Delirium Rating Scale-Revised-98 Research Articles

The 4AT, a rapid delirium detection tool for use in hospice inpatient units: Findings from a validation study

Background: Delirium is a serious neuropsychiatric syndrome with adverse outcomes, which is common but often undiagnosed in terminally ill people. The 4 ‘A’s test or 4AT (www.the4AT.com), a brief delirium detection tool, is widely used in general settings, but validation studies in terminally ill people are lacking. Aim: To determine the diagnostic accuracy of the 4AT in detecting delirium in terminally ill people, who are hospice inpatients. Design: A diagnostic test accuracy study in which participants underwent the 4AT and a reference standard based on the fifth edition of the Diagnostic and Statistical Manual of Mental Disorders. The reference standard was informed by Delirium Rating Scale Revised-98 and tests assessing arousal and attention. Assessments were conducted in random order by pairs of independent raters, blinded to the results of the other assessment. Setting/participants: Two hospice inpatient units in Scotland, UK. Participants were 148 hospice inpatients aged ⩾18 years. Results: A total of 137 participants completed both assessments. Three participants had an indeterminate reference standard diagnosis and were excluded, yielding a final sample of 134. Mean age was 70.3 (SD = 10.6) years. About 33% (44/134) had reference standard delirium. The 4AT had a sensitivity of 89% (95% CI 79%–98%) and a specificity of 94% (95% CI 90%–99%). The area under the receiver operating characteristic curve was 0.97 (95% CI 0.94–1). Conclusion: The results of this validation study support use of the 4AT as a delirium detection tool in hospice inpatients, and add to the literature evaluating methods of delirium detection in palliative care settings. Trial registry: ISCRTN 97417474.

Quetiapine Versus Haloperidol in the Management of Hyperactive Delirium: Randomized Controlled Trial.

In the population of patients in the intensive care unit (ICU), most studies compared the use of atypical antipsychotics, such as quetiapine, with the use of traditional haloperidol in patients with delirium of various forms and etiologies. The role of such agents in patients with hyperactive delirium is not fully understood. This study compares the effectiveness of quetiapine with haloperidol in treating the hyperactive form of delirium in terms of their effects on the Delirium Rating Scale-Revised-98 (DRS-R-98), length of stay in the ICU, and mortality in critically ill patients. One hundred adult patients diagnosed with hyperactive delirium were randomly assigned to receive either oral quetiapine (25-50mg/day) or haloperidol (1-2mg/day). The response, defined as "a DRS-R-98 severity score reduction from baseline of 50% or more" and a DRS-R-98 severity score of 12 or less without relapse, was the primary outcome. The mean age of all patients was 68 ± 6years. The study population's overall response rate was 92%. Response rates for the two groups were remarkably equal (p = 0.609). Secondary outcomes were comparable in both groups, such as ICU mortality (p = 0.496), in-hospital mortality (p = 0.321), in-hospital stay (p = 0.310), and the need for mechanical ventilation (p > 0.99). But the quetiapine group showed a statistically reduced mean ICU stay (10.1 ± 2.0 vs. 11.7 ± 2.6days, p = 0.018) and increased sleeping hours per night (p = 0.001). Quetiapine may be equally as effective as haloperidol in treating the symptoms of hyperactive delirium in critically ill patients, with no mortality benefit.

Delirium following traumatic brain injury in adolescents: Symptomatology and prediction of ability to return to school or employment 1-year post-injury.

There is a limited evidence-base describing clinical features of delirium in youth. What is known is largely extrapolated from studies of adults or samples with heterogeneous etiologies. It is unclear if the symptoms experienced by adolescents differ from those experienced by adults, or the degree to which delirium impacts the ability of adolescents to return to school or work. To describe delirium symptomatology among adolescents following a severe traumatic brain injury (TBI). Symptoms were compared by adolescent delirium status and across age groups. Delirium and its relationship with adolescent employability 1 year post-injury was also examined. Exploratory secondary analysis of prospectively collected data. Free-standing rehabilitation hospital. Severely injured TBI Model Systems neurorehabilitation admissions (n = 243; median Glasgow Coma Scale = 7). The sample was divided into three age groups (adolescents, 16-21 years, n = 63; adults 22-49 years, n = 133; older adults ≥50 years, n = 47). Not applicable. We assessed patients using Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition (DSM-IV) diagnostic criteria and the Delirium Rating Scale-Revised 98 (DRS-R-98). The employability item from the Disability Rating Scale was the primary 1-year outcome. Most items on the DRS-R-98 differentiated delirious from non-delirious adolescents. Only "delusions" differed among age groups. Among adolescents, delirium status 1 month post-TBI provided acceptable classification of employability prediction 1 year later (area under the curve [AUC]: 0.80, 95% confidence interval [CI]: 0.69-0.91, p < .001). Delirium symptom severity (AUC: 0.86, 95% CI: 0.68-1.03, SE: 0.09; p < .001) and days of post-traumatic amnesia (AUC: 0.85, 95% CI: 0.68-1.01, SE: 0.08; p < .001) provided excellent prediction of outcomes for TBI patients in delirium. Delirium symptomatology was similar among age groups and useful in differentiating the delirium status within the adolescent TBI group. Delirium and symptom severity at 1 month post-TBI were highly predictive of poor outcomes. Findings from this study support the utility of DRS-R-98 at 1 month post-injury to inform treatment and planning.

Data-driven categorization of postoperative delirium symptoms using unsupervised machine learning.

Phenotyping analysis that includes time course is useful for understanding the mechanisms and clinical management of postoperative delirium. However, postoperative delirium has not been fully phenotyped. Hypothesis-free categorization of heterogeneous symptoms may be useful for understanding the mechanisms underlying delirium, although evidence is currently lacking. Therefore, we aimed to explore the phenotypes of postoperative delirium following invasive cancer surgery using a data-driven approach with minimal prior knowledge. We recruited patients who underwent elective invasive cancer resection. After surgery, participants completed 5 consecutive days of delirium assessments using the Delirium Rating Scale-Revised-98 (DRS-R-98) severity scale. We categorized 65 (13 questionnaire items/day × 5 days) dimensional DRS-R-98 scores using unsupervised machine learning (K-means clustering) to derive a small set of grouped features representing distinct symptoms across all participants. We then reapplied K-means clustering to this set of grouped features to delineate multiple clusters of delirium symptoms. Participants were 286 patients, of whom 91 developed delirium defined according to Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition, criteria. Following the first K-means clustering, we derived four grouped symptom features: (1) mixed motor, (2) cognitive and higher-order thinking domain with perceptual disturbance and thought content abnormalities, (3) acute and temporal response, and (4) sleep-wake cycle disturbance. Subsequent K-means clustering permitted classification of participants into seven subgroups: (i) cognitive and higher-order thinking domain dominant delirium, (ii) prolonged delirium, (iii) acute and brief delirium, (iv) subsyndromal delirium-enriched, (v) subsyndromal delirium-enriched with insomnia, (vi) insomnia, and (vii) fit. We found that patients who have undergone invasive cancer resection can be delineated using unsupervised machine learning into three delirium clusters, two subsyndromal delirium clusters, and an insomnia cluster. Validation of clusters and research into the pathophysiology underlying each cluster will help to elucidate the mechanisms of postoperative delirium after invasive cancer surgery.

Delusions and Hallucinations Are Associated With Greater Severity of Delirium.

The 3 core domains of delirium (cognitive, higher level thinking, circadian) do not include the less common noncore psychotic symptoms. However, psychosis might inform about perturbations of neural circuitry, outcomes, or suggest tailored clinical management. We assessed relationships between psychosis and other characteristics of delirium in patients without dementia or antipsychotics treatment. Cross-sectional analysis of 366 adults with delirium per the Delirium Rating Scale Revised-98, whose items distinguish hallucinations and delusions from other types of misperceptions and abnormal thought content, assessed during the preceding 24 hours to capture symptom severity fluctuation. The relationship of psychosis with other delirium characteristics was assessed using bivariate comparisons and analysis of variance as appropriate for groups with no psychosis and any psychosis (hallucinations and/or delusions), and subgroups with only hallucinations, only delusions, or both. A discriminant logistic model assessed variables associated with presence of any psychotic features versus none. Delirium with any psychotic features occurred in 44.5% (163 of 366). Of the 366, 119 (32.5%) had only hallucinations (Hall), 14 (3.8%) had only delusions (Del), and 30 (8.2%) had both (Both). In the psychotic group (n= 163), 73.0% were Hall, 8.6% Del, and 18.4% Both. All psychotic patient groupings had significantly greater delirium severity on the Delirium Rating Scale Revised-98. Delusions and hallucinations were discordant for occurring together. The discriminant model found increased odds of having psychosis as 3 symptom severities increased (visuospatial ability, thought process, and sleep-wake cycle) where these each represented a delirium core domain. The noncore symptom of lability of affect had high odds ratio for psychosis, while motor retardation reduced odds of psychosis in this model. Consistent with prior reports, psychosis occurred in less than half of delirious patients with delusions being infrequent, and anassociation with affective lability was found. Given thatprevious functional magnetic resonance imaging research found a correlation between neural network dysconnectivity with greater severity of delirium, psychotic symptoms might be a clinical marker for greater underlying cerebral cortical neural circuitry dysfunction.

A dimensional approach to assessing delirium in COVID-19 in the elderly

The aim of the study was to investigate the structure of delirium in elderly patients with different outcomes of coronavirus infection.Materials and Methods. The study was carried out on the basis of Hospital for War Veterans, St. Petersburg. The study involved 30 patients: 13 male and 17 female (median age (Med) 70.5, interquartile range (IQR) 62-83) with clinical diagnosis: "New coronavirus infection COVID-19 (PCR+), F05.86 other delirium in association with other viral and bacterial neuroinfections. Peculiarities of delirium manifestations were studied using Delirium Rating Scale-Revised-98 (DRS-R-98). Current physical condition was monitored using The National Early Warning Score (NEWS2) for COVID-19.Results: All patients had moderate to severe disorders of the wake-sleep cycle on the DRS-R-98 scale. In addition, perceptual and long-term memory impairments were common. A significant correlation (p&lt;0.05) was found between the severity of the physical condition and disorders of the sleep-wake cycle, lability of affect, formal thought disorders, motor agitation, and disorientation. In addition, there were significant correlations (p&lt;0.05) between delirium symptoms and physical status scores on the NEWS2 scale. In lethal patients, more pronounced disturbances were recorded on sleep-wake indicators (Med.3.0, IQR 2.0-3.0 vs Med.2.0, IQR 2.0-3.0, p=0.0327) and motor agitation (Med.2.0, IQR 1.0-2.5 vs Med.1.0, IQR 0.0-2.0, p=0.441). A logit regression model showed that the variables "respiratory rate," "heart rate," and the final NEWS2 score could be considered predictors of disease outcome.Conclusion. Delirium, one of the most frequent manifestations of acute brain dysfunction, is a serious complication of COID-19 in hospitalized patients and a strong predictor of adverse outcome of coronavirus infection in older patients.

The Association between Electroencephalography with Auditory Steady-State Response and Postoperative Delirium.

Delirium is a disorder of consciousness and a risk factor for cognitive dysfunction and poor prognosis. We hypothesized that preoperative gamma activities would be linked to postoperative delirium. We enrolled 71 subjects for elective surgery and recorded auditory steady-state response (ASSR) by electroencephalography (EEG) before the surgery and examined postoperative delirium with DSM-5. The EEG data were analyzed for baseline power, and ASSR evoked power (EP) and phase-locking factor (PLF) within the gamma range. Postoperative delirium was found in 18 patients (delirium group) but not in 53 patients (non-delirium group). There were no significant differences in the 40-Hz EP or PLF between the two groups. The baseline gamma activity negatively correlated with the 40-Hz PLF in the non-delirium group (ρ = -0.444, p &lt; 0.01). The correlation between baseline gamma activity and 40-Hz EP was not significant in either the delirium or non-delirium group. In all patients, both preoperative PLF and EP had no significant correlations with the Delirium Rating Scale Revised-98 and the Memorial Delirium Assessment Measure at the post-operation, respectively. The disruption of the neurophysiological relationship between baseline gamma activity before sound stimuli and the PLF of the 40-Hz ASSR may be one of the potential neurophysiological indicators associated with postoperative delirium.

Contribution of intraoperative electroencephalogram suppression to frailty-associated postoperative delirium: mediation analysis of a prospective surgical cohort

BackgroundFrailty is a risk factor for postoperative delirium (POD), and has led to preoperative interventions that have reduced, but not eliminated, the risk. We hypothesised that EEG suppression, another risk factor for POD, mediates some of the frailty risk for POD. MethodsA prospective cohort study enrolled patients aged 65 yr or older, scheduled for noncardiac surgery under total intravenous anaesthesia. Frailty was assessed using the FRAIL scale. Cumulative duration of EEG suppression, defined as an amplitude between –5 and 5 μV for >0.5 s during anaesthesia, was measured. POD was diagnosed by either confusion assessment method (CAM), CAM-ICU, or medical records. The severity of POD was assessed using the Delirium Rating Scale – Revised-98 (DRS). Mediation analysis was used to estimate the relationships between frailty, EEG suppression, and severity of POD. ResultsAmong 252 enrolled patients, 51 were robust, 129 were prefrail, and 72 were frail. Patients classified as frail had higher duration of EEG suppression than either the robust (19 vs 0.57 s, P<0.001) or prefrail groups (19 vs 3.22 s, P<0.001). Peak delirium score was higher in the frail group than either the robust (17 vs 15, P<0.001) or prefrail groups (17 vs 16, P=0.007). EEG suppression time mediated 24.2% of the frailty–DRS scores association. ConclusionEEG suppression time mediated a statistically significant portion of the frailty–POD association in older noncardiac surgery patients. Trials directed at reducing EEG suppression time could result in intraoperative interventions to reduce POD in frail patients. Clinical trial registrationChiCTR2000041092 (Chinese Clinical Trial Registry).

Safety and Effectiveness of Perospirone in Comparison to Risperidone for Treatment of Delirium in Patients with Advanced Cancer: A Multicenter Prospective Observational Study in Real-World Psycho-Oncology Settings.

The clinical benefit of perospirone for treatment of delirium in patients with advanced cancer is not sufficiently clear. The objective of this study was to compare the safety and effectiveness of perospirone to those of risperidone for the treatment of delirium in patients with advanced cancer. This is a secondary analysis of a multicenter prospective observational study in nine psycho-oncology consultation services in Japan. The study used the Delirium Rating Scale (DRS) Revised-98 to measure effectiveness and the CTCAE (Common Terminology Criteria for Adverse Events) version 4 to assess safety. Data from 16 patients who received perospirone and 53 patients who received risperidone were analyzed. The mean age was 70 years in the perospirone group and 73 years in the risperidone group. Both groups showed a significant decrease in the total score of DRS-R-98 after three days of treatment (perospirone: 11.7 (7.9-15.4) to 7.0 (3.3-10.7), difference -4.7, effect size=0.72, p=0.003; risperidone: 15.5 (13.6-17.4) to 12.2 (10.1-14.2), difference -3.3, effect size=0.55, p=0.00). The risperidone group showed significant improvements in sleep-wake cycle disturbance, orientation, attention, and visuospatial ability. In the perospirone group, there was a significant improvement of sleep-wake cycle disturbance. The median daily dose of perospirone was 4 mg/day. There were fewer episodes of somnolence as an adverse event in the perospirone group. Low-dose perospirone was thus found to be effective for the treatment of delirium in patients with advanced cancer and may be associated with fewer episodes of over-sedation as an adverse event.

A decision tree prediction model for a short-term outcome of delirium in patients with advanced cancer receiving pharmacological interventions: A secondary analysis of a multicenter and prospective observational study (Phase-R).

There is no widely used prognostic model for delirium in patients with advanced cancer. The present study aimed to develop a decision tree prediction model for a short-term outcome. This is a secondary analysis of a multicenter and prospective observational study conducted at 9 psycho-oncology consultation services and 14 inpatient palliative care units in Japan. We used records of patients with advanced cancer receiving pharmacological interventions with a baseline Delirium Rating Scale Revised-98 (DRS-R98) severity score of ≥10. A DRS-R98 severity score of <10 on day 3 was defined as the study outcome. The dataset was randomly split into the training and test dataset. A decision tree model was developed using the training dataset and potential predictors. The area under the curve (AUC) of the receiver operating characteristic curve was measured both in 5-fold cross-validation and in the independent test dataset. Finally, the model was visualized using the whole dataset. Altogether, 668 records were included, of which 141 had a DRS-R98 severity score of <10 on day 3. The model achieved an average AUC of 0.698 in 5-fold cross-validation and 0.718 (95% confidence interval, 0.627-0.810) in the test dataset. The baseline DRS-R98 severity score (cutoff of 15), hypoxia, and dehydration were the important predictors, in this order. We developed an easy-to-use prediction model for the short-term outcome of delirium in patients with advanced cancer receiving pharmacological interventions. The baseline severity of delirium and precipitating factors of delirium were important for prediction.

Evaluation of point-of-care thumb-size bispectral electroencephalography device to quantify delirium severity and predict mortality.

We have developed the bispectral electroencephalography (BSEEG) method for detection of delirium and prediction of poor outcomes. To improve the BSEEG method by introducing a new EEG device. In a prospective cohort study, EEG data were obtained and BSEEG scores were calculated. BSEEG scores were filtered on the basis of standard deviation (s.d.) values to exclude signals with high noise. Both non-filtered and s.d.-filtered BSEEG scores were analysed. BSEEG scores were compared with the results of three delirium screening scales: the Confusion Assessment Method for the Intensive Care Unit (CAM-ICU), the Delirium Rating Scale-Revised-98 (DRS) and the Delirium Observation Screening Scale (DOSS). Additionally, the 365-day mortalities and the length of stay (LOS) in the hospital were analysed. We enrolled 279 elderly participants and obtained 620 BSEEG recordings; 142 participants were categorised as BSEEG-positive, reflecting slower EEG activity. BSEEG scores were higher in the CAM-ICU-positive group than in the CAM-ICU-negative group. There were significant correlations between BSEEG scores and scores on the DRS and the DOSS. The mortality rate of the BSEEG-positive group was significantly higher than that of the BSEEG-negative group. The LOS of the BSEEG-positive group was longer compared with that of the BSEEG-negative group. BSEEG scores after s.d. filtering showed stronger correlations with delirium screening scores and more significant prediction of mortality. We confirmed the usefulness of the BSEEG method for detection of delirium and of delirium severity, and prediction of patient outcomes with a new EEG device.

Harmonization of Four Delirium Instruments: Creating Crosswalks and the Delirium Item-Bank (DEL-IB)

ObjectivesOver 30 instruments are in current, active use for delirium identification. In a recent systematic review, we recommended 4 commonly used and well-validated instruments for clinical and research use. The goal of this study is to harmonize the four instruments on the same metric using modern methods in psychometrics. DesignSecondary data analysis from 3 studies, and a simulation study based on the observed data. SettingHospitalized (non-ICU) adults over 65 years old in the United States, Ireland, and Belgium. ParticipantsThe total sample comprised 600 participants, contributing 1,623 assessments. MeasurementsConfusion Assessment Method (long-form and short-form), Delirium Observation Screening Scale, Delirium Rating Scale-Revised-98 (DRS-R-98) (total and severity scores), and Memorial Delirium Assessment Scale. ResultsUsing item response theory, we linked scores across instruments, placing all four instruments and their separate scorings on the same metric (the propensity to delirium). Kappa statistics comparing agreement in delirium identification among the instruments ranged from 0.37 to 0.75, with the highest agreement between the DRS-R-98 total score and MDAS. After linking scores, we created a harmonized item bank, called the Delirium Item Bank (DEL-IB), consisting of 50 items. The DEL-IB allowed us to create six crosswalks, to allow scores to be translated across instruments. ConclusionsWith our results, individual instrument scores can be directly compared to aid in clinical decision-making, and quantitatively combined in meta-analyses.

Immune, Blood Cell, and Blood Gas Biomarkers of Delirium in Elderly Individuals with Hip Fracture Surgery

Background: Postoperative delirium in elderly people with hip fracture is associated with various adverse clinical outcomes. Nevertheless, the pathophysiological processes underpinning delirium have remained elusive. Objectives: The aim of this study was to explore the associations between delirium and its features and immune-inflammatory and blood gas biomarkers. Methods: In this prospective study, we examined 65 patients who underwent a hip fracture surgery and assessed the Confusion Assessment Method for the Intensive Care Unit, Richmond Agitation-Sedation Scale (RASS), and Delirium Rating Scale Revised-98 (DRS-R-98) before and during 4 days after the surgery. Complete blood count and venous blood gas markers were obtained at the same time points. Results: Delirium was observed in 19 patients and was accompanied by significantly increased pO₂, number of white blood cells, neutrophil percentage, and neutrophil/lymphocyte ratio, and lower mean platelet volume (MPV) after adjusting for age, central nervous system (CNS) disease, blood loss during surgery, sleep disorders, and body mass index. The severity of delirium was associated with lowered number of platelets and MPV. Psychomotor disorders were associated with lower bicarbonate levels. The requirement of physical restraint of the patients was predicted by increased percentages of neutrophils and lymphocytes. Prior CNS disease was together with these biomarkers a significant predictor of delirium and severity of delirium. Conclusion: Delirium and psychomotor disorders following hip fracture and surgery may be caused by immune-inflammatory and oxidative stress pathways probably attributable to an aseptic inflammatory process.

Serum Biomarkers in Postoperative Delirium After Esophagectomy

BackgroundEsophagectomy is associated with postoperative delirium, but its pathophysiology is not well defined. We conducted this study to measure the relationship among serum biomarkers of inflammation and neuronal injury and delirium incidence and severity in a cohort of esophagectomy patients. MethodsBlood samples were obtained from patients preoperatively and on postoperative days 1 and 3 and were analyzed for S100 calcium-binding protein B, C-reactive protein (CRP), interleukin (IL) 8 and IL-10, tumor necrosis factor-α, and insulin-like growth factor 1. Delirium was assessed twice daily using the Richmond Agitation Sedation Scale and Confusion Assessment Method for Intensive Care Unit. Delirium severity was assessed once daily with the Delirium Rating Scale–Revised-98. ResultsSamples from 71 patients were included. Preoperative biomarker concentrations were not associated with postoperative delirium. Significant differences in change in concentrations from preoperatively to postoperative day 1 were seen in IL-8 (delirium, 38.6; interquartile range [IQR], 29.3-69.8; no delirium, 24.8; IQR, 16.0-41.7, P = .022), and IL-10 (delirium, 26.1; IQR, 13.9-36.7; no delirium, 12.4; IQR, 7.7-25.7; P = .025). Greater postoperative increase in S100 calcium-binding protein B (Spearman r = 0.289, P = .020) and lower levels of insulin-like growth factor 1 were correlated with greater delirium severity (Spearman r = −0.27, P = .040). Greater CRP change quartiles were associated with higher delirium incidence adjusting for severity of illness (odds ratio, 1.68; 95% confidence interval, 1.03-2.75; P = .037) or comorbidities (odds ratio, 1.70; 95% confidence interval, 1.05-2.76, P = .030). ConclusionsDifferences in change in serum CRP, IL-8, and IL-10 concentrations were associated with postoperative delirium, suggesting biomarker measurement early in the postoperative course is associated with delirium.

Factors associated with the severity of delirium.

Various factors affecting the development of delirium have been identified. However, the associations between the severity of delirium and potentially related factors have not been adequately investigated. The aim of the present study was to explore factors associated with the severity of delirium and to identify the reversible contributing factors. A total of 577 patients with delirium referred to the Department of Psychiatry during the 5 years from May 2015 to April 2020 at a general hospital were included. The Delirium Rating Scale-revised-98 (DRS-R-98) was used to measure the severity of delirium. Multiple regression analysis was used to determine whether individual factors were associated with the severity of delirium. Intensive care unit admission (p=0.003), use of benzodiazepines (p=0.01), dementia (p=0.02), and older age (p=0.045) were all positively associated the severity of delirium, while use of β-blockers (p=0.001) was negatively associated with the severity of delirium. Reversible contributing factors, that is use of benzodiazepines, should be avoided as much as possible, especially in elderly patients or patients with dementia or patients who need critical care in ICU. Reducing the dose of benzodiazepines or switching them to other drugs should be a priority.

Preoperative Cerebrospinal Fluid Cortisol and the Risk of Postoperative Delirium: A Prospective Study of Older Hip Fracture Patients

Background: Ageing, depression, and neurodegenerative disease are common risk factors for delirium in the elderly. These risk factors are associated with dysregulation of the hypothalamic-pituitary-adrenal axis, resulting in higher levels of cortisol under normal and stressed conditions and a slower return to baseline. Objectives: We investigated whether elevated preoperative cerebrospinal fluid (CSF) cortisol levels are associated with the onset of postoperative delirium. Methods: In a prospective cohort study CSF samples were collected after cannulation for the introduction of spinal anesthesia of 75 patients aged 75 years and older admitted for surgical repair of acute hip fracture. Delirium was assessed with the confusion assessment method (CAM) and the Delirium Rating Scale-Revised-98 (DRS-R98). Because the CAM and DRS-R98 were available for time of admission and 5 postoperative days, we used generalized estimating equations and linear mixed modeling to examine the association between preoperative CSF cortisol levels and the onset of postoperative delirium. Results: Mean age was 83.5 (SD 5.06) years, and prefracture cognitive decline was present in one-third of the patients (24 [33%]). Postoperative delirium developed in 27 (36%) patients. We found no association between preoperative CSF cortisol levels and onset or severity of postoperative delirium. Conclusions: These findings do not support the hypothesis that higher preoperative CSF cortisol levels are associated with the onset of postoperative delirium in elderly hip fracture patients.

Evaluation of association of impairment of attention with other symptoms of delirium

Aim: To evaluate the association of impairment of attention with other symptoms of delirium. Methodology: Eighty-six patients with delirium as per the Diagnostic and Statistical Manual, 5th Revision seen in the consultation-liaison psychiatry setup of a tertiary care hospital were cross-sectionally assessed on the short informant questionnaire on cognitive decline in the elderly (Retrospective), montreal cognitive assessment (MoCA), and delirium rating scale revised-98 (DRS-R98) version. Results: The mean age of the study participants was 46.6 (standard deviation [SD] – 16.4) years. All the patients had impairment in attention with the altered sleepwake cycle, acute onset of illness, with the fluctuating course and underlying physical disease. In terms of severity, the severity score was the highest for the item of sleep-wake cycle disturbances, followed by motor agitation. The mean noncognitive symptoms domain of the DRS-R98 domain were more than the mean score of the cognitive symptom domain of DRS-R98. The mean total score on MoCA was 11.9 (SD: 7.5). Higher attention impairment was associated with more severe noncognitive and cognitive symptoms and higher delirium severity as assessed by DRS-R98. Higher severity of attention deficit was also associated with higher impairment in other domains of cognition of MoCA. Cognitive symptoms, as evaluated by DRS-R98, had more significant correlations with various domains of MoCA except for language and abstraction. Conclusion: Attention deficits are the core symptom of delirium and have a significant impact on other cognitive and noncognitive symptoms of delirium.

The Harmonization of Four Delirium Instruments

Delirium is a clinical syndrome characterized by acute cognitive dysfunction, which is pervasive in older persons. Delirium affects over 2.6 million Americans over age 65 annually. One major problem in detection of delirium is that over 40 different instruments have been created to identify delirium in different clinical settings. There is no single agreed upon reference standard instrument. In previous work, we performed a systematic review to identify the four most commonly cited and well-validated instruments for delirium identification. The aim of this study is to harmonize these four commonly used instruments: Confusion Assessment Method (CAM), Delirium Observation Screening Scale (DOSS), Delirium Rating Scale-Revised-98 (DRS-R-98), and Memorial Delirium Assessment Scale (MDAS). We used data from three separate sources (N = 1623). Participants were rated by multiple and overlapping instruments across studies, allowing us to apply item response theory linking procedures. We fit generalized structural equation models, and found unidimensional factor models fit well. We found the instruments were highly correlated (all r > 0.9) and kappa statistics for delirium case identification were high (range: 0.89 to 0.95). We generated crosswalks to map sum scores on one instrument to another. Our results suggest the same underlying construct, propensity to delirium, is measured across the four instruments. The crosswalks facilitate comparison and combination for immediate clinical use or for future meta-analyses. In future steps, we will use our results to find the optimal cut-points for use across all instruments to identify delirium.

Phenomenological examinations of delirium in advanced cancer patients: exploratory structural equation modelling and latent profile analysis

BackgroundThis study examined phenomenological manifestations of delirium in advanced cancer patients by examining the factor structure of the Delirium Rating Scale-Revised-98 (DRS-R-98) and profiles of delirium symptoms.MethodsNinety-three patients with advanced cancer admitted to inpatient palliative care units in South Korea were examined by psychiatrists using the DRS-R-98 and the Confusion Assessment Method (CAM). The factor structure of the DRS-R-98 was examined by exploratory structural equation modelling analysis (ESEM) and profiles of delirium were examined by latent profile analysis (LPA).ResultsCAM-defined delirium was present in 66.6% (n = 62) of patients. Results from the ESEM analysis confirmed applicability of the core and noncore symptom factors of the DRS-R-98 to advanced cancer patients. LPA identified three distinct profiles of delirium characterizing the overall severity of delirium and its core and noncore symptoms. Class 1 (n = 55, 59.1%) showed low levels of all delirium symptoms. Class 2 (n = 17, 18.3%) showed high levels of core symptoms only, whereas Class 3 (n = 21, 22.6%) showed high levels of both core and noncore symptoms except motor retardation.ConclusionsClinical care for delirium in advanced cancer patients may benefit from consideration of the core and noncore symptom factor structure and the three distinct phenomenological profiles of delirium observed in the present study.

Are common delirium assessment tools appropriate for evaluating delirium at the end of life in cancer patients?

The objectives of this study are to investigate how many advanced cancer patients became unconscious or non-communicative after pharmacological treatment for delirium, and to explore whether existing delirium assessment tools can successfully evaluate its severity at the end of life. This was a secondary analysis of a registry study that examined the efficacy and safety of antipsychotics for advanced cancer patients with delirium. A total of 818 patients were recruited from 39 specialized palliative care services in Japan. The severity of delirium was measured using the Richmond Agitation-Sedation Scale-Palliative care version, the Delirium Rating Scale-Revised-98 (DRS-R-98), and the Nursing Delirium Screening Scale (Nu-DESC) on Day 3. Data from 302 patients with motor anxiety with an Agitation Distress Scale score ≥2 on Day 0 were analyzed for this study. The patients were categorized into four treatment response groups: complete response (CR: no agitation and fully communicative), partial response (PR: no/mild agitation and partially communicative), unconscious/non-communicative (UC), and no change (NC). On Day 3, 29 (10%; 95% confidence intervals [CI], 7-13) and 2 (1%; 95% CI, 0-2) patients became unconscious and non-communicative, respectively. Forty-four patients were categorized as CR, 97 as PR, 31 as UC, and 96 as NC. The scores of the DRS-R-98 and Nu-DESC in the UC group were rated higher than patients in the NC group were. A considerable number of cancer patients with delirium became unconscious or non-communicative. Existing delirium assessment tools may be inappropriate for measuring the severity of delirium in end-of-life.