Introduction
Delirium is an acute neuropsychiatric syndrome characterized by confusion, attentional deficits, and a fluctuating cognitive impairment.1 It is associated with substantial morbidity, functional decline, long-term cognitive deterioration, higher healthcare costs and mortality, contributing up to $152 billion annually in the United States.1–3 Delirium incidence varies widely across healthcare settings, affecting up to 20% of all hospitalized patients and up to 80% of those in intensive care or post-surgical environments.4 Older patients are particularly vulnerable, with the risk of delirium increasing by approximately 2% for every additional year beyond the age of 65.5 As the population ages and longevity increases,6 the number of vulnerable individuals at risk for delirium is expected to rise, emphasizing the need for enhanced understanding of risk factors and effective prevention strategies.
Delirium is a multifactorial condition resulting from a combination of predisposing and precipitating factors including medications.7 Evaluating medications is critical due to their ubiquitous use before, during and after hospitalization and the modifiability of their use. Medications are suggested to be the sole precipitant for 12-39% of cases of delirium.8 Medications with anticholinergic potential, in particular, have been identified as high-risk due to their antagonistic effects on acetylcholine, a neurotransmitter crucial for cognitive functions often disrupted in delirium such as attention, sleep, and memory.9 The widespread prescription of anticholinergic drugs for a plethora of conditions including mental, neurological, respiratory, ophthalmic, and urological disorders,10 coupled with their known negative cognitive impact11–13 underscores the need for a critical evaluation of their use in vulnerable populations.
Existing delirium research has predominantly focused on anticholinergic medication use within hospital settings, neglecting the anticholinergic burden that may carry from regularly prescribed medicines.14 To our knowledge, no review has specifically examined how community-based anticholinergic burden relates to delirium outcomes. By systematically evaluating existing literature in these underexplored settings, we aim to clarify the strength and consistency of this association. The main research question is whether anticholinergic burden of regularly used, community-based medications increases delirium occurrence severity, or duration. Such insights have the potential to refine clinical decision-making, guide prescribing practices, and ultimately inform strategies to prevent or mitigate delirium in vulnerable populations.
Methods
A protocol for this review was prospectively registered with PROSPERO (CRD42023314206). This review is reported in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses Guidelines (PRISMA) .15The review was performed using Covidence®,16 an online tool designed to streamline the systematic review process by facilitating abstract screening, full-text screening, study selection, quality assessment, and data extraction.
Data sources and search Strategy
A comprehensive literature search was conducted across multiple electronic databases including PubMED, EMBASE, PsycINFO, CINAHL, and Web of Science from their inception to November 2023. The search strategy was modified from similar searches created by Egberts et al17 with additional terms added. Terms related to delirium (e.g "delirium", “acute confusion”, “cognitive dysfunction”) were combined with terms related to anticholinergic drugs (e.g “anticholinergic”). The search terms and strategies for all databases are shown in Supplement B. Reference lists of identified articles and relevant reviews were manually searched to ensure comprehensive coverage.
Eligibility Criteria
Studies included if they (i) assessed anticholinergic burden of medicines taken prior to hospital or long-term care facility admission; (ii) reported any of incidence, prevalence, duration of delirium or delirium severity as an outcome; and (iii) included adult participants (≥18 years). Studies were excluded if they (i) focused exclusively on in-hospital anticholinergic exposure; (ii) were case reports, case series, abstracts, study protocols editorials, or review articles; (iii) lacked primary data or clear delirium outcomes, (iv) studies that used a composite measure of sedative and anticholinergic burden, (v) studies that used a consolidated dementia-delirium outcome, (vi) studies with unclear exposure assessment period, (vii) studies not in English.
Study Screening and Selection
All references identified by search queries were added to Covidence®16 and duplicates were removed. One author (H.K) screened titles and abstracts for potentially eligible studies. Two authors (H.K and N.K) independently assessed full-text articles against the eligibility criteria. Disagreements at any stage were resolved through consensus.
Data Extraction
Data was extracted independently by two reviewers using a standardized extraction form. Extracted information included study characteristics (authors, year of publication, country), study design, sample size, participant demographics, method for assessing anticholinergic burden, medication data source, delirium assessment tools, and main findings of each study with regards to the relationship between medications and the outcomes of interest.
Quality assessment
Two reviewers independently assessed the methodological quality of included studies. Cohort and case-control studies were assessed using the Newcastle-Ottawa Scale (NOS).18 The Modified NOS scale was used for cross-sectional studies.19 Each study was evaluated for the adequacy of sample selection, comparability of groups and assessment of outcomes. The score ranged from 0 (lowest degree) to 9 (highest degree). Studies ≤ 4 stars, 5-6 stars, and ≥ 7 stars were defined as low, medium, and high quality respectively. In the event of disagreement on critical appraisal score, agreement was met through discussion between evaluators.
Data Analysis
The data extraction tables were reviewed to determine the most appropriate analysis technique to answer the research question. There was considerable heterogeneity in relation to population characteristics, methods, and data sources to obtain anticholinergic exposure, duration of exposure, follow-up period, outcome measurement and reporting of data. Therefore, a meta-analysis was not feasible. Accordingly, a qualitative narrative review of the literature was performed to assess the association between anticholinergic burden and delirium outcomes.
Results
Study selection
The initial literature search resulted in 4311 with 2437 remaining after duplicate removal. Screening excluded 2324 records, leaving 110 full-text articles for eligibility assessment. Of these, 24 studies met the inclusion criteria and were included (Figure 1).
Characteristics of included studies
The 24 studies included were published between 2004 and 2023. They comprised 8 prospective cohorts,20–27 6 retrospective cohorts,28–33 5 cross-sectional studies,34–38 3 case-controls,39–41 1 nested case-control,42 and 1 post-hoc analysis of a randomized control trial.43 Studies were performed in 15 different countries with two being multi-country. In total, 673,938 participants were included (mean age range of 63-86.3, 45.3% male).
Seventeen of the included studies were conducted in hospital settings,20–23,25–27,31–34,36,38–41,43 with 6 specifically examining surgical patients.20–23,32,43 The remaining hospital studies focused on a range of populations including patients admitted to geriatric or medical wards,34,36,38 internal medicine wards,26 and intensive care units (ICU),27 as well as patients admitted for advanced cancer treatment,31 stroke,39 emergency admissions,25,33,41 and rehabilitation.40 Two studies were in a nursing homes24,35 and one at a hospice/home,37 and four were population-based studies using health insurance records28–30,42 (Table 1). One study exclusively included patients with dementia,28 while four excluded patients with dementia.20–22,32
Details on the methodological quality of the studies included according to the NOS are provided in section B of supplement. Quality scores ranged from 3 to 9 stars (average 7.5 stars). The findings indicate that the evidence-base was largely moderate to high in methodological quality.
Assessment of Delirium
Delirium was using the Diagnostic and Statistical Manual of Mental Disorders criteria (DSM-IV or V, 6 studies),22,23,34,39,41,43 the Confusion Assessment Method in its various forms (CAM, 12 studies),20–27,32,33,41,43 diagnosis codes for delirium according to the international classification of diseases 9th and 10th edition (ICD-9 or 10, 4 studies),28–30,42 4AT test (2 studies),36,37 medical record documentation (3 studies),31,38,40 and the Nu-DESC (1 study).22 One study used recorded pre-specified symptoms indicating acute mental status changes from a cross-sectional study.35 Delirium incidence ranged between 66 of 118750 patients (0.05%)30 to 36 of 67 (53.7%)21 and prevalence ranged between 124 of 461 (26.9%)37 and 125 of 251 (49.8%)41 among included studies (Table 1).
Delirium severity was measured with the Delirium Rating Scale (DRS) in two studies,39,43 however only one43 assessed the possible association between anticholinergic burden and severity. Delirium duration similarly was assessed by only one study.43 In addition, one study further explored the impact of anticholinergic burden on subsyndromal delirium.33
Anticholinergic drug burden measurement
Among the 24 included studies, 22 used anticholinergic scales, with the remainder relying on anticholinergics listed in prior literature21 or pharmacological categories based on national drug formularies.39 The most frequently utilized anticholinergic scales were the Anticholinergic Cognitive Burden scale (ACB, 12 studies),20,22,26,31,33–37,40–42 the Anticholinergic Drug Scale (ADS, 8 studies),20,22,27,32,38,41–43 and the Anticholinergic Risk Scale (ARS, 7 studies).22–24,29,34,35,42 Ah et al. (2019) modified the ACB scale28 and Hwang et al. (2019) modified the ARS scale30 to account for anticholinergics available in their study countries. Less common scales included the list of Chew34 and Coupland’s Anticholinergic Burden Score (ABS).23,46 One study25 combined the ACB and ADS scales to account for the greatest number of possible anticholinergics. Fourteen studies used one scale24,26–33,36–38,40,43 while nine used multiple.20–23,25,34,35,41,42 Studies implemented scales by summing potency points (17 studies), or they were used to identify anticholinergic drugs and subsequently classify patients as users versus non-users (4 studies) or the number of anticholinergics taken by patients (7 studies) (Table 2).
Exposure assessment was typically based on a single time point (21 studies), most commonly at hospital admission (12 studies) (Table 2). Others specified distinct time windows for exposure assessment: Huang et al. (2012)29 used an 1-year exposure period, Landi et al. (2014)24 used a 7 day time-frame, Oudewortel et al. (2021)35 considered 3 days, and Moorey et al. (2016)41 48 hours. Duprey et al. (2022)20 considered patients taking anticholinergics if they reported them in an interview 2 weeks before planned hospital admission. Three studies did not specify the time point of anticholinergic assessment22,25,39 and sufficed to indicate medications taken before admission,25,39 or long-term medications taken regularly.22 Among studies using a single time point assessment, only one incorporated doses to quantify anticholinergic burden.25 Longitudinal exposure measures incorporating dosage, duration, and anticholinergic potency was performed by only 3 studies,1–3 all of which calculated an average daily burden score (Equation in Supplement.C). Ah et al. (2019)28 calculated an average daily ACB score over 3 months, Hwang et al. (2019)30 calculated an average ARS score over 3 months, and Hwang et al. (2021)42 calculated average KABS, ARS, ACB, and ADS over 30 days.
Anticholinergics and Delirium Outcomes
Hospitalized non-surgical populations
In non-surgical hospitalized patients, four studies reported a positive association between higher anticholinergic burden measured at or before admission and incident delirium.26,27,31,40 Three of these studies used the ACB scale26,31,40 and one used the ADS27 to identify medicines. The populations included patients in inpatient rehabilitation,40 advanced cancer patients admitted to a medical ward,31 general internal medicine patients,26 and patients admitted to the ICU27 (Table 3).
Prevalent delirium was positively associated with anticholinergic burden measured at a single time point on or before hospitalization in three34,38,39 of seven25,33,34,36,38,39,41 studies, examining acutely ill patients admitted to geriatric wards,34,38 and stroke patients.39 These three studies utilized different methods to quantify exposure: one used the ARS scale,34 another categorized patient based on ADS-defined users versus non-users, and the third employed pharmacologic categories rather than standardized scales (Table 3).
Surgical populations
In surgical populations, two23,32 of five20–23,32 studies demonstrated anticholinergic burden measured at or before admission was positively associated with incident delirium. Herrmann et al. (2022)23 and Mueller et al. (2020)32 both reported a similar elevated adjusted-risk per anticholinergic scale point (54% and 49% respectively), although they were used different scales (ARS and ADS respectively). The remaining three surgical studies did not detect a similar association20–22 (Table 3).
Nursing Home and Long-term care residents
In nursing home settings, Landi et al (2014)24 reported a 16% higher risk of incident delirium for each additional ARS point measured at a single timepoint. Similarly Oudewortel et al. (2021),35 observed a 17% higher risk of prevalent delirium for each additional ARS point and a 14% higher risk for each ACB point, though this association was restricted to patients with dementia. In hospice or home care settings, one study identified a relationship between anticholinergic burden (ACB scale) and prevalent delirium37 (Table 3).
Population-level studies
There were four population-based studies incorporating national health insurance claims that consistently supported an association between anticholinergic burden and delirium risk.28–30,42(p2) Of these, three studies used an average daily anticholinergic score to characterize burden. Longer exposure durations and measures that accounted for dose and potency typically yielded stronger associations. Hwang et al. (2021)42 reported increased odds of delirium with higher categorized ACB, ARS, ADS, and KABS scores with dose-response relationships evident across scales. Similarly, Ah et al. (2019)28 found that an average daily ACB score >3 increased the hazard of developing delirium (HR 1.52) (Table 3).
Delirium Severity and Duration
Only one study43 specifically examined the relationship between anticholinergic drug burden and delirium severity or duration in surgical patients population, reporting no significant results.
Discussion
This systematic review examined the relationship between pre-admission anticholinergic drug burden and delirium outcomes. Across 24 included studies, 11 identified a positive association between higher anticholinergic burden and increased risk of incident delirium, while 4 reported a similar association with prevalent delirium. However, substantial variability in measurement methods, populations, and study designs complicates drawing definitive conclusions.
A central challenge identified in this review was the absence of a standardized method to quantify anticholinergic exposure. Among the included studies, there were 7 unique scales employed (ACB, ADS, ARS, List of Chew, ABS, Duran and La roche, KABS), and 3 modified scales (mACB, mARS, ACB-ADS). These tools differ in their derivation, including medications, and potency scoring ratings. Nine studies20–23,25,34,35,41,42 used multiple scales reflecting the lack of a universally optimal tool. Measurement approaches varied even within the same scale: some studies assessed the number of anticholinergic medications20 or categorized patients as users versus non-users,29,38,39. Others summed potency scores, and either considered anticholinergic burden a continuous variable22–24,32 or categorical thresholds.27,33,36,37,40,42,44 Such methodological heterogeneity complicates cross-study comparisons and reduces the clinical utility of findings.
The most utilized tools were the ACB, ARS, and ADS scales, in line with prior research by Salahudeen et al. (2015).13 Among these, the ARS scale showed the most consistent association with delirium, showing a positive relationship in 7 of 8 studies in line with a prior review.17 In contrast, the ACB and ADS scales were less consistent, showing associations in 5 of 12 and 4 of 8 studies, respectively. The ARS’s inclusion of both central and peripheral anticholinergic effects may explain its higher predictive value. Higher anticholinergic burden scores (e.g., ARS≥3) were consistently associated with delirium whereas lower scores had inconsistent effects.
Most of the studies in this review identified anticholinergic use at a single time point, commonly at hospital admission. Three studies29,42,45 however, measured anticholinergic use over an extended period, calculating an average ACB or ARS score by incorporating prescribed dosages over predefined durations. These studies consistently found a significant positive association between prolonged anticholinergic use and delirium risk. Specifically, two studies30,45 examined 3-month exposure periods, and one42 used a 30-day period. This suggests that long-term anticholinergic burden may offer greater predictive value for delirium risk. Notably, no study has used cumulative total standardized doses to assess delirium, a method that is not solely dependent on scale scores44,49 and could provide a more nuanced understanding of dose-response effects independent of specific scale scores. Research in related fields, such as dementia, has demonstrated that cumulative medication exposure over several years can significantly increase dementia risk.46,49 Further studies are needed to see if a similar relationship exists for delirium.
A notable gap in the current literature is the limited focus on core outcomes50 of delirium beyond incidence or prevalence. Only one study in this review examined the relationship between anticholinergic burden and delirium severity and it found no significant association43 between the ADS and delirium severity as measured by the (DRS-R-98). In an earlier study by Han et al. (2001)51 examining in-hospital anticholinergic burden among older inpatients, anticholinergic exposure was significantly associated with delirium severity, as measured with the Delirium Index. Given that delirium severity and duration may affect mortality,52 cognitive and functional decline,53 and being discharged home,54 future research should incorporate standardized severity measures, and evaluate whether anticholinergics influence the depth or persistence of delirium symptoms.
There are several limitations to this study. First, the studies included in this review used retrospective cohort designs or cross-sectional analyses, which limit the ability to infer causality. Although many of the studies controlled for potential confounders, such as age, comorbidities, and polypharmacy, there remains the possibility of residual confounding. For example, patients taking anticholinergic medications may have underlying conditions (e.g., dementia, urinary incontinence) that independently increase their risk for delirium. While the studies tried to adjust for such factors, the observational nature of most studies precludes definitive conclusions about the causative role of anticholinergic burden in the development of delirium. Finally, the potential for publication bias also exists, as studies with null findings may be less likely to be published and included in the review. Other than the variability in measurement of anticholinergic burden, heterogeneity in the study designs, populations, and methodologies poses a significant challenge for drawing definitive conclusions. Studies varied in terms of the populations studied (e.g., general hospital populations, patients undergoing surgery, cancer patients, and dementia patients) and settings (hospital, nursing home, hospice). Furthermore, differences in the tools, employed to assess delirium (e.g., CAM, DSM criteria, ICD codes) may contribute to the inconsistent findings across studies. Lastly, delirium itself is a complex syndrome with the potential to include multiple neurobiological mechanisms.9 While a disruption of cholinergic function can be sufficient to trigger delirium in some, this work does not clarify whether anticholinergic medications are sufficient to result in delirium or serve to increase vulnerability for a different mechanism to result in delirium.
This review has several strengths, including a comprehensive search strategy across multiple databases and the inclusion of a wide range of study designs and populations. By focusing specifically on outpatient and nursing home anticholinergic exposure, this review addresses a gap in the literature, as most prior studies have concentrated on anticholinergic use during hospital stays or have not clearly described time of anticholinergic exposure measurement. For example, Vondeling et al. (2020)27 in ICU patients reported a significantly higher risk of delirium in patients with outpatient prehospital ADS scores ≥2, whereas in a previous study of a similar population Wolters et al. (2015)55 the ADS scale of inpatient medicines was not associated with delirium at any level.
Conclusion
In conclusion, while this review supports an association between elevated anticholinergic burden and delirium, variability in measurement methods, limited longitudinal data, and a focus predominantly on incidence and prevalence rather than severity or duration restricts the generalizability and clinical applicability of the findings. Addressing these gaps through standardized methodologies, comprehensive exposure assessments, and prospective studies will be critical to understanding the true impact of anticholinergic burden on delirium and informing evidence-based interventions.