Risk Of Delirium Research Articles

Association between residential greenness and incident delirium: A prospective cohort study in the UK Biobank

BackgroundContemporary environmental health investigations have identified green space as an emerging factor with promising prospects for bolstering human well-being. The incidence of delirium increases significantly with age and is fatal. To date, there is no research elucidating the enduring implications of green spaces on the occurrence of delirium. Therefore, we explored the relationship between residential greenness and the incidence of delirium in a large community sample from the UK Biobank. MethodsEnrollment of participants spanned from 2006 to 2010. Assessment of residential greenness involved the land coverage percentage of green space within a buffer range of 300 m and 1000 m. The relationship between residential greenness and delirium was assessed using the Cox proportional hazards model. Further, we investigated the potential mediating effects of physical activity, particulate matter (PM) with diameters ≤2.5 (PM2.5), and nitrogen oxides (NOx). ResultsOf 232,678 participants, 3722 participants were diagnosed with delirium during a 13.4-year follow-up period. Compared with participants with green space coverage at a 300 m buffer in the lowest quartile (Q1), those in the highest quartile (Q4) had 15 % (Hazard ratio [HR] = 0.85, 95 % confidence interval [CI]: 0.77, 0.94) lower risk of incident delirium. As for the 1000 m buffer, those in Q4 had a 16 % (HR = 0.84, 95 % CI: 0.76, 0.93) lower risk of incident delirium. The relationship between green space in the 300 m buffer and delirium was mediated partially by physical activity (2.07 %) and PM2.5(49.90 %). Comparable findings were noted for the green space percentage within the 1000 m buffer. ConclusionsOur results revealed that long-term exposure to residential greenness was related to a lower risk of delirium. Air pollution and physical activity exerted a significant mediating influence in shaping this association.

#1858 Delirium among patients admitted to a Nephrology ward-risk factors and association with short-term outcomes: an observational prospective cohort study

Abstract Background and Aims To date, delirium is considered one of the most frequent neuropsychiatric acute syndromes among hospitalized populations. In general medicine, the risk factors for delirium are well-established but there are limited data concerning the incidence and predictors of delirium in nephrological patients. The aims of the study were (i) to assess the prevalence and the risk factors for delirium in hospitalized patients with acute kidney injury (AKI) and chronic kidney disease (CKD), and (ii) to evaluate the effect of delirium on in-hospital mortality. Method A cohort of 942 patients admitted to the Nephrology Department of a tertiary-care Hospital from January 2023 to December 2023 were enrolled in a prospective observational study. Delirium was diagnosed by a psychiatrist during the hospitalization. The endpoint was defined as hospital death or hospital discharge. Relevant sociodemographic, nephrological- and medical-related clusters were assessed with logistic uni- and multivariable regression methods to evaluate their association with delirium and in-hospital mortality. A two-tailed value <0.05 was considered significant. Results In the studied group, mean age was 62.85 years, 519 (55.09%) patients being males. The prevalence of delirium was 5.41% (51/942 patients). The delirious patients were older (mean 70.04 vs. 62.44 years; P<0.001) and with a longer duration of hospitalization (13.12 ± 7.90 days vs. 10.76 ± 8.92 days; P=0.007). Univariable regression analysis showed that delirium was associated with age (r=0.117, P<0.001), alcohol abuse (r=0.144, P<0.001), history of stroke (r=0.184, P<0.001), vascular dementia (r=0.125, P<0.001), dehydration (r=0.175, P<0.001), sepsis (r=0.144, P<0.001), and acute kidney injury (AKI) stage 2 and 3 (r=0.155, P<0.001). In multivariable regression analysis, the independent predictors of delirium were: age (adjusted odds ratio (OR) 1.029, 95% confidence interval (CI): 1.002–1.056, P=0.034), alcohol abuse (OR=4.728, 95% CI: 1.968-11.359, P=0.001), history of stroke (OR=3.493, 95% CI: 1.849-6.598, P<0.001), and AKI stage 2 and 3 (OR=2.175, 95% CI: 1.152-4.105, P=0.017). Chronic kidney disease was not associated with a higher risk of delirium (OR=0.583, 95% CI: 0.308-1.110, P=0.097). Delirium was associated with increased in-hospital mortality (47.05% vs. no-delirium 14.36%, P<0.001) and was an independent predictor of in-hospital mortality (OR=3.074, 95% CI: 1.630-5.797, P=0.001). Conclusion In this study conducted on patients hospitalized in a nephrology ward age, alcohol abuse, history of stroke, and AKI stage 2 and 3 were independent risk factors for delirium. Delirium significantly increased in-hospital mortality. The findings of the study emphasize the strong connectivity between AKI and acute brain dysfunction.

Frailty index and risk of delirium in hospitalized patients: a two-sample Mendelian randomization study.

Observational studies suggest that the frailty index (FI) is closely related to delirium, but the relationship between them is still uncertain due to the influence of various confounding factors. Therefore, two-sample Mendelian randomization (MR) was used to explore the causal relationship between the FI and delirium risk. This study obtained pooled statistics for the FI and delirium from two of the most extensive genome-wide association studies. To make the results more robust and reliable, supplementary analyses were performed using several robust analytical methods (inverse-variance weighting, MR-Egger regression, and weighted median). In addition, this study used the MR-Egger intercept test, Cochran's Q test, funnel plots and the leave-one-out method to evaluate the pleiotropy and heterogeneity among the abovementioned genetic variation instrumental variables. Frailty might increase the relative risk of delirium, as shown by IVW (OR = 1.849, 95% CI 0.027∼2.067, P = 0.044), weighted median (OR = 1.726, 95% CI -0.178∼2.664, P = 0.083), MR-Egger regression (OR = 1.768, 95% CI -3.08∼6.171, P = 0.525) and leave-one-out sensitivity analysis (P = 0.058). Although the WME method and MR-Egger regression analysis showed no statistically significant causal relationship between the FI and the risk of delirium, the direction of the causal effect was consistent with the IVW method. There is a notable correlation between a higher FI and an elevated risk of delirium. This indicates that healthcare providers should take proactive measures to prevent delirium in hospitalized patients with a higher FI.

Risk of drug-induced delirium in older patients- a pharmacovigilance study of FDA adverse event reporting system database

ABSTRACT Background Drug-induced delirium is one of the numerous known risk factors associated with increased morbidity and mortality in older patients. The objective of this study was to evaluate the risk of drug-related delirium in older patients based on the FDA Adverse Event Reporting System (FAERS). Research design and methods Delirium reports in older patients (age ≥65) from 2004 quarter 1 through 2021 quarter 3 extracted from the FAERS database using Open Vigil 2.1. The reported odds ratio and the proportional r7eported ratio were calculated to detect the adverse reaction signal of delirium. Combined with published evidence, suspected drugs were categorized as known, possible, or new potential delirium-risk-increasing drugs. Results Of the 130,885 reports (including 28,850 delirium events and 1,857 drug) analyzed for this study, 314 positive signal drugs were detected. Positive signal drugs are mainly concentrated on the drug of nervous system [n = 149, ROR 3.60, 95% CI (3.56–3.64)], cardiovascular system [n = 35, ROR 1.45, 95% CI (1.43–1.47)], alimentary tract and metabolism [n = 35, ROR 1.25, 95% CI (1.23–1.26)] and anti-infectives for systemic use [n = 27, ROR 1.70, 95% CI (1.66–1.74)]. Of the positive signal drugs, 26.11% (82/314) were known delirium-risk increasing drugs [ROR 4.12, 95%CI (3.85–4.41)], 44.90% (141/314) were possible [ROR 3.59, 95%CI (3.37–3.83)] and 28.98% (91/314) were new potential [ROR 3.68, 95%CI (3.22–4.21)]. Conclusion Drug-induced delirium risk is prevalent in the older patients according to the FAERS. The risk level of drug-induced delirium should be taken into account to optimize drug therapy in clinical practice.

Interpretable machine learning model for early prediction of delirium in elderly patients following intensive care unit admission: a derivation and validation study.

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.

Effect of a fall within three months of admission on delirium in critically Ill elderly patients: a population-based cohort study

BackgroundDelirium is common among elderly patients in the intensive care unit (ICU) and is associated with prolonged hospitalization, increased healthcare costs, and increased risk of death. Understanding the potential risk factors and early prevention of delirium is critical to facilitate timely intervention that may reverse or mitigate the harmful consequences of delirium.AimTo clarify the effects of pre-admission falls on ICU outcomes, primarily delirium, and secondarily pressure injuries and urinary tract infections. MethodsThe study relied on data sourced from the Medical Information Mart for Intensive Care IV (MIMIC-IV) database. Statistical tests (Wilcoxon rank-sum or chi-squared) compared cohort characteristics. Logistic regression was employed to investigate the association between a history of falls and delirium, as well as secondary outcomes, while Kaplan–Meier survival curves were used to assess short-term survival in delirium and non-delirium patients.ResultsStudy encompassed 22,547 participants. Delirium incidence was 40%, significantly higher in patients with a history of falls (54.4% vs. 34.5%, p < 0.001). Logistic regression, controlling for confounders, not only confirmed that a history of falls elevates the odds of delirium (OR: 2.11; 95% CI: 1.97–2.26; p < 0.001) but also showed it increases the incidence of urinary tract infections (OR:1.50; 95% CI:1.40–1.62; p < 0.001) and pressure injuries (OR:1.36; 95% CI:1.26–1.47; p < 0.001). Elderly delirium patients exhibited lower 30-, 180-, and 360-day survival rates than non-delirium counterparts (all p < 0.001).ConclusionsThe study reveals that history of falls significantly heighten the risk of delirium and other adverse outcomes in elderly ICU patients, leading to decreased short-term survival rates. This emphasizes the critical need for early interventions and could inform future strategies to manage and prevent these conditions in ICU settings.

Malnutrition elevates delirium and ICU stay among critically ill older adult COVID-19 patients.

Malnutrition among intensive care unit (ICU) patients is associated with a higher risk of mortality and prolonged hospitalization. However, the influence of malnutrition on severe outcomes of ICU patients with coronavirus disease 2019 (COVID-19) is unclear. By evaluating the effect of malnutrition on the outcomes of COVID-19 in the ICU in older adult patients, this study will contribute to new knowledge of assessing the nutritional status and recovery of these patients. In the current single center prospective study, 310 critically ill COVID-19 patients with an age range of ≥65 years were recruited. Data on demographic characteristics, laboratory parameters, comorbidities, medications, and types of mechanical ventilation were collected in the first 24 h of ICU admission. Malnutrition was defined based on the two-step approach of the Global Leadership Initiative on Malnutrition (GLIM) scale at baseline. During the 45 days after the baseline, we collected data on delirium incidence, mortality, invasive mechanical ventilation (IMV) requirement, length of ICU and hospital admission, and re-hospitalization. In this study, the prevalence of malnutrition was 63.4% among critically ill COVID-19 patients. During the 45-day follow-up, 190 (61.3%) COVID-19 deaths were recorded among the baseline 310 patients. After controlling for potential confounders, malnutrition was associated with an increased risk of delirium so malnourished COVID-19 patients had a significantly 35% higher risk of delirium than those without malnutrition (HR: 1.35, 95% CI: 1.01-1.83). Such a significant association was not for COVID-19 mortality and IMV requirement. In addition, malnutrition was associated with a significantly 84% greater odds of prolonged ICU admission (OR: 1.84, 95% CI: 1.09-3.10). No significant association was seen between malnutrition and re-hospitalization and also prolonged hospital admission. Malnutrition was associated with an increased risk of delirium and prolonged ICU admission among critically ill older adult COVID-19 patients. Prevention, diagnosis, and treatment of malnutrition could be a key component in improving outcomes in these patients.

Impact of clinical frailty on surgical and non-surgical complications after major emergency abdominal surgery.

Major emergency abdominal surgery is associated with a high risk of morbidity and mortality. Given the ageing and increasingly frail population, understanding the impact of frailty on complication patterns after surgery is crucial. The aim of this study was to evaluate the association between clinical frailty and organ-specific postoperative complications after major emergency abdominal surgery. A prospective cohort study including all patients undergoing major emergency abdominal surgery at Copenhagen University Hospital Herlev, Denmark, from 1 October 2020 to 1 August 2022, was performed. Clinical frailty scale scores were determined for all patients upon admission and patients were then analysed according to clinical frailty scale groups (scores of 1-3, 4-6, or 7-9). Postoperative complications were registered until discharge. A total of 520 patients were identified. Patients with a low clinical frailty scale score (1-3) experienced fewer total complications (120 complications per 100 patients) compared with patients with clinical frailty scale scores of 4-6 (250 complications per 100 patients) and 7-9 (277 complications per 100 patients) (P < 0.001). A high clinical frailty scale score was associated with a high risk of pneumonia (P = 0.009), delirium (P < 0.001), atrial fibrillation (P = 0.020), and infectious complications in general (P < 0.001). Patients with severe frailty (clinical frailty scale score of 7-9) suffered from more surgical complications (P = 0.001) compared with the rest of the cohort. Severe frailty was associated with a high risk of 30-day mortality (33% for patients with a clinical frailty scale score of 7-9 versus 3.6% for patients with a clinical frailty scale score of 1-3, P < 0.001). In a multivariate analysis, an increasing degree of clinical frailty was found to be significantly associated with developing at least one complication. Patients with frailty have a significantly increased risk of postoperative complications after major emergency abdominal surgery, especially atrial fibrillation, delirium, and pneumonia. Likewise, patients with frailty have an increased risk of mortality within 90 days. Thus, frailty is a significant predictor for adverse events after major emergency abdominal surgery and should be considered in all patients undergoing major emergency abdominal surgery.

Nomogram for predicting the risk of postoperative delirium in elderly patients undergoing orthopedic surgery

ObjectiveTo retrospectively analyze the risk factors for postoperative delirium (POD) after orthopedic surgery in elderly patients and establish an individualized nomogram to predict the risk of POD.MethodsThe data of 1011 patients who underwent orthopedic surgery from January 2019 to January 2022 were retrospectively analyzed. Univariate and multivariate logistic analyses were used to screen for independent risk factors. Stepwise regression was conducted to screen risk factors to construct a nomogram to predict the risk of POD after orthopedic surgery in elderly individuals, and nomogram validation analyses were performed.ResultsThe logistic regression results showed that age (≥ 75 years old vs. < 75 years old; odds ratio (OR) = 2.889; 95% confidence interval (CI), 1.149, 7.264), sex (male vs. female, OR = 2.368; 95% CI, 1.066, 5.261), and preoperative cognitive impairment (yes vs. no, OR = 13.587; 95% CI, 4.360, 42.338) were independent risk factors for POD in elderly patients who underwent orthopedic surgery (P < 0.05). A nomogram was constructed using 7 risk factors, i.e., age, American Society of Anesthesiologists (ASA) classification, sex, preoperative hemoglobin (Hb), preoperative pulmonary disease, cognitive impairment, and intraoperative infusion volume. The area under the curve (AUC) showed good discrimination (0.867), the slope of the calibration curve was 1.0, and the optimal net benefit of the nomogram from the decision curve analysis (DCA) was 0.01–0.58.ConclusionThis study used 7 risk factors to construct a nomogram to predict the risk of POD after major orthopedic surgery in elderly individuals, and the nomogram had good discrimination ability, accuracy, and clinical practicability.

A nomogram for predicting postoperative delirium in pediatric patients following cardiopulmonary bypass: A prospective observational study

ObjectivesTo create a nomogram for early delirium detection in pediatric patients following cardiopulmonary bypass. Research Methodology/DesignThis prospective, observational study was conducted in the Cardiac Intensive Care Unit at a Children's Hospital, enrolling 501 pediatric patients from February 2022 to January 2023. Perioperative data were systematically collected through the hospital information system. Postoperative delirium was assessed using the Cornell Assessment of Pediatric Delirium (CAPD). For model development, Least Absolute Shrinkage and Selection Operator (LASSO) regression was employed to identify the most relevant predictors. These selected predictors were then incorporated into a multivariable logistic regression model to construct the predictive nomogram. The performance of the model was evaluated by Harrell's concordance index, receiver operating characteristic (ROC) curve, calibration curve, and decision curve analysis. External validity of the model was confirmed through the C-index and calibration plots. ResultsFive independent predictors were identified: age, SpO2 levels, lymphocyte count, diuretic use, and midazolam administration, integrated into a predictive nomogram. This nomogram demonstrated strong predictive capacity (AUC 0.816, concordance index 0.815) with good model fit (Hosmer-Lemeshow test p = 0.826) and high accuracy. Decision curve analysis showed a significant net benefit, and external validation confirmed the nomogram's reliability. ConclusionsThe study successfully developed a precise and effective nomogram for identifying pediatric patients at high risk of post-cardiopulmonary bypass delirium, incorporating age, SpO2 levels, lymphocyte counts, diuretic use, and midazolam medication. Implications for Clinical PracticeThis nomogram aids early delirium detection and prevention in critically ill children, improving clinical decisions and treatment optimization. It enables precise monitoring and tailored medication strategies, significantly contributes to reducing the incidence of delirium, thereby enhancing the overall quality of patient care.

Delirium Knowledge, Risk Factors, and Attitude Among the General Public in Saudi Arabia: A Cross-Sectional Study.

Introduction Delirium is a common and serious neuropsychiatric disorder, of acute onset, present at any age, but more common in older adults, and very common in clinical practice. It combines mental and behavioral symptoms with a fluctuating course, with worsening of the condition in the afternoon and at night, with important repercussions on increased mortality, greater risk of cognitive impairment, and hospitalization costs. Delirium's impact extends to patients, families, and healthcare systems, emphasizing the need for public awareness and education in Saudi Arabia. Methodology It is a cross-sectional conducted in Saudi Arabia that aims to assess knowledge, risk factors, and attitudes regarding delirium among all Saudi and non-Saudi residents aged 18 and older. A 36 self-administered questionnaire, standardized Nordic, was used. Data were cleaned in Microsft Excel (Microsoft Corporation, USA) and analyzed using IBM SPSS Statistics (IBM Corp., Armonk, NY).This study was conducted in Saudi Arabia from May 2023 till March 2024. Results Our study involved 1,470 participants from Saudi Arabia, primarily females (79.1%), Saudi nationals (89.9%), and unmarried individuals (65.4%). Most participants were aged 18-24 (59.5%) and held bachelor's degrees (57.3%). Commonly recognized delirium risk factors included increasing age (63.3%), dementia (58.2%), and longer ICU stays (48.7%). The participants showed moderate knowledge of delirium symptoms and consequences. Attitudes varied, with many agreeing that delirium requires intervention (30.7%) but fewer considering it preventable (17.1%). Sociodemographic factors, including gender and age, significantly influenced knowledge and attitudes, while education levels did not. Conclusion Our study found that gender and age influenced knowledge and attitudes, highlighting the importance of targeted education. Future research should further investigate the effectiveness of such interventions in enhancing knowledge and awareness and promoting preventive actions.

Postoperative Delirium and the Older Adult: Untangling the Confusion.

Postoperative delirium is one of the most prevalent postoperative complications, affecting mostly older adults. Its incidence is expected to rise because of surgical advances, shifting demographics, and increased life expectancy. Although an acute alteration in brain function, postoperative delirium is associated with adverse outcomes, including progressive cognitive decline and dementia, that place significant burdens on patients' lives and healthcare systems. This has prompted efforts to understand the mechanisms of postoperative delirium to provide effective prevention and treatment. There are multiple mechanisms involved in the etiology of postoperative delirium that share similarities with the physiological changes associated with the aging brain. In addition, older patients often have multiple comorbidities including increased cognitive impairment that is also implicated in the genesis of delirium. These tangled connections pinpointed a shift toward creation of a holistic model of the pathophysiology of postoperative delirium. Scientific advancements integrating clinical risk factors, possible postoperative delirium biomarkers, genetic features, digital platforms, and other biotechnical and information technological innovations, will become available in the near future. Advances in artificial intelligence, for example, will aggregate cognitive testing platforms with patient-specific postoperative delirium risk stratification studies, panels of serum and cerebrospinal fluid molecules, electroencephalogram signatures, and gut microbiome features, along with the integration of novel polygenetic variants of sleep and cognition. These advances will allow for the enrollment of high-risk patients into prevention programs and help uncover new pharmacologic targets.

The association between the fibrinogen-to-albumin ratio and delirium after deep brain stimulation surgery in Parkinson's disease.

Postoperative delirium (POD) remains one of the most prevalent neuropsychiatric complications after deep brain stimulation (DBS) surgery. The fibrinogen-to-albumin ratio (FAR) has been shown to significantly correlate with the prognosis of many diseases related to inflammation. However, the association between FAR and POD remains unclear. We aimed to explore the association between POD and FAR in patients with Parkinson's disease (PD) undergoing DBS surgery. Patients with PD who underwent DBS surgery in our hospital were included in this retrospective study. FAR was calculated from the blood sample collected on admission. The association between baseline FAR and delirium after surgery was assessed by binary logistic regression analysis, interaction analysis, and stratified analyses. Of 226 patients, 37 (16.4%) suffered from delirium after surgery. The average age of the participants was 63.3 ± 7.2 years, and 51.3% were male patients. Multivariate logistic regression analysis indicated that patients in the highest FAR tertile had a higher risk of POD compared with patients in the lowest FAR tertile (OR = 3.93, 95% CI: 1.24 ~ 12.67). Subgroup analysis demonstrated that FAR and the preoperative Mini-Mental State Examination score (p = 0.013) had an association with delirium after surgery. Our data suggest that a higher preoperative FAR was significantly associated with delirium after DBS surgery. FAR on admission is a useful candidate biomarker to identify patients with PD who are at a high risk of delirium following DBS surgery.

Intravenous infusion of dexmedetomidine during the surgery to prevent postoperative delirium and postoperative cognitive dysfunction undergoing non-cardiac surgery: a meta-analysis of randomized controlled trials.

Dexmedetomidine plays a pivotal role in mitigating postoperative delirium and cognitive dysfunction while enhancing the overall quality of life among surgical patients. Nevertheless, the influence of dexmedetomidine on such complications in various anaesthesia techniques remains inadequately explored. As such, in the present study, a meta-analysis was conducted to comprehensively evaluate its effects on postoperative delirium and cognitive dysfunction. A number of databases were searched for randomised controlled trials comparing intravenous dexmedetomidine to other interventions in preventing postoperative delirium and cognitive dysfunction in non-cardiac and non-neurosurgical patients. These databases included PubMed, Embase, and Cochrane Library. Statistical analysis and graphing were performed using Review Manager, STATA, the second version of the Cochrane risk-of-bias tool for randomised controlled trials, and GRADE profiler. This meta-analysis comprised a total of 24 randomised controlled trials, including 20 trials assessing postoperative delirium and 6 trials assessing postoperative cognitive dysfunction. Across these 24 studies, a statistically significant positive association was observed between intravenous administration of dexmedetomidine and a reduced incidence of postoperative delirium (RR: 0.55; 95% CI 0.47 to 0.64,p < 0.00001, I2 = 2%) and postoperative cognitive dysfunction (RR: 0.60; 95% CI 0.38 to 0.96,p = 0.03, I2 = 60%). Subgroup analysis did not reveal a significant difference in the incidence of postoperative delirium between the general anaesthesia and non-general anaesthesia groups, but a significant difference was observed in the incidence of postoperative cognitive dysfunction. Nonetheless, when the data were pooled, it was evident that the utilisation of dexmedetomidine was associated with an increased incidence of hypotension (RR: 1.42; 95% CI 1.08 to 1.86,p = 0.01, I2 = 0%) and bradycardia (RR: 1.66; 95% CI 1.23 to 2.26,p = 0.001, I2 = 0%) compared with other interventions. However, there was no significantly higher occurrence of hypertension in the DEX groups (RR = 1.35, 95% CI 0.81-2.24, p = 0.25,I2 = 0%). Compared with other interventions, intravenous dexmedetomidine infusion during non-cardiac and non-neurosurgical procedures may significantly reduce the risk of postoperative delirium and cognitive dysfunction. The results of subgroup analysis reveal a consistent preventive effect on postoperative delirium in both general and non-general anaesthesia groups. Meanwhile, continuous infusion during general anaesthesia was more effective in reducing the risk of cognitive dysfunction. Despite such findings, hypotension and bradycardia were more frequent in patients who received dexmedetomidine during surgery.

Risk stratification and predictive modeling of postoperative delirium in chronic subdural hematoma.

Background- Postoperative delirium is a common complication associated with the elderly, causing increased morbidity and prolonged hospital stay. However, its risk factors in chronic subdural hematoma patients have not been well studied. Methods- A total of 202 consecutive patients with chronic subdural hematoma at Peking University Third Hospital between January 2018 and January 2023 were enrolled. Various clinical indicators were analyzed to identify independent risk factors for postoperative delirium using univariate and multivariate regression analyses. Delirium risk prediction models were developed as a nomogram and a Markov chain. Results- Out of the 202 patients (age, 71 (IQR, 18); female-to-male ratio, 1:2.7) studied, 63 (31.2%) experienced postoperative delirium. Univariate analysis identified age (p < 0.001), gender (p = 0.014), restraint belt use (p < 0.001), electrolyte imbalance (p < 0.001), visual analog scale score (p < 0.001), hematoma thickness (p < 0.001), midline shift (p < 0.001), hematoma side (p = 0.013), hematoma location (p = 0.018), and urinal catheterization (p = 0.028) as significant factors. Multivariate regression analysis confirmed the significance of restraint belt use (B = 7.657, p < 0.001), electrolyte imbalance (B = -3.993, p = 0.001), visual analog scale score (B = 2.331, p = 0.016), and midline shift (B = 0.335, p = 0.007). Hematoma thickness and age had no significant impact. Conclusion- Increased midline shift and visual analog scale scores, alongside restraint belt use and electrolyte imbalance elevate delirium risk in chronic subdural hematoma surgery. Our prediction models may offer reference value in this context.

Sex Differences in Delirium after Coronary Artery Bypass Graft Surgery and Perioperative Neuropsychiatric Conditions: A Secondary Analysis of a Cohort Study.

Biological sex influences the risk of depression and cognitive impairment, but its role in relation to postoperative delirium is unclear. This analysis investigates sex differences in delirium risk after coronary artery bypass graft (CABG) surgery and sex-related differences in relation to affective and cognitive symptoms. This is a secondary analysis of the Neuropsychiatric Outcomes After Heart Surgery (NOAHS) study, a single-site, observational study of a CABG surgery cohort (n = 149). Preoperative characteristics are stratified by sex, and baseline variables that differ by sex are evaluated to understand whether sex modifies their relationships with delirium. We also evaluate sex differences in one-month depression and cognition. Female sex is associated with several delirium risk factors, including higher risk of preoperative depression and middle cerebral artery (MCA) stenosis. MCA stenosis was statistically associated with delirium only among women (OR 15.6, 95% CI 1.5, 164.4); mild cognitive impairment (MCI) was associated with delirium only in men (OR 4.6, 95% CI 1.2, 17.9). Other sex-based differences failed to reach statistical significance. Depression remained commoner among women 1month post-CABG. Women in this CABG cohort were more likely to have depression at baseline and 1month postoperatively, as well as MCA stenosis and postoperative delirium. Sex might modify the relationship between post-CABG delirium and its risk factors including MCA stenosis and MCI. Cerebrovascular disease deserves study as a potential explanation linking female sex and a range of poor outcomes among women with coronary heart disease.

Burden of delirium on mortality and healthcare resource utilization in geriatric patients hospitalized for inflammatory bowel disease

Background Delirium is prevalent in elderly patients, linked to elevated mortality rates, heightened healthcare resource use, and caregiver burden. Inflammatory bowel disease (IBD) poses various delirium risk factors, yet the impact on geriatric IBD patient outcomes remains unexplored. Methods Using 2016–2019 National Inpatient Sample data, we identified ≥65-year-old patients admitted for IBD (Crohn’s, ulcerative colitis) management stratified by delirium presence as a secondary diagnosis. The study aimed to assess delirium’s impact on geriatric IBD patient outcomes. Results Among 67,534 elderly IBD admissions, 0.7% (470) developed delirium. The delirium group had a 4.8-fold increase in in-hospital mortality risk (odds ratio 4.80, P < 0.001, 95% confidence interval [CI] 1.94–11.8). IBD patients with delirium experienced prolonged length of stay (adjusted mean difference 5.15 days, 95% CI 3.24–7.06, P < 0.001) and increased care costs (adjusted mean difference $48,328, 95% CI $26,485–$70,171, P < 0.001) compared to those without delirium. Conclusion Elderly IBD patients with delirium face higher mortality risk, prolonged hospitalization, and increased healthcare costs. Clinicians should recognize delirium’s detrimental effects in this vulnerable group and adhere to preventive protocols for improved care.

Effectiveness of Consolidated National Institute for Health and Care Excellence Delirium Prediction Rule for Predicting the Risk of Delirium in Intensive Care Unit Patients with Stroke Managed by Pharmacist-led Interventions (P11-2.006)

Effectiveness of Consolidated National Institute for Health and Care Excellence Delirium Prediction Rule for Predicting the Risk of Delirium in Intensive Care Unit Patients with Stroke Managed by Pharmacist-led Interventions (P11-2.006)

A novel nomogram for the prediction of subsyndromal delirium in patients in intensive care units: A prospective, nested case-controlled study

BackgroundSubsyndromal delirium is a dynamic, recognizable condition commonly observed in intensive care unit (ICU) patients that can lead to poor patient prognosis, and its prompt recognition and management can prevent disease progression. However, no evidence-based predictive tool has been developed specifically to assess the occurrence of subsyndromal delirium in the ICU. ObjectiveTo develop and validate a novel, simple and effective tool for estimating the risk of subsyndromal delirium among ICU patients. DesignA prospective, nested case-controlled study. Data sourcesA total of 731 patients were recruited from the central ICU of a tertiary hospital in southwestern China from August 2021 to November 2022. MethodsThe least absolute shrinkage and selection operator was applied to screen potential features for univariate and multivariate logistic regression. A nomogram was constructed using the selected variables. The performance of the nomogram was evaluated by combining the area under the receiver operating characteristic curve (AUC), calibration curves and decision curve analysis (DCA). ResultsThe prevalence of subsyndromal delirium among ICU patients was 23.06 %. Multiple logistic regression analysis revealed that the independent predictive factors for subsyndromal delirium among ICU patients were vision impairment, a history of falls, the use of restraint, blood transfusion, the use of antibiotics, surgery, the Caprini score, and the Braden score, all of which were used to construct the nomogram. The AUCs for the model were 0.710 (95 % CI, 0.654–0.766, P < 0.001) and 0.825 (95 % CI, 0.732–0.917, P < 0.001) in the training and validation cohorts, respectively, indicating that the model had high accuracy in distinguishing patients with and without subsyndromal delirium. The calibration curve of the nomogram showed good consistency between the predicted and actual probabilities. The DCA indicated that the nomogram has clinical application for patients in the ICU. ConclusionsWe developed an easy-to-use nomogram for identifying subsyndromal delirium in ICU patients with satisfactory predictive ability based on simple and easily accessible clinical features. The nomogram can identify ICU patients at high-risk for subsyndromal delirium and may be a useful subsyndromal delirium tool for current ICU physicians.

Organizational Context and Facilitation Interactions on Delirium Risk in Long-Term Care: A Cross-Sectional Study

ObjectivesOrganizational context (eg, leadership) and facilitation (eg, coaching behaviors) are thought to interact and influence staff best practices in long-term care (LTC), including the management of delirium. Our objective was to assess if organizational context and facilitation—individually, and their interactions—were associated with delirium in LTC. DesignRetrospective cross-sectional analysis of secondary data. Setting and ParticipantsWe included 8755 residents from 281 care units in 86 LTC facilities in 3 Canadian provinces. MethodsDelirium (present/absent) was assessed using the Resident Assessment Instrument-Minimum Data Set 2.0 (RAI-MDS 2.0). The Alberta Context Tool (ACT) measured 10 modifiable features of care unit organizational context. We measured the care unit's total care hours per resident day and the proportion of care hours that care aides contributed (staffing mix). Facilitation included the facility manager's perception of RAI-MDS reports' adequacy and pharmacist availability. We included unit managers' change-oriented organizational citizenship behavior (OCB) and an item reflecting how often care aides recommended policy changes. Associations of organizational context, facilitation, and their interactions with delirium were analyzed using mixed-effects logistic regressions, controlling for covariates. ResultsDelirium symptoms were prevalent in 17.4% of residents (n = 1527). Manager-perceived adequacy of RAI-MDS reports was linked to reduced delirium symptoms [odds ratio (OR) = 0.63]. Higher care hours per resident day (OR = 1.2) and an available pharmacist in the facility (OR = 1.5) were associated with increased delirium symptoms. ACT elements showed no direct association with delirium. However, on care units with low social capital scores (context), increased unit managers' OCB decreased delirium symptoms. On care units with high vs low evaluation scores (context), increased staffing mix reduces delirium symptoms more substantially. Conclusions and ImplicationsUnit-level interactions between organizational context and facilitation call for targeted quality improvement interventions based on specific contextual factors, as effectiveness may vary across contexts.