“…Our finding that anticholinergic drug exposure measured with the ARS is associated with delirium, is in agreement with the results of previous studies performed in critically ill patients (Wolters et al. ), palliative care patients (Zimmerman et al. ), patients with Parkinson's disease (Crispo et al.…”
Section: Discussionsupporting
confidence: 93%
“…Our finding that anticholinergic drug exposure measured with the ARS is associated with delirium, is in agreement with the results of previous studies performed in critically ill patients (Wolters et al 2015), palliative care patients (Zimmerman et al 2014), patients with Parkinson's disease (Crispo et al 2016) and older nursing home residents (Landi et al 2014). Also, previous studies found no association between anticholinergic drug exposure, measured with the ACB or the Anticholinergic Drug Scale, and delirium in older hospitalized patients (Moorey et al 2016;Campbell et al 2011;Wolters et al 2015). These findings strengthen the observation that results may differ depending on which scale is used when assessing anticholinergic drug exposure.…”
Section: Discussionsupporting
confidence: 93%
“…; Wolters et al. ). These findings strengthen the observation that results may differ depending on which scale is used when assessing anticholinergic drug exposure.…”
Several studies investigated the possible association between anticholinergic drugs and diverse clinical outcomes in older persons, but the results are inconsistent. The aim of this study was to investigate whether anticholinergic drug exposure is associated with delirium on admission, length of hospital stay, postdischarge institutionalization and in‐hospital mortality in acutely ill hospitalized older patients. In this observational chart review study, we included acutely ill patients aged 65 and older who were admitted to the geriatric ward of the Erasmus University Medical Center, Rotterdam, The Netherlands, between 2012 and 2015 (n = 905). Anticholinergic drug exposure on admission was defined as the use of anticholinergic drugs, total number of anticholinergic drugs and anticholinergic drug burden score (ADB), quantified with the Anticholinergic Risk Scale (ARS), the Anticholinergic Cognitive Burden scale (ACB) and the list of Chew et al. (Chew). Logistic regression analyses were performed to investigate possible associations between anticholinergic drug exposure and the aforementioned outcomes. Analyses were adjusted for age, sex, comorbidities, non‐anticholinergic drugs and delirium, where appropriate. Moderate and high ADB measured with the ARS were associated with delirium on admission with odds ratios (OR) of 1.70 (95% confidence interval (CI) = 1.16–2.49) and 1.83 (95% CI = 1.06–3.15), respectively. High ADB measured with the ARS was also associated with postdischarge institutionalization (OR = 2.43, 95% CI = 1.24–4.75). No associations were found using the ACB and Chew. Future studies are warranted to investigate the clinical usefulness of the ARS in reducing complications in older persons.
“…Our finding that anticholinergic drug exposure measured with the ARS is associated with delirium, is in agreement with the results of previous studies performed in critically ill patients (Wolters et al. ), palliative care patients (Zimmerman et al. ), patients with Parkinson's disease (Crispo et al.…”
Section: Discussionsupporting
confidence: 93%
“…Our finding that anticholinergic drug exposure measured with the ARS is associated with delirium, is in agreement with the results of previous studies performed in critically ill patients (Wolters et al 2015), palliative care patients (Zimmerman et al 2014), patients with Parkinson's disease (Crispo et al 2016) and older nursing home residents (Landi et al 2014). Also, previous studies found no association between anticholinergic drug exposure, measured with the ACB or the Anticholinergic Drug Scale, and delirium in older hospitalized patients (Moorey et al 2016;Campbell et al 2011;Wolters et al 2015). These findings strengthen the observation that results may differ depending on which scale is used when assessing anticholinergic drug exposure.…”
Section: Discussionsupporting
confidence: 93%
“…; Wolters et al. ). These findings strengthen the observation that results may differ depending on which scale is used when assessing anticholinergic drug exposure.…”
Several studies investigated the possible association between anticholinergic drugs and diverse clinical outcomes in older persons, but the results are inconsistent. The aim of this study was to investigate whether anticholinergic drug exposure is associated with delirium on admission, length of hospital stay, postdischarge institutionalization and in‐hospital mortality in acutely ill hospitalized older patients. In this observational chart review study, we included acutely ill patients aged 65 and older who were admitted to the geriatric ward of the Erasmus University Medical Center, Rotterdam, The Netherlands, between 2012 and 2015 (n = 905). Anticholinergic drug exposure on admission was defined as the use of anticholinergic drugs, total number of anticholinergic drugs and anticholinergic drug burden score (ADB), quantified with the Anticholinergic Risk Scale (ARS), the Anticholinergic Cognitive Burden scale (ACB) and the list of Chew et al. (Chew). Logistic regression analyses were performed to investigate possible associations between anticholinergic drug exposure and the aforementioned outcomes. Analyses were adjusted for age, sex, comorbidities, non‐anticholinergic drugs and delirium, where appropriate. Moderate and high ADB measured with the ARS were associated with delirium on admission with odds ratios (OR) of 1.70 (95% confidence interval (CI) = 1.16–2.49) and 1.83 (95% CI = 1.06–3.15), respectively. High ADB measured with the ARS was also associated with postdischarge institutionalization (OR = 2.43, 95% CI = 1.24–4.75). No associations were found using the ACB and Chew. Future studies are warranted to investigate the clinical usefulness of the ARS in reducing complications in older persons.
“…[1][2][3][4]26,27 We found that not all sepsis/septic shock patients could be screened during their initial sepsis course (89%, 95% confidence interval [CI]: 80--95%), and on only 53% (95% CI: 48-59%) of all patient-days in the cohort was CAPD screening definitely possible. The anticholinergic medication burden in our sepsis/septic shock PICU population is higher than has been reported in critically ill adults, 28 and maximum ADS was associated with higher mortality in this cohort. We also saw a relationship between ADS and highest severity of illness, as measured by PRISM-III score and VIS, which likely modulates this relation-ship.…”
In sepsis, anticholinergic dysregulation may result in encephalopathy or delirium during severe illness, either as a result of central inflammation or because of exposure to medications with anticholinergic activity. In this retrospective study, we determined the magnitude of anticholinergic drug exposure in 75 children with severe sepsis. We found that exposure over the first 5 days was high—median (interquartile range) daily anticholinergic drug scale score 4 (2–5)—and associated with higher vasoactive scores and death. We conclude that anticholinergic drug exposure is significant in severe sepsis, which means it may be a modifiable factor that should be studied further.
“…The list of medications with anticholinergic activity is long, a lack of consensus regarding which anticholinergic activity scale is the "gold standard" exists, and how each scale should be best summarized and modeled remains unclear. [26][27][28] Two anticholinergic scoring systems (i.e., the Anticholinergic Cognitive Burden scale (ACB) and the Anticholinergic Drug Scale (ADS)) have gained the most widespread use despite each having only moderate concordance with the other. [28][29][30][31][32] Although the ACB categorizes medications using clinical measures of anticholinergic function (e.g., changes in cognition and mortality within 2 years), 30 the ADS categorizes medications using serum anticholinergic activity (a laboratory measure of anticholinergic function).…”
Section: Strategy 3: Use Of Validated Scales To Combine Structurally mentioning
OBJECTIVES
Methods for pharmacoepidemiologic studies of large‐scale data repositories are established. Although clinical cohorts of older adults often contain critical information to advance our understanding of medication risk and benefit, the methods best suited to manage medication data in these samples are sometimes unclear and their degree of validation unknown. We sought to provide researchers, in the context of a clinical cohort study of delirium in older adults, with guidance on the methodological tools to use data from clinical cohorts to better understand medication risk factors and outcomes.
DESIGN
Prospective cohort study.
SETTING
The Successful Aging After Elective Surgery (SAGES) prospective cohort.
PARTICIPANTS
A total of 560 older adults (aged ≥70 years) without dementia undergoing elective major surgery.
MEASUREMENTS
Using the SAGES clinical cohort, methods used to characterize medications were identified, reviewed, analyzed, and distinguished by appropriateness and degree of validation for characterizing pharmacoepidemiologic data in smaller clinical data sets.
RESULTS
Medication coding is essential; the American Hospital Formulary System, most often used in the United States, is not preferred over others. Use of equivalent dosing scales (e.g., morphine equivalents) for a single medication class (e.g., opioids) is preferred over multiclass analgesic equivalency scales. Medication aggregation from the same class (e.g., benzodiazepines) is well established; the optimal prevalence breakout for aggregation remains unclear. Validated scale(s) to combine structurally dissimilar medications (e.g., anticholinergics) should be used with caution; a lack of consensus exists regarding the optimal scale. Directed acyclic graph(s) are an accepted method to conceptualize causative frameworks when identifying potential confounders. Modeling‐based strategies should be used with evidence‐based, a priori variable‐selection strategies.
CONCLUSION
As highlighted in the SAGES cohort, the methods used to classify and analyze medication data in clinically rich cohort studies vary in the rigor by which they have been developed and validated.
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