs) [4045]. Apart from polypharmacy, age-related pharmacokinetic and pharmacodynamic changes can pose higher risk for undesirable DRPs [46,47]. Furthermore, older people with dementia have an alteration of blood-brain permeability and levels of endogenous neurotransmitters which may increase their sensitivity to neurological effects of medications, leading to greater experience of ADRs [46,48,49]. The PP and DRPs result in an increased risk of hospital admission, morbidity, mortality and health care burdens [5053]. These problems tend to occur more frequently and are more serious in geriatric population with dementia due to their vulnerability than in younger population. The exposure to the combination of PP and DRPs is commonly identified in older patients with dementia. Many previous studies have reported high prevalence of PP and DRPs among older patients with dementia admitted to hospitals. Studies have reported the exposure of 82–98% of this vulnerable population to the PP [5456], 22.4–96% to the PIM [5659] and 43.2% to the DDI [60].

However, although many studies have assessed aspects related to PP, PIM or DDI, no previous study has explored prevalence and associated risk factors for the exposure to three criteria or triad combination of PP, PIM and DDI among the older people with dementia admitted in acute care setting.

The first aim of the current study was to evaluate risk factors associated with the exposure to triad combination of PP, PIM and DDI among patients with dementia. The other aim was to assess prevalence and characteristics of PP, PIM and DDI and to determine the most frequently implicated medications in the context of this vulnerable population.

Materials and methods

Study design, setting and participants

The present study was a secondary analysis of data from the Comprehensive electronic Geriatric Assessment database [61] of patients referred for specialist geriatric consultation at Princess Alexandra Hospital, Brisbane, Australia during the period from January 1, 2006 to December 31, 2016. The interRAI Acute Care (AC) tool was used for comprehensive geriatric assessment [62]. The criteria for selection of individuals into the study were patients aged 65 years and over with dementia based on the medical records of disease diagnosis “dementia” combined with cognitive performance scale (CPS) scores ranging from 2 to 6, derived from the interRAI Acute Care assessment. The participants were categorized into two groups: triad combination group and non-triad combination group. The triad combination group comprised those patients exposed to all three criteria of PP, PIM and DDI. The non-triad combination group comprised those without exposure to the combination of three criteria of PP, PIM and DDI.

Data collection and measurement tools

In this study, all data were de-identified health data provided from the interRAI Acute Care (AC) database [62,63]. A standardized interRAI Acute Care (AC) assessment tool was used to support comprehensive geriatric assessment (CGA) in the acute setting for the older patients [61] at admission, trained nurse assessors gathered comprehensive health information data including physical, physiological-behavioral and socio-economic status, and conducted many clinical assessments for example, cognitive status, psycho-behavioural conditions and activities of daily living. If patients were not able to provide the medical information, a relative or a proxy informant could offer the required information. The individual variables (covariates) included baseline characteristics, living situation, primary diagnosis, comorbidities, geriatric syndrome, activity of daily living (ADL), instrumental activity of daily living (IADL), moods and behavioral patterns, cognitive functions, service utilization and all prescribed medications [62]. Within 24 hours of admission, trained nurse assessors gathered and recorded all health data and lists of prescribed medications. The participant’ s cognitive function was evaluated by embedded computer algorithms of InterRAI Acute Care (AC), which interpreted collected clinical data such as moods, behavior, and cognitive functions to create a CPS, correlated with Mini-Mental State Examination (MMSE), with scores ranging from 0 (intact cognition) to 6 (very severe cognitive impairment) [64]. Functional capacity and levels of dependence were evaluated by short ADL scale at admission and premorbid IADLs scale which were also embedded in InterRAI Acute Care (AC) database [63,65]. The ADL short-form scale at admission evaluates obtained assistance in performing four activities including eating, personal hygiene, toilet use and walking, ranging from 0 to 16 with higher scores indicating greater level of incapacity [63,66]. Premorbid IADL scale summarized the performance on seven IADL items (housework, meal preparation, shopping, finances, transport, phone use and medication management). Performance scores for each item range from 0 (independent) to 6 (total dependence). The summed scores were analysed to generate a scale ranging from 0 to 42, with higher scores indicating a greater level of dependence [63,66]. With regard to medication data, the medication name, frequency, route of administration and doses were recorded in the databases. All recorded medications were classified by Anatomical Therapeutic Chemical (ATC) codes [67], following recommendation by the World Health Organization, as the international standard to present medication usage data. Finally, the prevalence and characteristics of PP, PIM and DDI were determined by a geriatrician and/or pharmacist using following definitions.

Definitions

Drug-Related Problem (DRP).

DRP is defined as any undesirable circumstance involving medication therapy which potentially interferes with desired health consequences [68]. In the current study, DRPs consist of presence of PIM and DDI.

Polypharmacy (PP).

PP is defined as the simultaneous consumption of five or more prescribed medications, based upon the number of regular prescribed medications documented in the InterRAI Acute Care (AC) database [69].

Potentially Inappropriate Medication (PIM).

By definition, PIM is a medication that should be avoided in an individual due to the health risks outweighing the clinical benefits [70]. In this study, PIMs were determined using the 2019 American Geriatrics Society (AGS) Beers Criteria® (AGS Beers Criteria®), which are the fifth updated of the AGS Beers Criteria® [71]. In the present study, PIMs independent of medical condition and PIMs that should be avoided in the older adults due to drug-disease or drug-syndrome interactions were determined.

Drug-Drug Interaction (DDI).

The definition of DDI is a situation in which one substance affects the activity of another drug when both are used simultaneously, regardless whether adverse events will occur or not [72]. All prescribed medications were analyzed by Micromedex Drug Interaction Database [73] to determine drug interactions which were considered only single pairwise of drug combination. In this study, potential drug interactions were reported in terms of severity and interaction effect. With respect to severity rating risk, DDIs were categorized into four classifications: minor, moderate, major and contraindicated DDIs [73]. Only the risk of potential adverse outcomes related to drug interactions were explored, but clinical relevant outcomes were not included.

Statistical analysis

Statistical analyses were performed using the SPSS for Windows Software Package, Version 25 (SPSS Inc., Chicago, Ill., USA). To describe population characteristics and medication profiles, the percentage was used for categorical variables and mean ± standard deviation (SD) or median ± interquartile range (IQR) was used for continuous variables. Pearson’s chi-squared test or Fisher’s exact for categorical variables and Unpaired Student’s t-test or Mann-Whitney U test for continuous variables were performed to compare baseline characteristics, physical and cognitive function, medication profiles between triad combination group and non-triad combination group. Univariate logistic regression analysis was used first to evaluate the effect of variables on the exposure to triad combination of PP, PIM and DDI. Factors determined as significant variables from univariate logistic analysis (significance set at p<0.05 level), age, gender, number of comorbidity, short ADL scale at admission and premorbid IADLs were included in the final multivariate logistic regression analysis to estimate independent risk factors associated with the exposure to triad combination of PP, PIM and DDI. Additionally, subgroup analyses were performed to evaluate risk factors associated with greater exposure to each criterion of PP, PIM and DDI using bivariate and multivariate logistic regression analyses. The results from logistic regression analyses were presented as odd ratios (ORs) and 95% confidence intervals (CIs). Statistical significance levels for variables were determined at the level of p<0.05.

The present study was a secondary retrospective cross-sectional analysis of de-identified data provided by the interRAI Acute Care (AC) assessment database. The researchers did not require to identify the data and to contact the participants. Exemption from ethics approval was obtained from the Metro South Human Research Ethics Committee and Human Research.

Results

Baseline and clinical characteristics

Of 2,992 older patients age 65 years and older referred for geriatric consultation services at Princess Alexandra Hospital from 2006 to 2016, a total of 416 older patients with dementia (13.9%) were enrolled. The eligible participants were categorized into two groups: triad combination group and non-triad combination group. Overall, 181 (43.5%) participants and 235 (56.5%) participants were classified as triad combination group and non-triad combination group respectively. The descriptive analysis and a comparison of population study in terms of baseline and clinical characteristics between the two groups are presented in Table 1.

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Table 1. Demographic and clinical characteristics of the population.

https://doi.org/10.1371/journal.pone.0236830.t001

The majority of the participants were female (n = 224; 53.8%). The age ranged from 65 to 101 years with mean of 82.3 years (SD 7.1 years), which was not significantly different between the two groups. Over half of the participants were widowed, divorced or separated. The majority of the total population (> 80%) resided in their own homes, but less than half of them lived alone. In the current study, it was found that the number of the patients lived alone in triad combination group was significantly lower as compared to the non-triad combination group. Approximately one tenth were admitted from residential aged care facilities. The median length of hospital admission was not significantly different between the two groups (p = 0.408). With regard to discharge destination, over 40% were discharged to RACF. In both groups, approximately 6% ended their lives in hospital. Dementia with psycho-behavioural symptoms (29.8%), falls (22.8%) and urinary tract infection (15.4%) were the main causes of the current hospitalization. The participants in the triad combination group had substantially more comorbidities as compared to the non-triad combination group (p = 0.001). More than three quarters of the total population had three or more comorbidities. In both groups, the participants were more likely to have hypertension, infection and coronary artery disease. It was found that the number of participants having diabetes, coronary artery disease, atrial fibrillation and osteoporosis in the triad combination were markedly higher comparing with the non-triad combination group (p<0.05). With respect to functional capacity and geriatric syndrome, the majority of the participants were more likely to have impaired hearing (49.3%), urinary incontinence (65.4%), and mild to moderate cognitive impairment (78.8%) with CPS scores ranging from 2 to 4. The participants in the triad combination group had a tendency to be of greater dependence in IADL as compared to those in the non-triad combination group [31.8 (SD 11.2) in the triad combination group vs 29.3 (SD 12.8) in the non-triad combination group, p = 0.032].

Medication use

The most common prescribed medications categorized by ATC codes are presented in Table 2. The total number of regular prescribed medications was 3,027. The number of regular prescribed medications per person ranged from 0 to 19. Two participants in the non-triad combination group and six in the triad combination group consumed more than 15 medications. The median number of prescribed medications was 8 (IQR 6–10 medications) in the triad combination group and 6 (IQR 4–8 medications) in the non-triad combination group. This was significantly different between the two groups (p< 0.001). Three most frequently prescribed medication categories were antithrombotic agents (76.4%), followed by drugs for constipation (41.8%) and agent acting on the renin-angiotensin system (39.4%). In the triad combination group, prescriptions of cardiac therapy, diuretics, psycholeptics and psychoanaleptics were substantially higher as compared to the non-triad combination group (p<0.001). Up to 10% of the total participants were using anti-dementia medications which consisted of three cholinesterase inhibitors and one N-methyl-D-aspartate (NMDA) receptor antagonists.

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Table 2. Prescribed medications use of the population according to ATC system.

https://doi.org/10.1371/journal.pone.0236830.t002

PP, PIM and DDI

In both groups, approximately 78% of the participants were exposed to PP. Approximately 76% of the participants experienced at least 1 potential DDI, and 233 participants (56%) had at least 1 PIM, as shown in Table 3.

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Table 3. Prevalence of medication issues in the study population.

https://doi.org/10.1371/journal.pone.0236830.t003

Four participants (1%) were on 4 PIMs. With regard to DDI, 23 participants (5.5%) were exposed to > 10 potential DDIs. Overall, 373 participants (89.7%) were exposed to at least 1 criteria of PP, PIM and/or DDI. Of these 373, 50 (12%) were exposed to one criterion, 142 (34.1%) to two criteria, and 181 (43.5%) to all three criteria.

A total of 657 PIMs were identified among the study population, as presented in Table 4. The most common prescribed PIM were for neurological and cardiovascular systems. Antipsychotics and benzodiazepines were the most frequently prescribed PIMs.

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Table 4. Potentially inappropriate medications of the population study according to the 2019 Beers Criteria.

https://doi.org/10.1371/journal.pone.0236830.t004

In the current study, 1360 medication combinations resulted in potential DDIs, as shown in Tables 3 and 5. The majority of the participants (49.4%) were exposed to major DDIs. Three single pairwise of drug combinations contributed to contraindicated DDIs, for example, the combination of haloperidol with metoclopramide, citalopram with metoclopramide and oxybutynin with potassium. The drug combination frequently implicated in potential DDI was that of heparin with aspirin, the interactive effect of which increases the risk of bleeding.

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Table 5. Lists of contraindicated drug interactions and most common major drug interactions with potential effects according to Micromedex Drug Interaction Database.

https://doi.org/10.1371/journal.pone.0236830.t005

Factors associated with the exposure to triad combination

After univariate logistic regression analyses were performed, significant variables for the exposure to all three criteria of PP, PIM and DDI were identified, as shown in Table 6. These significant variables, age, sex, number of comorbidities, short ADL at admission, premorbid IADL were added to adjust multivariate logistic model. After this adjustment, the independent risk factors of triad combination were the presence of diagnosis of atrial fibrillation (OR = 2.12 [1.93–3.96]) and increased medication use in cardiac therapy (OR = 3.49 [1.76–6.92]), psycholeptics (OR = 7.09 [4.23–11.87]) and psychoanaleptics (OR = 2.41 [1.44–4.03]). However, the degree of cognitive impairment, age, sex, ADLs and number of comorbidities were not associated factors for the exposure to triad combination of PP, PIM and DDI.

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Table 6. Logistic regression model of factors associated with exposure to triad combination of PP, PIM and DDI.

https://doi.org/10.1371/journal.pone.0236830.t006

Factors associated with polypharmacy

The results of the multivariate logistic regression analyses for independent risk factors of polypharmacy are presented in Table 7. The findings revealed that the presence of the diagnosis of gastroesophageal reflux disease (GERD) (OR = 6.03 [1.64–22.09]) and that of DDI (OR = 34.16 [9.59–121.69]) were associated with increased polypharmacy. Moreover, a greater number of prescribed medications for constipation, mineral supplements, antithrombotic agents, diuretics, agents acting on the renin-angiotensin system, lipid modifying agents, antibacterial drugs, analgesics and psycholeptics were strong associated risk factors of polypharmacy (P<0.001).

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Table 7. Logistic regression model of factors associated with exposure to each criteria of PP, PIM and DDI.

https://doi.org/10.1371/journal.pone.0236830.t007

Factors associated with inappropriate medication use

The adjusted logistic regression analyses presented a greater risk of PIM which substantially increased with the condition of higher medication use in cardiac therapy (OR = 3.47 [1.80–6.66]), antihypertensives (OR = 6.24 [1.26–30.83]), psycholeptics (OR = 18.38 [9.73–34.73]) and psychoanaleptics (OR = 2.26 [1.30–3.93]), as presented in Table 7. Furthermore, the occurrence of DDI was associated with PIM (OR = 1.97 [1.08–3.62]).

Factors associated with drug-drug interactions

According to multivariate logistic regression analyses, associated independent risk factors of greater DDI were a higher number of comorbidities (OR = 1.24 [1.03–1.48]) and prescribed medications (OR = 1.46 [1.17–1.82]) as well as the presence of polypharmacy (OR = 3.04 [1.12–8.27]) and PIM (OR = 2.07 [1.07–4.00]). The prescriptions of diuretics (OR = 12.72 [1.64–98.68]) and psychoanaleptics (OR = 6.14 [2.35–16.08]) marginally increased the prevalence of DDI, as presented in Table 7.

Discussion

The current study has reported the risk factors associated with the exposure to three criteria or triad combination of PP, PIM and DDI and has explored the prevalence and characteristics of PP, PIM and DDI among the older people living with dementia admitted to an acute care setting during the period from 2006 to 2016. The prevalence of dementia in hospitalized elderly patients aged 65 and over was 13.9%, similar to the results of previous studies [74,75]. With regard to primary diagnosis, consistent with the study of Toot et al and Andrieu et al, patients having behavioural and psychological symptoms of dementia (BPSD) are related to an increased risk of hospitalization [76,77] as a result of caregivers’ stress and burdens [78,79]. In addition, falls and urinary tract infection are also common reasons for admission of people living with dementia, which is in line with previous studies [17,7988]. However, falls and urinary tract infection could have been prevented in this geriatric population. Amongst patients diagnosed with dementia, a higher use of indwelling catheters, dehydration, poor hygiene and urinary incontinence may be associated with an increased risk of urinary tract infection (UTI) [8992]. Furthermore, in terms of neuropsychiatric treatment, sedatives or antipsychotics are widely prescribed, which may exacerbate urinary retention and reduce the patient’s activity, leading to worsening UTI. Falls are common issues in these patients owing to having impaired visuospatial and executive functions as well as developing negative health outcomes from some medications to maintain cognitive functions and behavioral symptoms [93]. The most common co-morbidities are hypertension, followed by infection and coronary artery disease. The results of current study are similar to common combinations of chronic diseases found in the previous studies [9497]. The most common pre-existing comorbidities with dementia such as hypertension and cardiovascular diseases could be explained that they are the predictors of the risk of dementia [95,96,98]. Compared to the non-triad combination group, the number of patients having diabetes mellitus, coronary artery disease and atrial fibrillation in the triad combination were substantially higher. Due to management, most patients with these chronic diseases were treated with multiple medications and with narrow therapeutic medications such as digoxin and warfarin, leading to an increased risk of the exposure to three criteria of PP, PIM and DDI [98].

The most frequently prescribed medication categories were antithrombotic agents and agents acting on the renin-angiotensin system which were prescribed for treatment of common chronic diseases such as hypertension and coronary artery diseases [99]. Furthermore, antithrombotic agents were widely prescribed for patients with hip fractures to prevent venous thromboembolism [54]. Comparing with non-triad combination group, the number of medications use in cardiac therapy, diuretics, psycholeptics and psychoanaleptics in triad combination group were substantially higher.

As would be expected, hospitalized older patients with dementia are prone to be prescribed five or more medications daily [41,100], which are associated with higher co-morbidities and greater demented-related complications [33,40]. In accordance to the study of Brunet et al and Von-Ranteln Kruse et al, between 82–98% of hospitalized older people living with dementia experienced polypharmacy [55,56]. With regard to factors associated with polypharmacy, a higher number of prescribed medication in cardiac therapy, psycholeptics and psychoanaleptics were revealed. The findings from previous studies contribute to a growing body of evidence which demonstrates the presence of drug interactions associated with a higher risk of polypharmacy [101103]. According to Park H-Y el al’s study [104] polypharmacy is associated with the increase of comorbidities, which was not seen in our study.

In the case of inappropriate medication use, more than half of this geriatric population were more likely to be exposed to at least 1 PIM. This prevalence was higher than the results of previous studies [57,105,106]. However, the variability in prevalence of PIM depends on the population characteristics, healthcare settings and the PIMs lists used such as the Beer Criteria, the STOPP/START criteria, PRISCUS list and Laroche list [71,107109]. Regarding characteristics of PIMs according to the 2019 Beers criteria, the most common prescribed PIM classifications are cardiovascular system medications including cardiac therapy (antiarrhythmic agents) and central nervous system medications including psycholeptics and psychoanaleptics. These findings can explain why using of cardiac therapy, psycholeptics and psychoanaleptics are strong predictors of the occurrence of PIM. According to the 2019 Beers criteria, antipsychotics and benzodiazepines are considered common prescribed PIMs which may result in worsening of cognitive function and detrimental health consequences [71,110116]. Furthermore, antipsychotics are known as an increased risk of cardiovascular events (stroke and heart arrhythmia) and mortality [117120] whereas benzodiazepines are labeled as the predictor of falls and fractures [121]. However, these PIMs could have been prevented if medication prescribing is carefully balanced between risks and benefits and is avoided for unsuitable patients. Although some dispensed medications such as antipsychotics and benzodiazepines could relieve BPSD, these medications should not be used as the first line treatment [114]. Therefore, precipitating causes should be managed and non-pharmacological treatment should be attempted before the initiation of antipsychotics [122,123]. In contrast to previous studies [39,124126], PP and number of medications were not linked to the use of PIMs in this study. In dementia, common risk factors of PIMs are the use of medications to relieve BPSD such as psycholeptics and psychoanaleptics. Unlike our results, other studies [39,127] have shown the associations of some medical conditions, such as urinary incontinence and osteoarthritis, with the use of PIMs.

The prevalence of DDI in this geriatric population with dementia in acute care setting was substantially higher than those prevalence in a previous study [60]. In this study, more than one third of elderly patients with dementia were exposed to major potential DDI, which is in line with Bogetti-Salazar ‘s study [128]. The most common potential DDI was the combination of heparin with aspirin which are prescribed to treat common comorbidities such as cardiovascular diseases. This common drug combination, in the study could be prescribed to prevent venous thromboembolism as complication of falls and fractures. This study demonstrates that the more prescribed medications patients take, the greater risks of DDIs they experience [60,101,128]. Furthermore, taking of PIMs and PP poses a significant risk of drug interactions [101,129]. Additionally, specific medication classifications including psychoanaleptics (antidepressants and anti-dementia drugs) and diuretic are associated with a higher risk of DDI due to age-related pharmacokinetic and pharmacodynamic changes [60,128,130,131]. However, no relationship was found between DDI and any specific medical condition factor, sex, age, activity of daily living [60,128].

In terms of exposure to triad combination, older patients diagnosed with dementia are prone to triad combination of PP, PIM and DDI. In the context of predictors of triad combination, older patients with dementia having atrial fibrillation were found to be more likely to be exposed to triad combination of PP, PIM and DDIs as compared to those without atrial fibrillation. In treatment of atrial fibrillation and prophylaxis complications, many types of medications such as antiarrhythmic drugs and antithrombotic agents are prescribed as a combination of drugs of choice. These medications have significant narrow therapeutic index and dose-response variability, which may contribute to increased risk of PIM and DDI [132]. Additionally, an increased use of cardiac therapy, psychoanaleptics and psycholeptics were important risk factors of the exposure to triad combination of PP, PIM and DDI.

Medication management should vary based on individuals and prescribers should carefully consider patients’ preferences for treatment as well as taking into account the risks and benefits of medication prescribing. Moreover, raising practitioners’ awareness regarding careful medication use is essential to avoid undesirable drug problems such as PIMs and DDIs, the great proportion of which could be prevented. Therefore, strategies of comprehensive medication reviews and medication reconciliation by physicians and pharmacists should be initiated to optimize medication prescribing for hospitalized elderly patients with dementia in order to limit the occurrence of PP, PIM and DDI.

The strengths and limitations

To our knowledge, this is the first study to explore risk factors associated with the exposure to the triad combination of PP, PIM and DDI and to evaluate the prevalence and characteristics of PP, PIM and DDI among older patients with dementia in an acute care setting during a ten-year period. Furthermore, a standardized interRAI Acute Care (AC) assessment tool was used to gather clinical information, social attributes and medication prescribing profiles of the geriatric population with dementia. Trained nurse assessors gathered all comprehensive health information data and conducted many clinical assessments for dementia to refer to interRAI acute care (AC) databases, as standard assessment database for acute care setting. The participants were determined by using a combination of medical records with standard cognitive testing including CPS scores ranging from 2 to 4 in order to support accuracy in dementia diagnosis.

Several limitations of this study have to be taken into consideration. First, this study was conducted only in older patients with dementia referred for specialist geriatric consultation in a single acute care setting; therefore, the findings may not be applicable to older persons admitted to other facilities or who are not diagnosed with dementia. Patients are generally referred for geriatric assessment for complex care needs and multimorbidity as well as decisions around discharge to residential aged care facilities, admission to transition care programs, and potential for rehabilitation. Not all patients with dementia are referred for specialist consultation and so the number enrolled in this study is likely to be an underestimation of the number of older patients with dementia admitted to hospital. Second, the number of older patients with dementia may be underestimated due to under-diagnosis before admission [12,17,20,21]. Third, the identification of dementia subtypes may present differences in the results, but dementia was not classified following etiologies in this study. Fourth, the absence of detailed duration and indication of medication prescribing during admission may result in underestimation of PIMs. Fifth, clinical relevant outcomes due to drug interactions were not taken into account. Furthermore, all drug interactions were considered only by single pairwise of drug combination, but interactions from three drug combination or more were not accounted for. Finally, this study did not address other common DRPs among the elderly with dementia, such as ADRs [44].

Conclusion

The exposure to triad combination of PP, PIM and DDI are common among people with dementia as a result of their vulnerable conditions and the greater risks of adverse events from medications use. This study identified the use of cardiac therapy, psycholeptics and psychoanaleptics as predictors of exposure to PP, PIM and DDI. Therefore, use of these medications should be carefully considered and closely monitored. Furthermore, comprehensive medication reviews to optimize medication prescribing should be initiated and continually implemented for this vulnerable population.

Supporting information

S1 File. Potentially inappropriate medications among older adults living with dementia.

https://doi.org/10.1371/journal.pone.0236830.s001

(DOC)

S2 File. Drug interactions among older adults living with dementia.

https://doi.org/10.1371/journal.pone.0236830.s002

(DOC)

Acknowledgments

The authors would like to thank all trained nurse assessors for gathering comprehensive data in interRAI Acute Care (AC) assessment system database.

References

  1. 1. Alzheimer’s Disease International. Dementia Statistics. 2017 [Cited 2019 Oct 24]. Available from: https://www.alz.co.uk/research/statistics
  2. 2. Dementia Australia (2018). Dementia Prevalence Data 2018–2058, commissioned research undertaken by The National Centre for Social and Economic Modelling (NATSEM), University of Canberra. 2018 [Cited 2019 Oct 25]. Available from: https://www.dementia.org.au/files/documents/2018-2058%20Prevalence%20CED_AUSTRALIA_alpha.pdf
  3. 3. Department of Health, National Framework for Action on Dementia 2015–2019. 2019 Feb 15 [Cited 2019 Oct 25]. Available from: https://agedcare.health.gov.au/sites/default/files/documents/09_2015/national-framework-for-action-on-dementia-2015-2019.pdf
  4. 4. ICD-10, Organic, including symptomatic, mental disorders (F00-F09). 2016 [Cited 2019 Oct 25] Available from: https://icd.who.int/browse10/2016/en#/F00-F09
  5. 5. Australian Institute of Health and Welfare 2012. Dementia in Australia. Cat. no. AGE 70. Canberra: AIHW. 2012 [Cited 2019 Oct 25]. Available from: https://www.aihw.gov.au/getmedia/13995.pdf.aspx
  6. 6. The National Centre for Social and Economic Modelling NATSEM (2016) Economic Cost of Dementia in Australia 2016–2056. 2017 Feb. [Cited 2019 Oct25]. Available from: http://www.dementia.org.au/files/NATIONAL/documents/The-economic-cost-of-dementia-in-Australia-2016-to-2056.pdf
  7. 7. Australian Bureau of Statistics (2019). Causes of Death, Australia, 2018. Cat. no. 3303.0. Canberra. 2019 Sep 25 [Cited 2019 Oct 25]. Available from: http://www.abs.gov.au/ausstats/abs@.nsf/mf/3303.0
  8. 8. Brodaty H, Seeher K, Gibson L. Dementia time to death: a systematic literature review on survival time and years of life lost in people with dementia. Int Psychogeriatr. 2012;24(7):1034–45.
  9. 9. Staekenborga SS, Pijnenburg YA, Lemstra AW, Scheltensa P, Vd Flier WM. Dementia and Rapid Mortality: Who is at Risk? J Alzheimers Dis. 2016;53(1):135–42. pmid:27104894
  10. 10. Bynum JP, Rabins PV, Weller W, Niefeld M, Anderson GF, Wu AW. The relationship between a dementia diagnosis, chronic illness, medicare expenditures, and hospital use. J Am Geriatr Soc. 2004;52(2):187–94. pmid:14728626
  11. 11. Bunn F, Burn AM, Goodman C, Rait G, Norton S, Robinson L, et al. Comorbidity and dementia: a scoping review of the literature. BMC Med. 2014;12:192.
  12. 12. Timmons S, Manning E, Barrett A, Brady NM, Browne V, O’Shea E, et al. Dementia in older people admitted to hospital: a regional multi-hospital observational study of prevalence, associations and case recognition. Age Ageing. 2015;44(6):993–9. pmid:26420638
  13. 13. Alzheimer’s Association (2011). Alzheimer’s disease facts and figures. Alzheimer’s & Dementia, 7(2), 208–244. 2011. [Cited 2019 Oct 25]. Available from: http://www.sciencedirect.com/science/journal/15525260/7/2.
  14. 14. Hill J, Fillit H, Shah SN, del Valle MC, Futterman R. Patterns of healthcare utilization and costs for vascular dementia in a community-dwelling population. J Alzheimers Dis. 2005;8(1):43–50. pmid:16155348
  15. 15. Zhao Y, Kuo TC, Weir S, Kramer MS, Ash AS. Healthcare costs and utilization for Medicare beneficiaries with Alzheimer’s. BMC Health Serv Res. 2008;8:108. pmid:18498638
  16. 16. Phelan EA, Borson S, Grothaus L, Balch S, Larson EB. Association of incident dementia with hospitalizations. JAMA. 2012;307(2):165–72. pmid:22235087
  17. 17. Sampson EL, Blanchard MR, Jones L, Tookman A, King M. Dementia in the acute hospital: prospective cohort study of prevalence and mortality. Br J Psychiatry. 2009;195(1):61–6. pmid:19567898
  18. 18. Australian Commission on Safety and Quality in Health Care (2013). Evidence for the safety and quality issues associated with the care of patients with cognitive impairment in acute care settings: a rapid review. ACSQHC Sydney. 2013. [Cited 2019 Oct 30]. Available from: http://www.safetyandquality.gov.au
  19. 19. Connolly S, O’Shea E. The impact of dementia on length of stay in acute hospitals in Ireland. Dementia (London). 2015;14(5):650–8.
  20. 20. Fogg C, Griffiths P, Meredith P, Bridges J. Hospital outcomes of older people with cognitive impairment: An integrative review. Int J Geriatr Psychiatry. 2018;33(9):1177–97.
  21. 21. Reynish EL, Hapca SM, De Souza N, Cvoro V, Donnan PT, Guthrie B. Epidemiology and outcomes of people with dementia, delirium, and unspecified cognitive impairment in the general hospital: prospective cohort study of 10,014 admissions. BMC Med. 2017;15(1):140. pmid:28747225
  22. 22. Sheehan B, Lall R, Gage H, Holland C, Katz J, Mitchell K. A 12-month follow-up study of people with dementia referred to general hospital liaison psychiatry services. Age Ageing. 2013;42 (6):786–90. pmid:24166239
  23. 23. Guijarro R, San Román CM, Gómez-Huelgas R, Villalobos A, Martín M, Guil M, et al. Impact of dementia on hospitalization. Neuroepidemiology. 2010;35(2):101–8. pmid:20551696
  24. 24. King B, Jones C, Brand C. Relationship between dementia and length of stay of general medical patients admitted to acute care. Australas J Ageing. 2006;25(1):20–3.
  25. 25. Fong TG, Jones RN, Marcantonio ER, Tommet D, Gross AL, Habtemariam D, et al. Adverse outcomes after hospitalization and delirium in persons with Alzheimer disease. Ann Intern Med. 2012;156(12):848–56. pmid:22711077
  26. 26. Mukadam N, Sampson EL. A systematic review of the prevalence, associations and outcomes of dementia in older general hospital inpatients. Int Psychogeriatr. 2011;23(3):344–55. pmid:20716393
  27. 27. MacDermott S, Yates M, Theobald M, Morvell M, Mohebbi M, West E, et al. National Rollout and Evaluation of the Dementia Care in Hospitals Program (DCHP), Ballarat: Victoria (Prepared for the Department of Health). 2017 [Cited 2019 Oct 27]. Available from: http://www.healthroundtable.org/Portals/0/PublicLibrary/2017/FinalReport_DCHP_Evaluation2015_2017.pdf
  28. 28. Briggs R, Coary R, Collins R, Coughlan T, O’Neill D, Kennelly SP. Acute hospital care: how much activity is attributable to caring for patients with dementia? QJM: Int J Med. 2016;109(1):41–4.
  29. 29. Zekry D, Herrmann FR, Grandjean R, Vitale AM, De Pinho MF, Michel JP, et al. Does dementia predict adverse hospitalization outcomes? A prospective study in aged inpatients. Int J Geriatr Psychiatry. 2009;24(3):283–91. pmid:18727147
  30. 30. Royal College of Psychiatrists. Who cares wins, 2006. [Cited 2019 Nov 15]. Available from: http://www.yumpu.com/en/document/view/4279828/who-cares-wins-royal-college-of-psychiatrists
  31. 31. Mukaetova-Ladinska EB, Teodorczuk A, Cerejeira JM. Dementia in the acute hospital. Brit J Psychiat. 2009;195(5):461–2. pmid:19880940
  32. 32. Timmons S, Barrett A, Browne V, Manning E, Cahill S, O’ Sullivan K, et al. A multi-hospital study of dementia in older people admitted to acute hospitals: prevalence, associations and long term outcomes (Cork Dementia Study). Ir Ageing Stud Rev. 2015;6(1):105.
  33. 33. Clague F, Mercer SW, McLean G, Reynish E, Gurthrie B. Comorbidity and polypharmacy in people with dementia: insights from a large, population-based cross-sectional analysis of primary care data. Age Ageing. 2017;46(1):33–9. pmid:28181629
  34. 34. Peron EP, Slattum PW, Powers KE, et al. Pharmacotherapy: a pathophysiologic approach. In: DiPiro JT, Talbert RL, Yee GC, et al., editors. Alzheimer disease. New York (NY): McGraw-Hill Education; 2017. 10e.
  35. 35. Mueller C, Molokhia M, Perera G, Veronese N, Stubbs B, Shetty H, et al. Polypharmacy in people with dementia: Associations with adverse health outcomes. Exp Gerontol. 2018;106:240–5. pmid:29452289
  36. 36. Hoffmann F, van den Bussche H, Wiese B, Schön G, Koller D, Eisele M, et al. Impact of geriatric comorbidity and polypharmacy on cholinesterase inhibitors prescribing in dementia. BMC Psychiatry. 2011;11:190. pmid:22145796
  37. 37. Leelakanok N, D’Cunha RR. Association between polypharmacy and dementia-A systematic review and metaanalysis. Aging Ment Health. 2019;23(8):932–41. pmid:29746153
  38. 38. Andersen F, Viitanen M, Halvorsen DS, Straume B, Engstad TA. Co-morbidity and drug treatment in Alzheimer’s disease. A cross sectional study of participants in the dementia study in northern Norway. BMC Geriatr. 2011;11(1):58.
  39. 39. Lau DT, Mercaldo ND, Harris AT, Trittschuh E, Shega J, Weintraub S. Polypharmacy and potentially inappropriate medication use among community-dwelling elders with dementia. Alzheimer Dis Assoc Disord. 2010;24(1):56–63. pmid:19561441
  40. 40. Lalic S, Sluggett JK, Ilomaki J, Wimmer BC, Tan EC, Robson L, et al. Polypharmacy and medication regimen complexity as risk factors for hospitalization among residents of long-term care facilities: a prospective cohort study. J Am Med Dir Assoc. 2016;17(11):1067.e1–6.
  41. 41. Pfister B, Jonsson J, Gustafsson M. Drug-related problems and medication reviews among old people with demntia. BMC Pharmacol Toxicol. 2017;18(1):52. pmid:28655357
  42. 42. Hukins D, Macleod U, Boland JW. Identifying potentially inappropriate prescribing in older people with dementia: a systematic review. Eur J Clin Pharmacol. 2019;75(4):467–81. pmid:30610274
  43. 43. Eshetie TC, Nguyen TA, Gillam MH, Kalisch Ellett LM. A narrative review of problems with medicines use in people with dementia. Expert Opin Drug Saf. 2018;17(8):825–36. pmid:29993294
  44. 44. Gustafsson M, Sjolander M, Pfister B, Jonsson J, Schneede J, Lovheim H. Drug-related hospital admissions among old people with dementia. Eur J Clin Pharmacol. 2016;72(9):1143–53. pmid:27377393
  45. 45. Wucherer D, Thyrian JR, Eichler T, Hertel J, Kilimann I, Richter S, et al. Drug-related problems in community-dwelling primary care patients screened positive for dementia. Int Psychogeriatr. 2017;29(11):1857–68. pmid:28780910
  46. 46. Reeve E, Trenaman SC, Rockwood K, Hilmer SN. Pharmacokinetic and pharmacodynamic alterations in older people with dementia. Expert Opin Drug Metab Toxicol. 2017;13(6):651–68. pmid:28460576
  47. 47. Mangoni AA, Jackson SH. Age-related changes in pharmacokinetics and pharmacodynamics: basic principles and practical applications. Br J Clin Pharmacol. 2004;57(1):6–14. pmid:14678335
  48. 48. Nicolazzo JA, Mehta DC. Transport of drugs across the blood-brain barrier in Alzheimer’s disease. Ther Deliv. 2010;1(4):595–611. pmid:22833970
  49. 49. Shi S, Morike K, Klotz U. The clinical implications of ageing for rational drug therapy. Eur J Clin Pharmacol. 2008;64(2):183–99. pmid:18180915
  50. 50. Payne RA, Abel GA, Avery AJ, Mercer SW, Roland MO. Is polypharmacy always hazardous? A retrospective cohort analysis using linked electronic health records from primary and secondary care. Br J Clin Pharmacol. 2014;77(6):1073–82. pmid:24428591
  51. 51. Lai SW, Liao KF, Liao CC, Muo CH, Liu CS, Sung FC. Polypharmacy correlates with increased risk for hip fracture in the elderly: a population-based study. Medicine (Baltimore). 2010;89(5):295–9.
  52. 52. Richardson K, Ananou A, Lafortune L, Brayne C, Matthews FE. Variation over time in the association between polypharmacy and mortality in the older population. Drugs Aging. 2011;28(7):547–60. pmid:21721599
  53. 53. Richardson K, Bennett K, Kenny RA. Polypharmacy including falls risk-increasing medications and subsequent falls in community-dwelling middle-aged and older adults. Age Ageing. 2015;44(1):90–6. pmid:25313240
  54. 54. Kable A, Fullerton A, Fraser S, Palazzi K, Hullick C, Oldmeadow C, et al. Comparison of potentially inappropriate medications for people with dementia at admission and discharge during an unplanned admission to hospital: results from the SMS dementia study. Healthcare (Basel). 2019;7(1).pii:E8.
  55. 55. Molist-Brunet N, Sevilla-Sánchez D, Amblás-Novellas J, Codina-Jane C, Gomez-Batiste X, Mclntosh J, et al (2014) Optimizing drug therapy in patients with advanced dementia: A patient-centered approach. Eur Geriatr Med. 2014;5(1):66–71.
  56. 56. von Renteln-Kruse W, Neumann L, Klugmann B, Liebetrau A, Golgert S, Dapp U, et al. Geriatric patients with cognitive impairment: patient characteristics and treatment results on a specialized ward. Dtsch Arztebl Int. 2015;112(7):103–12. pmid:25780869
  57. 57. Wawruch M, Fialova D, Zikavska M, Wsolová L, Jezova D, Kuzelova M, et al. Factors influencing theuse of potentially inappropriate medication in older patients in Slovakia. J Clin Pharm Ther. 2008; 33(4):381–92. pmid:18613856
  58. 58. Redston MR, Hilmer SN, McLachlan AJ, Clough AJ, Gnjidic D. Prevalence of potentially inappropriate medication use in older inpatients with and without cognitive impairment: A systematic review. J Alzheimers Dis. 2018;61(4):1639–52. pmid:29278890
  59. 59. Gutierrez-Valencia M, Izquierdo M, Malafarina V, Alonso-Renedo J, Gonzalez-Glaria B, Larrayoz- Sola B, et al. Impact of hospitalization in an acute geriatirc unit on polypharmacy and potentially inappropriate prescriptions: A retrospective study. Geriatr Gerontol Int. 2017;17(12):2354–60. pmid:28422415
  60. 60. Sönnerstam E, Sjölander M, Lövheim H, Gustafsson M. Clinically relevant drug-drug interactions among elderly people with dementia. Eur J Clin Pharmacol. 2018;74(10):1351–60. pmid:29967921
  61. 61. Gray L, Wootton R. Comprehensive geriatric assessment ‘online’. Australas J Ageing 2008;27(4): 205–8. pmid:19032623
  62. 62. Gray LC, Bernabei R, Berg K, Finne-Soveri H, Fries BE, Hirdes JP, et al. Standardizing assessment of elderly people in acute care: the interRAI Acute Care instrument. J Am Geriatr Soc. 2008;56(3):536–41. pmid:18179498
  63. 63. Gray L, Ariño-Blasco S, Berg K, Bernabei R, Carpenter I, Finne-Soveri H et al. interRAI Acute Care (AC) Assessment Form and User’s Manual. Washington, DC: interRAI; 2010.
  64. 64. Travers C, Byrne GJ, Pachana NA, Klein K, Gray L. Validation of the interRAI cognitive performance scale against independent clinical diagnosis and the Mini-Mental State Examination in older hospitalized patients. J Nutr Health Aging. 2013;17(5):435–9. pmid:23636544
  65. 65. Gray LC, Berg K, Fries BE, Henrard JC, Hirdes JP, Steel K, et al. Sharing clinical information across care settings: the birth of an integrated assessment system. BMC Health Serv Res. 2009;9:71. pmid:19402891
  66. 66. Lakhan P, Jones M, Wilson A, Courtney M, Hirdes J, Gray LC. A prospective cohort study of geriatric syndromes among older medical patients admitted to acute care hospitals. J Am Geriatr Soc. 2011;59(11):2001–8. pmid:22092231
  67. 67. WHO Collaborating Centre for Drug Statistics Methodology. Guidelines for ATC classification and DDD assignment. Oslo. 2019 [Cited 2019 Nov 15]. Available from: http://www.whocc.no/filearchive/publications/2019_guidelines_web.pdf.
  68. 68. Pharmaceutical Care Network Europe Foundation. The PCNE Classification V 9.0—Classification for Drug related problems. 2019 [Cited 2019 Nov 15]. Available from: http://www.pcne.org/upload/files/_PCNE_classification_V9-0.pdf.
  69. 69. Gnjidic D, Hilmer SN, Blyth FM, Naganathan V, Waite L, Seibel MJ, et al. Polypharmacy cutoff and outcomes: five or more medicines were used to identify community-dwelling older men at risk of different adverse outcomes. J Clin Epidemiol. 2012;65(9):989–95. pmid:22742913
  70. 70. Beers MH. Explicit criteria for determining potentially inappropriate medication use by the elderly. An update. Arch Intern Med. 1997;157(14):1531–6. pmid:9236554
  71. 71. By the 2019 American Geriatrics Society Beers Criteria Update Expert Panel. American Geriatrics Society 2019 updated AGS Beers Criteria for potentially inappropriate medication use in older adults. J Am Geriatr Soc. 2019;67(4):674–94. pmid:30693946
  72. 72. Triplitt C. Drug interactions of medications commonly used in diabetes. Diabetes. 2006;19(4):202–11.
  73. 73. Micromedex® HealthCare Series (internet database) Version 2.0. Greenwood Village, Colorado: Thomson Healthcare Inc. 2013 [Cited 2019 Nov 5]. Available from: http://www.micromedexsolutions.com.
  74. 74. Bickel H, Hendlmeier I, Hessler JB, Junge MN, Leonhardt-Achilles S, Weber J, et al. The prevalence of dementia and cognitive impairment in hospitals. Dtsch Arztebl Int. 2018;115(44):733–40. pmid:30565543
  75. 75. Travers C, Byrne G, Pachana N, Klein K, Gray L. Prospective observational study of dementia and delirium in the acute hospital setting. Intern Med J. 2013;43(3):262–9. pmid:22998322
  76. 76. Toot S, Devine M, Akporobaro A, Orrell M. Causes of hospital admission for people With dementia: a systematic review and meta-analysis. J Am Med Dir Assoc. 2013;14(7):463–70. pmid:23510826
  77. 77. Andrieu S, Reynish E, Nourhashemi F, Shakespeare A, Moulias S, Ousset PJ, et al. Predictive factors of acute hospitalization in 134 patients with Alzheimer’s disease: a one year prospective study. Int J Geriatr Psychiatry. 2002;17(5):422–6. pmid:11994930
  78. 78. Bradshaw LE, Goldberg SE, Schneider JM, Harwood RH. Carers for older people with co-morbid cognitive impairment in general hospital: characteristics and psychological well-being. Int J Geriatr Psychiatry. 2013;28(7):681–90. pmid:22887452
  79. 79. Kurrle S, Brodaty H, Hogarth R. Physical comorbidities of dementia. 1st ed. Cambridge, UK: Cambridge University Press; 2012.
  80. 80. Draper B, Karmel R, Gibson D, Peut A, Anderson P. The hospital dementia services project: age differences in hospital stays for older people with and without dementia. Int Psychogeriatr. 2011;23(10):1649–58. pmid:21902861
  81. 81. Australian Institute of Health and Welfare (2019). Hospital care for people with dementia 2016–17. Cat. no. AGE 94. Canberra: AIHW. 2019 [Cited 2019 Nov 15]. Available from: http://www.aihw.gov.au/getmedia/aihw-age-94.pdf.aspx
  82. 82. Carter MW, Porell FW. Vulnerable populations at risk of potentially avoidable hospitalizations: the case of nursing home residents with Alzheimer’s disease. Am J Alzheimers Dis Other Demen. 2005; 20(6):349–58. pmid:16396440
  83. 83. Beveridge LA, Davey PG, Philips G, McMurdo MET. Optimal management of urinary tract infections in older people. Clin Interv Aging. 2011;6:173–80. pmid:21753872
  84. 84. Malone DC, McLaughlin TP, Wahl PM, Leibman C, Arrighi HM, Cziraky MJ, et al. Burden of Alzheimer’s disease and association with negative health outcomes. Am J Manag Care. 2009;15(8):481–8. pmid:19670951
  85. 85. Chang JT, Morton SC, Rubenstein LZ, Mojica WA, Maglione M, Suttorp MJ, et al. Interventions for the prevention of falls in older adults: systematic review and meta-analysis of randomised clinical trials. BMJ. 2004;328(7441):680. pmid:15031239
  86. 86. Department of Health and Ageing 2003a. Unnecesssary and avoidable hospital admissions for older people. Canberra: Commonwealth of Australia. 2006 [Cited 2019 Nov 15]. Available from: http://www.aihw.gov.au/getmedia/14347_20130321.pdf.aspx
  87. 87. Sharma S, Mueller C, Stewart R, Veronese N, Vancampfort D, Koyanagi A, et al. Predictors of falls and fractures leading to hospitalization in people with dementia: a representative cohort study. J Am Med Dir Assoc. 2018;19(7):607–12. pmid:29752159
  88. 88. Scrutton J, Brancati CU. Dementia and comorbidities. Ensuring parity of care. London, UK: ILC; 2016.
  89. 89. Bail K, Berry H, Grealish L, Draper B, Karmel R, Gibson D, et al. Potentially preventable complications of urinary tract infections, pressure areas, pneumonia, and delirium in hospitalised dementia patients: retrospective cohort study. BMJ Open. 2013;3:e002770. pmid:23794540
  90. 90. Sakakibara R, Panicker J, Fowler CJ, Tateno F, Kishi M, Tsuyuzaki Y, et al. Vascular incontinence: incontinence in the elderly due to ischemic white matter changes. Neurol Int. 2012;4(2):e13. pmid:23139851
  91. 91. Thomazi R, Silveira LVA, Boas PJFV, Jacinto AF. Frequency of dementia among elderly admitted to a Geriatrics Inpatients Sector of a Brazilian public hospital. Dement Neuropsychol. 2018;12(1):35–9. pmid:29682231
  92. 92. Mecocci P, von Strauss E, Cherubini A, Ercolani S, Mariani E, Senin U, et al. Cognitive impairment is the major risk factor for development of geriatric syndromes during hospitalization: results from the GIFA study. Dement Geriatr Cogn Disord. 2005;20(4):262‐9. pmid:16103670
  93. 93. Kurrle S, Brodaty H, Hogarth R, Gupta A. The physical comorbidities of dementia. Health Northern Sydney Local Health District. 2018 [Cited 2019 Nov 15]. Available from: www.nslhd.health.nsw.gov.au.
  94. 94. Sinnige J, Braspenning J, Schellevis F, Stirbu-Wagner I, Westert G, Korevaar J. The prevalence of disease clusters in older adults with multiple chronic diseases–a systematic literature review. PLoS One. 2013;8(11):e79641. pmid:24244534
  95. 95. Nagai M, Hoshide S, Kario K. Hypertension and dementia. Am J Hypertens. 2010;23(2):116–24. pmid:19927134
  96. 96. Justin BN, Turek M, Hakim AM. Heart disease as a risk factor for dementia. Clin Epidemiol. 2013; 5:135–45. pmid:23658499
  97. 97. Tate JA, Snitz BE, Alvarez KA, Nahin RL, Weissfeld LA, Lopez O, et al. Infection hospitalization increases risk of dementia in the elderly. Crit Care Med, 2014;42(5):1037–46. pmid:24368344
  98. 98. Lai SW, Lin CH, Liao KF, Su LT, Sung FC, Lin CC. Association between polypharmacy and dementia in older people: A population-based case-control study in Taiwan. Geriatr Gerontol Int. 2012;12(3):491–8. pmid:22233227
  99. 99. Liu E, Dyer SM, O’Donnell LK, Milte R, Bradley C, Harrison SL, et al. Association of cardiovascular system medications with cognitive function and dementia in older adults living in nursing homes in Australia. J Geriatr cardiol. 2017;14(6):407–15. pmid:29056948
  100. 100. Briggs R, Dyer A, Nabeel S, Collins R, Doherty J, Coughlan T, et al. Dementia in the acute hospital: the prevalence and clinical outcomes of acutely unwell patients with dementia. QJM: Int J Med. 2017;110(1):33–7.
  101. 101. Oesterhus R, Aarsland D, Soennesyn H, Rongve A, Selbaek G, Kjosavik SR. Potentially inappropriate medications and drug-drug interactions in home-dwelling people with mild dementia. Int J Getriatr Psychiatry. 2017;32(2):183–92.
  102. 102. Ferreira F, Diniz JSV, Medeiros-Souza P, Freitas MPD, Camargos EF, Kusano LTE, et al. Potential high-risk drug-drug interactions among elderly outpatients with dementia: a cross-sectional study. Geriatr Gerontol Aging. 2015;9(1):21–5.
  103. 103. Wastesson JW, Morin L, Tan ECK, Johnell K. An updated on the clinical consequences of polypharmacy in older adults: a narrative review. Expert opin drug saf. 2018;17(12):1185–96. pmid:30540223
  104. 104. Park HY, Park JW, Song HJ, Sohn HS, Kwon JW. The association between polypharmacy and dementia: A nested case-control study based on a 12-year longitudinal cohort database in South Korea. PLoS One. 2017;12(1): e0169463. pmid:28056068
  105. 105. Johnell K. Inappropriate drug use in people with cognitive mpairment and dementia: a systematic review. Curr Clin Pharmacol. 2015;10(3):178–84. pmid:26054404
  106. 106. Sönnerstam E, Sjölander M, Gustafsson M. An evaluation of the prevalence of potentially inappropriate medications in older people with cognitive impairment living in Northern Sweden using the EU(7)-PIM list. Eur J Clin Pharmacol. 2017;73(6):735–42. pmid:28246889
  107. 107. Gallagher P, Ryan C, Byrne S, Kennedy J, O'Mahony D. STOPP (screening tool of older person’s prescriptions) and START (screening tool to alert doctors to right treatment). Consensus validation. Int J Clin Pharmacol Ther. 2008;46(2):72–83. pmid:18218287
  108. 108. Holt S, Schmiedl S, Thürmann PA. Potentially inappropriate medications in the elderly: the PRISCUS list. Dtsch Arztebl Int. 2010;107(31–32):543–51. pmid:20827352
  109. 109. Laroche ML, Charmes JP, Merle L. Potentially inappropriate medications in the elderly: a French consensus panel list. Eur J Clin Pharmacol. 2007;63(8):725–31. pmid:17554532
  110. 110. Gustafsson M, Karlsson S, Lovheim H. Inappropriate long-term use of antipsychotic drugs is common among people with dementia living in specialized care units. BMC Pharmacol Toxicol. 2013;14:10. pmid:23391323
  111. 111. Park H, Satoh H, Miki A, Urushihara H, Sawada Y. Medications associated with falls in older people: systematic review of publications from a recent 5-year period. Eur J Clin Pharmacol. 2015;71(12):1429–40. pmid:26407688
  112. 112. Bell JS, Mezrani C, Blacker N, LeBlanc T, Frank O, Alderman CP, et al. Anticholinergic and sedative medicines-prescribing considerations for people with dementia. Aust Fam Physician. 2012;41(1–2):45–9. pmid:22276284
  113. 113. Guthrie B, Clark SA, McCowan C. The burden of psychotropic drug prescribing in people with dementia: a population database study. Age Ageing. 2010;39(5):637–42. pmid:20625185
  114. 114. Eshetie TC, Nguyen TA, Gillam MH, Kalisch Ellett LM. Potentially inappropriate prescribing in people with dementia: an Australian population-based study. Int J Geriatr Psychiatry. 2019;34(10):1498–1505. pmid:31173395
  115. 115. Markota M, Rummans TA, Bostwick JM, Lapid MI. Benzodiazepine use in older adults: dangers, management, and alternative therapies. Mayo Clin Proc. 2016;91(11):1632‐39. pmid:27814838
  116. 116. Pariente A, de Gage SB, Moore N, Bégaud B. The benzodiazepine-dementia disorders link: Current state of knowledge. CNS Drugs. 2016;30(1):1–7. pmid:26715389
  117. 117. Douglas IJ, Smeeth L. Exposure to antipsychotics and risk of stroke: self-controlled case series study. BMJ. 2008;337:a1227. pmid:18755769
  118. 118. Liu ME, Tsai SJ, Chang WC, Hsu CH, Lu T, Hung KS, et al. Population-based 5-year follow-up study in Taiwan of dementia and risk of stroke. PLoS One. 2013;8(4):e61771. pmid:23626726
  119. 119. Pariente A, Fourrier-Reglat A, Ducruet T, Farrington P, Beland SG, Dartigues JF, et al. Antipsychotic use and myocardial infarction in older patients with treated dementia. Arch Intern Med. 2012;172(8):648–53. pmid:22450214
  120. 120. Ralph SJ, Espinet AJ. Increased all-cause mortality by antipsychotic drugs: updated review and meta-analysis in dementia and general mental health care. J Alzheimers Dis Rep. 2018;2(1):1–26. pmid:30480245
  121. 121. Yu NW, Chen PJ, Tsai HJ, Huang CW, Chiu YW, Tsay WI. Association of benzodiazepine and Z- drug use with the risk of hospitalisation for fall-related injuries among older people: a nationwide nested case-control study in Taiwan. BMC Geriatr. 2017;17(1):140. pmid:28693443
  122. 122. Alzheimer’s Society. Optimising treatment and care for people with behavioural and psychological symptoms of dementia. 2011 [Cited 2019 Nov 15]. Available from: http://www.alzheimers.org.uk/site/scripts/download_info
  123. 123. Azermai M, Petrovic M, Elseviers MM, Bourgeois J, Van Bortel LM, Vander Stichele RH. Systematic appraisal of dementia guidelines for the management of behavioural and psychological symptoms. Ageing Res Rev. 2012;11(1):78–86. pmid:21856452
  124. 124. Guthrie B, McCowan C, Davey P, Simpson CR, Dreischulte T, Barnett K. High risk prescribing in primary care patients particularly vulnerable to adverse drug events: cross sectional population database analysis in Scottish general practice. BMJ. 2011;342:d3514. pmid:21693525
  125. 125. Cross AJ, George J, Woodward MC, Ames D, Brodaty H, Ilomaki J, et al. Potentially inappropriate medications and anticholinergic burden in older people attending memory clinics in Australia. Drugs Aging. 2016;33(1):37–44. pmid:26645294
  126. 126. Montastruc F, Gardette V, Cantet C, Piau A, Lapeyre-Mestre M, Vellas B, et al. Potentially inappropriate medication use among patients with Alzheimer disease in the REAL.FR cohort: be aware of atropinic and benzodiazepine drugs!. Eur J Clin Pharmacol. 2013;69(8):1589–97. pmid:23588564
  127. 127. Koyama A, Steinman M, Ensrud K, Hillier TA, Yaffe K. Ten-year trajectory of potentially inappropriate medications in very old women: importance of cognitive status. J Am Geriatr Soc. 2013;61(2):258–63. pmid:23320787
  128. 128. Bogetti-Salazar M, González-González C, Juárez-Cedillo T, Sánchez-Garcia S, Rosas-Carrasco O. Severe potential drug-drug interactions in older adults with dementia and associated factors. Clinics (Sao Paulo). 2016;71(1):17–21.
  129. 129. Gustafsson M, Sjölander M, Pfister B, Schneede J, Lövheim H. Effects of Pharmacists’ interventions on inappropriate drug use and drug-related readmissions in people with dementia-a secondary analysis of a randomized controlled trial. Pharmacy (Basel). 2018;6(1).pii:E7.
  130. 130. Pasqualetti G, Tognini S, Calsolaro V, Polini A, Monzani F. Potential drug-drug interactions in Alzheimer patients with behavioral symptoms. Clin Interv Aging. 2015;10:1457–66. pmid:26392756
  131. 131. Seritan AL. Prevent drug-drug interactions with cholinesterase inhibitors. Curr Psychiatry. 2008;7(2):57–66.
  132. 132. January CT, Wann LS, Calkins H, Chen LY, Cigarroa JE, Cleveland JC Jr, et al. AHA/ACC/HRS focused update of the 2014 AHA/ACC/HRS guideline for the management of patients with atrial fibrillation: a report of the American College of Cardiology/American Heart Association Task Force on Clinical Practice Guidelines and the Heart Rhythm Society. Curculation. 2019;140:e125–e151.