Predictors Of Delirium Research Articles

Using Machine Learning and Electronic Health Records to Identify Neuropsychiatric Risk Scores for Delirium in ICU and General Hospital Settings.

Delirium is a common and acute neuropsychiatric syndrome that requires timely intervention to prevent its associated morbidity and mortality. Yet, its diagnosis and symptoms are often overlooked due to its variable clinical presentation and fluctuating nature. Thus, in this study, we address the barriers to delirium diagnosis by utilizing a machine learning-based predictive algorithm for incident delirium that relies on archived electronic health records (EHRs) data. We used the Medical Information Mart for Intensive Care (MIMIC) database to create a detailed dataset for identifying delirium in intensive care unit (ICU) patients. Our approach involved training machine learning models on this dataset to pinpoint critical clinical features for delirium detection. These features were then refined and applied to non-ICU patients using EHRs from the American University of Beirut Medical Center (AUBMC). Our study assessed machine learning models like Extreme Gradient Boosting (XGBoost), Categorical Boosting (CatBoost), Classification and Regression Trees (CART), Random Forest (RF), Neural Oblivious Decision Ensembles (NODE), and Logistic Regression (LR), highlighting superior delirium detection in diverse clinical settings. The CatBoost model excelled in ICU environments with an F1 Score of 89.2%, while XGBoost performed best in general hospital settings with a 75.4% F1 Score. Interpretations using Tabular Local Interpretable Model-agnostic Explanations (LIME) revealed critical indicators such as prothrombin time and hematocrit levels, enhancing model transparency and clinical applicability. These clinical insights help differentiate the delirium predictors between ICU patients, who are often sensitive to various factors. The proposed predictive algorithm improves delirium detection rates and streamlines efficiency in hospital electronic systems, thereby enabling prompt interventions to prevent delirium progression and associated complications. The clinical indicators for delirium that we identified in general hospital settings and ICU can greatly help healthcare professionals identify potential causes of delirium and reduce misdiagnosis.

Delirium Incidence and Predictors in SARS-CoV-2 Vaccinated Residents in Long-Term Care Facilities (LTCF): Insights from the GeroCovid Vax Study

ObjectiveSARS-CoV-2 vaccination can bring an important benefit for older people in terms of reduction of mortality and hospitalization; however, reports of rare adverse effects like altered consciousness and delirium among this demographic have raised concerns. This study aimed to assess delirium incidence post-SARS-CoV-2 vaccination and its predictors in older residents across 60 Italian long-term care facilities (LTCFs). DesignThis is a prospective cohort study considering data from GeroCovid Vax, a multicenter cohort study jointly performed by the Italian Society of Gerontology and Geriatrics (SIGG) (Florence, Italy) and the Italian National Institute of Health (Istituto Superiore di Sanità—ISS, Rome, Italy), and sponsored by the Italian Medicines Agency (Agenzia Italiana del Farmaco—AIFA). Setting and ParticipantsGeroCovid Vax enrolled LTCFs residents aged ≥60 who received at least 1 anti–SARS-CoV-2 vaccine dose. MethodsBaseline data covered sociodemographic details, chronic diseases, medications, nutritional status, cognitive and functional assessments, mobility, and frailty. Delirium was assessed post-first, second, and booster vaccine doses using DSM-5 criteria. Data analysis involved descriptive statistics, multivariate logistic regression, and network analysis. ResultsA total of 2521 participants (mean age 83.10 ± 9.21 years, 70.7% female) were analyzed. Delirium incidence post-first, second, and booster doses was 3.5%, 1.6%, and 1.5%, respectively. Age, preexisting cognitive disorders, and frailty were significant predictors of delirium, with odds ratios (ORs) of 1.70 (95% CI, 1.08–2.77), 2.05 (95% CI, 1.40–2.97), and 1.77 (95% CI, 1.25–2.52), respectively. Prior use of antipsychotics (OR, 1.75; 95% CI, 1.22–2.51) and antidepressants (OR, 1.77; 95% CI, 1.25–2.52) correlated significantly with delirium. Network analysis indicated a strong association between anorexia and delirium. Conclusion and ImplicationsPost-vaccination delirium is infrequent and decreases with subsequent doses. Timely assessments for frailty and cognitive impairment could aid in stratifying delirium risk among LTCF residents, facilitating enhanced prevention measures and close monitoring for delirium indicators.

Genetic assessment of the causal effect of plasma metabolites and metabolic pathways on delirium

PurposeDelirium has a significant impact on millions of people globally and is closely linked to an unfavorable prognosis for complications. Observational studies suggest that plasma metabolites may play significant roles as markers and effectors of delirium, but causal relationships have not yet been elucidated. Based on the most recent genome-wide association study (GWAS) data, our study aims to present novel insights into the genetic relationship between delirium and plasma metabolites. This investigation offers potential clues for utilizing plasma metabolites as predictors of delirium development.MethodsWe performed a thorough Mendelian randomization (MR) analysis to investigate the causal relationship between 1,091 individual metabolites and 309 metabolite ratios in plasma with respect to delirium. Inverse-variance weighting (IVW) was employed as the primary estimation method, while MR-Egger and weighed median methods were utilized to assess the robustness of the results. Sensitivity analyses encompassing the MR Pleiotropy RESidual Sum and Outlier (MR-PRESSO) test, Cochran Q test, leave-one-out analysis and MR Egger intercept analysis were also undertaken. Additionally, the MR Steiger test was performed to explore any potential reverse causal effect of metabolites on delirium.ResultsA total of 63 types of plasma metabolites associated with delirium were detected using the IVW method (p < 0.05). Among the known metabolites, our analysis revealed that two specific metabolites (1-palmitoyl-2-palmitoleoyl-gpc (16:0/16:1) and homovanillate) and a metabolite ratio (phosphate to oleoyl-linoleoyl-glycerol (18:1 to 18:2)) demonstrated a consistent and significant causal relationship with delirium across all analysis methods. Finally, no evidence of pleiotropy was detected in our analysis.ConclusionsOur study has revealed a causal association between blood metabolites and the risk of delirium. homovanillate is known to be associated with immunity and redox, 1-palmitoyl-2-palmitoleoyl-gpc (16:0/16:1) and metabolite ratio (phosphate to oleoyl-linoleoyl-glycerol (18:1 to 18:2)) may play a role in lipid regulation. These findings may provide fresh insights into the identification of suitable diagnostic markers and potential treatment strategies focused on specific plasma metabolites in patients with delirium. However, further experiments are required to gain a comprehensive understanding of the underlying biological mechanisms involved.

Cardio Delirium Day: national study on the prevalence of delirium in Italian cardiology wards

To date delirium prevalence in the adult acute Italian hospital cardiac population is unknown. In a multicenter study, we assessed the prevalence of delirium over a single day among a population of patients admitted to acute cardiac hospital wards in Italy. This is a point prevalence study (called "Cardio Delirium Day") which involved 55 Italian cardiologic centers (23 North, 18 Central, 12 South, 2 Sardinia) that collected data on 152 patients older than 65 years hospitalized on March 15, 2023. Delirium was assessed on the same day in all patients using the Confusion Assessment Method for the Intensive Care Unit algorithm, a validated and briefly administered tool which does not require specialized training. We also collected data about clinical variables, functional and nutritional status, dementia, comorbidity, medications, and physical restraints. The mean sample age was 79.0 ± 10 years (33% female). Delirium was diagnosed in 25 patients (16.4%); 17.1% were hospitalized in the intensive cardiac care unit and 13.8% in the cardiology ward (p=NS). Hyperactive was the commonest subtype (48%), followed by mixed (36%) and hypoactive type (8%). In a multivariate logistic regression, male sex (odds ratio [OR] 3.81, 95% confidence interval [CI] 1.18-12.26; p=0.025), chronic obstructive pulmonary disease (OR 0.24, 95% CI 0.063-0.66; p=0.008), sensorial deficit (OR 3.75, 95% CI 1.18-11.95; p=0.025), sleep deprivation (OR 5.81, 95% CI 1.47-22.9; p=0.012) and the presence of ≥3 precipitating factors (OR 7.63, 95% CI 2.32-25.2; p=0.001) were independent predictors of delirium. Delirium occurred in 16.4% of patients in a cardiology setting. The "Cardio Delirium Day" project might become a useful method to assess delirium over time and sensitize the interest and the culture of Italian cardiology in this important aspect of hospital care.

Delirium in Neurocritical Care: Uncovering Undisclosed Psychotropic Substance and Medication Use and Stress Exposure by Hair Analysis.

In intensive care, delirium is frequent, prolongs the stay, increases health care costs, and worsens patient outcome. Several substances and medications as well as stress can impact the risk of delirium; however, assessment of previous exposure to psychotropic agents and stress by self-reports or third-party information is not always reliable. Hair analysis can be used to objectively assess medication and substance use (including chronic alcohol consumption), and allows for the determination of stress-related long-term changes in steroid hormones and endocannabinoids. Consecutive adult patients with acute brain injury admitted to the neurocritical care unit were included. Delirium was diagnosed using the Confusion Assessment Method for the Intensive Care Unit. Liquid chromatography coupled with tandem mass spectrometry was used to investigate psychoactive substances and medications, ethyl glucuronide, steroid hormones, and endocannabinoids in hair samples. Univariable and multivariable analyses were used to reveal any associations with the occurrence of delirium. Of 50 consecutive patients, 21 (42%) were diagnosed with delirium. Detection of antipsychotics or antidepressants in hair was more frequent in patients with delirium (antidepressants: 43% vs. 14%, p = 0.040; antipsychotics: 29% vs. 0%, p = 0.021). These patients also displayed higher ethyl glucuronide levels (p = 0.049). Anandamide (AEA) concentrations were higher in patients with delirium (p = 0.005), whereas oleoylethanolamide (p = 0.045) and palmitoylethanolamide (PEA) (p = 0.017) concentrations were lower in patients with delirium. Backward stepwise logistic regression analysis revealed antidepressants and AEA/PEA to be independent relevant predictors of delirium. Hair analysis provides crucial and otherwise unattainable information regarding chronic stress and the use of psychotropic substances and medications. Undisclosed antidepressant/antipsychotic use or intense chronic alcohol consumption is susceptible to treatment (continuation of medication or provision of low-dose benzodiazepines in case of alcohol). Chronic stress can be evaluated using stress markers and endocannabinoids in hair, potentially allowing for personalized delirium risk stratification and preventive measures.

#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 &amp;lt;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&amp;lt;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&amp;lt;0.001), alcohol abuse (r=0.144, P&amp;lt;0.001), history of stroke (r=0.184, P&amp;lt;0.001), vascular dementia (r=0.125, P&amp;lt;0.001), dehydration (r=0.175, P&amp;lt;0.001), sepsis (r=0.144, P&amp;lt;0.001), and acute kidney injury (AKI) stage 2 and 3 (r=0.155, P&amp;lt;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&amp;lt;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&amp;lt;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.

Incidence and risk factors of postoperative delirium following hepatic resection: a retrospective national inpatient sample database study

BackgroundPostoperative delirium (POD) is a common complication after major surgery and can cause a variety of adverse effects. However, no large-scale national database was used to assess the occurrence and factors associated with postoperative delirium (POD) following hepatic resection.MethodsPatients who underwent hepatic resection from 2015 to 2019 were screened using the International Classification of Diseases (ICD) 10th edition clinical modification code from the National Inpatient Sample (NIS) Database. Peri-operative factors associated with delirium were screened and underwent statistical analysis to identify independent predictors for delirium following hepatic resection.ResultsA total of 80,070 patients underwent hepatic resection over a five-year period from 2015 to 2019. The overall occurrence of POD after hepatic resection was 1.46% (1039 cases), with a slight upward trend every year. The incidence of elective admission was 6.66% lower (88.60% vs. 81.94%) than that of patients without POD after hepatic resection and 2.34% (45.53% vs. 43.19%) higher than that of patients without POD in teaching hospitals (P < 0.001). In addition, POD patients were 6 years older (67 vs. 61 years) and comprised 9.27% (56.69% vs. 47.42%) more male patients (P < 0.001) compared to the unaffected population. In addition, the occurrence of POD was associated with longer hospitalization duration (13 vs. 5 days; P < 0.001), higher total cost ($1,481,89 vs. $683,90; P < 0.001), and higher in-hospital mortality (12.61% vs. 4.11%; P < 0.001). Multivariate logistic regression identified hepatic resection-independent risk factors for POD, including non-elective hospital admission, teaching hospital, older age, male sex, depression, fluid and electrolyte disorders, coagulopathy, other neurological disorders, psychoses, and weight loss. In addition, the POD after hepatic resection has been associated with sepsis, dementia, urinary retention, gastrointestinal complications, acute renal failure, pneumonia, continuous invasive mechanical ventilation, blood transfusion, respiratory failure, and wound dehiscence / non-healing.ConclusionAlthough the occurrence of POD after hepatic resection is relatively low, it is beneficial to investigate factors predisposing to POD to allow optimal care management and improve the outcomes of this patient population.

The impact of delirium on clinical and functional outcomes in hospitalized patients with acute coronary syndrome.

Delirium, which is prevalent in critical care settings, remains underexplored in acute coronary syndrome (ACS) patients in the cardiac intensive care unit (CICU). To investigate the prevalence and clinical significance of delirium in patients with ACS admitted to the CICU. A prospective study (n = 106, mean age 74.2 ± 5.7 years) assessed delirium using the confusion assessment method-intensive care unit (CAM-ICU) tool in 21.7% of ACS patients during their CICU stay. Baseline characteristics, geriatric conditions and clinical procedures were compared between delirious and nondelirious patients. The outcomes included in-hospital mortality, 30-day and 6-month mortality, acute adverse events and length of CICU stay and hospital stay (LOS). Delirious patients who were older and had a higher incidence of coronary artery disease underwent more complex procedures (e.g., pacemaker placement). Multivariate analysis identified central venous catheter insertion, urinary catheterization and benzodiazepine use as independent predictors of delirium. Delirium was correlated with prolonged LOS (p < .001) and increased in-hospital, 30-day and 6-month mortality (p < .001). Delirium in ACS patients in the CICU extends hospitalization and increases in-hospital, 30-day and 6-month mortality. Early recognition and targeted interventions are crucial for mitigating adverse outcomes in this high-risk population. This study highlights the critical impact of delirium on outcomes in hospitalized patients with ACS in the CICU. Delirium, often overlooked in ACS management, significantly extends hospitalization and increases mortality rates. Nurses and physicians must be vigilant in identifying delirium early, particularly in older ACS patients or those with comorbidities. Recognizing independent predictors such as catheterization and benzodiazepine use allows for targeted interventions to reduce delirium incidence. Integrating routine delirium assessments and preventive strategies into ACS management protocols can improve outcomes, optimize resource utilization and enhance overall patient care in the CICU setting.

Letter to the editor in response to "S100B as a predictor of delirium in critically ill obstetric patients: A nested case-control study".

Letter to the editor in response to "S100B as a predictor of delirium in critically ill obstetric patients: A nested case-control study".

Unraveling the Predictors for Delirium and ICU Stay Duration in Patients with Heart Failure and Reduced Ejection Fraction (HFrEF) Undergoing Coronary Artery Bypass Grafting-A Multicentric Analysis.

Objective: This study assesses predictors for postoperative delirium (POD) and ICU stay durations in HFrEF patients undergoing CABG, focusing on ONCAB versus OPCAB surgical methods. Summary Background Data: In cardiac surgery, especially CABG, POD significantly impacts patient recovery and healthcare resource utilization. With varying incidences based on surgical techniques, this study provides an in-depth analysis of POD in the context of HFrEF patients, a group particularly susceptible to this complication. Methods: A retrospective analysis of 572 patients who underwent isolated CABG surgery with a preoperative ejection fraction under 40% was conducted at four German university hospitals. Patients were categorized into ONCAB and OPCAB groups for comparative analysis. Results: Age and Euro Score II were significant predictors of POD. The ONCAB group showed higher incidences of re-sternotomy (OR: 3.37), ECLS requirement (OR: 2.29), and AKI (OR: 1.49), whereas OPCAB was associated with a lower incidence of delirium. Statistical analysis indicated a significant difference in ICU stay durations between the two groups, influenced by surgical complexity and postoperative complications. Conclusions: This study underscores the importance of surgical technique in determining postoperative outcomes in HFrEF patients undergoing CABG. OPCAB may offer advantages in reducing POD incidence. These findings suggest the need for tailored surgical decisions and comprehensive care strategies to enhance patient recovery and optimize healthcare resources.

The evaluation of frequency and predictors of delirium and its short-term and long-term outcomes in hospitalized older adults’

BackgroundDelirium is a common complication in hospitalized older adults with multifactorial etiology and poor health outcomes. AimTo determine the frequency and predictors of delirium and its short-term and long-term outcomes in hospitalized older adults. MethodsA prospective observational study was performed in patients aged ≥60 years consecutively admitted to geriatric ward. Potential risk factors were assessed within 24 hours of hospital admission. Delirium screening was performed on admission and daily thereafter throughout the hospital stay using Confusion Assessment Method (CAM). Patients were followed up at 1-year post-discharge. ResultsThe study included 200 patients with mean age 73.1 ± 8.83 years. Incidence and prevalence rate of delirium were 5% and 20% respectively. Multivariable regression analysis revealed emergency admission (OR= 5.12 (1.94–13.57), p=0.001), functional dependency (Katz index of Independence in Activities of Daily Living (Katz-ADL) score <5) 2 weeks before admission (OR= 3.08 (1.30–7.33), p=0.011) and more psychopathological symptoms (higher Brief Psychiatric Rating Scale (BPRS) total score) (OR=1.12 (1.06–1.18), p=0.001) to be independently associated with delirium. Patients in delirium group had significantly high in-hospital mortality (OR= 5.02 (2.12–11.8), p=0.001) and post-discharge mortality (HR= 2.02 (1.13–3.61), p=0.017) and functional dependency (Katz-ADL score <5) (OR= 5.45 (1.49–19.31), p=0.01) at 1-year follow up. ConclusionDelirium is quite frequent in geriatric inpatients and is associated with high in-hospital and post-discharge mortality risk and long-term functional dependency. Emergency admission, pre-hospitalization functional dependency, and more general psychopathological symptoms are independently associated factors. Hence, earliest identification and treatment with early implementation of rehabilitation services is warranted.

Association between perioperative self-reported sleep disturbances and delirium risk in elderly patients following total joint arthroplasty: a cohort study.

Perioperative sleep disturbance may increase delirium risk. However, the role of perioperative sleep disturbance in delirium following total joint arthroplasty remains unclear. This prospective cohort study aimed to observe the delirium risk in patients with sleep disturbances. After excluding pre-existing sleep disturbances, older patients scheduled for total joint arthroplasty from July 17, 2022, to January 12, 2023, were recruited. Preoperative sleep disturbance or postoperative sleep disturbance was defined as a Chinese version of the Richards-Campbell Sleep Questionnaire (RCSQ) score of <50 during hospitalisation. A cut-off score of 25 was used to classify the severity of sleep disturbance. The primary outcome was the incidence of postoperative delirium. In all, 11.6% of cohort patients (34/294) developed delirium. After multivariate analysis, a preoperative Day 1 RCSQ score of ≤25 (odds ratio [OR] 3.62, 95% confidence interval [CI] 1.19-10.92; p = 0.02), occurrence of sleep disturbances (OR 2.76, 95% CI 1.19-6.38; p = 0.02) and RCSQ score of ≤25(OR 2.91, 95% CI 1.33-6.37; p = 0.007) postoperatively were strong independent predictors of delirium. After sensitivity analysis for daily delirium, a postoperative Day 1 RCSQ score of ≤25 (OR 9.27, 95% CI 2.72-36.15; p < 0.001) was associated with a greater risk of delirium on postoperative Day 1, with a reasonable discriminative area under the curve of 0.730. We concluded that postoperative but not preoperative sleep disturbances may be an independent factor for delirium risk. Sleep disturbance on the first night after surgery was a good predictor of subsequent delirium, no matter the nature of self-reported sleep disturbance.

ICU admission Braden score independently predicts delirium in critically ill patients with ischemic stroke

BackgroundDelirium is a common and severe complication in intensive care unit (ICU) patients with acute ischemic stroke, exacerbating cognitive and physical impairments. It prolongs hospitalization, increases healthcare costs, and raises mortality risk. Early prediction is crucial because it facilitates prompt interventions that could possibly reverse or alleviate the detrimental consequences of delirium. Braden scores, traditionally used to assess pressure injury risk, could also signal frailty, providing an early warning of delirium and aiding in prompt and effective patient management. ObjectiveTo examine the association between the Braden score and delirium. MethodsA retrospective analysis of adult ischemic stroke patients in the ICU of a tertiary academic medical center in Boston from 2008 to 2019 was performed. Braden scores were obtained on admission for each patient. Delirium, the primary study outcome, was assessed using the Confusion Assessment Method for Intensive Care Unit and a review of nursing notes. The association between Braden score and delirium was determined using Cox proportional hazards modeling, with hazard ratios (HR) and 95% confidence intervals (CI) calculated. ResultsThe study included 3,680 patients with a median age of 72 years, of whom 1,798 were women (48.9 %). The median Braden score at ICU admission was 15 (interquartile range 13–17). After adjustment for demographics, laboratory tests, severity of illness, and comorbidities, the Braden score was inversely associated with the risk of delirium (adjusted HR: 0.94, 95 % CI: 0.92–0.96, P < 0.001). ConclusionsThe Braden score may serve as a convenient and simple screening tool to identify the risk of delirium in ICU patients with ischemic stroke. Implication for Clinical PracticeThe use of the Braden score as a predictor of delirium in ischemic stroke patients in the ICU allows early identification of high-risk patients. This facilitates timely intervention, thereby improving patient outcomes and potentially reducing healthcare costs.

EVALUATING THE RISK OF DELIRIUM IN ELDERLY INPATIENTS IN COVID-19 INTENSIVE CARE: A PROSPECTIVE AND OBSERVATIONAL STUDY

Introduction: Delirium is dangerous, often preventable, and associated with a high financial burden and increased morbidity and mortality. This study aimed to evaluate the risk of delirium in elderly inpatients in COVID-19 intensive care units. Materials and Method: This study used a prospective and observational design. Between July and November 2022, 49 intensive care patients were admitted to a training and research hospital in northeast Turkey. The data were collected using the Patient Information Form, Critical-Care Pain Observation Tool, Ramsay Sedation Scale, and Nursing-Delirium Screening Scale. Results: The patients’ mean age was 76.90±8.29 years. The longer the length of stay in the intensive care unit, the incidence of delirium increased. The incidence of delirium increased in patients aged 70–95 years (p=0.007). Patients with delirium experienced insomnia and agitation and used more sedative drugs (p&lt;0.05). The predictors of early delirium were sedation (β=0.869), agitation (β=-0.582), and diastolic blood pressure (β=0.258). The predictors of delirium were pain (β=-0.599) and sedation (β=0.267). Conclusion: The study demonstrated that older age, agitation, sedation, pain, and diastolic blood pressure predicted delirium in elderly COVID-19 inpatients. It is necessary to identify and eliminate risk factors to reduce the risk of delirium in elderly patients. Nurses should play an active role in identifying and managing delirium in elderly COVID-19 patients. Keywords: COVID-19; Delirium; Aged; Intensive Care.

Frequency and risk factors of delirium in the pediatric intensive care unit of a tertiary care hospital: A prospective observational study

Abstract Background: Critical illness is one of the most common causes of delirium in children which can be associated with increased morbidity and mortality. Delirium continues to be an overlooked aspect of the management of critically ill children. This study was conducted with the objective of determining the frequency and risk factors of delirium in critically ill children. Subjects and Methods: This prospective observational study included patients admitted for at least a period of 24 h of teaching in the pediatric intensive care unit (PICU) of a medical college of Pakistan from March 2022 to September 2022. Each patient was screened for developing delirium twice a day using the Cornell Assessment of Pediatric Delirium. Results: The median age of the patients was 19.5 months (interquartile range: 10.7–72). There were 64.6% (n = 106) of male children, and 97.2% (n = 143) were admitted due to medical conditions. Delirium was identified in 97 (59.1%) patients. Mortality was observed in 3 (1.8%) cases. The average length of stay and frequency of hypoxia was higher among the pediatric delirium group (P = 0.002 and P = 0.022, respectively). Independent predictors of delirium in PICU patients were length of stay (odds ratio [OR], 2.42; 95% confidence interval [CI], 1.39–4.20), use of inotropes (OR, 3.32; 95% CI, 1.0.4–10.64), use of narcotics (OR, 8.78; 95% CI, 0.96–80.51), and hypoxia (OR, 3.02; 95% CI, 1.17–7.81). Conclusion: Delirium is common in children admitted to PICU. Length of PICU stay, use of narcotics, inotropes, and hypoxia were found as independent risk factors for delirium.

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

Determine if biomarkers of Alzheimer's disease and neural injury may play a role in the prediction of delirium risk. In a cohort of older adults who underwent elective surgery, delirium case-no delirium control pairs (N=70, or 35 matched pairs) were matched by age, sex and vascular comorbidities. Biomarkers from CSF and plasma samples collected prior to surgery, including amyloid beta (Aβ)42 , Aβ40 , total (t)-Tau, phosphorylated (p)-Tau181 , neurofilament-light (NfL), and glial fibrillary acid protein (GFAP) were measured in cerebrospinal fluid (CSF) and plasma using sandwich enzyme-linked immunosorbent assays (ELISAs) or ultrasensitive single molecule array (Simoa) immunoassays. Plasma GFAP correlated significantly with CSF GFAP and both plasma and CSF GFAP values were nearly two-fold higher in delirium cases. The median paired difference between delirium case and control without delirium for plasma GFAP was not significant (p=0.074) but higher levels were associated with a greater risk for delirium (odds ratio 1.52, 95% confidence interval 0.85, 2.72 per standard deviation increase in plasma GFAP concentration) in this small study. No matched pair differences or associations with delirium were observed for NfL, p-Tau 181, Aβ40 and Aβ42 . These preliminary findings suggest that plasma GFAP, a marker of astroglial activation, may be worth further investigation as a predictive risk marker for delirium.

The hyperdense middle cerebral artery sign is an early predictor of delirium in ischemic stroke patients

The hyperdense middle cerebral artery sign is an early predictor of delirium in ischemic stroke patients

Unveiling the nexus of postoperative fever and delirium in cardiac surgery: identifying predictors for enhanced patient care.

Postoperative delirium (POD) is a significant complication observed in cardiac surgery patients, characterized by acute cognitive decline, fluctuating mental status, consciousness impairment, and confusion. Despite its impact, POD often goes undiagnosed. Postoperative fever, a common occurrence after cardiac surgery, has not been comprehensively studied in relation to delirium. This study aims to identify perioperative period factors associated with POD in patients undergoing cardiopulmonary bypass, with the potential for implementing preventive interventions. In a prospective observational study conducted between February 2023 and April 2023 at the Department of Cardio-Thoracic Surgery, Nanjing Drum Tower Hospital, Affiliated Hospital of Nanjing University Medical School, a total of 232 patients who underwent cardiac surgery were enrolled. POD assessment utilized the Confusion Assessment Method for the ICU (CAM-ICU), while high fever was defined as a bladder temperature exceeding 39°C. Statistical analysis included univariate and multivariate analyses, logistic regression, nomogram development, and internal validation. The overall incidence of postoperative delirium was found to be 12.1%. Multivariate analysis revealed that postoperative lactate levels [odds ratio (OR) = 1.787], maximum temperature (OR = 11.290), and cardiopulmonary bypass time (OR = 1.015) were independent predictors of POD. A predictive nomogram for POD was developed based on these three factors, demonstrating good discrimination and calibration. The prediction model exhibited a C-statistic value of 0.852 (95% CI, 0.763-0.941), demonstrating excellent discriminatory power. Sensitivity and specificity, based on the area under the receiver operating characteristic (AUROC) curve, were 91.2% and 67.9%, respectively. This study underscores the high prevalence of POD in cardiac surgery patients and identifies postoperative lactate levels, cardiopulmonary bypass duration, and postoperative fever as independent predictors of delirium. The association between postoperative fever and POD warrants further investigation. These findings have implications for implementing preventive strategies in high-risk patients, aiming to mitigate postoperative complications and improve patient outcomes.

Social determinants of health and incident postoperative delirium: Exploring key relationships in the SAGES study.

Examining the associations of social determinants of health (SDOH) with postoperative delirium in older adults will broaden our understanding of this potentially devastating condition. We explored the association between SDOH factors and incident postoperative delirium. A retrospective study of a prospective cohort of patients enrolled from June 18, 2010, to August 8, 2013, across two academic medical centers in Boston, Massachusetts. Overall, 560 older adults age ≥70 years undergoing major elective non-cardiac surgery were included in this analysis. Exposure variables included income, lack of private insurance, and neighborhood disadvantage. Our main outcome was incident postoperative delirium, measured using the Confusion Assessment Method long form. Older age (odds ratio, OR: 1.01, 95% confidence interval, CI: 1.00, 1.02), income <20,000 a year (OR: 1.12, 95% CI: 1.00, 1.26), lack of private insurance (OR: 1.19, 95% CI: 1.04, 1.38), higher depressive symptomatology (OR: 1.02, 95% CI: 1.01, 1.04), and the Area Deprivation Index (OR: 1.02, 95% CI: 1.01, 1.04) were significantly associated with increased risk of postoperative delirium in bivariable analyses. In a multivariable model, explaining 27% of the variance in postoperative delirium, significant independent variables were older age (OR 1.01, 95% CI 1.00, 1.02), lack of private insurance (OR 1.18, 95% CI 1.02, 1.36), and depressive symptoms (OR 1.02, 95% CI 1.00, 1.03). Household income was no longer a significant independent predictor of delirium in the multivariable model (OR:1.02, 95% CI: 0.90, 1.15). The type of medical insurance significantly mediated the association between household income and incident delirium. Lack of private insurance, a social determinant of health reflecting socioeconomic status, emerged as a novel and important independent risk factor for delirium. Future efforts should consider targeting SDOH factors to prevent postoperative delirium in older adults.

Occurrence and predictors of delirium in critically ill older patients: a prospective cohort study.

This study aims to analyze the occurrence of delirium in critically ill older patients and to identify predictors of delirium. This prospective study included critically ill older patients admitted into level II units of Intensive Care Medicine Department of a University Hospital. Patients with Glasgow Coma Scale score ≤11, traumatic brain injury, terminal disease, history of psychosis, blindness/deafness, or inability to understanding/speaking Portuguese were excluded. The Confusion Assessment Method-Short Form (CAM-4) was used to assess the presence of delirium. The final sample (n = 105) had a median age of 80 years, most being female (56.2%), widowed (49.5%), and with complete primary education (53%). Through CAM-4, 36.2% of the patients had delirium. The delirium group was more likely to have previous cognitive decline (48.6% vs 19.6%, P = .04) and severe dependency in instrumental activities of daily living (34.3% vs 14.8%, P = .032), comparing with patients without delirium. The final multiple logistic regression model explained that patients with previous cognitive decline presented a higher risk for delirium (odds ratio: 4.663, 95% confidence Interval: 1.055-20.599, P = .042). These findings corroborate previous studies, showing that cognitive decline is an independent predictor for delirium in older patients. This study is an important contribution for the knowledge regarding the predictors of delirium. The recognition of these factors will help to identify patients who are at high risk for this syndrome and implement early screening and prevention strategies. However, further studies with larger samples, recruited from other clinical settings as well as analyzing other potential factors for delirium, will be needed.