Sharon K. Inouye, MD, MPH

Delirium (acute confusion) is common in older adults and leads to poor outcomes, such as death, clinician and caregiver burden, and prolonged cognitive and functional decline.[1, 2, 3, 4] Delirium is extremely costly, with estimates ranging from $143 to $152 billion annually (2005 US$).[5, 6] Early detection and management may improve the poor outcomes and reduce costs attributable to delirium,[3, 7] yet delirium identification in clinical practice has been challenging, particularly when translating research tools to the bedside.[8, 9, 10]As a result, only 12% to 35% of delirium cases are detected in routine care, with hypoactive delirium and delirium superimposed on dementia most likely to be missed.[11, 12, 13, 14, 15]

To address these issues, we recently developed and published the three‐dimensional Confusion Assessment Method (3D‐CAM), the 3‐minute diagnostic assessment for CAM‐defined delirium.[16] The 3D‐CAM is a structured assessment tool that includes mental status testing, patient symptom probes, and guided interviewer observations for signs of delirium. 3D‐CAM items were selected through a rigorous process to determine the most informative items for the 4 CAM diagnostic features.[17] The 3D‐CAM can be completed in 3 minutes, and has 95% sensitivity and 94% specificity relative to a reference standard.[16]

Despite the capabilities of the 3D‐CAM, there are situations when even 3 minutes is too long to devote to delirium identification. Moreover, a 2‐step approach in which a sensitive ultrabrief screen is administered, followed by the 3D‐CAM in positives, may be the most efficient approach for large‐scale delirium case identification. The aim of the current study was to use the 3D‐CAM database to identify the most sensitive single item and pair of items in the diagnosis of delirium, using the reference standard in the diagnostic accuracy analysis. We hypothesized that we could identify a single item with greater than 80% sensitivity and a pair of items with greater than 90% sensitivity for detection of delirium.

METHODS

RESULTS

Characteristics of the patients are shown in Table 1. Subjects had a mean age of 84 years, 62% were female, and 28% had a baseline dementia. Forty‐two (21%) had delirium based on the clinical reference standard. Twenty (10%) had less than a high school education and 100 (49%) had at least a college education.

DISCUSSION

Identifying simple, efficient, bedside case‐identification methods for delirium is an essential step toward improving recognition of this highly morbid syndrome in hospitalized older adults. In this study, we identified a single cognitive item, Months of the year backwards, that identified 83% of delirium cases when compared with a reference standard diagnosis. Furthermore, we identified 2 items, Months of the year backwards and What is the day of the week? which when used in combination identified 93% of delirium cases. The same 1 and 2 items also worked well in patients with dementia, in whom delirium is often missed. Although these items require further clinical validation, the development of an ultrabrief 2‐item test that identifies over 90% of delirium cases and can be completed in less than 1 minute (recently, we administered the best 2‐item screener to 20 consecutive general medicine patients over age 70 years, and it was completed in a median of 36.5 seconds), holds great potential for simplifying bedside delirium screening and improving the care of hospitalized older adults.

Our current findings both confirm and extend the emerging literature on best screening items for delirium. Sands and colleagues (2010)[26] tested a single test for delirium, Do you think (name of patient) has been more confused lately? in 21 subjects and achieved a sensitivity of 80%. Han and colleagues developed a screening tool in emergency‐department patients using the LOC question from the Richmond Agitation‐Sedation Scale and spelling the word lunch backwards, and achieved 98% sensitivity, but in a younger emergency department population with a low prevalence of dementia.[27] O'Regan et al. recently also found Months of the year backwards to be the best single‐screening item for delirium in a large sample, but only tested a 1‐item screen.[28] Our study extends these studies in several important ways by: (1) employing a rigorous clinical reference standard diagnosis of delirium, (2) having a large sample with a high prevalence of patients with dementia, (3) use of a general medical population, and (4) examining the best 2‐item screens in addition to the best single item.

Systematic intervention programs[29, 30, 31] that focus on improved delirium evaluation and management have the potential to improve patient outcomes and reduce costs. However, targeting these programs to patients with delirium has proven difficult, as only 12% to 35% of delirium cases are recognized in routine clinical practice.[11, 12, 13, 14, 15] The 1‐ and 2‐item screeners we identified could play an important role in future delirium identification. The 3D‐CAM combines high sensitivity (95%) with high specificity (94%)[16] and therefore would be an excellent choice as the second step after a positive screen. The feasibility, effectiveness, and cost of administering these screeners, followed by a brief diagnostic tool such as the 3D‐CAM, should be evaluated in future work.

Our study has noteworthy strengths, including the use of a large purposefully challenging clinical sample with advanced age that included a substantial proportion with dementia, a detailed assessment, and the testing of very brief and practical tools for bedside delirium screening.[25] This study also has several important limitations. Most importantly, we presented secondary analysis of individual items and pairs of items drawn from the 3D CAM assessment; therefore, the 2‐item bedside screen requires prospective clinical validation. The reference standard was based on the DSM‐IV, because this study was conducted prior to the release of DSM‐V. In addition, the ordering of the reference standard and 3D‐CAM assessments was not randomized due to feasibility constraints. In addition, this study was cross‐sectional, involved only a single hospital, and enrolled only older medical patients during the day shift. Our sample was older (aged 75 years and older), and a younger sample may have had a different prevalence of delirium, which could affect the positive predictive value of our ultrabrief screen. We plan to test this in a sample of patients aged 70 years and older in future studies. Finally, it should be noted that these best 1‐item and 2‐item screeners miss 17% and 7% of delirium cases, respectively. In cases where this is unacceptably high, alternative approaches might be necessary.

It is important to remember that these 1‐ and 2‐item screeners are not diagnostic tools and therefore should not be used in isolation. Optimally, they will be followed by a more specific evaluation, such as the 3D‐CAM, as part of a systematic delirium identification process. For instance, in our sample (with a delirium rate of 21%), the best 2‐item screener had a positive predictive value of 41%, meaning that positive screens are more likely to be false positives than true positives (see Supporting Tables 2 and 3 in the online version of this article).[32] Nevertheless, by reducing the total number of patients who require diagnostic instrument administration, use of these ultrabrief screeners can improve efficiency and result in a net benefit to delirium case‐identification efforts.[32]

Time has been demonstrated to be a barrier to delirium identification in previous studies, but there are likely others. These may include, for instance, staff nihilism about screening making a difference, ambiguous responsibility for delirium screening and management, unsupportive system leadership, and absent payment for these activities.[31] Moreover, it is possible that the 2‐step process we propose may create an incentive for staff to avoid positive screens as they see it creating more work for themselves. We plan to identify and address such barriers in our future work.

In conclusion, we identified a single screening item for delirium, Months of the year backwards, with 83% sensitivity, and a pair of items, Months of the year backwards and What is the day of the week?, with 93% sensitivity relative to a rigorous reference standard diagnosis. These ultrabrief screening items work well in patients with and without dementia, and should require very little training of staff. Future studies should further validate these tools, and determine their translatability and scalability into programs for systematic, widespread delirium detection. Developing efficient and accurate case identification strategies is a necessary prerequisite to appropriately target delirium management protocols, enabling healthcare systems to effectively address this costly and deadly condition.

Delirium (acute confusion) is common in older adults and leads to poor outcomes, such as death, clinician and caregiver burden, and prolonged cognitive and functional decline.[1, 2, 3, 4] Delirium is extremely costly, with estimates ranging from $143 to $152 billion annually (2005 US$).[5, 6] Early detection and management may improve the poor outcomes and reduce costs attributable to delirium,[3, 7] yet delirium identification in clinical practice has been challenging, particularly when translating research tools to the bedside.[8, 9, 10]As a result, only 12% to 35% of delirium cases are detected in routine care, with hypoactive delirium and delirium superimposed on dementia most likely to be missed.[11, 12, 13, 14, 15]

To address these issues, we recently developed and published the three‐dimensional Confusion Assessment Method (3D‐CAM), the 3‐minute diagnostic assessment for CAM‐defined delirium.[16] The 3D‐CAM is a structured assessment tool that includes mental status testing, patient symptom probes, and guided interviewer observations for signs of delirium. 3D‐CAM items were selected through a rigorous process to determine the most informative items for the 4 CAM diagnostic features.[17] The 3D‐CAM can be completed in 3 minutes, and has 95% sensitivity and 94% specificity relative to a reference standard.[16]

Despite the capabilities of the 3D‐CAM, there are situations when even 3 minutes is too long to devote to delirium identification. Moreover, a 2‐step approach in which a sensitive ultrabrief screen is administered, followed by the 3D‐CAM in positives, may be the most efficient approach for large‐scale delirium case identification. The aim of the current study was to use the 3D‐CAM database to identify the most sensitive single item and pair of items in the diagnosis of delirium, using the reference standard in the diagnostic accuracy analysis. We hypothesized that we could identify a single item with greater than 80% sensitivity and a pair of items with greater than 90% sensitivity for detection of delirium.

METHODS

RESULTS

Characteristics of the patients are shown in Table 1. Subjects had a mean age of 84 years, 62% were female, and 28% had a baseline dementia. Forty‐two (21%) had delirium based on the clinical reference standard. Twenty (10%) had less than a high school education and 100 (49%) had at least a college education.

DISCUSSION

Identifying simple, efficient, bedside case‐identification methods for delirium is an essential step toward improving recognition of this highly morbid syndrome in hospitalized older adults. In this study, we identified a single cognitive item, Months of the year backwards, that identified 83% of delirium cases when compared with a reference standard diagnosis. Furthermore, we identified 2 items, Months of the year backwards and What is the day of the week? which when used in combination identified 93% of delirium cases. The same 1 and 2 items also worked well in patients with dementia, in whom delirium is often missed. Although these items require further clinical validation, the development of an ultrabrief 2‐item test that identifies over 90% of delirium cases and can be completed in less than 1 minute (recently, we administered the best 2‐item screener to 20 consecutive general medicine patients over age 70 years, and it was completed in a median of 36.5 seconds), holds great potential for simplifying bedside delirium screening and improving the care of hospitalized older adults.

Our current findings both confirm and extend the emerging literature on best screening items for delirium. Sands and colleagues (2010)[26] tested a single test for delirium, Do you think (name of patient) has been more confused lately? in 21 subjects and achieved a sensitivity of 80%. Han and colleagues developed a screening tool in emergency‐department patients using the LOC question from the Richmond Agitation‐Sedation Scale and spelling the word lunch backwards, and achieved 98% sensitivity, but in a younger emergency department population with a low prevalence of dementia.[27] O'Regan et al. recently also found Months of the year backwards to be the best single‐screening item for delirium in a large sample, but only tested a 1‐item screen.[28] Our study extends these studies in several important ways by: (1) employing a rigorous clinical reference standard diagnosis of delirium, (2) having a large sample with a high prevalence of patients with dementia, (3) use of a general medical population, and (4) examining the best 2‐item screens in addition to the best single item.

Systematic intervention programs[29, 30, 31] that focus on improved delirium evaluation and management have the potential to improve patient outcomes and reduce costs. However, targeting these programs to patients with delirium has proven difficult, as only 12% to 35% of delirium cases are recognized in routine clinical practice.[11, 12, 13, 14, 15] The 1‐ and 2‐item screeners we identified could play an important role in future delirium identification. The 3D‐CAM combines high sensitivity (95%) with high specificity (94%)[16] and therefore would be an excellent choice as the second step after a positive screen. The feasibility, effectiveness, and cost of administering these screeners, followed by a brief diagnostic tool such as the 3D‐CAM, should be evaluated in future work.

Our study has noteworthy strengths, including the use of a large purposefully challenging clinical sample with advanced age that included a substantial proportion with dementia, a detailed assessment, and the testing of very brief and practical tools for bedside delirium screening.[25] This study also has several important limitations. Most importantly, we presented secondary analysis of individual items and pairs of items drawn from the 3D CAM assessment; therefore, the 2‐item bedside screen requires prospective clinical validation. The reference standard was based on the DSM‐IV, because this study was conducted prior to the release of DSM‐V. In addition, the ordering of the reference standard and 3D‐CAM assessments was not randomized due to feasibility constraints. In addition, this study was cross‐sectional, involved only a single hospital, and enrolled only older medical patients during the day shift. Our sample was older (aged 75 years and older), and a younger sample may have had a different prevalence of delirium, which could affect the positive predictive value of our ultrabrief screen. We plan to test this in a sample of patients aged 70 years and older in future studies. Finally, it should be noted that these best 1‐item and 2‐item screeners miss 17% and 7% of delirium cases, respectively. In cases where this is unacceptably high, alternative approaches might be necessary.

It is important to remember that these 1‐ and 2‐item screeners are not diagnostic tools and therefore should not be used in isolation. Optimally, they will be followed by a more specific evaluation, such as the 3D‐CAM, as part of a systematic delirium identification process. For instance, in our sample (with a delirium rate of 21%), the best 2‐item screener had a positive predictive value of 41%, meaning that positive screens are more likely to be false positives than true positives (see Supporting Tables 2 and 3 in the online version of this article).[32] Nevertheless, by reducing the total number of patients who require diagnostic instrument administration, use of these ultrabrief screeners can improve efficiency and result in a net benefit to delirium case‐identification efforts.[32]

Time has been demonstrated to be a barrier to delirium identification in previous studies, but there are likely others. These may include, for instance, staff nihilism about screening making a difference, ambiguous responsibility for delirium screening and management, unsupportive system leadership, and absent payment for these activities.[31] Moreover, it is possible that the 2‐step process we propose may create an incentive for staff to avoid positive screens as they see it creating more work for themselves. We plan to identify and address such barriers in our future work.

In conclusion, we identified a single screening item for delirium, Months of the year backwards, with 83% sensitivity, and a pair of items, Months of the year backwards and What is the day of the week?, with 93% sensitivity relative to a rigorous reference standard diagnosis. These ultrabrief screening items work well in patients with and without dementia, and should require very little training of staff. Future studies should further validate these tools, and determine their translatability and scalability into programs for systematic, widespread delirium detection. Developing efficient and accurate case identification strategies is a necessary prerequisite to appropriately target delirium management protocols, enabling healthcare systems to effectively address this costly and deadly condition.

Delirium (acute confusion) is common in older adults and leads to poor outcomes, such as death, clinician and caregiver burden, and prolonged cognitive and functional decline.[1, 2, 3, 4] Delirium is extremely costly, with estimates ranging from $143 to $152 billion annually (2005 US$).[5, 6] Early detection and management may improve the poor outcomes and reduce costs attributable to delirium,[3, 7] yet delirium identification in clinical practice has been challenging, particularly when translating research tools to the bedside.[8, 9, 10]As a result, only 12% to 35% of delirium cases are detected in routine care, with hypoactive delirium and delirium superimposed on dementia most likely to be missed.[11, 12, 13, 14, 15]

To address these issues, we recently developed and published the three‐dimensional Confusion Assessment Method (3D‐CAM), the 3‐minute diagnostic assessment for CAM‐defined delirium.[16] The 3D‐CAM is a structured assessment tool that includes mental status testing, patient symptom probes, and guided interviewer observations for signs of delirium. 3D‐CAM items were selected through a rigorous process to determine the most informative items for the 4 CAM diagnostic features.[17] The 3D‐CAM can be completed in 3 minutes, and has 95% sensitivity and 94% specificity relative to a reference standard.[16]

Despite the capabilities of the 3D‐CAM, there are situations when even 3 minutes is too long to devote to delirium identification. Moreover, a 2‐step approach in which a sensitive ultrabrief screen is administered, followed by the 3D‐CAM in positives, may be the most efficient approach for large‐scale delirium case identification. The aim of the current study was to use the 3D‐CAM database to identify the most sensitive single item and pair of items in the diagnosis of delirium, using the reference standard in the diagnostic accuracy analysis. We hypothesized that we could identify a single item with greater than 80% sensitivity and a pair of items with greater than 90% sensitivity for detection of delirium.

METHODS

RESULTS

Characteristics of the patients are shown in Table 1. Subjects had a mean age of 84 years, 62% were female, and 28% had a baseline dementia. Forty‐two (21%) had delirium based on the clinical reference standard. Twenty (10%) had less than a high school education and 100 (49%) had at least a college education.

DISCUSSION

Identifying simple, efficient, bedside case‐identification methods for delirium is an essential step toward improving recognition of this highly morbid syndrome in hospitalized older adults. In this study, we identified a single cognitive item, Months of the year backwards, that identified 83% of delirium cases when compared with a reference standard diagnosis. Furthermore, we identified 2 items, Months of the year backwards and What is the day of the week? which when used in combination identified 93% of delirium cases. The same 1 and 2 items also worked well in patients with dementia, in whom delirium is often missed. Although these items require further clinical validation, the development of an ultrabrief 2‐item test that identifies over 90% of delirium cases and can be completed in less than 1 minute (recently, we administered the best 2‐item screener to 20 consecutive general medicine patients over age 70 years, and it was completed in a median of 36.5 seconds), holds great potential for simplifying bedside delirium screening and improving the care of hospitalized older adults.

Our current findings both confirm and extend the emerging literature on best screening items for delirium. Sands and colleagues (2010)[26] tested a single test for delirium, Do you think (name of patient) has been more confused lately? in 21 subjects and achieved a sensitivity of 80%. Han and colleagues developed a screening tool in emergency‐department patients using the LOC question from the Richmond Agitation‐Sedation Scale and spelling the word lunch backwards, and achieved 98% sensitivity, but in a younger emergency department population with a low prevalence of dementia.[27] O'Regan et al. recently also found Months of the year backwards to be the best single‐screening item for delirium in a large sample, but only tested a 1‐item screen.[28] Our study extends these studies in several important ways by: (1) employing a rigorous clinical reference standard diagnosis of delirium, (2) having a large sample with a high prevalence of patients with dementia, (3) use of a general medical population, and (4) examining the best 2‐item screens in addition to the best single item.

Systematic intervention programs[29, 30, 31] that focus on improved delirium evaluation and management have the potential to improve patient outcomes and reduce costs. However, targeting these programs to patients with delirium has proven difficult, as only 12% to 35% of delirium cases are recognized in routine clinical practice.[11, 12, 13, 14, 15] The 1‐ and 2‐item screeners we identified could play an important role in future delirium identification. The 3D‐CAM combines high sensitivity (95%) with high specificity (94%)[16] and therefore would be an excellent choice as the second step after a positive screen. The feasibility, effectiveness, and cost of administering these screeners, followed by a brief diagnostic tool such as the 3D‐CAM, should be evaluated in future work.

Our study has noteworthy strengths, including the use of a large purposefully challenging clinical sample with advanced age that included a substantial proportion with dementia, a detailed assessment, and the testing of very brief and practical tools for bedside delirium screening.[25] This study also has several important limitations. Most importantly, we presented secondary analysis of individual items and pairs of items drawn from the 3D CAM assessment; therefore, the 2‐item bedside screen requires prospective clinical validation. The reference standard was based on the DSM‐IV, because this study was conducted prior to the release of DSM‐V. In addition, the ordering of the reference standard and 3D‐CAM assessments was not randomized due to feasibility constraints. In addition, this study was cross‐sectional, involved only a single hospital, and enrolled only older medical patients during the day shift. Our sample was older (aged 75 years and older), and a younger sample may have had a different prevalence of delirium, which could affect the positive predictive value of our ultrabrief screen. We plan to test this in a sample of patients aged 70 years and older in future studies. Finally, it should be noted that these best 1‐item and 2‐item screeners miss 17% and 7% of delirium cases, respectively. In cases where this is unacceptably high, alternative approaches might be necessary.

It is important to remember that these 1‐ and 2‐item screeners are not diagnostic tools and therefore should not be used in isolation. Optimally, they will be followed by a more specific evaluation, such as the 3D‐CAM, as part of a systematic delirium identification process. For instance, in our sample (with a delirium rate of 21%), the best 2‐item screener had a positive predictive value of 41%, meaning that positive screens are more likely to be false positives than true positives (see Supporting Tables 2 and 3 in the online version of this article).[32] Nevertheless, by reducing the total number of patients who require diagnostic instrument administration, use of these ultrabrief screeners can improve efficiency and result in a net benefit to delirium case‐identification efforts.[32]

Time has been demonstrated to be a barrier to delirium identification in previous studies, but there are likely others. These may include, for instance, staff nihilism about screening making a difference, ambiguous responsibility for delirium screening and management, unsupportive system leadership, and absent payment for these activities.[31] Moreover, it is possible that the 2‐step process we propose may create an incentive for staff to avoid positive screens as they see it creating more work for themselves. We plan to identify and address such barriers in our future work.

In conclusion, we identified a single screening item for delirium, Months of the year backwards, with 83% sensitivity, and a pair of items, Months of the year backwards and What is the day of the week?, with 93% sensitivity relative to a rigorous reference standard diagnosis. These ultrabrief screening items work well in patients with and without dementia, and should require very little training of staff. Future studies should further validate these tools, and determine their translatability and scalability into programs for systematic, widespread delirium detection. Developing efficient and accurate case identification strategies is a necessary prerequisite to appropriately target delirium management protocols, enabling healthcare systems to effectively address this costly and deadly condition.

Much attention has been given recently to hospitalized older adults, the critical 30‐day period, and posthospital syndrome.[1] What is missing from this dialogue is the contribution and significance of underlying cognitive impairment. By 2050, 14 million older persons in the United States are expected to have dementia.[2] Increasing numbers of older adults diagnosed with dementia are hospitalized and are at increased risk of developing delirium; in fact, delirium occurs in over half of hospitalized persons with dementia.[3] Further, current evidence suggests that delirium may accelerate the clinical course and trajectory of cognitive decline, and may be associated with considerably worse long‐term outcomes, including prolonged hospitalization, rehospitalization within 30 days, nursing home placement, and death.[3, 4, 5, 6] However, the problem of delirium superimposed on dementia (DSD) remains a neglected area of investigation in hospitalized patients. Delirium is superimposed on dementia when an acute change in mental status (characterized by a fluctuating course, inattention, and either disorganized thinking or altered level of consciousness) is layered on top of preexisting dementia.[4]

Despite the poor outcomes and high prevalence of DSD, little is known about the natural history in hospitalized older adults with dementia. Delirium studies often exclude persons with dementia, even though the prevalence of DSD is extremely high in both community (13%19%) and hospital (40%89%) populations and associated with higher costs and utilization compared to dementia and delirium alone.[4, 5, 7] In 1 study, annual costs for DSD were $9566 compared to $7557 for dementia alone.[7] The few risk‐factor studies of DSD were conducted in intensive care unit (ICU) or long‐term care settings.[8, 9]

The purpose of this study was to describe the incidence, risk factors, and outcomes associated with incident delirium in a prospective cohort of hospitalized older adults with dementia. The study aims were to: (1) estimate the incidence of new delirium in hospitalized persons with dementia, (2) identify the risk factors associated with incident delirium superimposed on dementia in this sample, (3) describe the outcomes associated with development of delirium, and (4) evaluate the contributions of delirium severity and duration to outcomes.

METHODS

This 24‐month prospective cohort study recruited and enrolled consecutive hospital admissions with dementia in a 300‐bed community hospital in central Pennsylvania from July 2006 through November 2008. Data were collected daily from patients during hospitalization, followed by a 1‐month posthospitalization interview with patients and their caregivers in the community setting. Patients were included if they spoke English, had been hospitalized fewer than 24 hours, and met the screening criteria for dementia. Patients were excluded if they had any significant neurological condition associated with cognitive impairment other than dementia (eg, brain tumor), a major acute psychiatric disorder, were unable to communicate, or had no caregiver to interview. The interviewers included experienced research assistants (RAs) who were either registered nurses or trained in a health‐related field. All staff training of instruments were done with scripted training manuals and video training using manuals for the Confusion Assessment Method (CAM). After training was completed, final inter‐rater reliability assessments were conducted until staff reached 100% agreement. The RAs were blinded to the aims and completed over 10 hours of training. Inter‐rater reliability checks were conducted on 10% of the sample in the field with >90% agreement attained on all instruments. This study was reviewed by and approved by The Pennsylvania State University institutional review board, and consent was received from all subjects.

RESULTS

Of 256 eligible patients, dual consent was obtained from 154 patient and 154 family research subjects (308 consents). The refusal rate was 39% (n=102). Fourteen subjects were consented and enrolled but later dropped out due to family/proxy concerns regarding the patient's ability to participate in interviews. Thus, the final sample included 139 patients.

Descriptive statistics for baseline measures are given in Table 1. Briefly, the average age of subjects was 83 years (standard deviation [SD]=7); 41% were male; 57% were single, divorced, or widowed; and the average number of years of education was 12 years (SD=3). Thirty‐three percent were dehydrated on admission, and 33% had fallen within 2 weeks prior to admission. Thirty‐four percent had an infection at baseline, and 36% had some sensory impairment.

The overall incidence of delirium was 32% (44/139) and the range of days to incident delirium was 1 to 8 days. During the baseline period (Table 1), subjects with delirium were older, more likely to be male, had lower Katz impairment scores, higher GDS score, lower MMSE scores on admission, and higher Blessed scores than subjects without delirium. Slightly more persons with delirium had a prior fall, although the RR was not statistically significant. Length of stay measured at discharge was significantly higher for those with delirium (mean=9.1) than those without delirium (mean=5.7) (P<0.0001). Subjects with delirium were more likely to have died at 1 month than those without delirium (P=0.0153).

In addition, we analyzed the adjusted relative risk estimates for the final model of incident delirium. Significant risk factors or risk factors with RR estimates at least 1.5 (or <0.66 if protective [Table 1]) that were examined in a more comprehensive multiple proportional hazards model included age, gender, having had a fall in the last 2 weeks, number of impaired ADLs (based on Katz), GDS scores, MMSE scores at baseline, and Blessed scores at baseline. The final proportional hazards included gender and GDS score. Males were nearly 1.8 times as likely to develop delirium than females, and for every 1 unit increase in the GDS, subjects were 1.5 times more likely to develop delirium.

Finally, Table 2 gives the results of examining outcomes related to incident delirium measures. For mortality, there were no statistically significant predictors of death after controlling for age, gender, or GDS. For length of stay, subjects with incident delirium had significantly longer lengths of stay, as incident delirium severity increased by 1 unit the length of stay increased by 0.4 days, and as the number of inpatient days with delirium increased by 1 day the length of stay increased by 1.8 days. For change in the impaired Katz ADLs from admission to follow‐up, as incident delirium severity increased by 1 unit the change in impaired Katz ADLs increased by 0.05 units.

DISCUSSION

The most compelling finding from this study is the high incidence of delirium in hospitalized older adults with dementia and the association with poor clinical outcomes in those who develop delirium superimposed on dementia. DSD is difficult to detect and prevent; persons with DSD are at risk for poor quality of life. Those with delirium had a 25% short‐term mortality rate (P=0.0153), substantially increased length of stay (9.1 vs 5.1 days with an odds ratio of 1.8) and poorer physical function at discharge and follow‐up. At 1 month follow‐up, subjects with delirium had greater functional decline and lower GDS scores than those without delirium.

The incidence of delirium in this study was high (32%). Being delirious any time was associated with death and poor function. Delirium was also associated with the stage of the persons' baseline dementia, advanced age, lower MMSE scores, and falling before admission.

Previous studies have found delirium associated with increased mortality. Three studies found that within 1 year of a delirium episode, a significant number of persons died or were institutionalized.[24, 25, 26] Other research has reported death within 1 year of documented delirium episodes, and a 3‐fold increased rate of death in the ICU.[24, 27, 28, 29, 30, 31, 32] This study is 1 of only a few to focus on increased mortality with DSD and to focus uniquely on hospitalized patients with delirium and dementia.

The main risk factors for delirium in this study were male sex and severity of dementia. Our results, combined with those from other recent studies by Voyer and colleagues,[8, 33, 34] point to the critical importance of screening for dementia in hospitalized older adults as dementia severity is a significant indicator of delirium severity. For instance, Voyer and colleagues[34] reported that persons with mild dementia were likely to experience a mild delirium, whereas those with a more severe level of dementia were more likely to experience moderate to severe delirium. Our findings show that those who experienced episodes of delirium represented a highly vulnerable population with advanced dementia, sensory impairment, more falls and dehydration at admission, and higher Blessed scores. A recent study by Saczynski and colleagues[35] found 40% of patients who had experienced postoperative delirium did not return to their baseline at 6 months. Clearly, preventing delirium should be a critical priority to prevent such deterioration in the highly vulnerable population of hospitalized patients with dementia.

Patients in this study were on a mean of over 11 medications. One‐third of dementia patients in our study had also experienced a fall and dehydration at baseline. Other studies have found a relationship between cognitive decline, falling, and medications.[36] Many of these patients came into the hospital with potentially modifiable and preventable community or ambulatory care conditions of polypharmacy, falling, sensory impairment, and dehydration.

Importantly, in our study, length of stay was significantly higher (9.1 vs 5.7) for those with delirium compared to those without delirium. This finding is alarming when examining the economic impact of preventing delirium. Previous studies have found the cost of delirious episodes rivals those for diabetes and heart disease, and that decreasing length of stay by just 1 day would save over $20 million dollars per year.[4, 37]

In summary, this study is 1 of the first to report a high incidence of DSD and poorer outcomes for persons who experience delirium compared to those with dementia alone. This is 1 of only a few studies examining unique risk factors and delirium severity for DSD in the acute care setting. Findings from the current study report potential risk factors for development of incident delirium and highlight the challenge of preventing DSD before and during hospitalization. The generalizability of this study may be limited by the use of a nondiverse study population drawn from a single hospital in the northeast United States, though the use of a community hospital increases the relevance to real‐world practice settings. Determination of baseline cognitive status and the differentiation of delirium and dementia are difficult, but validated, state‐of‐the‐art methods were used that have been applied in previous studies.

This study provides fundamental methodological improvements over previous work, and advances the science by providing valuable data on the natural history, correlates, and outcomes of DSD. The strengths of this study include the prospective cohort design, the daily assessment for delirium based on a 24‐hour period, methods for determining cognitive status at baseline in this difficult population, and utilizing strict blinding of the well‐trained outcome assessors.

This study lays the groundwork for future studies to improve care for persons with dementia who present to acute care and to plan prevention programs for delirium before they are admitted to the hospital. We must be able to translate best practice for DSD into the acute care and community settings to prevent or minimize effects of delirium in persons with dementia. Interventions to increase early detection of delirium by hospital staff have the potential to decrease the severity and duration of delirium and prevent unnecessary suffering and costs from the complications of delirium and preventable readmissions to the hospital.

Thus, this study holds substantial clinical and economic implications for this population in the acute care setting, and will direct future studies leading to changes in real‐world practice settings for persons with dementia.

Much attention has been given recently to hospitalized older adults, the critical 30‐day period, and posthospital syndrome.[1] What is missing from this dialogue is the contribution and significance of underlying cognitive impairment. By 2050, 14 million older persons in the United States are expected to have dementia.[2] Increasing numbers of older adults diagnosed with dementia are hospitalized and are at increased risk of developing delirium; in fact, delirium occurs in over half of hospitalized persons with dementia.[3] Further, current evidence suggests that delirium may accelerate the clinical course and trajectory of cognitive decline, and may be associated with considerably worse long‐term outcomes, including prolonged hospitalization, rehospitalization within 30 days, nursing home placement, and death.[3, 4, 5, 6] However, the problem of delirium superimposed on dementia (DSD) remains a neglected area of investigation in hospitalized patients. Delirium is superimposed on dementia when an acute change in mental status (characterized by a fluctuating course, inattention, and either disorganized thinking or altered level of consciousness) is layered on top of preexisting dementia.[4]

Despite the poor outcomes and high prevalence of DSD, little is known about the natural history in hospitalized older adults with dementia. Delirium studies often exclude persons with dementia, even though the prevalence of DSD is extremely high in both community (13%19%) and hospital (40%89%) populations and associated with higher costs and utilization compared to dementia and delirium alone.[4, 5, 7] In 1 study, annual costs for DSD were $9566 compared to $7557 for dementia alone.[7] The few risk‐factor studies of DSD were conducted in intensive care unit (ICU) or long‐term care settings.[8, 9]

The purpose of this study was to describe the incidence, risk factors, and outcomes associated with incident delirium in a prospective cohort of hospitalized older adults with dementia. The study aims were to: (1) estimate the incidence of new delirium in hospitalized persons with dementia, (2) identify the risk factors associated with incident delirium superimposed on dementia in this sample, (3) describe the outcomes associated with development of delirium, and (4) evaluate the contributions of delirium severity and duration to outcomes.

METHODS

This 24‐month prospective cohort study recruited and enrolled consecutive hospital admissions with dementia in a 300‐bed community hospital in central Pennsylvania from July 2006 through November 2008. Data were collected daily from patients during hospitalization, followed by a 1‐month posthospitalization interview with patients and their caregivers in the community setting. Patients were included if they spoke English, had been hospitalized fewer than 24 hours, and met the screening criteria for dementia. Patients were excluded if they had any significant neurological condition associated with cognitive impairment other than dementia (eg, brain tumor), a major acute psychiatric disorder, were unable to communicate, or had no caregiver to interview. The interviewers included experienced research assistants (RAs) who were either registered nurses or trained in a health‐related field. All staff training of instruments were done with scripted training manuals and video training using manuals for the Confusion Assessment Method (CAM). After training was completed, final inter‐rater reliability assessments were conducted until staff reached 100% agreement. The RAs were blinded to the aims and completed over 10 hours of training. Inter‐rater reliability checks were conducted on 10% of the sample in the field with >90% agreement attained on all instruments. This study was reviewed by and approved by The Pennsylvania State University institutional review board, and consent was received from all subjects.

RESULTS

Of 256 eligible patients, dual consent was obtained from 154 patient and 154 family research subjects (308 consents). The refusal rate was 39% (n=102). Fourteen subjects were consented and enrolled but later dropped out due to family/proxy concerns regarding the patient's ability to participate in interviews. Thus, the final sample included 139 patients.

Descriptive statistics for baseline measures are given in Table 1. Briefly, the average age of subjects was 83 years (standard deviation [SD]=7); 41% were male; 57% were single, divorced, or widowed; and the average number of years of education was 12 years (SD=3). Thirty‐three percent were dehydrated on admission, and 33% had fallen within 2 weeks prior to admission. Thirty‐four percent had an infection at baseline, and 36% had some sensory impairment.

The overall incidence of delirium was 32% (44/139) and the range of days to incident delirium was 1 to 8 days. During the baseline period (Table 1), subjects with delirium were older, more likely to be male, had lower Katz impairment scores, higher GDS score, lower MMSE scores on admission, and higher Blessed scores than subjects without delirium. Slightly more persons with delirium had a prior fall, although the RR was not statistically significant. Length of stay measured at discharge was significantly higher for those with delirium (mean=9.1) than those without delirium (mean=5.7) (P<0.0001). Subjects with delirium were more likely to have died at 1 month than those without delirium (P=0.0153).

In addition, we analyzed the adjusted relative risk estimates for the final model of incident delirium. Significant risk factors or risk factors with RR estimates at least 1.5 (or <0.66 if protective [Table 1]) that were examined in a more comprehensive multiple proportional hazards model included age, gender, having had a fall in the last 2 weeks, number of impaired ADLs (based on Katz), GDS scores, MMSE scores at baseline, and Blessed scores at baseline. The final proportional hazards included gender and GDS score. Males were nearly 1.8 times as likely to develop delirium than females, and for every 1 unit increase in the GDS, subjects were 1.5 times more likely to develop delirium.

Finally, Table 2 gives the results of examining outcomes related to incident delirium measures. For mortality, there were no statistically significant predictors of death after controlling for age, gender, or GDS. For length of stay, subjects with incident delirium had significantly longer lengths of stay, as incident delirium severity increased by 1 unit the length of stay increased by 0.4 days, and as the number of inpatient days with delirium increased by 1 day the length of stay increased by 1.8 days. For change in the impaired Katz ADLs from admission to follow‐up, as incident delirium severity increased by 1 unit the change in impaired Katz ADLs increased by 0.05 units.

DISCUSSION

The most compelling finding from this study is the high incidence of delirium in hospitalized older adults with dementia and the association with poor clinical outcomes in those who develop delirium superimposed on dementia. DSD is difficult to detect and prevent; persons with DSD are at risk for poor quality of life. Those with delirium had a 25% short‐term mortality rate (P=0.0153), substantially increased length of stay (9.1 vs 5.1 days with an odds ratio of 1.8) and poorer physical function at discharge and follow‐up. At 1 month follow‐up, subjects with delirium had greater functional decline and lower GDS scores than those without delirium.

The incidence of delirium in this study was high (32%). Being delirious any time was associated with death and poor function. Delirium was also associated with the stage of the persons' baseline dementia, advanced age, lower MMSE scores, and falling before admission.

Previous studies have found delirium associated with increased mortality. Three studies found that within 1 year of a delirium episode, a significant number of persons died or were institutionalized.[24, 25, 26] Other research has reported death within 1 year of documented delirium episodes, and a 3‐fold increased rate of death in the ICU.[24, 27, 28, 29, 30, 31, 32] This study is 1 of only a few to focus on increased mortality with DSD and to focus uniquely on hospitalized patients with delirium and dementia.

The main risk factors for delirium in this study were male sex and severity of dementia. Our results, combined with those from other recent studies by Voyer and colleagues,[8, 33, 34] point to the critical importance of screening for dementia in hospitalized older adults as dementia severity is a significant indicator of delirium severity. For instance, Voyer and colleagues[34] reported that persons with mild dementia were likely to experience a mild delirium, whereas those with a more severe level of dementia were more likely to experience moderate to severe delirium. Our findings show that those who experienced episodes of delirium represented a highly vulnerable population with advanced dementia, sensory impairment, more falls and dehydration at admission, and higher Blessed scores. A recent study by Saczynski and colleagues[35] found 40% of patients who had experienced postoperative delirium did not return to their baseline at 6 months. Clearly, preventing delirium should be a critical priority to prevent such deterioration in the highly vulnerable population of hospitalized patients with dementia.

Patients in this study were on a mean of over 11 medications. One‐third of dementia patients in our study had also experienced a fall and dehydration at baseline. Other studies have found a relationship between cognitive decline, falling, and medications.[36] Many of these patients came into the hospital with potentially modifiable and preventable community or ambulatory care conditions of polypharmacy, falling, sensory impairment, and dehydration.

Importantly, in our study, length of stay was significantly higher (9.1 vs 5.7) for those with delirium compared to those without delirium. This finding is alarming when examining the economic impact of preventing delirium. Previous studies have found the cost of delirious episodes rivals those for diabetes and heart disease, and that decreasing length of stay by just 1 day would save over $20 million dollars per year.[4, 37]

In summary, this study is 1 of the first to report a high incidence of DSD and poorer outcomes for persons who experience delirium compared to those with dementia alone. This is 1 of only a few studies examining unique risk factors and delirium severity for DSD in the acute care setting. Findings from the current study report potential risk factors for development of incident delirium and highlight the challenge of preventing DSD before and during hospitalization. The generalizability of this study may be limited by the use of a nondiverse study population drawn from a single hospital in the northeast United States, though the use of a community hospital increases the relevance to real‐world practice settings. Determination of baseline cognitive status and the differentiation of delirium and dementia are difficult, but validated, state‐of‐the‐art methods were used that have been applied in previous studies.

This study provides fundamental methodological improvements over previous work, and advances the science by providing valuable data on the natural history, correlates, and outcomes of DSD. The strengths of this study include the prospective cohort design, the daily assessment for delirium based on a 24‐hour period, methods for determining cognitive status at baseline in this difficult population, and utilizing strict blinding of the well‐trained outcome assessors.

This study lays the groundwork for future studies to improve care for persons with dementia who present to acute care and to plan prevention programs for delirium before they are admitted to the hospital. We must be able to translate best practice for DSD into the acute care and community settings to prevent or minimize effects of delirium in persons with dementia. Interventions to increase early detection of delirium by hospital staff have the potential to decrease the severity and duration of delirium and prevent unnecessary suffering and costs from the complications of delirium and preventable readmissions to the hospital.

Thus, this study holds substantial clinical and economic implications for this population in the acute care setting, and will direct future studies leading to changes in real‐world practice settings for persons with dementia.

Much attention has been given recently to hospitalized older adults, the critical 30‐day period, and posthospital syndrome.[1] What is missing from this dialogue is the contribution and significance of underlying cognitive impairment. By 2050, 14 million older persons in the United States are expected to have dementia.[2] Increasing numbers of older adults diagnosed with dementia are hospitalized and are at increased risk of developing delirium; in fact, delirium occurs in over half of hospitalized persons with dementia.[3] Further, current evidence suggests that delirium may accelerate the clinical course and trajectory of cognitive decline, and may be associated with considerably worse long‐term outcomes, including prolonged hospitalization, rehospitalization within 30 days, nursing home placement, and death.[3, 4, 5, 6] However, the problem of delirium superimposed on dementia (DSD) remains a neglected area of investigation in hospitalized patients. Delirium is superimposed on dementia when an acute change in mental status (characterized by a fluctuating course, inattention, and either disorganized thinking or altered level of consciousness) is layered on top of preexisting dementia.[4]

Despite the poor outcomes and high prevalence of DSD, little is known about the natural history in hospitalized older adults with dementia. Delirium studies often exclude persons with dementia, even though the prevalence of DSD is extremely high in both community (13%19%) and hospital (40%89%) populations and associated with higher costs and utilization compared to dementia and delirium alone.[4, 5, 7] In 1 study, annual costs for DSD were $9566 compared to $7557 for dementia alone.[7] The few risk‐factor studies of DSD were conducted in intensive care unit (ICU) or long‐term care settings.[8, 9]

The purpose of this study was to describe the incidence, risk factors, and outcomes associated with incident delirium in a prospective cohort of hospitalized older adults with dementia. The study aims were to: (1) estimate the incidence of new delirium in hospitalized persons with dementia, (2) identify the risk factors associated with incident delirium superimposed on dementia in this sample, (3) describe the outcomes associated with development of delirium, and (4) evaluate the contributions of delirium severity and duration to outcomes.

METHODS

This 24‐month prospective cohort study recruited and enrolled consecutive hospital admissions with dementia in a 300‐bed community hospital in central Pennsylvania from July 2006 through November 2008. Data were collected daily from patients during hospitalization, followed by a 1‐month posthospitalization interview with patients and their caregivers in the community setting. Patients were included if they spoke English, had been hospitalized fewer than 24 hours, and met the screening criteria for dementia. Patients were excluded if they had any significant neurological condition associated with cognitive impairment other than dementia (eg, brain tumor), a major acute psychiatric disorder, were unable to communicate, or had no caregiver to interview. The interviewers included experienced research assistants (RAs) who were either registered nurses or trained in a health‐related field. All staff training of instruments were done with scripted training manuals and video training using manuals for the Confusion Assessment Method (CAM). After training was completed, final inter‐rater reliability assessments were conducted until staff reached 100% agreement. The RAs were blinded to the aims and completed over 10 hours of training. Inter‐rater reliability checks were conducted on 10% of the sample in the field with >90% agreement attained on all instruments. This study was reviewed by and approved by The Pennsylvania State University institutional review board, and consent was received from all subjects.

RESULTS

Of 256 eligible patients, dual consent was obtained from 154 patient and 154 family research subjects (308 consents). The refusal rate was 39% (n=102). Fourteen subjects were consented and enrolled but later dropped out due to family/proxy concerns regarding the patient's ability to participate in interviews. Thus, the final sample included 139 patients.

Descriptive statistics for baseline measures are given in Table 1. Briefly, the average age of subjects was 83 years (standard deviation [SD]=7); 41% were male; 57% were single, divorced, or widowed; and the average number of years of education was 12 years (SD=3). Thirty‐three percent were dehydrated on admission, and 33% had fallen within 2 weeks prior to admission. Thirty‐four percent had an infection at baseline, and 36% had some sensory impairment.

The overall incidence of delirium was 32% (44/139) and the range of days to incident delirium was 1 to 8 days. During the baseline period (Table 1), subjects with delirium were older, more likely to be male, had lower Katz impairment scores, higher GDS score, lower MMSE scores on admission, and higher Blessed scores than subjects without delirium. Slightly more persons with delirium had a prior fall, although the RR was not statistically significant. Length of stay measured at discharge was significantly higher for those with delirium (mean=9.1) than those without delirium (mean=5.7) (P<0.0001). Subjects with delirium were more likely to have died at 1 month than those without delirium (P=0.0153).

In addition, we analyzed the adjusted relative risk estimates for the final model of incident delirium. Significant risk factors or risk factors with RR estimates at least 1.5 (or <0.66 if protective [Table 1]) that were examined in a more comprehensive multiple proportional hazards model included age, gender, having had a fall in the last 2 weeks, number of impaired ADLs (based on Katz), GDS scores, MMSE scores at baseline, and Blessed scores at baseline. The final proportional hazards included gender and GDS score. Males were nearly 1.8 times as likely to develop delirium than females, and for every 1 unit increase in the GDS, subjects were 1.5 times more likely to develop delirium.

Finally, Table 2 gives the results of examining outcomes related to incident delirium measures. For mortality, there were no statistically significant predictors of death after controlling for age, gender, or GDS. For length of stay, subjects with incident delirium had significantly longer lengths of stay, as incident delirium severity increased by 1 unit the length of stay increased by 0.4 days, and as the number of inpatient days with delirium increased by 1 day the length of stay increased by 1.8 days. For change in the impaired Katz ADLs from admission to follow‐up, as incident delirium severity increased by 1 unit the change in impaired Katz ADLs increased by 0.05 units.

DISCUSSION

The most compelling finding from this study is the high incidence of delirium in hospitalized older adults with dementia and the association with poor clinical outcomes in those who develop delirium superimposed on dementia. DSD is difficult to detect and prevent; persons with DSD are at risk for poor quality of life. Those with delirium had a 25% short‐term mortality rate (P=0.0153), substantially increased length of stay (9.1 vs 5.1 days with an odds ratio of 1.8) and poorer physical function at discharge and follow‐up. At 1 month follow‐up, subjects with delirium had greater functional decline and lower GDS scores than those without delirium.

The incidence of delirium in this study was high (32%). Being delirious any time was associated with death and poor function. Delirium was also associated with the stage of the persons' baseline dementia, advanced age, lower MMSE scores, and falling before admission.

Previous studies have found delirium associated with increased mortality. Three studies found that within 1 year of a delirium episode, a significant number of persons died or were institutionalized.[24, 25, 26] Other research has reported death within 1 year of documented delirium episodes, and a 3‐fold increased rate of death in the ICU.[24, 27, 28, 29, 30, 31, 32] This study is 1 of only a few to focus on increased mortality with DSD and to focus uniquely on hospitalized patients with delirium and dementia.

The main risk factors for delirium in this study were male sex and severity of dementia. Our results, combined with those from other recent studies by Voyer and colleagues,[8, 33, 34] point to the critical importance of screening for dementia in hospitalized older adults as dementia severity is a significant indicator of delirium severity. For instance, Voyer and colleagues[34] reported that persons with mild dementia were likely to experience a mild delirium, whereas those with a more severe level of dementia were more likely to experience moderate to severe delirium. Our findings show that those who experienced episodes of delirium represented a highly vulnerable population with advanced dementia, sensory impairment, more falls and dehydration at admission, and higher Blessed scores. A recent study by Saczynski and colleagues[35] found 40% of patients who had experienced postoperative delirium did not return to their baseline at 6 months. Clearly, preventing delirium should be a critical priority to prevent such deterioration in the highly vulnerable population of hospitalized patients with dementia.

Patients in this study were on a mean of over 11 medications. One‐third of dementia patients in our study had also experienced a fall and dehydration at baseline. Other studies have found a relationship between cognitive decline, falling, and medications.[36] Many of these patients came into the hospital with potentially modifiable and preventable community or ambulatory care conditions of polypharmacy, falling, sensory impairment, and dehydration.

Importantly, in our study, length of stay was significantly higher (9.1 vs 5.7) for those with delirium compared to those without delirium. This finding is alarming when examining the economic impact of preventing delirium. Previous studies have found the cost of delirious episodes rivals those for diabetes and heart disease, and that decreasing length of stay by just 1 day would save over $20 million dollars per year.[4, 37]

In summary, this study is 1 of the first to report a high incidence of DSD and poorer outcomes for persons who experience delirium compared to those with dementia alone. This is 1 of only a few studies examining unique risk factors and delirium severity for DSD in the acute care setting. Findings from the current study report potential risk factors for development of incident delirium and highlight the challenge of preventing DSD before and during hospitalization. The generalizability of this study may be limited by the use of a nondiverse study population drawn from a single hospital in the northeast United States, though the use of a community hospital increases the relevance to real‐world practice settings. Determination of baseline cognitive status and the differentiation of delirium and dementia are difficult, but validated, state‐of‐the‐art methods were used that have been applied in previous studies.

This study provides fundamental methodological improvements over previous work, and advances the science by providing valuable data on the natural history, correlates, and outcomes of DSD. The strengths of this study include the prospective cohort design, the daily assessment for delirium based on a 24‐hour period, methods for determining cognitive status at baseline in this difficult population, and utilizing strict blinding of the well‐trained outcome assessors.

This study lays the groundwork for future studies to improve care for persons with dementia who present to acute care and to plan prevention programs for delirium before they are admitted to the hospital. We must be able to translate best practice for DSD into the acute care and community settings to prevent or minimize effects of delirium in persons with dementia. Interventions to increase early detection of delirium by hospital staff have the potential to decrease the severity and duration of delirium and prevent unnecessary suffering and costs from the complications of delirium and preventable readmissions to the hospital.

Thus, this study holds substantial clinical and economic implications for this population in the acute care setting, and will direct future studies leading to changes in real‐world practice settings for persons with dementia.