Abstract
Objectives:
Delirium may be associated with neuroinflammation and reduced blood-brain barrier (BBB) stability. ACE Inhibitors (ACEIs) and Angiotensin Receptor Blockers (ARBs) reduce neuroinflammation and stabilize the BBB, thus slowing the progression of memory loss in patients with dementia. This study evaluated the effect of these medications on delirium prevalence.
Methods:
This was a retrospective study of data from all patients admitted to a Cardiac ICU between January 1, 2020-December 31, 2020. The presence of delirium was determined based on the International Classification of Diseases (ICD) 10 codes and nurse delirium screening.
Results:
Of the 1684 unique patients, almost half developed delirium. Delirious patients who did not receive either ACEI or ARB had higher odds (odds ratio [OR] 5.88, 95% CI 3.7–9.09, P<.001) of in-hospital death and experienced significantly shorter ICU lengths of stay (LOS) (P=.01). There was no significant effect of medication exposure on the time to delirium onset.
Conclusions:
While ACEIs and ARBs have been shown to slow the progression of memory loss for patients with Alzheimer’s disease, we did not observe a difference in time to delirium onset.
Keywords: antihypertensives, ACE Inhibitor, Angiotensin Receptor Blocker, cardiac intensive care unit, delirium
Introduction
Delirium is an acute syndrome expressed as global cognitive impairment with an altered level of consciousness or disorganized thinking that affects as many as 80% of critically ill adults [1–4]. The acute brain dysfunction associated with delirium is believed to be multifactorial and may include both blood-brain barrier (BBB) instability and activation of the inflammatory response [1, 5, 6]. Disruption of the BBB and decreased cerebral perfusion associated with hypertension can result in cognitive dysfunction [7–9].
It has been hypothesized that delirium may be associated with underlying neuroinflammatory responses and reductions in the stability of the BBB in critically ill patients [1, 5, 10, 11]. Additionally, in prior studies, neuroinflammation has been associated with behavioral and cognitive changes. Older age has also been associated with microglial priming, thus increasing pro-inflammatory cytokine release and neuronal hippocampal atrophy [5, 10, 12].
Research has suggested that antihypertensives, including ACEIs and ARBs, slow the progression of memory loss in patients with mild to moderate Alzheimer’s disease. ACEIs and ARBs regulate the reticular activating system (RAS) functions [13–17]. The reduction in angiotensin II supply associated with ACEI reduces the inflammatory response, while ARBs downregulate angiotensin I, stabilizing the BBB [13–18]. Therefore, ACEI and ARB administration might assist with delirium prevention in critically ill patients [9, 16]. Although ACEIs and ARB have effectively managed hypertension and heart failure, evidence suggests these medications may not have identical cardio-cerebrovascular protective effects [14, 19].
There has been some literature on the effects of prescribed prehospital ACEI/ARB medications on delirium prevention in the ICU setting [9, 16]. We conducted a retrospective analysis of patient electronic medical record (EMR) documentation to examine the effect of ACEI and ARB in patients who experienced delirium in the cardiac intensive care unit (CICU) to add to the growing body of literature. We hypothesized that for ICU patients with delirium, those who received ACEI or ARBs would experience a delayed onset of delirium compared to patients who did not receive these medications. Therefore, the objective of this study was to evaluate the effect of ACE Inhibitors (ACEIs) and Angiotensin Receptor Blockers (ARBs) on delirium prevalence in a cardiac intensive care unit (CICU).
Materials and methods
Study design
The University of North Carolina (UNC) Institutional Review Board (IRB) reviewed and approved the study titled “Neuroprotection for Delirium from ACE-Inhibitors and Angiotensin Receptor Blockers” (#21–1061) with a waiver of consent on 10/27/2021. All procedures were followed per the UNC IRB ethical standards of human experimentation and with the Helsinki Declaration of 1975. The Carolina Data Warehouse provided de-identified patient data for analysis.
Patients who experienced delirium while in the ICU based on the International Classification of Diseases (ICD) 10 codes or nurse-performed Confusion Assessment Method for the ICU (CAM-ICU) screening were included in this analysis. A large data set of CICU patients with delirium allowed us to examine the relationship between ACEI or ARB exposure and clinical outcomes.
Setting
All participants were admitted to the CICU between January 1-December 31, 2020, at a Magnet-designated community hospital that is part of a large academic health system in central North Carolina. The hospital has 439 inpatient beds, including 20 CICU beds averaging 1757 admissions annually.
Sample
Inclusion criteria included: 1) admission to the CICU; 2) age 18 years or older; 3) being delirium positive by either CAM-ICU assessment or medical provider diagnosis (ICD-10) at any point during their ICU stay. Exclusion criteria included 1) age <18 years and 2) not delirium positive by either CAM-ICU or medical provider diagnosis.
Measures
ACEI and ARB exposure was defined as documented administration in the medication administration record (MAR) during CICU admission, regardless of pre-hospitalization use.
Screening and outcome measures
Participants were considered delirium positive if medical providers coded patients with either delirium or encephalopathy using ICD 10 codes (n=281) or had a documented delirium-positive nurse screening (n=767). Bedside nurses completed CAM-ICU to assess each patient for delirium twice daily while in the ICU, per standard of care. Eligibility for CAM-ICU assessment was determined based on the patient’s Richmond Agitation Sedation Scale (RASS) [20]. A RASS cutoff score of −3, meaning the patient could respond to verbal stimulation [21]. Patients were considered delirium positive based on the CAM-ICU if they exhibited signs of acute mental status change, fluctuating course, displaying features of inattention, and either disorganized thinking or altered level of consciousness (n=767). Patients whose RASS scores were −4 or −5, indicating they required physical stimulation to obtain any response or were unresponsive to stimuli, were deemed unable to assess.
Other data collection
Baseline demographics, including age, race, sex, and diagnosis, were collected. We also examined the administration of medications used to manage behaviors associated with delirium, including benzodiazepines and other sedatives or hypnotics extracted from the EMR.
Statistical analysis
Descriptive statistics were used to describe the overall sample including clinical and demographic factors such as age, race, sex, clinical condition, stratified by medication exposure. Univariate logistic regression models were used to model medication exposure in the overall sample and in the subset of participants with a primary diagnosis of MI, HF, and HTN, while controlling for various demographic factors (Table 2).
Table 2.
Logistic regression results modeling ACE and/or ARB exposure
| Demographic & Clinical Conditions | Overall | Hypertension, heart failure, and myocardial infarction |
||
|---|---|---|---|---|
| OR (95% CI) | P Value | OR (95% CI) | P Value | |
| Age | 1.02 (1.01, 1.03) | .001 | 0.99 (0.96, 1.01) | .40 |
| Race | ||||
| White | 0.29 (0.11, 0.72) | .001 | 5.24 (0.66, 44.24) | .12 |
| Black | 0.31 (0.12, 0.77) | .01 | 3.04 (0.43, 22.72) | .27 |
| Other | 0.46 (0.16, 1.34) | .16 | 4.34 (0.45, 44.38) | .21 |
| Sex | ||||
| Male | 1.04 (0.77, 1.40) | .82 | 0.64 (0.34, 1.18) | .15 |
| Female (ref) | ||||
| Discharge Disposition | ||||
| Deceased | 0.17 (0.11, 0.27) | <.001 | 0.28 (0.12, 0.63) | .002 |
| Post-Acute Care | 0.83 (0.58, 1.18) | .30 | 0.87 (0.41, 1.85) | .71 |
| Other | 0.52 (0.22, 1.17) | .13 | 0.22 (0.01, 2.88) | .27 |
| Home (ref) | ||||
| ICU LOS | 0.96 (0.92, 0.99) | .01 | 0.94 (0.88, 1.00) | .07 |
| Hospital LOS | 1.00 (0.99, 1.02) | .65 | 1.04 (1.00, 1.09) | .09 |
Note: OR=odds ratio.
Linear regression was used to examine the effects of medication exposure on hospital and ICU LOS and to control for demographic factors (Table 3). Univariate logistic regression was also used to assess the relationship between exposure to benzodiazepines, sedatives, or hypnotics and medication exposure (Table 4). A time-to-event analysis was conducted using the Cox proportional hazards model to assess the effect of medication exposure on the time to delirium onset (Table 5).
Table 3.
Univariate linear regression results modeling hospital and ICU LOS in days
| Demographic & Clinical Variables | Hospital LOS | ICU LOS | ||
|---|---|---|---|---|
| Estimate (95% CI) | P Value | Estimate (95% CI) | P Value | |
| Med | ||||
| ACE only | −1.04 (−3.06, 0.96) | .31 | −1.36 (−2.36, −0.36) | .01 |
| ARB only | −0.97 (−3.62, 1.67) | .47 | −1.12 (−2.43, 0.19) | .10 |
| Both | 2.53 (−6.38, 11.44) | .58 | 2.18 (−2.26, 6.61) | .34 |
| Age | −0.17 (−0.23, −0.11) | <.001 | −0.08 (−0.11, −0.05) | <.001 |
| Race | ||||
| Black | 0.01 (−1.91, 1.94) | .99 | 0.39 (−0.52, 1.12) | .42 |
| Other | 4.83 (1.48, 8.19) | .004 | 3.16 (1.49, 4.84) | <.001 |
| Sex | ||||
| Male | 0.35 (−1.30, 1.99) | .68 | 0.29 (−0.52, 1.12) | .48 |
| Discharge Disposition | ||||
| Deceased | 0.26 (−1.97, 2.48) | .82 | 1.93 (0.82, 3.03) | <.001 |
| Other | 6.29 (4.38, 8.21) | <.001 | 2.33 1.37, 3.28) | <.001 |
Table 4.
Logistic regression results modeling benzo/sedative/hypnotics exposure
| OR (95% CI) | P Value | |
|---|---|---|
| Med | ||
| ACE | 0.04 (0.01, 0.11) | <.001 |
| ARB | 0.04 (0.01, 0.11) | <.001 |
| Age | 0.95 (0.92, 0.98) | .004 |
| Race | ||
| Black | 0.77 (0.38, 1.58) | .58 |
| Other | 0.85 (0.29, 2.88) | .83 |
| White (ref) | ||
| Sex | ||
| Male | 3046.73 (254.55, 49149.17) | <.001 |
| Female | 1831.65 (146.01, 30746.71) | <.001 |
| Discharge Disposition | ||
| Deceased | 12.12 (2.37, 222.17) | .02 |
| Post-Acute Care | 1.09 (0.56, 2.14) | .80 |
| Other | 0.31 (0.07, 1.64) | .13 |
| ICU LOS | 1.23 (1.09, 1.40) | .001 |
| Hospital LOS | 1.01 (0.97, 1.05) | .75 |
Note: OR=odds ratio.
Table 5.
Cox proportional hazards model results modeling time to delirium
| Demographic and Clinical Conditions | HR (95% CI) | P Value |
|---|---|---|
| Med | ||
| ACE only | 0.92 (0.77, 1.09) | .32 |
| ARB only | 0.92 (0.73, 1.16) | .48 |
| Both | 0.95 (0.47, 1.92) | .88 |
| Neither (ref) | 1.00 | |
| Age | 1.00 (0.95, 1.00) | .55 |
| Race | ||
| Black | 1.01 (0.85, 1.19) | .94 |
| Other | 1.21 (0.91, 1.61) | .20 |
| White (ref) | 1.00 | |
| Sex | ||
| Male | 1.03 (0.51, 1.90) | .66 |
| Female (ref) | 1.00 | |
| Discharge Disposition | ||
| Deceased | 1.01 (0.84, 1.22) | .91 |
| Other | 0.92 (0.78, 2.09) | .33 |
| Home (ref) | 1.00 | |
| ICU LOS | 1.00 (0.99, 1.02) | .99 |
| Hospital LOS | 1.01 (0.99, 1.01) | .10 |
Note: HR=hazards ratio.
Results
Study population
Of the 1684 patients admitted to the CICU between January 1, 2020, and December 31, 2020, 281 (16.7%) were identified as having delirium by a medical provider, 767 (45.5%) were considered delirium positive based on nurse-performed CAM-ICU assessment. The two were not mutually exclusive. After inclusion and exclusion criteria were applied, 841 of the 1684 (49.9%) unique patients who experienced delirium were included in this study.
The mean age of the participants was 71.27 (SD 14.43) years, with 26.2% (220/841) African Americans and 45.7% (384/841) females. Medication exposure included 60.4% (508/841) with no exposure to ACEI or ARBs, 23.4% (197/841) with ACEI alone, 13.4% (113/841) with ARB alone, 1.2% (10/841) with both an ACEI and an ARB, and 1.5% (13/841) with no information on medication recorded. Of those only receiving an ACEI, males were more likely to receive one (120/199, 60.3%) than females (79/199, 39.7%). Of those only receiving an ARB, while females were more likely to receive one (57.8%, 59/102) than males (43/102, 42.2%). The most prevalent diagnoses in the cohort included myocardial infarction at 15.5% (130/841), hypertension at 8.3% (70/841), and heart failure at 1.5% (13/841). Table 1 provides the characteristics of the study cohort stratified by medication exposure (ACEI, ARB, both, and neither).
Table 1.
Comparison of demographic and clinical conditions by medication status
| % (n) | ||||
|---|---|---|---|---|
| Demographic and Clinical Conditions | ACE only (n=199) | ARB only (n=102) | Both (n=8) | Neither (n=519) |
| Age | ||||
| 18–49 | 6.5 (13) | 4.9 (5) | 12.5 (1) | 8.5 (44) |
| 50–59 | 9.5 (19) | 5.9 (6) | 0.0 (0) | 13.9 (72) |
| 60–69 | 24.1 (48) | 15.7 (16) | 37.5 (3) | 19.7 (102) |
| 70+ | 59.8 (119) | 73.5 (75) | 50.0 (4) | 58.0 (301) |
| Race | ||||
| White or Caucasian | 69.8 (139) | 61.8 (63) | 12.5 (1) | 68.6 (356) |
| Black or African American | 21.1 (42) | 30.4 (31) | 87.5 (7) | 26.0 (135) |
| Other | 9.0 (18) | 7.8 (8) | 0.0 (0) | 5.4 (28) |
| Gender | ||||
| Female | 39.7 (79) | 57.8 (59) | 37.5 (3) | 45.7 (237) |
| Male | 60.3 (120) | 42.2 (43) | 62.5 (5) | 54.3 (282) |
| ICU Length of Stay (days) | ||||
| 0–3 | 52.3 (104) | 53.9 (55) | 37.5 (3) | 45.9 (238) |
| 4–6 | 25.6 (51) | 27.5 (28) | 12.5 (1) | 21.0 (109) |
| 7–9 | 12.1 (24) | 11.8 (12) | 37.5 (3) | 13.9 (72) |
| 10–19 | 8.0 (16) | 5.9 (6) | 12.5 (1) | 15.4 (80) |
| 20–29 | 2.0 (4) | 1.0 (1) | 0.0 (0) | 2.1 (11) |
| 30–39 | 0.0 (0) | 0.0 (0) | 0.0 (0) | 1.0 (5) |
| 40–49 | 0.0 (0) | 0.0 (0) | 0.0 (0) | 0.6 (3) |
| 50+ | 0.0 (0) | 0.0 (0) | 0.0 (0) | 0.2 (1) |
| Hospital Length of Stay (days) | ||||
| 0–3 | 11.1 (22) | 11.8 (12) | 12.5 (1) | 16.9 (88) |
| 4–6 | 22.6 45) | 26.5 (27) | 0.0 (0) | 19.3 (100) |
| 7–9 | 17.6 (35) | 19.6 (20) | 0.0 (0) | 16.2 (84) |
| 10–19 | 29.6 (59) | 27.5 (28) | 75.0 (6) | 30.1 (156) |
| 20–29 | 13.6 (27) | 8.8 (9) | 12.5 (1) | 9.4 (49) |
| 30–39 | 3.0 (6) | 2.0 (2) | 0.0 (0) | 3.5 (18) |
| 40–49 | 0.5 (1) | 2.0 (2) | 0.0 (0) | 2.3 (12) |
| 50+ | 2.0 (4) | 2.0 (2) | 0.0 (0) | 2.3 (12) |
Table 2 provides the results of univariate logistic regression assessing the relationship between exposure to ACEI and/or ARB and clinical outcomes in patients with delirium, while controlling for demographic data. A sensitivity analysis included only participants with myocardial infarction, hypertension, or heart failure.
Patients who received neither an ACEI nor ARB had higher odds of in-hospital death (OR 5.88, 95% CI 3.7–9.09, P<.001) compared to those who received an ACEI and/or ARB. A sensitivity analysis performed in the subset of patients with a primary diagnosis of myocardial infarction, hypertension, or heart failure also demonstrated that those who did not receive an ACEI or ARB had higher odds of in-hospital death (OR 3.57, 95% CI 1.59–8.33, P=.002) compared to those who received an ACEI and/or ARB.
Hospital and ICU length of stay
Most patients had an ICU LOS of 3 days or less (407/841, 48.4%), with an average ICU LOS of 6 days. The average hospital length of stay was 13 days. Table 3 provides the results of two linear regression models, modeling ICU and hospital lengths of stay separately, while adjusting for clinical and demographic factors. Exposure to ACEI was associated with a decrease in ICU LOS (P=.01). For patients who had only ACEI exposure, hospital LOS was 4.9 days compared to 6.3 days for those who did not have ACEI exposure. Age was associated with both hospital (P<.001) and ICU (P<.001) LOS.
Exposure to deliriogenics
Univariate logistic regression was also used to assess the relationship between exposure to benzodiazepines, sedatives, and hypnotics and exposure to ACEI or ARBs while controlling for demographic factors and clinical outcomes. Exposure to benzodiazepines, sedatives, or hypnotics was significantly associated with receiving an ACEI (OR 0.04, 95% CI 0.01–0.11, P<.001) or ARB (OR 0.04, 95% CI 0.01–0.11, P<.001), age (OR 0.95, 95% CI 0.92–0.98, P<.001), mortality (OR 12.12, 95% CI 2.37–222.17, P=.02), and ICU LOS (OR 1.12, 95% CI 1.09–1.4, P=.001) (Table 4).
Time to delirium onset
The Cox proportional hazards model was used to assess the effect of receiving ACEI or ARBs on time to delirium onset while adjusting for clinical and demographic factors. Time to onset of delirium was not significantly different for those who were exposed to ACEI and/or ARB compared to those who did not receive AN ACEI or ARB after adjusting for age, race, sex, discharge disposition, and ICU and hospital LOS. (Table 5)
Discussion
With the rising number of aged individuals being admitted to critical care units, the likelihood of delirium among patients increases [22]. Given the belief that the pathogenesis of delirium may be associated with neuroinflammation, there is an urgent need to evaluate the potential benefit of medications known to stabilize the BBB, thus reducing the exposure of peripheral inflammation in the brain.
We observed that participants who received either ACEI or ARB had a shorter length of stay, were more likely to discharge home or to a post-acute care facility, and had lower in-hospital mortality rates than those who did not receive an ACEI or ARB. While there was an association between ACEI and ARB exposure and clinical outcomes, further research is needed to determine whether these drugs provide a neuroprotective effect for delirium.
Studies have shown that increases in anti-inflammatory activities and oxidants have led to disruption in the BBB [23]. Reducing nitric oxide production within the RAS may result in reduced apoptosis and promote vasodilation, thus improving intracerebral blood flow while also stabilizing the BBB to minimize proinflammatory cytokine entering cerebral blood flow, as seen in studies evaluating the neuroprotective effects of ACEI and ARBs in traumatic brain injury, dementia, and other neurological conditions [17]. In a recent systematic review, 12 studies evaluating cognitive outcomes associated with the use of ACEI and ARBs found could play a beneficial role in cognitive outcomes associated with traumatic brain injury.
A novel aspect of the study was evaluating the inpatient use of ACEI and ARBs in patients admitted to a cardiac ICU. However, our study has limitations that should be considered when evaluating these results. While patients were admitted to the cardiac ICU, many were admitted with sepsis and other diagnoses. Prehospital exposure to ACEI and ARBs in this sample is unknown and could partially explain some of the findings. Patients with greater severity of illness were less likely to receive these antihypertensive medications in the ICU.
Conclusions
While ACEI and/or ARBs have been shown to regulate RAS activity and slow the progression of memory loss in patients with mild to moderate Alzheimer’s disease, we did not observe a difference in time to onset delirium based on the administration of either or both ACEI and ARBs. However, further research is needed to evaluate the true neuroprotective potential of ACEI and ARBs for delirium.
Supplementary Material
Acknowledgements
We thank Dr. Babar Khan for his insight during the data collection and analysis.
Declaration of funding
This paper was supported by a Geriatric Advanced Practice Nurse Association Research Grant and the National Institute of Nursing Research (grant number: NRSA T32 NR018407).
Footnotes
Declaration of financial/other relationships
The authors have no relevant affiliations or financial involvement with any organization or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the manuscript. This includes employment, consultancies, honoraria, stock ownership or options, expert testimony, grants or patents received or pending, or royalties. Peer reviewers on this manuscript have no relevant financial or other relationships to disclose.
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