a b s t r a c t

Study objective: To evaluate the association between delirium and subsequent short-term mortality in Geriatric patients presenting to the emergency department (ED).

Methods: This was an observational cohort study of adults age >=75 years who presented to an academic ED and were screened for delirium during their ED visit. The Delirium Triage Screen followed by the Brief Confusion Assessment Method were used to ascertain the presence of delirium. In-hospital, 7-day, and 30-day mortality were compared between patients with and without ED delirium. Odds ratios with 95% confidence intervals (CIs) were calculated through logistic regression after adjusting for confounders including age, sex, history of dementia, ED disposition, and acuity.

Results: A total of 967 ED visits were included for analysis among which delirium was detected in 107 (11.1%). The median age of the cohort was 83 years (IQR 79, 88), 526 (54.4%) were female, 285 (29.5%) had documented dementia, and 171 (17.7%) had a high acuity Emergency Severity Index triage level 1 or 2. During the hospitali- zation, 5/107 (4.7%) of those with delirium and 4/860 (0.5%) of those without delirium died. Within 7 days of ED departure, 6/107 (5.6%) of those with delirium and 6/860 (0.7%) of those without delirium died (unadjusted OR 8.46, 95% CI 2.68-26.71). Within 30 days, 18/107 (16.8%) of those with delirium and 37/860 (4.3%) of those with- out delirium died (unadjusted OR 4.50, 95% CI 2.46-8.23). ED delirium remained associated with higher 7-day (adjusted OR 5.23, 95% CI 1.44-19.05, p = 0.008) and 30-day mortality (adjusted OR 2.82, 95% CI 1.45-5.46,

p = 0.002).

Conclusion: Delirium is an important prognostic factor that ED clinicians and nurses must be aware of to optimize delirium prevention, management, disposition, and communication with patients and families.

(C) 2023

1. Introduction

Delirium is an acute physiological disruption in the brain networks that support cognition resulting in fluctuating changes in the level of consciousness, attention, and cognition [1]. Delirium is poorly detected

* Corresponding author at: Department of Emergency Medicine, Mayo Clinic, Rochester, MN, USA.

E-mail address: [email protected] (F. Bellolio).

in the emergency department (ED) [2,3] but is important to recognize as it has been associated with decreased long-term functioning [4] and in- creased mortality [5], especially following prolonged episodes [6]. Moreover, delirium is a common presentation in the ED, with studies showing prevalence in geriatric ED patients of around 10% [7,8].

Multiple validated Screening tools are available that can be adminis- tered in <5 min [9-11]. Nonetheless, delirium continues to be unde- tected in as many as 83% of ED cases [2,3], mostly due to the predominance of hypoactive presentations [8,12], time constraints lim- iting testing, and missed opportunities to recognize a fluctuating course.

https://doi.org/10.1016/j.ajem.2023.01.040

0735-6757/(C) 2023

While previous ED-based studies have reported an increased risk of death at 30 days [5,13,14] and at longer follow-up periods [5,14], less is known about shorter term mortality (<30 days). This has created a gap in knowledge surrounding short-term mortality for patients diagnosed with delirium in the ED. The ED is the frontline for Emergent medical care and often the first opportunity to diagnose delirium. A better un- derstanding of the short-term mortality of this condition may increase the urgency for consistent delirium screening, improve the ability to communicate prognosis with patients and families, and allow for timely medical interventions to potentially reduce Morbidity and mortality rates. There is also evidence that delirium that goes undiagnosed in the ED is likely to be unrecognized by the admitting provider as well [12].

In this cohort study, we aimed to evaluate the association between delirium and subsequent short-term mortality (in-hospital, within 7 days, and within 30 days) in geriatric patients presenting to the ED.

1. Methods

This manuscript adheres to the STrengthening the Reporting of OB- servational studies in Epidemiology (STROBE) reporting guidelines for an observational cohort study [15]. It was approved by our center’s in- stitutional review board. All patients included in this study had consented to research authorization for Medical records review.

• 1. Study design, setting, and participants

This was a pre-planned analysis of an observational cohort study of older adults aged >=75 years who presented to a quaternary academic ED in Minnesota with approximately 80,000 annual ED patient visits in- cluding 30,000 ED visits for older adults. Other analyses derived from this cohort have been published elsewhere [8,16]. Patients presented to the ED between December 2nd, 2019 and February 1st, 2021. All study participants were screened by a bedside nurse for delirium during their ED visit through a validated sequential two-step approach: the De- lirium Triage Screen (DTS) and the brief Confusion Assessment Method (bCAM) [17,18].

• • 1. Delirium measurement

During the study period, delirium screening through DTS/bCAM [17,18] was recommended for all patients aged >=75 years as part of stan- dard of care, with the exception of comatose or stuporous patients (both populations deemed not assessable for delirium). Nevertheless, it was at the discretion of nurses to decide which individuals to screen. Nurses re- ceived training on how to apply these tools including educational videos.

The DTS screening tool, which has a 98% sensitivity [17], was used first. If the DTS was negative, patients were ruled out from having delir- ium, and no further screening was performed. If the DTS was positive, patients would then be screened with the bCAM tool (84% sensitivity, 96% specificity) [17] for further assessment of delirium. If the bCAM was negative, patients were ruled out from having delirium. Patients were deemed positive for delirium if they had a positive DTS and bCAM. If they had no DTS on record but a positive bCAM, they were also considered positive for delirium. Patients with multiple delirium screenings performed throughout the duration of their ED visit were deemed positive for delirium if at least one instance of screening was positive. Finally, if delirium screening was equivocal, 2 investigators re- viewed the electronic health record in order to assess for the presence of delirium using a previously validated chart review-based method [19].

• • 1. Primary outcome (short-term mortality)

All ED visits were reviewed for in-hospital, 7-day, and 30-day mor- tality through electronic health record review.

• • 1. Potential confounders

Data regarding potential confounders in the association between de- lirium and subsequent short-term mortality were also extracted includ- ing age, sex, ED disposition, history of dementia, and triage ESI level 1 or 2 (surrogate variable for severity of illness). Inconsistencies in the data were manually reviewed by two investigators and resolved by a senior investigator.

• • 1. Data analysis

Statistical analysis was conducted by a biostatistician. Continuous features were summarized with quartiles. Categorical features were

Fig. 1. Flowchart of study participants.

summarized with frequencies and percentages. The association be- tween delirium and short-term mortality was evaluated using logistic regression. Odds ratios (OR) with 95% confidence intervals (CIs) were calculated to estimate the strength and direction of each association. Models were both unadjusted and adjusted for patient age, sex, ED dis- position, history of dementia, and triage ESI at level 1 or 2. Due to the low number of mortality events captured, multivariable models imple- mented a LASSO penalty to reduce the risk of overfitting. The optimal penalization parameter was determined using 10-fold cross validation. Multiple ED visits from individual patients were not excluded from analysis. To account for the potential correlation between repeat ED visits, a sensitivity analysis was performed using mixed effects logistic regression with a random intercept at the patient level. Finally, a Kaplan-Meier curve was plotted to visually depict the survival differ- ences between those with and without delirium. All statistical tests were 2-sided, and statistical significance was set at alpha <0.05.

1. Results

From 12,287 eligible ED visits, 1,060 (8.6%) underwent delirium screening during the study period. Ninety-three had no research

Table 1

Patient and ED visit characteristics stratified by presence of ED delirium.

authorization on file and were excluded from the analysis. Ultimately, 967 ED visits were included, with delirium present in 107 (11.1%). The flow chart is viewable in Fig. 1.

There were 897 unique patients comprising the 967 ED visits identi- fied for this study. A mixed effects logistic regression model assessing the risk of 30-day mortality found no significant effect for within- patient correlation, so standard logistic regression was used for analysis. Table 1 summarizes patient demographics for the cohort stratified by presence of ED delirium.

• 1. In-hospital and 7-day mortality

During the hospitalization 5/107 (4.7%) of those with delirium and 4/860 (0.5%) of those without delirium died. Within 7 days of ED depar- ture, 6/107 (5.6%) of those with delirium and 6/860 (0.7%) of those without delirium died (unadjusted OR 8.46, 95% CI 2.68 to 26.71, p < 0.001). Table 2 describes the associations between delirium and 7-day mortality. After accounting for key confounders, ED delirium remained significantly associated with a >5-fold increase in the odds of 7-day mortality (adjusted OR 5.23, 95% CI 1.44 to 19.05, p = 0.008).

• 1. 30-day mortality

Within 30 days, 18/107 (16.8%) of those with delirium and 37/860

No ED Delirium (N = 860)

Age, median (Q1, Q3) 83

(79.0, 88.0)

ED Delirium (N = 107)

85

(79.5, 89.5)

Overall

(N = 967)

83

(79.0, 88.0)

(4.3%) of those without delirium died (unadjusted OR 4.50, 95% CI 2.46 to 8.23). Table 3 describes associations between ED delirium and 30-day mortality. After accounting for patient age, sex, triage ESI, ED dis-

position, and history of dementia, ED delirium was significantly associ-

Sex - Male, n (%) 394 (45.8%) 47 (43.9%) 441 (45.6%)

Race, n (%)

African American	8 (0.9%)	1 (0.9%)	9 (0.9%)	mortality (OR 2.82, 95% CI 1.45 to 5.46, p = 0.002) (Fig. 2).
Asian	8 (0.9%)	0 (0.0%)	8 (0.8%)
White	831 (96.6%)	104 (97.2%)	935 (96.7%)
Other	11 (1.3%)	2 (1.9%)	13 (1.3%)	3.3. Mortality rates and ED disposition
Unknown	2 (0.2%)	0 (0.0%)	2 (0.2%)
Ethnicity, n (%) Despite low event numbers, patients discharged from the ED with Not Hispanic or Latino 841 (97.8%) 104 (97.2%) 945 (97.7%)
Hispanic or Latino	6 (0.7%)	2 (1.9%)	8 (0.8%)	delirium had higher 7-day mortality than those discharged without de-
Unknown	13 (1.5%)	1 (0.9%)	14 (1.4%)	lirium (7-day mortality: 1/11, 9.1% vs 2/340, 0.6%, p = 0.0255). Also, pa-
Triage ESI, n (%) Level 1 Level 2	2 (0.2%) 137 (15.9%)	1 (0.9%) 31 (29.0%)	3 (0.3%) 168 (17.4%)	tients discharged from the ED with delirium had worse prognosis than those admitted to the hospital without delirium. (Table 4).
Level 3	654 (76.0%)	75 (70.1%)	729 (75.4%)
Level 4	66 (7.7%)	0 (0.0%)	66 (6.8%)	Table 2
Level 5	1 (0.1%)	0 (0.0%)	1 (0.1%)	Association between ED delirium and 7-day mortality in univariable and multivariable lo-
ED Benzodiazepines, n (%)	16 (1.9%)	4 (3.7%)	20 (2.1%)	gistic regression.

ated with approximately a 3-fold increase in the odds of 30-day

ED Disposition, n (%)

Hospital Admit	387 (45.0%)	72 (67.3%)	459 (47.5%)
hospital observation	87 (10.1%)	14 (13.1%)	101 (10.4%)
Send to OR	5 (0.6%)	0 (0.0%)	5 (0.5%)
ICU Admit	36 (4.2%)	9 (8.4%)	44 (4.6%)
Discharge	340 (39.5%)	11 (10.3%)	351 (36.3%)
Transfer to Health Care Facility	2 (0.2%)	0 (0.0%)	2 (0.2%)
Left AMA	0 (0.0%)	1 (0.9%)	1 (0.1%)
Eloped	1 (0.1%)	0 (0.0%)	1 (0.1%)
Expired in the ED	1 (0.1%)	0 (0.0%)	1 (0.1%)
Unknown Disposition	1 (0.1%)	0 (0.0%)	1 (0.1%)

Medical History, n (%)

History of Dementia	226 (26.3%)	59 (55.1%)	285 (29.5%)
History of Stroke	206 (24.0%)	37 (34.6%)	243 (25.1%)
History of Delirium	119 (13.8%)	17 (15.9%)	136 (14.1%)
History of Depression	233 (27.1%)	41 (38.3%)	274 (28.3%)
History of Anxiety	247 (28.7%)	38 (35.5%)	285 (29.5%)
History of Seizures	27 (3.1%)	11 (10.3%)	38 (3.9%)
History of Visual impairment	22 (2.6%)	7 (6.5%)	29 (3.0%)
History of Auditory Impairment	345 (40.1%)	37 (34.6%)	382 (39.5%)

Patient Outcomes, n (%)

In-hospital Mortality	4 (0.5%)	5 (4.7%)	9 (1.0%)
7-day Mortality	6 (0.7%)	6 (5.6%)	12 (1.2%)
30-day Mortality	37 (4.3%)	18 (16.8%)	55 (5.7%)

ED = emergency department; ESI = emergency severity index; OR = operating room; ICU = intensive care unit; AMA = against medical advice.

Univariable Multivariable ?

		OR (95% CI)	P-value	OR (95% CI)	P-Value
ED Delirium History of Dementia		8.46 (2.68-26.71) 3.41	< 0.001 0.038	5.23 (1.44-19.05) 1.71	0.008 0.25
Age (per 5 years)		(1.07-10.83) 1.25	0.34	(0.48-6.09) 1.17	0.56
Sex		(0.79-1.96)		(0.69-2.01)
Female		Reference	-	Reference	-
Male ED Disposition		1.68 (0.53-5.33)	0.38	1.12 (0.33-3.85)	0.77
Discharge Hospital Admit ICU Admit	??	Reference 1.04 (0.5-4.36) 8.29	- 0.96 0.011	Reference 0.61 (0.13-2.81) 5.22	- 0.53 0.044
		(1.62-42.37)		(1.12-24.29)

Triage ESI ESI Level 3, 4, or 5	Reference	-	Reference	-
ESI Level 1 or 2	3.39	0.039	2.13	0.25
	(1.06-10.83)		(0.58-7.83)

* Multivariable model included all variables listed in this table

?? Hospital admission includes non-ICU admissions and admissions for hospital obser- vation.

Fig. 2. Kaplan-Meier curve comparing survival rates between those with and without ED delirium.

Table 3

Association between ED delirium and 30-day mortality in univariable and multivariable logistic regression.

1. Discussion

We found that 11% of adults 75 years of age and older presenting to

the ED screened positive for delirium, which is consistent with the pub-

Univariable Multivariable¹

OR (95% CI) P-value OR (95% CI) P-Value

lished literature on delirium rates. For this cohort of 967 geriatric ED pa- tients, there was increased in-hospital, 7-day, and 30-day mortality for

ED Delirium 4.50

(2.46-8.23)

History of Dementia 1.77

(0.91-3.46)

Age (per 5 years) 1.41

(1.14-1.75)

Sex

< 0.001 2.82

(1.45-5.46)

0.092 2.70

(1.48-4.91)

0.002 1.33

(1.04-1.70)

0.002

0.001

0.021

patients with delirium in the ED compared to those without delirium. These data suggest that ED delirium is an important prognostic factor and may be considered as a form of acute brain failure.

We found a 30-day mortality rate of 16.8% compared to a mortality rate of 4.3% in those without ED delirium. Mortality was also higher for Delirious patients who were discharged home from the ED (9.1%

Female Reference - Reference -

mortality for those who went home with delirium compared to those

Male 2.18

(1.24-3.84)

ED Disposition

0.007 2.53

(1.37-4.70)

0.003

discharged home without delirium at 0.6%). In this study, the 30-day de-

lirium mortality rate was higher than other ED-based research that assessed 30-day outcomes. Prior studies included patients aged 65 and

Discharge Reference - Reference -

Hospital Admit² 2.74

(1.31-5.74)

ICU Admit 7.00

(2.47-19.87)

0.008 1.94

(0.90-4.18)

< 0.001 3.98

(1.31-12.10)

0.093

0.015

older, while our study included those 75 and older, who have a greater Comorbidity burden and baseline mortality rate. Kennedy et al. [13] re- ported 6% 30-day mortality among those with ED delirium (vs 1% with-

out delirium); Han et al. [ 5] reported 10.2% 30-day mortality (vs 2.2%

Triage ESI

ESI Level 3, 4, or 5 Reference - Reference -

without ED delirium); and Israni et al. [14] had a mortality of 11.9%

ESI Level 1 or 2 2.41

(1.34-4.35)

0.003 1.61

(0.84-3.06)

0.15

(vs 2.9% without delirium). The difference in mortality might be ex- plained by several factors but most likely age (our cutoff was higher),

¹ Multivariable model included all variables listed in this table.

² Hospital admission includes non-ICU admissions and admissions for hospital obser- vation.

comorbidity burden (our population had more comorbidities) and per- haps severity of acute illness. Nevertheless, all available evidence from ED-based studies points towards delirium in the ED being an important

Table 4 Mortality rates with subgroups based on admission status.
	30-day Mortality	7-day Mortality	In-Hospital Mortality
All Without ED Delirium (n = 860?)	37 (4.3%)	6 (0.7%)	4 (0.5%)
Admitted?? Without ED Delirium (n = 516)	29 (5.6%)	4 (0.8%)	4 (0.8%)
Discharged Without ED Delirium (n = 340)	8 (2.4%)	2 (0.6%)	-
All With ED Delirium (n = 107+)	18 (16.8%)	6 (5.6%)	5 (4.7%)
Admitted With ED Delirium (n = 95)	17 (17.9%)	5 (5.3%)	5 (5.3%)
Discharged With ED Delirium (n = 11)	1 (9.1%)	1 (9.1%)	-

* 4 visits were left out from the two categories of admission vs discharged (2 were transferred to another health care facility, 1 left against medical advice, and 1 had unknown dis- position).

?? Admitted includes admissions from ED to the hospital floor, hospital observation unit, intensive care unit, and operating room.

⁺ 1 patient left against medical advice.

prognostic factor [ 3,20-23]. Moreover, prior meta-analyses looking at the association between delirium in any type of hospital setting and subsequent mortality confirm this finding [20,21].

Our study found a 7-day mortality rate of 5.6% among patients with

ED delirium (compared to a mortality rate of 0.7% in those without diag- nosed ED delirium). To our knowledge, no other studies have specifi- cally analyzed mortality rates of ED-diagnosed delirium at 7 days. A study by Stanich et al. [24] looked at the mortality rates of patients with altered mental status at 7 days (3.2% mortality rate) and 30 days, finding them to be higher than other common chief complaints (gener- alized weakness, abdominal pain, chest pain, and headache) presenting to the ED. Delirium is a type of altered mental status, so these patients represent a group to focus on for targeted screening [7,8].

• 1. Clinical significance & future directions

While other studies have focused on long-term mortality greater than one month [20,21], we aimed to highlight the short-term mortality risks of delirium. Our findings indicate an increased risk of short-term mortality for patients who screen positive for delirium in the ED. This enforces the importance of delirium being viewed as an important prog- nostic factor [25] (and perhaps called as an acute brain failure), and management in the ED should be adjusted accordingly.

It has been shown that patients presenting with altered mental sta- tus (with delirium being a subtype of altered mental status) had a sig- nificantly higher mortality rate at 7 and 30 days compared to patients with a chief complaint of chest pain [24]. While patients with chest pain typically (and correctly) receive extensive workups to further as- sess their mortality risk, those with altered mental status may receive less targeted care, despite their higher risk. While chest pain is typically a patient-reported chief complaint, patients with altered mental status often have vague and non-specific complaints. It is therefore necessary to screen for causes of altered mental status. Knowing that short-term mortality is increased for delirium should prompt initiation of more consistent screening to reduce missed diagnoses and improve opportu- nities to intervene with treatment. As treatment is often based on treating the underlying delirium precipitant (e.g., infection), it is imper- ative for ED providers to work diligently to find the underlying cause(s). Shorter durations of delirium have been shown to improve outcomes [6], so Timely diagnosis and treatment are crucial. Improved treatment and prevention options should be further explored [26] to potentially improve patient outcomes and reduce mortality. Reducing the amount of unnecessary urinary catheterization in the ED, for example, is one possibility [16].

Additionally, knowing the short-term mortality risk of patients with delirium can allow for development of a more comprehensive follow-up plan once the patient is discharged from the ED or hospital. This should prompt further discussions with patients and families about return pre- cautions and the importance of attending follow-up appointments with their primary care provider or specialists. Careful review of medications with special attention to those that are deliriogenic [27] must be com- pleted. Also, almost as important as treating the underlying cause of

the delirium, providers must identify other symptoms that could continue to trigger a delirium like urinary urgency in the setting of infection or pain. Once delirium is diagnosed providers have an obli- gation given the heightened risks associated to do all that is possible to treat it. This presents a potential opportunity to reduce short-term mortality rates.

Finally, understanding the increased risk of short-term mortality al- lows for ED providers to better communicate potential severity of illness with patients and their families. Delirium indicates the patient is criti- cally ill and should prompt providers to engage in a goals of care discus- sion. Understanding the patient’s values and goals of care can allow providers to tailor care recommendations to meet the patient’s wishes. Detecting delirium in the ED also provides an opportunity to educate the patient’s family and/or care partners on nonpharmacologic mea- sures to reduce delirium [28] such as reorientation, cognitive stimula- tion, and sleep hygiene. These strategies can also be communicated during hand-off to the admitting team to provide a continuity of delirium care.

1. Limitations

First, our study focused on patients aged 75 and older while most other studies have included patients aged >=65 years. This leads to differ- ences when comparing rates across populations. Second, our findings may not be replicable at non-academic centers such as rural or commu- nity hospitals that have a different patient population compared to our academic ED. Third, our population lacked racial and ethnic diversity, as it was composed of mostly non-Hispanic white patients that represent the population of the communities that live in MN. Fourth, patients were selected for delirium screening at the discretion of the bedside nurses (8.6% of all visits by people aged 75 and older had EHR evidence of screening) with risk of introducing selection bias to the study. Never- theless, everyone who was screened during the study period was in- cluded in this analysis. Fifth, the method of chart review that was used for equivocal delirium cases was originally designed to be used in an in- patient setting, so it is possible there could have been differences in ap- plicability to our ED setting [19]. Sixth, as with all research that relies on medical records, it is possible that patients’ medical records do not list up-to-date medical history diagnoses, and if that was the case for any of our participants, there could have been underestimations of certain comorbidities (like history of dementia) that could affect the ability to control for these variables. Eight, we had a low sample size for our 7- day analysis, so we used penalized regression in the multivariable analysis to avoid overfitting our data. Despite this, there is low sta- tistical power with wide confidence intervals for the 7-day analysis, and its results should be interpreted with caution. Lastly, and most importantly, there is unmeasured confounding in our estimate of association between delirium and short-term mortality. For exam- ple, we did not account for all comorbidity burden but rather focused on a few comorbidities such as dementia. ESI was used as a marker for severity of illness, but is more of a marker of resource utilization.

1. Conclusions

Older adult patients who screen positive for delirium in the ED have increased risk of short-term mortality (in-hospital, at 7-days, and at 30- days) compared to those without delirium. Delirium is a very important prognostic factor, and ED management (screening, treatment, patient and family communications) should be adjusted accordingly.

Presentation

These findings were presented at the annual 2022 Society of Aca- demic Emergency Medicine (SAEM22) meeting.

Author contributions

Lucas Oliveira J. e Silva and Fernanda Bellolio designed the study. Lucas Oliveira J. e Silva and Aidan Mullan conducted the data analy-

sis.

Mariah Arneson drafted the manuscript, and all authors substan- tially contributed to its revision with content expertise.

Fernanda Bellolio was this project’s mentor and received grant funding.

Funding

This study received funding through the Kern Society Innovation Award, from the Mayo Clinic Robert D. and Patricia E. Kern Center for the Science of Health care delivery. This project was also supported by CTSA grant number UL1 TR002377 from the National Center for Ad- vancing Translational Science (NCATS). Its contents are solely the re- sponsibility of the authors and do not necessarily represent the official views of the NIH.

CRediT authorship contribution statement Mariah L. Arneson: Writing - original draft. Lucas Oliveira J. e Silva:

Writing - review & editing, Methodology, Formal analysis, Data

curation, Conceptualization. Jessica A. Stanich: Writing - review & editing. Molly M. Jeffery: Writing - review & editing, Methodology. Heidi L. Lindroth: Writing - review & editing. Alexander D. Ginsburg: Writing - review & editing. Susan M. Bower: Writing - review & editing. Aidan F. Mullan: Methodology, Formal analysis. Fernanda Bellolio: Writing - review & editing, Supervision, Methodology, Funding acquisition, Formal analysis, Conceptualization.

Declaration of Competing Interest

Dr. Bellolio has no conflicts of interest related to this work. She re- ceives funding from AHRQ for the study of diagnostic errors, NIH, FDA and Kern Center for palliative and Geriatric care related research.

The rest of the authors of this manuscript have no conflict of interest to disclose.

References

1. American Psychiatric Association. Diagnostic and Statistical Manual of Mental Disorders Published online; May 22, 2013. https://doi.org/10.1176/APPI.BOOKS. 9780890425596.
2. Hustey FM, Meldon SW, Smith MD, Lex CK. The effect of mental status screening on the care of elderly emergency department patients. Ann Emerg Med. 2003;41(5): 678-84. https://doi.org/10.1067/mem.2003.152.
3. Carpenter CR, Shelton E, Fowler S, et al. Risk factors and screening instruments to predict adverse outcomes for undifferentiated older emergency department pa- tients: a systematic review and meta-analysis. Acad Emerg Med. 2015;22(1):1-21. https://doi.org/10.1111/acem.12569.
4. Vida S, Galbaud du Fort G, Kakuma R, Arsenault L, Platt RW, Wolfson CM. An 18- month prospective cohort study of functional outcome of delirium in elderly pa- tients: activities of daily living. Int Psychogeriatr. 2006;18(4):681-700. https://doi. org/10.1017/S1041610206003310.
5. Han JH, Shintani A, Eden S, et al. Delirium in the emergency department: an inde- pendent predictor of death within 6 months. Ann Emerg Med. 2010;56(3): 244-52. https://doi.org/10.1016/j.annemergmed.2010.03.003.
6. Han JH, Vasilevskis EE, Chandrasekhar R, et al. Delirium in the emergency depart- ment and its extension into hospitalization (DELINEATE) study: effect on 6-month function and cognition. J Am Geriatr Soc. 2017;65(6):1333-8. https://doi.org/10. 1111/jgs.14824.
7. Silva L Oliveira JE, Berning MJ, Stanich JA, et al. Risk factors for delirium in older adults in the emergency department: A systematic review and meta-analysis. Ann Emerg Med. June 2021. https://doi.org/10.1016/j.annemergmed.2021.03.005. Pub- lished online.
8. Silva L Oliveira JE, Stanich JA, Jeffery MM, et al. REcognizing DElirium in Geriatric EMergency medicine: the REDEEM Risk stratification score. Acad Emerg Med. 2022;29(4):476-85. https://doi.org/10.1111/ACEM.14423.
9. Carpenter CR, Hammouda N, Linton EA, et al. Delirium prevention, detection, and treatment in emergency medicine settings: A geriatric emergency care applied re- search (GEAR) network scoping review and consensus statement. Acad Emerg Med. 2021;28(1):19-35. https://doi.org/10.1111/ACEM.14166/FULL.
10. Mariz J, Costa Castanho T, Teixeira J, Sousa N, Correia Santos N. Delirium diagnostic and screening instruments in the emergency department: an up-to-date systematic review. Geriatrics. 2016;1(3):22. https://doi.org/10.3390/geriatrics1030022.
11. Lamantia MA, Messina FC, Hobgood CD, Miller DK. Screening for delirium in the emergency department: A systematic review. Ann Emerg Med. 2014;63(5): 551-560.e2. https://doi.org/10.1016/j.annemergmed.2013.11.010.
12. Han JH, Zimmerman EE, Cutler N, et al. Delirium in older emergency department pa- tients: recognition, risk factors, and psychomotor subtypes. Acad Emerg Med. 2009; 16(3):193-200. https://doi.org/10.1111/j.1553-2712.2008.00339.x.
13. Kennedy M, Enander RA, Tadiri SP, Wolfe RE, Shapiro NI, Marcantonio ER. Delirium risk prediction, healthcare use and mortality of elderly adults in the emergency de- partment. J Am Geriatr Soc. 2014;62(3):462-9. https://doi.org/10.1111/jgs.12692.
14. Israni J, Lesser A, Kent T, Ko K. Delirium as a predictor of mortality in US Medicare beneficiaries discharged from the emergency department: a national claims-level analysis up to 12 months. BMJ Open. 2018;8(5):e021258. https://doi.org/10.1136/ bmjopen-2017-021258.
15. von Elm E, Altman DG, Egger M, Pocock SJ, Gotzsche PC, Vandenbroucke JP. The strengthening the reporting of observational studies in epidemiology (STROBE) statement: guidelines for reporting observational studies. Ann Intern Med. 2007; 147(8):573-7. https://doi.org/10.7326/0003-4819-147-8-200710160-00010.
16. Silva L Oliveira JE, Stanich JA, Jeffery MM, et al. Association between emergency de- partment modifiable risk factors and subsequent delirium among hospitalized older adults. Am J Emerg Med. 2022;53:201-7. https://doi.org/10.1016/J.AJEM.2021.12. 032.
17. Han JH, Wilson A, Vasilevskis EE, et al. Diagnosing delirium in older emergency de- partment patients: validity and reliability of the delirium triage screen and the brief confusion assessment method. Ann Emerg Med. 2013;62(5):457-65. https://doi. org/10.1016/j.annemergmed.2013.05.003.
18. Baten V, Busch HJ, Busche C, et al. Validation of the brief confusion assessment method for screening delirium in elderly Medical patients in a German emergency department. Acad Emerg Med. 2018;25(11):1251-62. https://doi.org/10.1111/ acem.13449.
19. Inouye SK, Leo-Summers L, Zhang Y, Bogardus ST, Leslie DL, Agostini JV. A chart- based method for identification of delirium: validation compared with interviewer ratings using the confusion assessment method. J Am Geriatr Soc. 2005;53(2): 312-8. https://doi.org/10.1111/j.1532-5415.2005.53120.x.
20. Cole MG, Primeau FJ. Prognosis of delirium in elderly hospital patients. CMAJ. Can Med Assoc J. 1993;149(1):41. Accessed September 5, 2022. /pmc/articles/ PMC1485278/?report=abstract.
21. Aung Thein MZ, Pereira JV, Nitchingham A, Caplan GA. A call to action for delirium research: Meta-analysis and regression of delirium associated mortality. BMC Geriatr. 2020;20(1). https://doi.org/10.1186/S12877-020-01723-4.
22. McCoy TH, Snapper L, Stern TA, Perlis RH. Underreporting of delirium in statewide Claims data: implications for clinical care and predictive modeling. Psychosomatics. 2016;57(5):480-8. https://doi.org/10.1016/J.PSYM.2016.06.001.
23. Carpenter CR, Shelton E, Fowler S, et al. Risk factors and screening instruments to predict adverse outcomes for undifferentiated older emergency department pa- tients: a systematic review and meta-analysis. Acad Emerg Med. 2015 Jan;22(1): 1-21. https://doi.org/10.1111/acem.12569.
24. Stanich JA, Silva L Oliveira JE, Ginsburg AD, Mullan AF, Jeffery MM, Bellolio F. In- creased short-term mortality among patients presenting with altered mental status to the emergency department: A cohort study. Am J Emerg Med. 2022;51:290-5. https://doi.org/10.1016/J.AJEM.2021.10.034.
25. Hsieh SJ, Madahar P, Hope AA, Zapata J, Gong MN. Clinical deterioration in older adults with delirium during early hospitalisation: A prospective cohort study. BMJ Open. 2015;5(9). https://doi.org/10.1136/bmjopen-2014-007496.
26. Lee S, Chen H, Hibino S, et al. Can we improve delirium prevention and treatment in the emergency department? A systematic review. J Am Geriatr Soc. 2022;70(6): 1838-49. https://doi.org/10.1111/JGS.17740.
27. American Geriatrics Society. 2019 Updated AGS Beers criteria(R) for Potentially Inap- propriate Medication Use in Older Adults. J Am Geriatr Soc. 2019;67(4):674-94. https://doi.org/10.1111/JGS.15767.
28. Burton JK, Craig LE, Yong SQ, et al. Non-pharmacological interventions for prevent- ing delirium in hospitalised non-ICU patients. Cochrane Database Syst Rev. 2021;7

(7). https://doi.org/10.1002/14651858.CD013307.PUB2.