Delirium is common among critically ill older patients with chronic obstructive pulmonary disease (COPD). This study aims to develop a nomogram model to predict the risk of ICU delirium in older patients with COPD.

This study included 1,912 older COPD patients admitted to the ICU from the MIMIC-IV database. The patients were randomly divided into training and validation sets in a 7:3 ratio. LASSO regression, univariable and multivariable logistic regression were used to select the best predictive factors based on demographic, clinical, laboratory, and treatment data at ICU admission. A nomogram model was then constructed. The model's accuracy was evaluated using calibration curves. Its predictive performance and clinical utility were assessed using the area under the receiver operating characteristic curve (AUC), decision curve analysis (DCA), and clinical impact curves (CIC).

A total of 638 patients (33.4%) developed ICU delirium, with a median age of 76.00 (IQR: 71.00-83.00) years. Ten independent factors were identified for the nomogram model, including cerebrovascular disease (OR: 1.91; 95% CI, 1.38-2.64), Charlson Comorbidity Index (OR: 1.08; 95% CI, 1.02-1.13), Glasgow Coma Scale (OR: 0.82; 95% CI, 0.77-0.87), SOFA score (OR: 1.15; 95% CI, 1.07-1.22), heart rate (OR: 1.01; 95% CI, 1.01-1.02), body temperature (OR: 1.60; 95% CI, 1.14-2.24), blood urea nitrogen (OR: 1.01; 95% CI, 1.00-1.02), 24-hour urine output (OR: 1.02; 95% CI, 1.01-1.02), fentanyl (OR: 1.94; 95% CI, 1.47-2.55), and oxygen flow (OR: 1.04; 95% CI, 1.02-1.07). The model achieved an AUC of 0.86 (95% CI, 0.83-0.90) in the training set and 0.86 (95% CI, 0.84-0.88) in the validation set. The calibration curve showed good agreement between predicted and observed values (P > 0.05). DCA and CIC results indicated the model's strong predictive value and clinical applicability.

This study developed an intuitive and simple nomogram model to predict the risk of ICU delirium in older patients with COPD. The model can help clinicians quickly identifying high-risk delirium patients upon ICU admission, thereby optimizing early intervention and treatment strategies.

Delirium is a serious postoperative complication, increasingly recognized for its heightened risk following the use of sedative drugs. This study aimed to assess the relationship of esketamine, sevoflurane, propofol, and dexmedetomidine with the risk of delirium.

Data were obtained from the FDA Adverse Event Reporting System (FAERS) database covering the period from the first quarter of 2004 to the second quarter of 2024. Cases of delirium associated with these medications were identified using preferred terms (PTs) defined by the Medical Dictionary for Regulatory Activities (MedDRA 20.0). Disproportionality analyses employed reported odds ratios (ROR) and multiple gamma-Poisson shrinkage (MGPS), while logistic regression assessed the effects of age and sex on the risk of delirium.

A total of 21,433,114 adverse events (AEs) were recorded in the FAERS database, including 16 cases of delirium associated with esketamine, 189 with propofol, 90 with sevoflurane, and 103 with dexmedetomidine. Propofol (ROR: 5.44, EBGM05: 4.8), sevoflurane (ROR: 9.9, EBGM05: 8.26), and dexmedetomidine (ROR: 21.1, EBGM05: 17.67) were significantly associated with the delirium risk, whereas esketamine (ROR: 1.45, EBGM05: 0.96) did not show a significant association. Age was identified as a significant risk factor for delirium, particularly in patients aged 55 years and older.

The findings indicate a significant correlation between propofol, sevoflurane, and dexmedetomidine and the risk of delirium, whereas esketamine does not appear to have a significant association with delirium. Future studies should further explore drug administration and dosage effects on delirium risk to improve clinical safety.

Several observational studies have revealed that different neurotrophic factors (NTFs) are associated with delirium, yet the direction and magnitude of the causal association remain poorly understood. Herein, we performed a two-sample Mendelian randomization (MR) analysis to investigate the causal relationship between these factors and delirium.

GWAS data for delirium were sourced from the FINN10 database; GWAS data for risk factors (protein kinase C-binding protein NELL1, neurotrophin-3, neurotrophin-4, brain-derived neurotrophic factor levels, nerve growth factor, ciliary neurotrophic factor, and glial cell-derived neurotrophic factor levels) were from the IEU Open GWAS. Inverse-variance weighted (IVW) was used as a primary analysis. MR-Egger, weighted median (WM), and weighted model were applied to validate the robustness of the results. The MR-Egger regression method was used to explore the presence of horizontal pleiotropy, and the MR pleiotropy residual sum, and outlier (MR-PRESSO) method was applied to detect potential outliers. Cochran's Q test assessed heterogeneity among instrumental variables (IVs). The leave-one-out (LOO) method was used to enhance the precision and veracity of our findings.

IVW analyses revealed no association between risk factors and delirium. MR Egger, WM, and the weighted mode approach further confirmed these data. MR-Egger regression analysis confirmed the absence of directional pleiotropy in our analysis. Heterogeneity and sensitivity analyses showed reliable results.

No association between other factors and delirium was identified; however, further research is needed to determine if these results apply to other races. Also, advances in molecular biology and epigenetics may shed light on this topic.

Behavioral symptoms in hospitalized older adults with cognitive impairment often lead to physical and chemical restraint use, despite associated harms. Patient-centered care models show promise in reducing restraint use but are rarely implemented in routine practice. This project implemented CoCare-CI, a clinical innovation to address behavioral symptoms in hospitalized older adults with cognitive impairment.

CoCare-CI was implemented on a 24-bed ACE unit in a 128-bed community hospital from January 2023 to August 2024 by a multidisciplinary team led by a geriatric nurse practitioner (GNP). CoCare-CI emphasized (1) systematic screening and assessment of mentation, and (2) individualized management plans for delirium or dementia. Implementation followed a phased, cyclical approach with champions supporting process improvement. Baseline restraint data (January-August 2023) were compared to intervention data (September 2023-August 2024). Primary outcomes included physical and chemical restraint use; process measures included documentation rates of the Confusion Assessment Method (CAM), CAM-Severity (CAM-S), Six-Item Cognitive Impairment Test (6CIT), and 4Ms checklist.

Among 949 patients (mean age 81.5 years, 59% female, 80.6% White), 34.1% had cognitive impairment at baseline, including 22.6% with dementia and 11.5% with a significant 6CIT score (≥ 8). Documentation rates improved for CAM (68%-86%), CAM-S (0%-79%), 6CIT (0%-89%), and 4Ms checklist (0%-96%). Physical restraint use decreased from 4.3% to 0.7%, and chemical restraint use dropped from 7.6% to 2.3%. Most restraint use (84.2%, 16/19) was deemed potentially avoidable, with root cause analysis revealing that 78.6% (11/14) of patients with restraint orders had moderate to severe dementia with behavioral symptoms.

CoCare-CI is associated with reductions in reduced physical and chemical restraint use, demonstrating potential for dissemination within routine clinical practice. Future research should assess sustainability, broader applicability, and integration of additional 4Ms components.

(1) Gain insight into the mechanisms of postoperative delirium (POD). (2) Determine mechanistic overlap with post-ictal delirium (PID). Epilepsy patients undergoing intracranial electrophysiological monitoring can experience both POD and PID, and thus are suitable subjects for these investigations.

POD was assessed daily after surgery. PID was assessed following seizures. Resting state data were collected following delirium assessments, during a control period, and during sleep. Slow-wave activity (SWA: 1-4 Hz) and resting state functional connectivity were compared between different time points and according to delirium status.

POD was present in 6 of 20 participants. Post-operatively, SWA was globally elevated in all participants but highest in POD+ participants. POD+ participants exhibited altered functional connectivity compared to POD-. These differences persisted even after resolution of delirium. PID was present in 7 of 15 participants and was predicted by seizures involving prefrontal cortex. PID+ participants exhibited higher post-ictal SWA versus PID-; no differences in functional connectivity were observed. Post-operative and post-ictal SWA was comparable to sleep in some participants.

Elevated SWA may predispose patients to both post-operative and post-ictal delirium and may indicate overlapping mechanisms.

Delirium treatments focused on SWA may be most effective for ameliorating cognitive symptoms.

Delirium is a heterogeneous syndrome primarily characterized by fluctuations in attention and awareness. Sleep-wake disturbances are a common and significant feature of delirium and can manifest as circadian rhythm inversion, sleep fragmentation, and reduced rapid eye movement (REM) and slow-wave sleep. Some literature suggests that the relationship between sleep disruption and delirium is reciprocal wherein the two reinforce one another and may share an underlying etiology. As there are no FDA-approved medications for delirium or delirium-related sleep disturbances, management is primarily focused on addressing underlying medical concerns and promoting physiologic circadian patterns with non-pharmacological behavioral interventions. In practice, however, medications are often used, albeit with limited evidence to support their use. This literature review explores the pharmacology and pharmacokinetics of several medications with literature investigating their use in delirium: melatonin, ramelteon, dual orexin receptor antagonists (DORAs), and dexmedetomidine. Current evidence suggests a possible benefit of ramelteon or melatonin, dexmedetomidine for patients in the ICU setting, and DORAs as therapeutic options for the re-regulation of sleep-wake cycle disruption in delirium. We discuss pertinent pharmacokinetic and pharmacodynamic factors that may influence clinical decision-making regarding these interventions.

As the global population ages, the mechanisms underlying age-related susceptibility to delirium have attracted attention. Given the central role of microglia in the pathogenesis of inflammation-related delirium, we investigated the temporal dynamics of neurobehavioral changes and microglial responses, following lipopolysaccharide (LPS, 200 μg/kg) administration in young and old male C57BL/6 mice. Although a similar illness trajectory across 48 h post-treatment (HPT) was observed in both age groups, old-LPS mice exhibited worsened delirium-like behavior. At 48 HPT, in old but not young mice, significantly decreased hippocampal neuronal activity coincided with microglial overactivation. Widespread hippocampal microglial activation was present at 3 HPT but subsided by 12 HPT in young but not old mice, indicating a generally retarded but prolonged microglial response to LPS challenge in old mice. However, for both age groups, at 3 HPT, p16INK4a-negative microglia (with low abundance in the aged brain) exhibited comparable morphological activation, which was not observed for p16INK4a-positive microglia (highly abundant in the aged brain). These results suggest that age-related susceptibility to LPS-induced delirium-like behavior accompanied by different patterns of microglial response might implicate microglial composition shifts and that optimizing microglial composition represents a promising approach to reduce vulnerability to inflammatory challenge.

This study carried out to examine the effects of nursing care given to coronary intensive care patients according to their circadian rhythms on sleep quality, pain, anxiety, and delirium.

This study was designed as a randomised controlled, clinical investigation. The study population consisted of patients treated in the coronary care unit of a training and research hospital between September 2022 and February 2023. Total of 44 participants were included. The included participants were followed up for 3 days in the coronary intensive care unit. Data were collected using "Patient Information Form, Sleep Quality Scale in Coronary Intensive Care Patients (SQ-CC), Visual Analogue Scale (VAS), Morningness-Eveningness Questionnaire (MEQ), Hospital Anxiety and Depression Scale (HADS), Intensive Care Delirium Screening Checklist (ICDSC)." In addition, melatonin and cortisol measurements were made, and sleep data were taken with a smartwatch. Patients with intermediate chronotype, delirium, on ventilator support, or using sedative drugs were excluded. The chronotypes of the participants were determined, and the patients in the intervention group were given nursing care by their circadian rhythms. No intervention was made to the control group, and their routine care was continued in accordance with intensive care unit functioning. Frequency distribution, dependent and independent sample t-test, Wilcoxon test, repeated measures analysis of variance, Mann Whitney U, and chi-square analysis were used to evaluate the data. The study has been registered in ClinicalTrials.gov (Identifiers: NCT04934436). During statistical analysis, the groups were coded as Group A and Group B, ensuring blinding for the statistician.

The intervention group's sleep quality increased compared to the control group (post-test SQ-CC total scores: intervention group 22.41 ± 6.67 vs. control group 50.45 ± 10.63, p < 0.001). Although no significant difference was found between the groups as a result of the study, there was a significant decrease in the pain score in the intervention group (VAS pre-test: 1.55 ± 2.15, post-test: 0.68 ± 2.21, p = 0.036). The anxiety of the intervention group decreased significantly compared to the control group (post-test HADS-Anxiety scores: intervention group 3.18 ± 3.29 vs. control group 8.50 ± 5.66, p = 0.001). The post-test delirium score was higher in the control group compared to the intervention group (post-test ICDSC scores: intervention group 0.32 ± 0.48 vs. control group 1.18 ± 0.50, p < 0.001). Melatonin increased and cortisol decreased in both groups without statistically significant differences between them (melatonin and cortisol levels: p > 0.05). Considering the sound levels in the environment, the first-night decibel mean was significantly higher in the intervention group than in the control group (first-night decibel mean: intervention group 56.58 ± 2.43 dB vs. control group 54.51 ± 2.41 dB, p < 0.05). Finally, the smartwatch data show no significant difference in sleep times between groups (p < 0.05), but the intervention group had more deep and total sleep, while the control group had less deep sleep.

Nursing care given in accordance with the circadian rhythm increases sleep quality and reduces the risk of delirium and anxiety in patients followed up with acute coronary syndrome in the coronary intensive care unit.

Although alcohol consumption is considered one of the risk factors for delirium in intensive care unit (ICU) patients, quantitative research on the association between alcohol use disorder (AUD) and the development of delirium in the ICU remains relatively scarce.

This retrospective cohort study was conducted using the Medical Information Mart for Intensive Care-IV database, including all patients admitted to the ICU for the first time and underwent delirium assessment. Patients were divided into AUD and non-AUD groups, with the primary outcome being the occurrence of ICU delirium. Propensity score matching (PSM) was used to balance baseline characteristics between the two groups. The association between AUD and the occurrence of ICU delirium was evaluated using Cox proportional hazards and competing risk models, with sensitivity and subgroup analyses to assess the stability of the results.

A total of 35,053 patients were included, with 3,455 (9.9%) in the AUD group. The incidence of ICU delirium and ICU mortality were significantly higher in the AUD group compared to the non-AUD group, with a longer median ICU stay. Multivariable Cox regression analysis, adjusting for all covariates, revealed a significant association between AUD and increased risk of ICU delirium (HR 1.59, 95% CI 1.50-1.69, P < 0.01). After PSM, multivariable Cox regression analysis showed consistent results (HR 1.52, 95% CI 1.41-1.65, P < 0.01), and these results remained consistent after performing competitive risk analysis.

We found a significant correlation between AUD and the incidence of delirium in the ICU, highlighting the importance of assessing and managing the risk of delirium in patients with AUD in the ICU.

Not applicable.

Disparities exist in the identification, treatment, and management of delirium. These disparities can be most holistically and comprehensively understood by using a social-ecological model-which acknowledges multilevel impacts including individual, interpersonal, organizational, community, and policy-level factors-as well as a social determinant of health framework, that considers nonmedical factors that influence health outcomes. This narrative review leverages both frameworks to identify and discuss existing literature pertaining to the intersection of these social risk factors and delirium, focusing specifically on disparities due to racial and/or ethnic identity, language ability, and socioeconomic differences. We also look at disparities and the potential role of these social risk factors throughout the continuum of care, including prehospitalization, hospitalization, and posthospitalization factors. Understanding and analyzing the role of these inequities is critical to ensuring better health outcomes for patients at risk of and/or with delirium.

The present study aimed to investigate the relationship between delirium and tryptophan and its metabolites in critically ill older patients.

This prospective and observational study was conducted on patients who were > 60 years of age and hospitalized for at least 24 h at the internal medicine ICU in the tertiary health care unit (n = 120). All consecutively selected patients were evaluated for delirium at the baseline and follow-up period at the bedside by an intensive care specialist. At the end of the 24 h follow up, the patients were divided into two groups (with and without delirium). Clinical properties and tryptophan (TRP) and its metabolites [kynurenine (KYN), kynurenic acid (KYNA), quinolinic acid (QA), 3-hydroxykynurenine (3-HK), 3-hydroxyanthranilic acid (3HAA)] were compared between groups.

The median age of the patients was 79.5 (62-95) years and 53.3% were female. The median age and CCI score were significantly higher among patients with delirium than in those without delirium (P = 0.001 and 0.031, respectively). The level of TRP was significantly (borderline) decreased among patients with delirium (P = 0.056). The KYN/TRP and QA/TRP ratios were statistically and significantly higher in patients with delirium than those without (P < 0.001 and P = 0.016, respectively). The best predictive values for detecting delirium were calculated as ≤ 14,100 ng/mL for TRP (AUC: 0.601, P = 0.052), > 1.12 for KYN/TRP ratio (AUC: 0.704, P < 0.001), and > 0.75 for QA/TRP ratio (AUC: 0.627, P = 0.013). The QA/TRP ratio showed independent and borderline significant association with being delirium in multivariable regression analysis (Odds ratio: 2.007, P = 0.066).

This study demonstrated that tryptophan and its metabolites obtained within the first 24 h of ICU admission might have predictive value for determining high-risk older patients for delirium.

This meta-analysis aimed to evaluate the performance of machine learning (ML) models in predicting postoperative delirium (POD) and to provide guidance for clinical application.

PubMed, Embase, Cochrane Library, and Web of Science databases were searched from inception to April 29, 2024. Studies reported ML models for predicting POD in adult patients were included. Data extraction and risk of bias assessment were performed using the Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis - AI (TRIPOD-AI) and Prediction model Risk Of Bias ASsessment Tool (PROBAST) tools. Meta-analysis with the area under the curve (AUC) was performed using MedCalc software.

A total of 23 studies were included after screening. Age (n = 20, 86.95%) and Random Forest (RF) (n = 24, 17.27%) were the most frequently used feature and ML algorithm, respectively. The meta-analysis showed an overall AUC of 0.792. The ensemble models (AUC = 0.805) showed better predictive performance than single models (AUC = 0.782). Additionally, considerable variations in AUC were found among different ML algorithms, with AdaBoost (AB) demonstrating good performance with AUC of 0.870. Notably, the generalizability of these models was uncertain due to limitations in external validation and bias assessment.

The performance of ensemble models were higher than single models, and the AB algorithms demonstrated better performance, compared with other algorithms. However, further research was needed to enhance the generalizability and transparency of ML models.

Delirium is acute neurological failure that alters cognition and results in a state of confusion and lack of self-awareness. It commonly affects critically ill patients within intensive care units (ICUs), and the wide array of fluctuating symptoms frequently leads to underdiagnosis. Delirium results in cognitive impairment and increased rates of fatality, and accurate assessments are essential for improving patient outcomes. Barriers to delirium assessment stem from a lack of knowledge and assessment training among ICU nurses.

Using the Cumulative Index to Nursing and Allied Health Literature electronic database, a literature synthesis was conducted, analyzing journal articles addressing delirium education and training among ICU nurses and barriers associated with assessment.

Current literature identifies methods to overcome barriers through training, education, and continuous reinforcement of delirium assessment. The goals of this review are to identify the barriers to delirium assessment and make recommendations for education methods to increase the confidence of ICU nurses in the recognition of delirium to improve patient outcomes.

Early identification of delirium is crucial to improving patient outcomes. A standardized delirium educational program should be developed and implemented throughout the U.S. health care system. [J Contin Educ Nurs. 2024;55(11):530-534.].

Although serum bicarbonate is a reliable predictor of various disease complications, its relationship with postoperative delirium (POD) remains unclear. Our research aimed to assess the effect of baseline serum bicarbonate levels on the incidence of POD in cardiac surgery patients.

A retrospective analysis was conducted on cardiac surgery patients who met specific inclusion and exclusion criteria, using data from the Marketplace for Information in Critical Care Medicine (MIMIC-IV) database. Univariate and multivariate logistic regression models are employed to explore the correlation between serum bicarbonate levels and the risk of POD, and their predictive efficacy is assessed by means of restricted cubic spline regression models (RCS) and receiver operating characteristic curves (ROC). In addition, subgroup and sensitivity analyses are conducted to test the robustness of the results.

In this study, 5,422 patients were included, where the incidence of POD was 13.0%. For each 1 mmol/L increase in bicarbonate, a 13% reduction in the risk of POD was observed in the fully adjusted model (OR = 0.87, 95% CI: 0.83-0.91, P < 0.001). The RCS model demonstrated a linear negative correlation between the level of bicarbonate and the risk of POD (P for nonlinearity = 0.987). The ROC curve analysis demonstrated that the bicarbonate level had moderate predictive efficacy (AUC = 0.629). Both subgroup and sensitivity analyses reaffirmed the robustness of these results.

Lower baseline serum bicarbonate levels in cardiac surgery patients are linked to a higher risk of POD. Monitoring and adjusting serum bicarbonate levels may help identify high-risk patients and potentially improve outcomes.

 Delirium is a common and serious neurological complication in intensive care units (ICUs), often leading to poor patient outcomes and increased mortality. This study aimed to compare the incidence of delirium in ICU patients with COVID-19 to those with other respiratory infections in a private hospital in Costa Rica. Additionally, it evaluated the prevalence, severity, duration, and treatment of delirium in these critically ill patients.

A retrospective observational study was conducted, analyzing multiple variables obtained from the electronic health records of patients hospitalized in the ICU of Hospital Clinica Biblica. The study included patients admitted between January 2020 and December 2023. It compared the incidence of delirium among patients admitted for COVID-19 and those admitted for other diagnoses. The main outcomes measured were the incidence of delirium and the correlation of its management with international guidelines. The measures included the use of mechanical ventilation, the development of delirium, and the use of sedatives.

A total of 137 patients were analyzed, of whom 57.7% were over 70 years old, 67.2% were men, 45.2% were admitted with a diagnosis of COVID-19, 90.5% used mechanical ventilation, and 49.6% of patients developed delirium. Dexmedetomidine was the most used sedative, which was the only one that showed a significant relationship with the development of delirium (p=0.0002). Delirium management was mainly done through the administration of dexmedetomidine (52.9%) and quetiapine (41.2%). There was no correlation between delirium development and mortality (p=0.2670).

The study results do not show a significant relationship between COVID-19-positive patients and the development of delirium. Similarly, no higher mortality was observed in those patients who experienced delirium during their ICU stay.

Delirium commonly occurs in paediatric patients with acute critical illness and negatively affects clinical outcomes. Variations in delirium knowledge levels and its management have been noted among nurses.

This study investigated nurses' experiences and knowledge levels regarding paediatric delirium. Additionally, we aimed to assess the gap between knowledge levels and practical experiences with paediatric delirium.

This cross-sectional descriptive study conveniently sampled paediatric nurses from a university hospital in South Korea between September 2022 and March 2023. Nursing experiences with paediatric delirium and delirium knowledge levels were measured using structured survey questionnaires. Delirium knowledge was scored 0 to 47, and higher scores indicated higher levels of delirium-related knowledge. Data were analysed using descriptive statistics and presented as mean, standard deviation, frequency and percentage.

A total of 127 paediatric nurses participated in this study; 40.2% had experience with 1-5 delirium cases in the previous year, and 86.6% (n = 110) had never used assessment tools for paediatric delirium assessment. The mean total delirium knowledge score was 34.45 ± 5.4; the mean scores of knowledge regarding aetiology, signs and symptoms and nursing management of delirium were 8.93 ± 1.31, 13.24 ± 2.81 and 12.3 ± 2.7, respectively. Interventions associated with a lower level of delirium-related knowledge and a lower performance rate included avoiding restraint use and maintaining hydration and electrolyte levels. Interventions associated with a higher level of delirium-related knowledge but a lower rate of performance comprised providing orientation, offering emotional support, allowing participants to stay with family members and administering medications to manage delirium.

Although nurses working in paediatric units exhibited high rate of delirium nursing care, there was the gap between their delirium-related knowledge and practice. Nurses need to be aware of the insufficient part of delirium care, and paediatric delirium education should be reinforced.

Preventing, assessing and systematically managing paediatric delirium is crucial, and considering the study results, delirium education among nurses is needed.

Several medications are associated with delirium; however, studies with adequate statistical power are limited, and it is difficult to determine the effects of the various concomitant medications used in clinical practice. Therefore, in this study, we aimed to comprehensively evaluate the safety signals of delirium-associated drugs using a spontaneous adverse event reporting system.

The JAPIC AERS (Food and Drug Administration Adverse Event Reporting System pre-processed by the Japan Pharmaceutical Information Center) was used for the analysis in this pharmacovigilance study. The reporting odds ratio (ROR) for delirium was adjusted for using multivariate logistic regression analysis with sex, age, indication, and melatonin receptor agonist use, and 22 drug categories were targeted as covariates.

After excluding patients with missing information, 7,527,568 patients were included in the study. Delirium signals were detected even after adjusting for covariates in 17 drug categories, including benzodiazepines (adjusted ROR, 1.76; 95% confidence interval [CI], 1.64-1.89), opioids (adjusted ROR, 4.42; 95% CI, 4.21-4.64), and tricyclic antidepressants (adjusted ROR, 2.44; 95% CI, 2.20-2.71).

These findings suggest that many drug classes, such as benzodiazepines, are independent risk factors for delirium and strengthen the evidence of an association between delirium and medications.

Delirium in neonates and infants is difficult to screen or assess because of their different developmental features and distinct delirium characteristics compared with those of older children. Some delirium management strategies, including assessment, pharmacological and non-pharmacological interventions, and prevention strategies, have been previously suggested for paediatric delirium. However, whether these strategies are effective for delirium in neonates and infants is unclear. This scoping review aims to explore comprehensive information on delirium in neonates and infants, such as the features of delirium, factors related to delirium, and current assessments and interventions in neonates and infants.

This study will be based on the Joanna Briggs Institute guidelines for scoping review protocol development and follow each stage of the framework proposed by Arksey and O'Malley. Research questions regarding delirium management in neonates and infants will be specified. A wide range of databases, including MEDLINE, EBSCO, Embase and the Cochrane Library, using optimised terms will be searched from 2004 to 2024. The summarised results will be reported in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension of the Scoping Reviews checklist.

Since this study will review and summarise published scientific literature, ethical approval is not required. The results of this scoping review will be disseminated through conference presentations and peer-reviewed publications. The study findings will be disseminated through seminars for experts so that they can be reflected in practice.

Background: Delirium is a common neuropsychiatric syndrome without an FDA-approved treatment. Commonly used modalities show little improvement in outcomes; therefore, prevention efforts are imperative. Abnormalities in the sleep/wake cycle have been linked to delirium, and melatonin has been proposed to replace the hypothesized low levels of endogenous melatonin and restore sleep/wake cycle synchronization. Objectives: The primary objective of this study was to evaluate the association between melatonin, benzodiazepines (BZDs) or zolpidem (ZLP), and the use of as-needed antipsychotics and BZDs for delirium in noncritically ill adult patients. Methods: This was a multicenter retrospective cohort study of noncritically ill adult patients admitted to two separate health systems from August 2012 to December 2018 receiving either melatonin or nonmelatonin medications (ZLP or BZDs) for sleep. The coprimary endpoint was the proportion of patients receiving a pro re nata (PRN) antipsychotic or BZD 5 days from the patient's first dose of melatonin, BZD, or ZLP. Secondary outcomes included evaluation of the coprimary outcome in patients 65 years of age or older, total number of PRN antipsychotic and BZD doses, and length of stay. Results: Two hundred and twenty-five patients were included in the final analysis. Administration of BZD or ZLP was associated with a higher risk of subsequent BZD administration as compared with melatonin (OR 2.78, 95% CI 1.2-1.87) and ZLP (OR 2.78, 95% CI 1.25-6.17). BZD or ZLP had no impact on PRN antipsychotic use compared with melatonin (OR 1.09, 95% CI 0.51-2.35) and ZLP (OR 1.16, 95% CI 0.56-2.4). Conclusion: Melatonin use was found to be associated with a significant decrease in PRN BZD use in noncritically ill patients hospitalized on general floors; however, there was no observed association with overall PRN antipsychotic use. These results suggest that using melatonin may help decrease utilization of medications commonly used to manage delirium.

Delirium is the most common neuropsychological complication among older adults admitted to the intensive care unit (ICU) and is often associated with a poor prognosis. This study aimed to construct and validate an interpretable machine learning (ML) for early delirium prediction in older ICU patients.

This was a retrospective observational cohort study and patient data were extracted from the Medical Information Mart for Intensive Care-IV database. Feature variables associated with delirium, including predisposing factors, disease-related factors, and iatrogenic and environmental factors, were selected using least absolute shrinkage and selection operator regression, and prediction models were built using logistic regression, decision trees, support vector machines, extreme gradient boosting (XGBoost), k-nearest neighbors and naive Bayes methods. Multiple metrics were used for evaluation of performance of the models, including the area under the receiver operating characteristic curve (AUC), accuracy, sensitivity, specificity, recall, F1 score, calibration plot, and decision curve analysis. SHapley Additive exPlanations (SHAP) were used to improve the interpretability of the final model.

Nine thousand seven hundred forty-eight adults aged 65 years or older were included for analysis. Twenty-six features were selected to construct ML prediction models. Among the models compared, the XGBoost model demonstrated the best performance including the highest AUC (0.836), accuracy (0.765), sensitivity (0.713), recall (0.713), and F1 score (0.725) in the training set. It also exhibited excellent discrimination with AUC of 0.810, good calibration, and had the highest net benefit in the validation cohort. The SHAP summary analysis showed that Glasgow Coma Scale, mechanical ventilation, and sedation were the top three risk features for outcome prediction. The SHAP dependency plot and SHAP force analysis interpreted the model at both the factor level and individual level, respectively.

ML is a reliable tool for predicting the risk of critical delirium in elderly patients. By combining XGBoost and SHAP, it can provide clear explanations for personalized risk prediction and more intuitive understanding of the effect of key features in the model. The establishment of such a model would facilitate the early risk assessment and prompt intervention for delirium.

Delirium is a complex condition, stressful for all involved. Although highly prevalent in palliative care settings, it remains underdiagnosed and associated with poor outcomes. Guideline-adherent delirium care may improve its detection, assessment and management.

To inform a future definitive study that tests whether an implementation strategy designed to improve guideline-adherent delirium care in palliative care settings improves patient outcomes (reduced proportion of in-patient days with delirium).

With Patient Involvement members, we conducted a feasibility study to assess the acceptability of and engagement with the implementation strategy by hospice staff (intervention), and whether clinical record data collection of process (e.g. guideline-adherent delirium care) and clinical outcomes (evidence of delirium using a validated chart-based instrument;) pre- and 12-weeks post-implementation of the intervention would be possible.

In-patient admissions in three English hospices.

Between June 2021 and December 2022, clinical record data were extracted from 300 consecutive admissions. Despite data collection during COVID-19, target clinical record data collection (n = 300) was achieved. Approximately two-thirds of patients had a delirium episode during in-patient stay at both timepoints. A 6% absolute reduction in proportion of delirium days in those with a delirium episode was observed. Post-implementation improvements in guideline-adherent metrics include: clinical delirium diagnosis 15%-28%; delirium risk assessment 0%-16%; screening on admission 7%-35%.

Collection of data on delirium outcomes and guideline-adherence from clinical records is feasible. The signal of patient benefit supports formal evaluation in a large-scale study.

It was aimed to determine the effect level of nonpharmacological methods applied by nurses to patients hospitalized in the intensive care unit on the duration of delirium.

For this study, relevant studies were accessed by searching in July-October 2022. After the necessary exclusions were made, 14 studies were included in the study. The total sample size of the studies was 1123.

According to the results, nonpharmacological interventions applied by nurses to intensive care patients were found to reduce the duration of delirium (SMD: - 0.625, 95% CI: - 1.1040-0.210; Z =  - 2.950, p = 0.003, I2 = 93.119%). The country of the study (SMD: - 0.047, p = 0.001) and the types of nonpharmacological interventions used (SMD: - 0.062, p = 0.000) influenced the effect size of modulators on the duration of delirium in ICU patients.

Nonpharmacological interventions applied by nurses, who have significant responsibilities in the protection and promotion of health, were found to reduce the duration of delirium in intensive care patients. This study shows that nurses, one of the main components of the multidisciplinary team in intensive care, are successful when they apply nonpharmacological interventions well.

Opioids or benzodiazepines use is known to increase the risk of delirium. The prevalence of delirium is high in pediatric cardiac intensive care units (CICUs) with associated morbidity and mortality. We investigate the short-term effects of quetiapine, an atypical antipsychotic medication, on opioid and benzodiazepine requirements, and any associated adverse events as we utilize quetiapine to treat delirium symptoms in this single-center, retrospective study. Twenty-eight patients who received quetiapine between January 2018 and June 2019 in the CICU met inclusion criteria for the analysis. The quetiapine initiation dose was 0.5 mg/kg/dose every 8 h and we allowed 48 h for quetiapine to reach a steady state. Overall opioid and benzodiazepine requirements were compared 72 h before and 72 h after the quetiapine steady state. There was a statistically significant reduction in the total daily opioid (p = 0.001) and benzodiazepine (p = 0.01) amounts following quetiapine initiation. There was also a statistically significant decrease in the total number of daily PRNs requirement for both opioids (p < 0.001) and benzodiazepines (p = 0.03). Nine out of 13 patients were completely weaned off continuous opioid drips following quetiapine initiation (p = 0.01). The presence of steady-state habituation medications, including methadone or lorazepam, did not have any statistically significant effect on weaning continuous opioid (p = 0.18) or benzodiazepine (p = 0.62) drips. There was no statistically significant effect of quetiapine on the QTc interval after quetiapine initiation (p = 0.58) with no clinically significant arrhythmias observed during the study period. Our study demonstrates a statistically significant reduction in opioid and benzodiazepine requirements following quetiapine initiation to treat delirium symptoms without significant adverse effects in patients with congenital heart disease in the short term.

Delirium is an acute reversible neuropsychiatric syndrome caused by multiple factors. It is associated with many adverse clinical outcomes including cognitive impairment, functional decline, prolonged hospitalization, and increased nursing service. The prevalence of delirium was high in department of cardiology, geriatric, and intensive care unit of hospital. With the increase in the aged population, further increases in delirium seem likely. However, it remains poorly recognized in the clinical practice. This article comprehensively discusses the latest research perspectives on the epidemiological data, risk factors, preventive interventions, overlapping symptoms, and clinical measures of delirium, including specific measures to manage delirium in clinical real-world situations. This article helps readers improve their knowledge and understanding of delirium and helps clinicians quickly identify and implement timely therapeutic measures to address various delirium subtypes that occur in the clinical settings to ensure patients are treated as aggressively as possible.

Although delirium is well known to acute care clinicians, the features required for its diagnosis and how to understand and operationalize them remain sticking points in the field. To clarify the delirium phenotype, we present a close reading of past and current sets of delirium diagnostic criteria.

We first differentiate the delirium syndrome (i.e., features evaluated at bedside) from additional criteria required for diagnosis. Next, we align related features across diagnostic systems and examine them in context to determine intent. Where criteria are ambiguous, we review common delirium instruments to illustrate how they have been interpreted.

An acute disturbance in attention is universally attested across diagnostic systems. A second core feature denotes confusion and has been included across systems as disturbance in awareness, impaired consciousness, and thought disorganization. This feature may be better understood as a disturbance in thought clarity and operationalized in terms of neuropsychological domains thereby clearly linking it to global neurocognitive disturbance. Altered level of activity describes a third core feature, including motor and sleep/wake cycle disturbances. Excluding stupor (wherein mental content cannot be assessed due to reduced arousal) from delirium, as in DSM-5-TR, is appropriate for a psychiatric diagnosis, but the brain injury exclusion in ICD-11 is unjustified.

The delirium phenotype involves a disturbance in attention, qualitative thought clarity, and quantitative activity level, including in relation to expected sleep/wake cycles. Future diagnostic systems should include a severity threshold and specify that delirium diagnosis refers to a 24-h period.

Delirium is a syndrome of acute brain failure which is prevalent amongst older adults in the Intensive Care Unit (ICU). Incidence of delirium can significantly worsen prognosis and increase mortality, therefore necessitating its rapid and continual assessment in the ICU. Currently, the common approach for delirium assessment is manual and sporadic. Hence, there exists a critical need for a robust and automated system for predicting delirium in the ICU. In this work, we develop a machine learning (ML) system for real-time prediction of delirium using Electronic Health Record (EHR) data. Unlike prior approaches which provide one delirium prediction label per entire ICU stay, our approach provides predictions every 12 hours. We use the latest 12 hours of ICU data, along with patient demographic and medical history data, to predict delirium risk in the next 12-hour window. This enables delirium risk prediction as soon as 12 hours after ICU admission. We train and test four ML classification algorithms on longitudinal EHR data pertaining to 16,327 ICU stays of 13,395 patients covering a total of 56,297 12-hour windows in the ICU to predict the dynamic incidence of delirium. The best performing algorithm was Categorical Boosting which achieved an area under receiver operating characteristic curve (AUROC) of 0.87 (95% Confidence Interval; C.I, 0.86-0.87). The deployment of this ML system in ICUs can enable early identification of delirium, thereby reducing its deleterious impact on long-term adverse outcomes, such as ICU cost, length of stay and mortality.

Vagus nerve stimulation (VNS) has many clinical applications under development. In particular, there is a large interest in transcutaneous auricular VNS (taVNS) because it is non-invasive and provides easy access to neuromodulation. The present study proposes a novel approach for electroencephalography (EEG)-gated taVNS, with the ultimate goal of enhancing therapeutic outcomes, including for the treatment of delirium. Delirium arises from an altered state of consciousness and is the most common neuropsychiatric disorder observed in hospitalized patients, especially the elderly. Delirium has been linked to specific disturbances in EEG rhythms. Here, we propose an EEG-gated auricular vagal afferent nerve stimulation (EAVANS) approach to deliver stimulation targeting a specific instantaneous phase of the EEG Delta rhythm to modulate arousal and downstream reduction of neuroinflammation, two of the contributing factors to delirium. We hypothesize that treatment with EAVANS will modulate Delta power, which has been linked with delirium. As dominant Delta power is also a typical feature of non-rapid eye movement (NREM) sleep, we applied a prototype of an EAVANS device on healthy volunteers during sleep to establish preliminary validation. We successfully employed our closed-loop approach to target vagal afference during the rising Delta phase in the range [-π/2 0] radians. We found a significant reduction in Delta wave power for stimulation during the rising Delta phase compared to 1) absence of stimulation, 2) active stimulation during the descending Delta phase, and 3) active stimulation targeting non-vagal territory (i.e. greater auricular nerve) during the rising Delta phase. Further validation of our EEG-gated taVNS approach in the peri-operative period will be needed. As there is presently a lack of effective treatments for delirium, our non-pharmacological and non-invasive approach, if validated, could be easily deployed in clinical settings.Clinical Relevance- Given the serious health consequences and costs associated with delirium, and the absence of effective non-pharmacological treatments, the proposed neuromodulatory approach may be a promising option for reducing delirium and other disorders of consciousness. Our EAVANS prototype system has been tested on healthy volunteers during a NREM sleep state and will require further validation in different patient populations to optimize the proposed technology and gather more evidence to support its clinical utility. This novel non-pharmacological and non-invasive closed-loop neuromodulatory device could be used peri-operatively and in inpatient hospital settings to treat patients at risk of developing delirium. For instance, in a pre-operative setting, this technology may provide an effective preventative "pre-habilitation" approach for patients at high risk of developing delirium. Post-operatively, our technology may help manage patients with delirium more effectively.

Delirium is common in postoperative critically ill patients and may affect by intraoperative events. Biomarkers are vital indicators in the development and prediction of delirium.

This study aimed to investigate the associations between various plasma biomarkers and delirium.

We performed a prospective cohort study on cardiac surgery patients. Delirium assessment was performed twice daily using the confusion assessment method for the intensive care unit (ICU), and the Richmond Agitation Sedation Scale was used to assess the depth of sedation and agitation. Blood samples were collected on the day after ICU admission, and the concentrations of cortisol, interleukin (IL)-1β, IL-6, tumor necrosis factor α, soluble tumor necrosis factor receptor-1 (sTNFR-1), and sTNFR-2 were measured.

Delirium in the ICU was noted in 93 (29.2%, 95% CI 24.2-34.3) out of 318 patients (mean age 52 years, SD 12.0). The longer duration of cardiopulmonary bypass, aortic clamping and surgery, and higher plasma, erythrocytes, and platelet transfusion requirements were among the significant differences in intraoperative events between patients with and without delirium. Median levels of IL-6 (p = 0.017), TNF-α (p = 0.048), sTNFR-1 (p < 0.001), and sTNFR-2 (p = 0.001) were significantly higher in patients with delirium than in those without it. After adjusting for demographic variables and intraoperative events, only sTNFR-1 (odds ratio 6.83, 95% CI: 1.14-40.90) was associated with delirium.

Plasma IL-6, TNF-α, sTNFR-1, and sTNFR-2 levels were higher in ICU-acquired delirium patients after cardiac surgery. sTNFR-1 was a potential indicator of the disorder.

Delirium is an acute neuropsychiatric condition associated with increased morbidity and mortality. There is increasing recognition of delirium as a substantial health burden in younger patients, although few studies have characterized its occurrence. This study analyzes the occurrence of delirium diagnosis, its comorbidities, and cost among youth hospitalized in the United States.

The Kids' Inpatient Database, a national all-payers sample of pediatric hospitalizations in general hospitals, was examined for the year 2019. Hospitalizations with a discharge diagnosis of delirium among patients aged 1-20 years were included in the analysis.

Delirium was diagnosed in 43,138 hospitalizations (95% CI: 41,170-45,106), or 2.3% of studied hospitalizations. Delirium was diagnosed in a broad range of illnesses, with suicide and self-inflicted injury as the most common primary discharge diagnosis among patients with delirium. In-hospital mortality was seven times greater in hospitalizations caring a delirium diagnosis. The diagnosis of delirium was associated with an adjusted increased hospital cost of $8648 per hospitalization, or $373 million in aggregate cost.

Based on a large national claims database, delirium was diagnosed in youth at a lower rate than expected based on prospective studies. The relative absence of delirium diagnosis in claims data may reflect underdiagnosis, a failure to code, and/or a lower rate of delirium in general hospitals compared with other settings. Further research is needed to better characterize the incidence and prevalence of delirium in young people in the hospital setting.

Delirium is defined as a sudden onset of confusion due to disruption in normal brain functioning. Although it is highly prevalent in post-operative patients, most significantly the older adult population, limited information exists explaining why its onset occurs.

This integrative review aimed to synthesise specific comorbidities that can contribute to the development of post-operative delirium in older adult cardiac surgical patients.

PRISMA statement was used to report the identification, selection, appraisal and synthesis of articles and the PRISMA diagram reports the selection process. The Johns Hopkins Evidence-Based Practice Tools were used as guide in literature review, critical analysis, levelling of evidence and quality rating. PubMed, ProQuest, CINAHL plus, EMBASE, MEDLINE, Ovid Nursing Collection and Cochrane databases were searched from 2015 to 2020.

The initial search yielded 1529 articles. Following the removal of duplicates and screening, 14 articles were included for this review. The following comorbidities were identified in the studies: Diabetes mellitus, atrial fibrillation, depression, impaired olfaction, pre-existing cerebrovascular disease, pre-existing cardiovascular disease, insomnia and frailty.

There was a strong indication of the development of post-operative delirium among older adult cardiac surgical patients with comorbidities.

Awareness of the impact of comorbidities in developing post-operative delirium may help healthcare providers to plan and implement proper care management among older adult cardiac surgical patients with comorbidities.

Delirium superimposed on dementia (DSD) occurs when patients with pre-existing dementia develop delirium. This complication causes patients to become impaired, posing safety concerns for both hospital staff and patients. Furthermore, there is an increased risk of worsening functional disability and death. Despite medical advances, DSD provides both diagnostic and therapeutic challenges to providers. Identifying at-risk patients and providing personalized medicine and patient care can decrease disease burden in a time-efficient manner. This review delves into bioinformatics-based studies of DSD in order to design and implement a personalized medicine-based approach. Our findings suggest alternative medical treatment methods based on gene-gene interactions, gene-microRNA (miRNA) interactions, gene-drug interactions, and pharmacogenetic variants involved in dementia and psychiatric disorders. We identify 17 genes commonly associated with both dementia and delirium including apolipoprotein E (ApoE), brain-derived neurotrophic factor (BDNF), catechol-O-methyltransferase (COMT), butyrylcholinesterase (BChE), acetylcholinesterase (AChE), DNA methyltransferase 1 (DNMT1), prion protein (PrP), tumor necrosis factor (TNF), serine palmitoyltransferase long chain base subunit 1 (SPTLC1), microtubule-associated protein tau (MAPT), alpha-synuclein (αS), superoxide dismutase 1 (SOD1), amyloid beta precursor protein (APP), neurofilament light (NFL), neurofilament heavy, 5-hydroxytryptamine receptor 2A (HTR2A), and serpin family A member 3 (ERAP3). In addition, we identify six main genes that form an inner concentric model, as well as their associated miRNA. The FDA-approved medications that were found to be effective against the six main genes were identified. Furthermore, the PharmGKB database was used to identify variants of these six genes in order to suggest future treatment options. We also looked at previous research and evidence on biomarkers that could be used to detect DSD. According to research, there are three types of biomarkers that can be used depending on the stage of delirium. The pathological mechanisms underlying delirium are also discussed. This review will identify treatment and diagnostic options for personalized DSD management.

Postoperative delirium (POD) is a common complication in operative patients. Neuroinflammation has been reported to be a potential mechanism associated with the development of POD. Identifying available inflammatory markers such as C-reactive protein (CRP) would aid clinicians in early detection of POD. Previous studies have demonstrated that CRP may be a promising predictive marker for POD. Thus, this study aimed to explore the association between CRP and POD among those elderly colorectal cancer (CRC) patients.

643 patients with CRC were included in this study. CRP levels were measured before operation and on postoperative day 1. The univariate and multivariate regression analyses were used to identify risk factors for POD.

Of 643 patients with CRC, 112 cases (17.4%) had POD. CRC patients with POD showed older age, higher CRP level on postoperative day 1, and higher percentage of smoking, diabetes mellitus, and chronic obstructive pulmonary disease (COPD) than CRC patients without POD. Preoperative CRP level was not associated with the POD. Univariate and multivariate regression analyses showed that older age (> 70 years), diabetes mellitus, COPD, and higher CRP level on postoperative day 1 (> 48 mg/L) were risk factors for POD in CRC patients.

Postoperative CRP level is an independent indicator for POD among CRC patients, suggesting the predictive role of postoperative CRP levels for POD in elderly CRC patients undergoing surgery.

Delirium is an acute confusion state that is common and costly. According to different clinical manifestations, delirium can be divided into three subtypes: hyperactive, hypoactive and mixed. Subtype research has become a necessary branch. However, it is difficult to record all the changes in subtype research.

Publications on delirium subtypes in the Web of Science Core Collection (WOSCC) were identified and analyzed by visualization software VOSviewer and CiteSpace.

A total of 247 articles published from 1999 to 2022 were identified in the WOSCC, and the largest number of articles was published in 2021 (n = 33). The top three countries that contributed publications were the USA (n = 75), Ireland (n = 26), and the United Kingdom (n = 25), which communicated more often and focused on delirium subtypes earlier. Critical Care Medicine published the most articles regarding delirium subtypes, with 11 publications. Three instrument validation studies were cited most frequently. Six clusters were summarized, including descriptions of delirium among elderly people, delirium research, postoperative delirium, delirium motor subtype validation, critical delirium, and motor characteristics. The "postoperative delirium", "intensive care unit", and "cardiac surgery" keywords were seen in recent years.

Based on this bibliometric analysis of the publications in the last twenty years, a comprehensive analysis of the literature clarified the contributions, changes, and evolution regarding delirium subtypes. This research can provide medical staff and researchers with revelations into future directions of delirium subtype advancements.

Clinicians treating psychiatric disorders in medically ill patients need a comprehensive resource for comparing the risk and types of liver injury associated with antipsychotic therapy.

We conducted a narrative review aimed at developing a comprehensive resource comparing antipsychotics with regard to risk of inducing or worsening liver injuries, types of liver injury, associated pharmacokinetic changes, dosing, monitoring, and patient counseling recommendations.

We conducted database searches of LiverTox.nih.gov, DailyMed.nlm.nih.gov, and PubMed through June of 2022. Sources describing premarketing data, observational studies, case reports and case series of antipsychotic-induced liver injuries, types of hepatic dysfunction, interventions, recovery, and treatment for 15 antipsychotics were included. Duplicate reports were excluded. Antipsychotics were graded as low, low to moderate, moderate, moderate to high, or high risk for causing or worsening a liver disease.

Of the 1861 publications, 21 papers met criteria and were included. Evidence shows antipsychotic-induced liver dysfunction is uncommon to rare. Chlorpromazine, clozapine, and olanzapine pose the greatest risk of hepatoxicity; quetiapine and risperidone pose a moderate risk with haloperidol considered to pose low to moderate risk. Paliperidone, aripiprazole, lurasidone, and loxapine are lower-risk agents with no reports of liver failure. Transaminitis that is mild and self-limiting is the most common antipsychotic-induced liver injury followed by hepatocellular disease, steatosis, and mixed liver injury. A careful risk-benefit analysis should guide the decision to discontinue the antipsychotic in cases of severe liver disease. Dose adjustments and careful monitoring are recommended for a mild to moderate disease when the benefits of treating psychosis outweigh the risks. Patients without an existing liver disease initiating a treatment with a higher-risk antipsychotic should be counseled to report symptoms of liver injuries along with regular lab monitoring.

Antipsychotic selection, dosing, monitoring, and counseling should be individualized based on whether a patient has an existing liver disease and if they are receiving an agent that poses a higher risk of liver injury. The consultation-liaison psychiatry provider can guide the primary team in management through thoughtful integration of the known pathophysiologic changes in hepatic disease and risk-benefit analysis of antipsychotic safety profiles.

To investigate the incidence, characteristics and risk factors of delirium in the ICU.

Identifying the risk factors of delirium is important for early detection and to prevent adverse consequences.

An observational cohort study conducted according to STROBE Guidelines.

The study was conducted with patients who stayed in ICU ≥24 h and were older than 18 years. Patients were assessed twice daily using the RASS and CAM-ICU until either discharge or death. Cumulative incidence was calculated. Demographic/clinical characteristics, length of stay and mortality were compared between patients with and without delirium. A logistic regression model was used to investigate risk factors.

The incidence of delirium was 31.8% and hypoactive type was the most frequent (41.5%). The median onset of delirium was 3 days (IQR = 2) with a mean duration of 5.27 ± 2.32 days. Patients with delirium were significantly older, had higher APACHE-II, SOFA and CPOT scores, higher blood urea levels, higher requirements for mechanical ventilation, sedation and physical restraints, longer stays in the ICU and higher mortality than those without delirium. The logistic regression analysis results revealed that a CPOT score ≥3 points (OR = 4.70, 95% CI: 1.05-20.93; p = .042), physical restraint (OR = 10.40, 95% CI: 2.75-39.27; p = .001) and ICU stay ≥7 days (OR = 7.26, 95% CI: 1.60-32.84; p = .010) were independent risk factors of delirium.

In this study, the incidence of delirium was high and associated with several factors. It is critical that delirium is considered by all members of the healthcare team, especially nurses, and that protocols are established for improvements.

Based on the results of this study, delirium could be decreased by preventing the presence of pain, prudent use of physical restraints and shortening the ICU stay.

Objective Describe the incidence of delirium and associated outcomes among hospitalized, non-critically ill older people. Design Single-center, retrospective chart review. Setting A 217-bed academic teaching hospital in Cambridge, Massachusetts affiliated with Harvard Medical School. Patients People 65 years of age or older, admitted to a general medicine unit between January 1 and August 31, 2021, who were prescribed one or more deliriogenic medications prior to or during admission. Interventions Patient electronic medical records were reviewed for deliriogenic medications prescribed and administered during admission and associated clinical outcomes. Results The percentage of patients who developed delirium was 13% overall. The most implicated deliriogenic medications were benzodiazepines, antipsychotics, and histamine-2 receptor antagonists (H2RAs). Seventy-three percent of deliriogenic home medications were continued upon admission. Subgroup analyses of those with delirium had a mean length-of-stay of 20 days compared with 6 days in those who did not develop delirium. Those with delirium tended to have more deliriogenic medications used during admission. Conclusion This review describes the incidence of delirium for non-critically ill older people who were prescribed at least one deliriogenic medication. Of all the deliriogenic agents reviewed, moderate quality clinical evidence supports the association between use and development of delirium except for H2RAs, which have low-quality evidence. Pharmacist-driven efforts to deprescribe deliriogenic medications in at-risk patient populations may be better focused on agents with higher-quality evidence.

We conducted an updated, comprehensive, and contemporary systematic review to examine the efficacy of existing pharmacologic agents employed for management of delirium symptoms among hospitalized adults.

Searches of PubMed, Scopus, Embase, and Cochrane Library databases from inception to May 2021 were performed to identify studies investigating efficacy of pharmacologic agents for management of delirium.

Of 11,424 articles obtained from searches, a total of 33 articles (N = 3030 participants) of randomized or non-randomized trials, in which pharmacologic treatment was compared to active comparator, placebo, or no treatment, met all criteria and were included in this review. Medications used for management of delirium symptoms included antipsychotic medications (N = 27), alpha-2 agonists (N = 5), benzodiazepines (N = 2), antidepressants (n = 1), acetylcholinesterase inhibitors (N = 2), melatonin (N = 2), opioids (N = 1), and antiemetics (N = 2). Despite somewhat mixed findings and a relative lack of high-quality trials, it appears that antipsychotic medications (e.g., haloperidol, olanzapine, risperidone, or quetiapine) and dexmedetomidine have the potential to improve delirium outcomes.

Pharmacologic agents can reduce delirium symptoms (e.g., agitation) in some hospitalized patients. Additional double-blinded, randomized, placebo-controlled clinical trials are critically needed to investigate the efficacy of pharmacologic agents for diverse hospitalized populations (e.g., post-surgical patients, patients at the end-of-life, or in intensive care units).

Delirium is a common and serious neuropsychiatric syndrome characterized with acute cognitive and attentional deficits, however, the effective therapies are lacking. Here, using mouse models of delirium, we investigated the effects of tangeretin (TAN, a natural flavonoid) on cognitive impairment by assessing object preference with novel object recognition (NOR) test and spontaneous alternation with Y maze test. We found that TAN, as a RORα/γ agonist, prevented cognitive decline in delirious mice as evidenced by a normal novel object preference and increased spontaneous alternation. This was accompanied by decreased expression of ERK1/2, TNFα and IL-1β as well as diminished microglial activation in delirious mice. The protective effect of TAN on delirium was mainly attributed to increased hippocampal E4BP4 expression (a known target of RORs and a regulator of cognition in delirium through modulating the ERK1/2 cascade and microglial activation) via activation of RORα/γ. In addition, TAN treatment modulated the expression of RORα/γ target genes (such as E4bp4 and Bmal1) and inhibited the expression of TNFα and IL-1β in lipopolysaccharide (LPS)-stimulated cells, supporting a beneficial effect of TAN on delirium. In conclusion, TAN is identified as a RORα/γ agonist which promotes E4BP4 expression to prevent cognitive decline in delirious mice. Our findings may have implications for drug development of TAN for prevention and treatment of various diseases associated with cognitive deficiency.

Multimorbidity and polypharmacy are common among individuals hospitalized for heart failure (HF). Initiating high-risk medications such as antipsychotics may increase the risk of poor clinical outcomes, especially if these medications are continued unnecessarily into skilled nursing facilities (SNFs) after hospital discharge.

Examine how often older adults hospitalized with HF were initiated on antipsychotics and characteristics associated with antipsychotic continuation into SNFs after hospital discharge.

Retrospective cohort.

Veterans without prior outpatient antipsychotic use, who were hospitalized with HF between October 1, 2010, and September 30, 2015, and were subsequently discharged to a SNF.

Demographics, clinical conditions, prior healthcare utilization, and antipsychotic use data were ascertained from Veterans Administration records, Minimum Data Set assessments, and Medicare claims. The outcome of interest was continuation of antipsychotics into SNFs after hospital discharge.

Among 18,008 Veterans, antipsychotics were newly prescribed for 1931 (10.7%) Veterans during the index hospitalization. Among new antipsychotic users, 415 (21.5%) continued antipsychotics in skilled nursing facilities after discharge. Dementia (adjusted OR (aOR) 1.48, 95% CI 1.11-1.98), psychosis (aOR 1.62, 95% CI 1.11-2.38), proportion of inpatient days with antipsychotic use (aOR 1.08, 95% CI 1.07-1.09, per 10% increase), inpatient use of only typical (aOR 0.47, 95% CI 0.30-0.72) or parenteral antipsychotics (aOR 0.39, 95% CI 0.20-0.78), and the day of hospital admission that antipsychotics were started (day 0-4 aOR 0.36, 95% CI 0.23-0.56; day 5-7 aOR 0.54, 95% CI 0.35-0.84 (reference: day > 7 of hospital admission)) were significant predictors of continuing antipsychotics into SNFs after hospital discharge.

Antipsychotics are initiated fairly often during HF admissions and are commonly continued into SNFs after discharge. Hospital providers should review antipsychotic indications and doses throughout admission and communicate a clear plan to SNFs if antipsychotics are continued after discharge.

Delirium is a complex condition in which altered mental state and cognition causes severe distress and poor clinical outcomes for patients and families, anxiety and stress for the health professionals and support staff providing care, and higher care costs. Hospice patients are at high risk of developing delirium, but there is significant variation in care delivery. The primary objective of this study is to demonstrate the feasibility of an implementation strategy (designed to help deliver good practice delirium guidelines), participant recruitment and data collection.

Three work packages in three hospices in the UK with public involvement in codesign, study management and stakeholder groups: (1) experience-based codesign to adapt an existing theoretically-informed implementation strategy (Creating Learning Environments for Compassionate Care (CLECC)) to implement delirium guidelines in hospices; (2) feasibility study to explore ability to collect demographic, diagnostic and delirium management data from clinical records (n=300), explanatory process data (number of staff engaged in CLECC activities and reasons for non-engagement) and cost data (staff and volunteer hours and pay-grades engaged in implementation activities) and (3) realist process evaluation to assess the acceptability and flexibility of the implementation strategy (preimplementation and postimplementation surveys with hospice staff and management, n=30 at each time point; interviews with hospice staff and management, n=15). Descriptive statistics, rapid thematic analysis and a realist logic of analysis will be used be used to analyse quantitative and qualitative data, as appropriate.

Ethical approval obtained: Hull York Medical School Ethics Committee (Ref 21/23), Health Research Authority Research Ethics Committee Wales REC7 (Ref 21/WA/0180) and Health Research Authority Confidentiality Advisory Group (Ref 21/CAG/0071). Written informed consent will be obtained from interview participants. A results paper will be submitted to an open access peer-reviewed journal and a lay summary shared with study site staff and stakeholders.

ISRCTN55416525.

According to DSM-5, catatonia and delirium are mutually exclusive clinical syndromes. The investigators explored the co-occurrence of delirium and catatonia (i.e., catatonic delirium) and the clinical significance of this syndrome with a sample of neurological patients.

This prospective study with consecutive sampling included patients diagnosed with delirium at the National Institute of Neurology and Neurosurgery of Mexico. DSM-5 criteria for delirium, the Confusion Assessment Method, and the Delirium Rating Scale-Revised-98 were used to select and characterize patients. Catatonia was assessed using the Bush-Francis Catatonia Rating Scale and DSM-5 diagnostic criteria. Logistic regression analysis was performed to identify etiological factors associated with catatonic delirium.

A total of 264 patients with delirium were included, 61 (23%) of whom fulfilled the criteria for catatonia and delirium simultaneously. Brain tumors, subarachnoid hemorrhage, acute hydrocephalus, and ischemic stroke were associated with delirium without catatonic signs. Catatonic delirium was observed among patients with encephalitis, epilepsy, brain neoplasms, and brain tuberculosis. After multivariate analysis, the association between catatonic delirium and encephalitis (both viral and anti-N-methyl-d-aspartate receptor [NMDAR]) was confirmed.

Delirium is a common complication of neurological diseases, and it can coexist with catatonia. The recognition of catatonic delirium has clinical significance in terms of etiology, as it was significantly associated with viral and anti-NMDAR encephalitis.