Mitochondrial Dysfunction of Peripheral Platelets as a Predictive Biomarker for Postoperative Delirium in Elderly Patients.

OBJECTIVE: To determine the association between the preoperative Bioenergetic Health Index (BHI) of platelets and the occurrence of postoperative delirium (POD) in elderly patients. METHODS: Elderly patients scheduled for major abdominal surgery under general anesthesia were included. The presence of POD was assessed within the 3 days after surgery. Seahorse XF analysis and transmission electron microscopy were utilized to evaluate the mitochondrial metabolism and morphology of platelets. RESULTS: A total of 20 out of 162 participants developed POD. Participants with POD showed lower preoperative Mini-Mental State Examination scores and total protein levels, fewer educational years, longer surgery duration, higher mean platelet volume, and lower platelet BHI compared with those without POD. Damaged mitochondria with swollen appearance and distorted cristae was detected in platelets from participants with POD. Preoperative platelet BHI was independently associated with the occurrence of POD after adjusting for age, education, preoperative Mini-Mental State Examination score, preoperative mean platelet volume and total protein levels, surgical type and duration, and lymphocyte counts on the first postoperative day (OR 0.11, 95% CI 0.03-0.37, p < 0.001). The areas under the receiver operating curves for predicting POD were 0.83 (95% CI 0.76-0.88) for platelet BHI. It showed a sensitivity of 85.00% and specificity of 73.24%, with an optimal cutoff value of 1.61. Using a serial combination (mean platelet volume followed by BHI) yielded a sensitivity of 80.00% and specificity of 82.39%. INTERPRETATION: Preoperative platelet BHI was independently associated with the occurrence of POD in elderly patients and has the potential as a screening biomarker for POD risk. ANN NEUROL 2024;96:74-86.

From Traditional Typing to Intelligent Insights: A Narrative Review of Directions Toward Targeted Therapies in Delirium.

Delirium is a heterogeneous syndrome characterized by an acute change in level of consciousness that is associated with inattention and disorganized thinking. Delirium affects most critically ill patients and is associated with poor patient-oriented outcomes such as increased mortality, longer ICU and hospital length of stay, and worse long-term cognitive outcomes. The concept of delirium and its subtypes has existed since nearly the beginning of recorded medical literature, yet robust therapies have yet to be identified. Analogous to other critical illness syndromes, we suspect the lack of identified therapies stems from patient heterogeneity and prior subtyping efforts that do not capture the underlying etiology of delirium. The time has come to leverage machine learning approaches, such as supervised and unsupervised clustering, to identify clinical and pathophysiological distinct clusters of delirium that will likely respond differently to various interventions. We use sedation in the ICU as an example of how precision therapies can be applied to critically ill patients, highlighting the fact that while for some patients a sedative drug may cause delirium, in another cohort sedation is the specific treatment. Finally, we conclude with a proposition to move away from the term delirium, and rather focus on the treatable traits that may allow precision therapies to be tested.

A Toolkit for Delirium Identification and Promoting Partnerships Between Carers and Nurses: A Pilot Pre-Post Feasibility Study.

BACKGROUND: Delirium is frightening for people experiencing it and their carers, and it is the most common hospital-acquired complication worldwide. Delirium is associated with higher rates of morbidity, mortality, residential care home admission, dementia, and carer stress and burden, yet strategies to embed the prevention and management of delirium as part of standard hospital care remain challenging. Carers are well placed to recognize subtle changes indicative of delirium, and partner with nurses in the prevention and management of delirium. OBJECTIVE: To evaluate a Prevention & Early Delirium Identification Carer Toolkit (PREDICT), to support partnerships between carers and nurses to prevent and manage delirium. DESIGN: A pre-post-test intervention and observation study. MAIN MEASURES: Changes in carer knowledge of delirium; beliefs about their role in partnering with nurses and intended and actual use of PREDICT; carer burden and psychological distress. Secondary measures were rates of delirium. PARTICIPANTS: Participants were carers of Indigenous patients aged 45 years and older and non-Indigenous patients aged 65 years and older. INTERVENTION: Nurses implemented PREDICT, with a view to provide carers with information about delirium and strategies to address caregiving stress and burden. KEY RESULTS: Participants included 25 carers (43% response rate) (n = 17, 68% female) aged 29-88 (M = 65, SD = 17.7 years). Carer delirium knowledge increased significantly from pre-to-post intervention (p = < .001; CI 2.07-4.73). Carers' intent and actual use of PREDICT was (n = 18, 72%; and n = 17, 68%). Carer burden and psychological distress did not significantly change. The incidence of delirium in the intervention ward although not significant, decreased, indicating opportunity for scaling up. CONCLUSION: The prevention and management of delirium are imperative for safe and quality care for patients, carers, and staff. Further comprehensive and in-depth research is required to better understand underlying mechanisms of change and explore facets of nursing practice influenced by this innovative approach.

Late-onset delirious mania: Does it ring a bell?

BACKGROUND: Bell's mania was first described in 1849, and other terms have been used to describe this condition, including delirious mania, mania with delirium, and excited delirium. However, no international diagnostic manual has included mania as an independent diagnostic tool. The criteria for delirious mania were proposed by Bond et al. METHODS: We present a case of a man without a personal or family psychiatric history who experienced his first manic episode of delirium and psychosis at 76 years old. CONCLUSIONS: The case described in this study is compatible with mood disorders, the original description of Bell's mania, and Bond's definition of delirious mania. Although rare, extremely late-onset primary mania can occur without personal or family psychiatric history. The initial clinical presentation of delirium requires a thorough medical investigation, including magnetic resonance imaging (MRI) and lumbar puncture with neuronal antibodies. The addition of delirious mania to the group of bipolar disorders in future editions of The International Classification of Diseases (ICD) and Diagnostic and Statistical Manual of Mental Disorders (DSM) has therapeutic and prognostic implications. The Bond criteria can provide valuable information in this respect. Further investigations are necessary to clarify the pathophysiology and epidemiology of delirious mania.

Development of Postanesthesia Care Unit Delirium Is Associated with Differences in Aperiodic and Periodic Alpha Parameters of the Electroencephalogram during Emergence from General Anesthesia: Results from a Prospective Observational Cohort Study.

BACKGROUND: Intraoperative alpha-band power in frontal electrodes may provide helpful information about the balance of hypnosis and analgesia and has been associated with reduced occurrence of delirium in the postanesthesia care unit. Recent studies suggest that narrow-band power computations from neural power spectra can benefit from separating periodic and aperiodic components of the electroencephalogram. This study investigates whether such techniques are more useful in separating patients with and without delirium in the postanesthesia care unit at the group level as opposed to conventional power spectra. METHODS: Intraoperative electroencephalography recordings of 32 patients who developed perioperative neurocognitive disorders and 137 patients who did not were considered in this post hoc secondary analysis. The power spectra were calculated using conventional methods and the "fitting oscillations and one over f" algorithm was applied to separate aperiodic and periodic components to see whether the electroencephalography signature is different between groups. RESULTS: At the group level, patients who did not develop perioperative neurocognitive disorders presented with significantly higher alpha-band power and a broadband increase in power, allowing a "fair" separation based on conventional power spectra. Within the first third of emergence, the difference in median absolute alpha-band power amounted to 8.53 decibels (area under the receiver operator characteristics curve, 0.74 [0.65; 0.82]), reaching its highest value. In relative terms, the best separation was achieved in the second third of emergence, with a difference in medians of 7.71% (area under the receiver operator characteristics curve, 0.70 [0.61; 0.79]). The area under the receiver operator characteristics curve values were generally lower toward the end of emergence with increasing arousal. CONCLUSIONS: Increased alpha-band power during emergence in patients who did not develop perioperative neurocognitive disorders can be traced back to an increase in oscillatory alpha activity and an overall increase in aperiodic broadband power. Although the differences between patients with and without perioperative neurocognitive disorders can be detected relying on traditional methods, the separation of the signal allows a more detailed analysis. This may enable clinicians to detect patients at risk for developing perioperative neurocognitive disorders in the postanesthesia care unit early in the emergence phase.

Serum Neurofilament Light and Postoperative Delirium in Cardiac Surgery: A Preplanned Secondary Analysis of a Prospective Observational Study.

BACKGROUND: Impaired cognition is a major predisposing factor for postoperative delirium, but it is not systematically assessed. Anesthesia and surgery may cause postoperative delirium by affecting brain integrity. Neurofilament light in serum reflects axonal injury. Studies evaluating the perioperative course of neurofilament light in cardiac surgery have shown conflicting results. The authors hypothesized that postoperative serum neurofilament light values would be higher in delirious patients, and that baseline concentrations would be correlated with patients' cognitive status and would identify patients at risk of postoperative delirium. METHODS: This preplanned secondary analysis included 220 patients undergoing elective cardiac surgery with cardiopulmonary bypass. A preoperative cognitive z score was calculated after a neuropsychological evaluation. Quantification of serum neurofilament light was performed by the Simoa (Quanterix, USA) technique before anesthesia, 2 h after surgery, on postoperative days 1, 2, and 5. Postoperative delirium was assessed using the Confusion Assessment Method for Intensive Care Unit, the Confusion Assessment Method, and a chart review. RESULTS: A total of 65 of 220 (29.5%) patients developed postoperative delirium. Delirious patients were older (median [25th percentile, 75th percentile], 74 [64, 79] vs. 67 [59, 74] yr; P < 0.001) and had lower cognitive z scores (-0.52 ± 1.14 vs. 0.21 ± 0.84; P < 0.001). Postoperative neurofilament light concentrations increased in all patients up to day 5, but did not predict delirium when preoperative concentrations were considered. Baseline neurofilament light values were significantly higher in patients who experienced delirium. They were influenced by age, cognitive z score, renal function, and history of diabetes mellitus. Baselines values were significantly correlated with cognitive z scores (r, 0.49; P < 0.001) and were independently associated with delirium whenever the patient's cognitive status was not considered (hazard ratio, 3.34 [95% CI, 1.07 to 10.4]). CONCLUSIONS: Cardiac surgery is associated with axonal injury, because neurofilament light concentrations increased postoperatively in all patients. However, only baseline neurofilament light values predicted postoperative delirium. Baseline concentrations were correlated with poorer cognitive scores, and they independently predicted postoperative delirium whenever patient's cognitive status was undetermined.

Electroencephalogram Biomarkers from Anesthesia Induction to Identify Vulnerable Patients at Risk for Postoperative Delirium.

BACKGROUND: Postoperative delirium is a common complication in elderly patients undergoing anesthesia. Even though it is increasingly recognized as an important health issue, the early detection of patients at risk for postoperative delirium remains a challenge. This study aims to identify predictors of postoperative delirium by analyzing frontal electroencephalogram at propofol-induced loss of consciousness. METHODS: This prospective, observational single-center study included patients older than 70 yr undergoing general anesthesia for a planned surgery. Frontal electroencephalogram was recorded on the day before surgery (baseline) and during anesthesia induction (1, 2, and 15 min after loss of consciousness). Postoperative patients were screened for postoperative delirium twice daily for 5 days. Spectral analysis was performed using the multitaper method. The electroencephalogram spectrum was decomposed in periodic and aperiodic (correlates to asynchronous spectrum wide activity) components. The aperiodic component is characterized by its offset (y intercept) and exponent (the slope of the curve). Computed electroencephalogram parameters were compared between patients who developed postoperative delirium and those who did not. Significant electroencephalogram parameters were included in a binary logistic regression analysis to predict vulnerability for postoperative delirium. RESULTS: Of 151 patients, 50 (33%) developed postoperative delirium. At 1 min after loss of consciousness, postoperative delirium patients demonstrated decreased alpha (postoperative delirium: 0.3 µV2 [0.21 to 0.71], no postoperative delirium: 0.55 µV2 [0.36 to 0.74]; P = 0.019] and beta band power [postoperative delirium: 0.27 µV2 [0.12 to 0.38], no postoperative delirium: 0.38 µV2 [0.25 to 0.48]; P = 0.003) and lower spectral edge frequency (postoperative delirium: 10.45 Hz [5.65 to 15.04], no postoperative delirium: 14.56 Hz [9.51 to 16.65]; P = 0.01). At 15 min after loss of consciousness, postoperative delirium patients displayed a decreased aperiodic offset (postoperative delirium: 0.42 µV2 (0.11 to 0.69), no postoperative delirium: 0.62 µV2 [0.37 to 0.79]; P = 0.004). The logistic regression model predicting postoperative delirium vulnerability demonstrated an area under the curve of 0.73 (0.69 to 0.75). CONCLUSIONS: The findings suggest that electroencephalogram markers obtained during loss of consciousness at anesthesia induction may serve as electroencephalogram-based biomarkers to identify at an early time patients at risk of developing postoperative delirium.

DeltaScan for the Assessment of Acute Encephalopathy and Delirium in ICU and non-ICU Patients, a Prospective Cross-Sectional Multicenter Validation Study.

OBJECTIVES: To measure the diagnostic accuracy of DeltaScan: a portable real-time brain state monitor for identifying delirium, a manifestation of acute encephalopathy (AE) detectable by polymorphic delta activity (PDA) in single-channel electroencephalograms (EEGs). DESIGN: Prospective cross-sectional study. SETTING: Six Intensive Care Units (ICU's) and 17 non-ICU departments, including a psychiatric department across 10 Dutch hospitals. PARTICIPANTS: 494 patients, median age 75 (IQR:64-87), 53% male, 46% in ICUs, 29% delirious. MEASUREMENTS: DeltaScan recorded 4-minute EEGs, using an algorithm to select the first 96 seconds of artifact-free data for PDA detection. This algorithm was trained and calibrated on two independent datasets. METHODS: Initial validation of the algorithm for AE involved comparing its output with an expert EEG panel's visual inspection. The primary objective was to assess DeltaScan's accuracy in identifying delirium against a delirium expert panel's consensus. RESULTS: DeltaScan had a 99% success rate, rejecting 6 of the 494 EEG's due to artifacts. Performance showed and an Area Under the Receiver Operating Characteristic Curve (AUC) of 0.86 (95% CI: 0.83-0.90) for AE (sensitivity: 0.75, 95%CI=0.68-0.81, specificity: 0.87 95%CI=0.83-0.91. The AUC was 0.71 for delirium (95%CI=0.66-0.75, sensitivity: 0.61 95%CI=0.52-0.69, specificity: 72, 95%CI=0.67-0.77). Our validation aim was an NPV for delirium above 0.80 which proved to be 0.82 (95%CI: 0.77-0.86). Among 84 non-delirious psychiatric patients, DeltaScan differentiated delirium from other disorders with a 94% (95%CI: 87-98%) specificity. CONCLUSIONS: DeltaScan can diagnose AE at bedside and shows a clear relationship with clinical delirium. Further research is required to explore its role in predicting delirium-related outcomes.

Preoperative Delirium Risk Screening in Patients Undergoing a Cardiac Surgery: Results from the Prospective Observational FINDERI Study.

OBJECTIVE: Postoperative delirium (POD) is a common complication of cardiac surgery that is associated with higher morbidity, longer hospital stay, cognitive decline, and mortality. Preoperative assessments may help to identify patients´ POD risk. However, a standardized screening assessment for POD risk has not been established. DESIGN: Prospective observational FINd DElirium RIsk factors (FINDERI) study. PARTICIPANTS: Patients aged ≥50 years undergoing cardiac surgery. MEASUREMENTS: The primary aim was to analyze the predictive value of the Delirium Risk Screening Questionnaire (DRSQ) prior to cardiac surgery. Secondary aims are to investigate cognitive, frailty, and geriatric assessments, and to use data-driven machine learning (ML) in predicting POD. Predictive properties were assessed using receiver operating characteristics analysis and multivariate approaches (regularized LASSO regression and decision trees). RESULTS: We analyzed a data set of 504 patients (68.3 ± 8.2 years, 21.4% women) who underwent cardiac surgery. The incidence of POD was 21%. The preoperatively administered DRSQ showed an area under the curve (AUC) of 0.68 (95% CI 0.62, 0.73), and the predictive OR was 1.25 (95% CI 1.15, 1.35, p <0.001). Using a ML approach, a three-rule decision tree prediction model including DRSQ (score>7), Trail Making Test B (time>118), and Montreal Cognitive Assessment (score ≤ 22) was identified. The AUC of the three-rule decision tree on the training set was 0.69 (95% CI 0.63, 0.75) and 0.62 (95% CI 0.51, 0.73) on the validation set. CONCLUSION: Both the DRSQ and the three-rule decision tree might be helpful in predicting POD risk before cardiac surgery.

Acute encephalopathy in the ICU: a practical approach.

PURPOSE OF REVIEW: Acute encephalopathy (AE) - which frequently develops in critically ill patients with and without primary brain injury - is defined as an acute process that evolves rapidly and leads to changes in baseline cognitive status, ranging from delirium to coma. The diagnosis, monitoring, and management of AE is challenging. Here, we discuss advances in definitions, diagnostic approaches, therapeutic options, and implications to outcomes of the clinical spectrum of AE in ICU patients without primary brain injury. RECENT FINDINGS: Understanding and definitions of delirium and coma have evolved. Delirium is a neurocognitive disorder involving impairment of attention and cognition, usually fluctuating, and developing over hours to days. Coma is a state of unresponsiveness, with absence of command following, intelligible speech, or visual pursuit, with no imaging or neurophysiological evidence of cognitive motor dissociation. The CAM-ICU(-7) and the ICDSC are validated, guideline-recommended tools for clinical delirium assessment, with identification of clinical subtypes and stratification of severity. In comatose patients, the roles of continuous EEG monitoring and neuroimaging have grown for the early detection of secondary brain injury and treatment of reversible causes. SUMMARY: Evidence-based pharmacologic treatments for delirium are limited. Dexmedetomidine is effective for mechanically ventilated patients with delirium, while haloperidol has minimal effect of delirium but may have other benefits. Specific treatments for coma in nonprimary brain injury are still lacking.

How to manage catatonia, Parkinson and dementia in ICU.

PURPOSE OF REVIEW: The rising prevalence of neurodegenerative and mental disorders, combined with the challenges posed by their frailty, has presented intensivists with complex issues in the intensive care unit (ICU). This review article explores specific aspects of care for patients with catatonia, Parkinson's disease (PD), and dementia within the context of the ICU, shedding light on recent developments in these fields. RECENT FINDINGS: Catatonia, a neuropsychiatric syndrome with potentially life-threatening forms, remains underdiagnosed, and its etiologies are diverse. PD patients in the ICU present unique challenges related to admission criteria, dopaminergic treatment, and respiratory care. Dementia increases the risk of delirium. Delirium is associated with long-term cognitive impairment and dementia. SUMMARY: While evidence is lacking, further research is needed to guide treatment for ICU patients with these comorbidities.

Does the Etiology, Phenomenology and Motor Subtype of Delirium Differ When It Occurs in Patients With An Underlying Dementia?: A Multi-Site, International Study.

OBJECTIVES: To compare the etiology, phenomenology and motor subtype of delirium in patients with and without an underlying dementia. METHODS: A combined dataset (n = 992) was collated from two databases of older adults (>65 years) from liaison psychiatry and palliative care populations in Ireland and India. Phenomenology and severity of delirium were analysed using the Delirium Symptom Rating Scale Revised (DRS-R98) and contributory etiologies for the delirium groups were ascertained using the Delirium Etiology Checklist (DEC). Delirium motor subtype was documented using the abbreviated version of the Delirium Motor Subtype Scale (DMSS4). RESULTS: Delirium superimposed on dementia (DSD) showed greater impairment in short term memory, long term memory and visuospatial ability than the delirium group but showed significantly less perceptual disturbance, temporal onset and fluctuation. Systemic infection, cerebrovascular and other Central nervous system etiology were associated with DSD while metabolic disturbance, organ insufficiency and intracranial neoplasm were associated with the delirium only group. CONCLUSION: The etiology and phenomenology of delirium differs when it occurs in the patient with an underlying dementia. We discuss the implications in terms of identification and management of this complex condition.

Practical Application of a Battery of Brief Tools to Evaluate Geriatric Medical Inpatients for the Three Ds.

OBJECTIVE: The investigators aimed to identify the clinical characteristics of patients with or without delirium and preexisting depression, dementia, both, or neither by using validated tools easily administered in clinical practice. METHODS: In this cross-sectional prospective observational study conducted in Medellín, Colombia, 200 geriatric inpatients were evaluated with the Delirium Diagnostic Tool-Provisional (DDT-Pro), Informant Questionnaire on Cognitive Decline in the Elderly, Hachinski Ischemic Scale, Cornell Scale for Depression in Dementia, and Charlson Comorbidity Index-short form. Delirium motor subtype, mortality, and length of hospital stay were assessed. RESULTS: The study included 134 patients without delirium (67%), 14 with delirium only (7%), 16 with delirium and dementia (8%), 13 with delirium and depression (7%), and 23 with delirium, dementia, and depression (the three Ds) (12%). Prevalence rates of dementia (59%) and depression (55%) among 66 patients with delirium were higher than prevalence rates among patients without delirium (13% and 28%, respectively), suggesting that both conditions are risk factors. Main medical diagnoses, mortality, and dementia type did not differ among groups. Motor subtypes were similar among delirium groups. Patients in the delirium groups, except those in the delirium and depression group, were older than patients without delirium. Medical burden was highest among the patients with delirium and dementia and those with all three conditions. Delirium and dementia were more severe when comorbid with each other. Depression was most severe among patients with delirium and depression. Patients with all three conditions had a longer length of hospital stay than those without delirium. CONCLUSIONS: Using brief tools to detect dementia and depression in conjunction with the DDT-Pro to assess delirium diagnosis and severity is feasible and enables a more in-depth evaluation of elderly hospitalized patients. Because previous longitudinal research suggests that these comorbid conditions influence prognosis following a delirium episode, better identification of the three Ds offers proactive interventional opportunities. Depression is an underrecognized risk factor for delirium.

Biomarkers of neurodegeneration and neural injury as potential predictors for delirium.

OBJECTIVES: Determine if biomarkers of Alzheimer's disease and neural injury may play a role in the prediction of delirium risk. METHODS: In a cohort of older adults who underwent elective surgery, delirium case-no delirium control pairs (N = 70, or 35 matched pairs) were matched by age, sex and vascular comorbidities. Biomarkers from CSF and plasma samples collected prior to surgery, including amyloid beta (Aß)42 , Aß40 , total (t)-Tau, phosphorylated (p)-Tau181 , neurofilament-light (NfL), and glial fibrillary acid protein (GFAP) were measured in cerebrospinal fluid (CSF) and plasma using sandwich enzyme-linked immunosorbent assays (ELISAs) or ultrasensitive single molecule array (Simoa) immunoassays. RESULTS: Plasma GFAP correlated significantly with CSF GFAP and both plasma and CSF GFAP values were nearly two-fold higher in delirium cases. The median paired difference between delirium case and control without delirium for plasma GFAP was not significant (p = 0.074) but higher levels were associated with a greater risk for delirium (odds ratio 1.52, 95% confidence interval 0.85, 2.72 per standard deviation increase in plasma GFAP concentration) in this small study. No matched pair differences or associations with delirium were observed for NfL, p-Tau 181, Aß40 and Aß42 . CONCLUSIONS: These preliminary findings suggest that plasma GFAP, a marker of astroglial activation, may be worth further investigation as a predictive risk marker for delirium.

Assessing patterns of delirium symptoms reveals a novel subtype among elective surgical patients with postoperative delirium.

OBJECTIVES: Prior studies reported incidence of hypoactive and hyperactive subtypes of postoperative delirium, but did not consider cognitive symptoms of delirium which are highlighted in the DSM-5 criteria for delirium. This study aims to address this gap in the literature by classifying cases of delirium according to their constellation of cognitive and motoric symptoms of delirium using a statistical technique called Latent Class Analysis (LCA). METHODS: Data were from five independent study cohorts (N = 1968) of patients who underwent elective spine, knee/hip, or elective gastrointestinal and thoracic procedures, between 2001 and 2017. Assessments of delirium symptoms were conducted using the long form of the Confusion Assessment Method (CAM) pre- and post-surgery. Latent class analyses of CAM data from the first 2 days after surgery were conducted to determine subtypes of delirium based on patterns of cognitive and motoric symptoms of delirium. We also determined perioperative patient characteristics associated with each latent class of delirium and assessed whether the length of delirium for each of the patterns of delirium symptoms identified by the latent class analysis. RESULTS: The latent class model from postoperative day 1 revealed three distinct patterns of delirium symptoms. One pattern of symptoms, denoted as the Hyperalert class, included patients whose predominant symptoms were being hyperalert or overly sensitive to environmental stimuli and having a low level of motor activity. Another pattern of symptoms, denoted as the Hypoalert class, included patients whose predominant symptom was being hypoalert (lethargic or drowsy). A third pattern of symptoms, denoted as the Cognitive Changes class, included patients who experienced new onset of disorganized thinking, memory impairment, and disorientation. Among 352 patients who met CAM criteria for delirium on postoperative day 1, 34% had symptoms that fit within the Hyperalert latent class, 39% had symptoms that fit within the Hypoalert latent class, and 27% had symptoms that fit within the Cognitive Changes latent class. Similar findings were found when latent class analysis was applied to those who met CAM criteria for delirium on postoperative day 2. Multinomial regression analyses revealed that ASA class, surgery type, and preoperative cognitive status as measured by the Telephone Interview for Cognitive Status (TICS) scores were associated with class membership. Length of delirium differed between the latent classes with the Cognitive Changes latent class having a longer duration compared to the other two classes. CONCLUSIONS: Older elective surgery patients who did not have acute events or illnesses or a diagnosis of dementia prior to surgery displayed varying symptoms of delirium after surgery. Compared to prior studies that described hypoactive and hyperactive subtypes of delirium, we identified a novel subtype of delirium that reflects cognitive symptoms of delirium. The three subtypes of delirium reveal distinct patterns of delirium symptoms which provide insight into varying risks and care needs of patients with delirium, indicating the necessity of future research on reducing risk for cognitive symptoms of delirium.

Poor olfaction prior to cardiac surgery: Association with cognition, plasma neurofilament light, and post-operative delirium.

OBJECTIVES: Post-operative delirium (POD) affects up to 50% of cardiac surgery patients, with higher incidence in older adults. There is increasing need for screening tools that identify individuals most vulnerable to POD. Here, we examined the relationship between pre-operative olfaction and both incident POD and POD severity in patients undergoing cardiac surgery. We also examined cross-sectional relationships between baseline olfaction, cognition, and plasma neurofilament light (NfL). METHODS: Individuals undergoing cardiac surgery (n = 189; mean age = 70 years; 75% men) were enrolled in a clinical trial of cerebral autoregulation monitoring. At baseline, odor identification performance (Brief Smell Identification Test), cognitive performance, and plasma concentrations of NfL levels (Simoa™ NF-Light Assay) were measured. Delirium was assessed with the Confusion Assessment Method (CAM) or CAM-ICU, and delirium severity was assessed using the Delirium Rating Scale-Revised-98. The association of baseline olfaction, delirium incidence, and delirium severity was examined in regression models adjusting for age, duration of cardiopulmonary bypass, logistic European System for Cardiac Operative Risk Evaluation (EuroSCORE), and baseline cognition. RESULTS: Olfactory dysfunction was present in 30% of patients, and POD incidence was 44%. Pre-operative olfactory dysfunction was associated with both incident POD (OR = 3.17, p = 0.001) and greater severity of POD after cardiac surgery (OR = 3.94 p < 0.001) in models adjusted for age, duration of bypass, and a surgical risk score. The addition of baseline cognition attenuated the strength of the association, but it remained significant for incident POD (OR = 2.25, p = 0.04) and POD severity (OR 2.10, p = 0.04). Poor baseline olfaction was associated with greater baseline cognitive dysfunction (p < 0.001) and increased baseline plasma NfL concentrations (p = 0.04). Neither age, cognition, nor baseline NFL concentration modified the association of impaired olfaction and delirium outcomes. CONCLUSIONS: Olfactory assessment may be a useful pre-surgical screening tool for the identification of patients undergoing cardiac surgery at increased risk of POD. Identifying those at highest risk for severe delirium and poor cognitive outcomes following surgery would allow for earlier intervention and pre-operative rehabilitation strategies, which could ultimately impact the functional disability and morbidity associated with POD.

Association of perioperative plasma concentration of neurofilament light with delirium after cardiac surgery: a nested observational study.

BACKGROUND: Neurofilament light is a blood-based biomarker of neuroaxonal injury that can provide insight into perioperative brain vulnerability and injury. Prior studies have suggested that increased baseline and postoperative concentrations of neurofilament light are associated with delirium after noncardiac surgery, but results are inconsistent. Results have not been reported in cardiac surgery patients, who are among those at highest risk for delirium. We hypothesised that perioperative blood concentrations of neurofilament light (both baseline and change from baseline to postoperative day 1) are associated with delirium after cardiac surgery. METHODS: This study was nested in a trial of arterial blood pressure targeting during cardiopulmonary bypass using cerebral autoregulation metrics. Blood concentrations of neurofilament light were measured at baseline and on postoperative day 1. The primary outcome was postoperative delirium. Regression models were used to examine the associations between neurofilament light concentration and delirium and delirium severity, adjusting for age, sex, race, logistic European System for Cardiac Operative Risk Evaluation, bypass duration, and cognition. RESULTS: Delirium occurred in 44.6% of 175 patients. Baseline neurofilament light concentration was higher in delirious than in non-delirious patients (median 20.7 pg ml-1 [IQR 16.1-33.2] vs median 15.5 pg ml-1 [IQR 12.1-24.2], P<0.001). In adjusted models, greater baseline neurofilament light concentration was associated with delirium (odds ratio, 1.027; 95% confidence interval, 1.003-1.053; P=0.029) and delirium severity. From baseline to postoperative day 1, neurofilament light concentration increased by 42%, but there was no association with delirium. CONCLUSIONS: Baseline neurofilament light concentration, but not change from baseline to postoperative day 1, was associated with delirium after cardiac surgery.

Correlation of the Critical Care Pain Observation Tool and Numeric Rating Scale in Intensive Care Unit Patients.

PURPOSE: We sought to determine the correlation between the Numeric Rating Scale (NRS) and Critical-Care Pain Observation Tool (CPOT) to determine whether clinical factors modified the relationship between NRS and CPOT assessments. MATERIALS AND METHODS: We included nonventilated adults admitted to the MICU or SICU who could self-report pain and had at least 3 paired NRS and CPOT assessments. We performed Spearman correlation to assess overall correlation and performed proportional odds logistic regression to evaluate whether the relationship between NRS and CPOT assessments was modified by clinical factors. RESULTS: Nursing staff performed NRS and CPOT assessments every 4 h in 1302 patients, leading to 61,142 matched assessments. We found that the NRS and CPOT have a Spearman correlation coefficient of 0.56 and an intraclass correlation coefficient of 0.32 in intensive care unit patients. Factors that modified the relationship between the NRS and CPOT included the presence of delirium (P < .001) and lower mean daily Richmond Agitation Sedation Scale (<0.001). CONCLUSIONS: The correlation coefficient between the NRS and the CPOT was found to be 0.56. The presence of delirium, decreased level of arousal, modified the relationship between the NRS and CPOT. Self-reported and behavioral pain assessments cannot be used interchangeably in critically ill adults.

The Validity and Applicability of the Revised Delirium Rating Scale (DRS-R98) for Delirium Severity Assessment in a Critical Care Setting.

BACKGROUND: Delirium is a neuropsychiatric syndrome common in critical illness. Worsening delirium severity is associated with poorer clinical outcomes, yet its assessment remains under-reported with most severity assessment tools not validated for critical care. The DRS-R98 is a widely applied and validated tool. The aim of this project is to report the validation and utility of the DRS-R98 in critical illness. METHODS: This prospective, cohort study was conducted in adults with delirium admitted to a critical care unit and predicted to stay for ≥ 24 h. We excluded patients with severe neurological or communication barriers that would have interfered with the DRS-R98 assessment. Patients were screened using a delirium detection algorithm and the Confusion Assessment Method for the Intensive Care Unit. Eligible patient informations were collected and reported to qualified assessor/s before visiting clinical areas, confirming delirium presence and undertaking DRS- R98 assessments. To assess the tool's construct validity, an intensivist completed the Clinical Global Impression-Scale (CGI-S). To calculate the inter-rater reliability (IRR) a subset of patients were simultaneously evaluated by two assessors. RESULTS: We assessed 22 patients, 73% were male, with a median age of 65 years (IQR14). The DRS -R98 mean (SD) severity score was 24 (+/-7.7), total scale was 29 (+/18.0), and CGI-S 3.5 (+/11.5). Assessment duration was 90 min (+/-55) and 15 min (+/-5) for record data extraction and clinical assessment respectively. The CGI-S significantly correlated with DRS-R98 severity (r = 0.626) and total (r = 0.628) scales. The DRS-R98 Cronbach's alpha was 0.896 for severity scale and 0.886 for total scale. The inter-rater reliability (IRR) was assessed in six patients and reported an inter-correlation coefficient of 0.505 (p = 0.124) and 0.565 (p = 0.93) for the severity and total scale respectively. CONCLUSIONS: In critical care, the Delirium Rating Scale R98 had good construct validity, excellent internal consistency, and moderate inter-rater reliability.

Differences in Delirium Evaluation and Pharmacologic Management in Children With Developmental Delay: A Retrospective Case-Control Study.

Delirium is associated with increased mortality and cost, decreased neurocognition, and decreased quality of life in the pediatric intensive care unit (PICU) population. The Cornell Assessment for Pediatric Delirium (CAPD) is used in PICUs for delirium screening but lacks specificity in children with developmental delay (DD). Within a cohort of children receiving pharmacologic treatment for intensive care unit (ICU) delirium, we compared delirium scoring and medication management between children with and without DD. We hypothesized that CAPD scores and treatment decisions would differ between DD and neurotypical (NT) patients. In this retrospective case-control study, we queried the medical record of patients admitted to our PICU with respiratory failure from June 2018 to March 2022 who received antipsychotics typically used for ICU delirium. Antipsychotics prescribed for home use were excluded. Nonparametric statistics compared demographics, CAPD scores, medication choice, dosing (mg/kg), and medication continuation after discharge between those with and without DD based on the ICD-10 codes. Twenty-one DD admissions and 59 NT admissions were included. Groups did not significantly differ by demographics, LOS, drug, or initial dosage. DD patients had higher median CAPD scores at admission (17 vs 13; P = .02) and treatment initiation (18 vs 16.5; P = .05). Providers more frequently escalated doses in DD patients (13/21 vs 21/59; P = .04) and discharged them home on new antipsychotics (7/21 vs 5/59; P = .01). DD patients experience delirium screening and management differently than NT counterparts. Providers should be aware of baseline elevated scores in DD patients and carefully attend to indications for dosage escalation. Further work is needed to understand if prolonged duration, even after hospital discharge, benefits patients, or represents potential disparity in care.