Development Of Delirium Research Articles

Nomogram to predict the incidence of delirium in elderly patients with non-severe SARS-CoV-2 infection.

To construct and validate nomogram models that predict the incidence of delirium in elderly patients with non-severe SARS-CoV-2 infection. Elderly patients (≥65y) tested positive for SARS-CoV-2 infection at the hospital were included. We used the 3-min diagnostic Confusion Assessment Method for delirium diagnosis. Least absolute shrinkage and selection operator (LASSO) logistical regression analysis was performed to explore potential independent influencing factors of delirium. A predict model visualized by nomogram was constructed based on the confirmed variables. The predictive accuracy and clinical value of the model were evaluated using receiver operating characteristic (ROC) curves. The data of 311 elderly patients were analyzed, of whom 73 (23.47%) patients were diagnosed with delirium. Three independent influencing factors of delirium were confirmed: age (OR1.16,1.11-1.22), Glomerular filtration rate (OR 0.98,0.97-0.99), platelet-large cell ratio (1.06,1.02-1.10). These parameters were used to create a nomogram to predict the development of delirium, which showed good predictive accuracy confirmed by the ROC curves (AUC 0.82,0.76-0.88). We construct a credible nomogram to predict the development of delirium in elderly patients with Non-severe SARS-CoV-2 infection. Our finding may be useful to physicians in early prevention and treatment of delirium.

Causal relationship between dementia and delirium: Insights from a bidirectional two-sample Mendelian randomization analysis

BackgroundOur previous study found dementia as a significant risk factor for delirium development in elderly patients with hip fracture. However, the causal relationship between dementia and delirium remains unclear. MethodsTo assess the causal relationship between delirium and dementia, we conducted a bidirectional Mendelian randomization (MR) analysis. Inversevariance weighted (IVW), weighted median, MR Egger, weighted mode, and simple mode were employed to conduct the MR analysis. Heterogeneity was assessed using the Cochran Q statistic in MR-Egger and IVW methods. Horizontal pleiotropy was examined via the MR pleiotropy residual sum and outliers (MR-PRESSO) and MR-Egger intercept tests. ResultsThe forward MR analysis revealed a significant association between unclassified dementia (1.604 (1.326–1.941), p = 1.12 × 10−6), Alzheimer's disease (1.259 (1.128–1.405), p = 4.10 × 10−5), and dementia with Lewy bodies (1.121 (1.026–1.225), p = 0.011) with an increased risk of delirium. In the reverse MR analysis, delirium was also suggested to increase the risk of unclassified dementia (1.133 (1.066–1.204), p = 6.31 × 10−5) and vascular dementia (1.246 (1.075–1.444), p = 0.003). These significant results were further validated in the multivariable MR analysis. No evidence of heterogeneity or horizontal pleiotropy was observed (p > 0.05). Limitations(1) Limited to European populations. (2) Sample population overlap between delirium and dementia. (3) Not all dementia subtypes were causally associated with delirium. ConclusionsThis study provides genetic evidence supporting a causal relationship between dementia and delirium, indicating that dementia may influence the risk of delirium while delirium may also increase the risk of dementia.

Sustained delirium reduction in an inpatient neuroscience unit.

Delirium is described as acute brain dysfunction that often fluctuates throughout the day and is highly prevalent in hospitalized adults. Delirium negatively affects patient outcomes with consequences including decreased cognitive functioning and increased mortality and healthcare costs. Furthermore, neurological patients are at increased risk for developing delirium due to their underlying diagnoses. The purpose of this evidence-based practice project was to evaluate the long-term impact of nursing education and use of trained volunteers to prevent the development of delirium in an inpatient neuroscience unit. This was a pre-post designed evidence-based practice project to educate and prioritize nursing care interventions for delirium prevention compared to a delirium management framework. The interventions included delirium education for nurses and nursing assistants along with the development of a specialized volunteer program to implement non-pharmacological, multi-component delirium prevention interventions. Long-term sustainment and enculturation occurred over the subsequent year. The baseline data collection period included 2520 patients. The intervention period included 4515 patients, with both groups being similar in age, race, gender, and length of stay. The total number of patients with a discharge diagnosis of delirium decreased from 29.2% to 19.8% (p < .001). Fewer patients in the intervention group were discharged to a skilled nursing facility (p < .001) and other post-acute facility (p = .008), along with more patients being discharged to home care (p < .001). This evidence-based practice project demonstrates long-term sustained reduction of delirium in the neuroscience population. Despite the challenges during the COVID-19 pandemic, delirium prevention strategies were found to be effective in decreasing the rate at which patients develop delirium.

Predicting delirium and the effects of medications in hospitalized COVID-19 patients using machine learning: A retrospective study within the Korean Multidisciplinary Cohort for Delirium Prevention (KoMCoDe).

Delirium is commonly reported from the inpatients with Coronavirus disease 2019 (COVID-19) infection. As delirium is closely associated with adverse clinical outcomes, prediction and prevention of delirium is critical. We developed a machine learning (ML) model to predict delirium in hospitalized patients with COVID-19 and to identify modifiable factors to prevent delirium. The data set (n = 878) from four medical centers was constructed. Total of 78 predictors were included such as demographic characteristics, vital signs, laboratory results and medication, and the primary outcome was delirium occurrence during hospitalization. For analysis, the extreme gradient boosting (XGBoost) algorithm was applied, and the most influential factors were selected by recursive feature elimination. Among the indicators of performance for ML model, the area under the curve of the receiver operating characteristic (AUROC) curve was selected as the evaluation metric. Regarding the performance of developed delirium prediction model, the accuracy, precision, recall, F1 score, and the AUROC were calculated (0.944, 0.581, 0.421, 0.485, 0.873, respectively). The influential factors of delirium in this model included were mechanical ventilation, medication (antipsychotics, sedatives, ambroxol, piperacillin/tazobactam, acetaminophen, ceftriaxone, and propacetamol), and sodium ion concentration (all p < 0.05). We developed and internally validated an ML model to predict delirium in COVID-19 inpatients. The model identified modifiable factors associated with the development of delirium and could be clinically useful for the prediction and prevention of delirium in COVID-19 inpatients.

Predisposing and precipitating factors for the development of postoperative delirium in critically ill patients in a university intensive care unit.

to detect the incidence of postoperative delirium in critically ill patients admitted to a surgical intensive care unit and to evaluate the predisposing and precipitating factors associated with postoperative delirium in critically ill patients admitted to a surgical intensive care unit. this is a prospective cohort study of 157 critically ill surgical patients. Fisher's exact test and Chi-square test were used for the association between factors and the occurrence of delirium, the Wilcoxon test for numerical variables, and the logistic regression model for the analysis of predisposing and precipitating factors. the incidence of delirium was 28% (n=44). Age was a significant predisposing factor (p=0.001), followed by the length of surgery (p<0.001), blood transfusion (p=0.043), administration of crystalloids (p=0.008), and anti-inflammatory drugs (p=0.037), which were the precipitating factors identified. The best-adjusted models were: age, length of surgery, non-administration of anti-emetics, use of sufentanil, and blood transfusion. delirium is a frequent condition in critically ill adults undergoing surgery and the existence of precipitating and predisposing factors is relevant to the outcome, with the anesthetic-surgical procedure as the catalyst event.

Predisposing and precipitating factors for the development of postoperative delirium in critically ill patients in a university intensive care unit

Resumo Objetivo: detectar a incidência de delirium pós-operatório em pacientes críticos internados em uma unidade de terapia intensiva cirúrgica e avaliar os fatores predisponentes e precipitantes associados ao delirium pós-operatório em pacientes críticos internados em uma unidade de terapia intensiva cirúrgica. Método: trata-se de um estudo de coorte prospectivo com 157 pacientes críticos cirúrgicos. Utilizou-se teste Exato de Fisher e qui-quadrado para a associação entre os fatores e ocorrência de delirium, teste de Wilcoxon para as variáveis numéricas e o modelo de Regressão Logística para a análise dos fatores predisponentes e precipitantes. Resultados: a incidência de delirium foi 28% (n=44). O fator idade apresentou-se predisponente significativo (p=0,001), seguido do tempo de cirurgia (p&lt;0,001), a transfusão sanguínea (p=0,043), a administração de cristaloides (p=0,008) e anti-inflamatórios (p=0,037), estes foram os fatores precipitantes identificados. Obteve-se como melhor modelo ajustado: idade, tempo de cirurgia, a não administração de antieméticos, o uso de sufentanil e a transfusão sanguínea. Conclusão: o delirium consiste em acometimento frequente para adultos críticos cirúrgicos e a existência de fatores precipitantes e predisponentes tornam-se relevantes para o desfecho, tendo-se o procedimento anestésico-cirúrgico como evento catalisador.

Predisposing and precipitating factors for the development of postoperative delirium in critically ill patients in a university intensive care unit

Resumen Objetivo: detectar la incidencia de delirium postoperatorio en pacientes críticos internados en una unidad de terapia intensiva quirúrgica y evaluar los factores predisponentes y precipitantes asociados al delirium postoperatorio en pacientes críticos internados en una unidad de terapia intensiva quirúrgica. Método: se trata de un estudio de cohorte prospectivo con 157 pacientes críticos quirúrgicos. Se utilizó la prueba exacta de Fisher y chi-cuadrado para la asociación entre los factores y ocurrencia de delirium, prueba de Wilcoxon para las variables numéricas y el modelo de regresión logística para el análisis de los factores predisponentes y precipitantes. Resultados: la incidencia de delirium fue 28% (n=44). El factor edad se presentó como predisponente significativo (p=0,001), seguido del tiempo de cirugía (p&lt;0,001), la transfusión sanguínea (p=0,043), la administración de cristaloides (p=0,008) y antiinflamatorios (p=0,037), estos fueron los factores precipitantes identificados. Se obtuvo como mejor modelo ajustado: edad, tiempo de cirugía, la no administración de antieméticos, el uso de sufentanilo y la transfusión sanguínea. Conclusión: el delirium es un acometimiento frecuente para adultos críticos quirúrgicos y la existencia de factores precipitantes y predisponentes se vuelven relevantes para el desenlace, teniendo el procedimiento anestésico-quirúrgico como evento catalizador.

A Study of Delirium in a Tertiary Care Hospital in Ahmedabad City of Gujarat

Abstract Background: There are many risk factors for the development of delirium. According to the definition given by Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition, delirium is defined as “disturbances in attention and awareness over a short period of time, representations of changes from baseline attention, and awareness with a tendency to fluctuate over a period of time.” Aim: The aim of the study was to assess the prevalence of risk factors among patients of delirium in a tertiary care hospital. Materials and Methods: A cross-sectional study was conducted among patients of delirium in a tertiary care hospital of the city of Ahmedabad using the Confusional Assessment Method-Severity scale and sociodemographic questionnaire. A total of 100 patients were recruited in the study. The analysis was done using Microsoft Excel 2019. Results: In the study, we found that the majority of patients of delirium were of age &gt;65 years, males, suffering from cerebrovascular illness, and having dementia. It was reported from the study that the majority patients of delirium were admitted to the intensive care unit and having a prolonged hospital stay. Conclusions: Identification of risk factors and early intervention can have better outcomes in patients suffering from delirium and lead to better prognosis.

Differential effects of sevoflurane and desflurane on frontal intraoperative electroencephalogram dynamics associated with postoperative delirium

Study objectiveIntraoperative electroencephalogram (EEG) patterns associated with postoperative delirium (POD) development have been studied, but the differences in EEG recordings between sevoflurane- and desflurane-induced anesthesia have not been clarified. We aimed to distinguish the EEG characteristics of sevoflurane and desflurane in relation to POD development. Design and patientsWe collected frontal four-channel EEG data during the maintenance of anesthesia from 148 elderly patients who received sevoflurane (n = 77) or desflurane (n = 71); 30 patients were diagnosed with delirium postoperatively. The patients were divided into four subgroups based on anesthetics and delirium status: sevoflurane delirium (n = 17), sevoflurane non-delirium (n = 60), desflurane delirium (n = 13), and desflurane non-delirium (n = 58). We compared spectral power, coherence, and pairwise phase consistency (PPC) between sevoflurane and desflurane, and between non-delirium and delirium groups for each anesthetic. Main resultsIn patients without POD, the sevoflurane non-delirium group exhibited higher EEG spectral power across 8.5–35 Hz (99.5% CI bootstrap analysis) and higher PPC from alpha to gamma bands (p < 0.005) compared to the desflurane non-delirium group. Conversely, in patients with POD, no significant EEG differences were observed between the sevoflurane and desflurane delirium groups. For the sevoflurane-induced patients, the sevoflurane delirium group had significantly lower power within 7.5–31.5 Hz (99.5% CI bootstrap analysis), reduced coherence over 8.9–23.8 Hz (99.5% CI bootstrap analysis), and lower PPC values in the alpha band (p < 0.005) compared with the sevoflurane non-delirium group. For the desflurane-induced patients, there were no significant differences in the EEG patterns between delirium and non-delirium groups. ConclusionsIn normal patients without POD, sevoflurane demonstrates a higher power spectrum and prefrontal connectivity than desflurane. Furthermore, reduced frontal alpha power, coherence, and connectivity of intraoperative EEG could be associated with an increased risk of POD. These intraoperative EEG characteristics associated with POD are more noticeable in sevoflurane-induced anesthesia than in desflurane-induced anesthesia.

Increased A1 astrocyte activation-driven hippocampal neural network abnormality mediates delirium-like behavior in aged mice undergoing cardiac surgery.

Delirium is the most common neurological complication after cardiac surgery with adverse impacts on surgical outcomes. Advanced age is an independent risk factor for delirium occurrence but its underlying mechanisms are not fully understood. Although increased A1 astrocytes and abnormal hippocampal networks are involved in neurodegenerative diseases, whether A1 astrocytes and hippocampal network changes are involved in the delirium-like behavior of aged mice remains unknown. In the present study, a mice model of myocardial ischemia-reperfusion mimicking cardiac surgery and various assessments were used to investigate the different susceptibility of the occurrence of delirium-like behavior between young and aged mice and the underlying mechanisms. The results showed that surgery significantly increased hippocampal A1 astrocyte activation in aged compared to young mice. The high neuroinflammatory state induced by surgery resulted in glutamate accumulation in the extrasynaptic space, which subsequently decreased the excitability of pyramidal neurons and increased the PV interneurons inhibition through enhancing N-methyl-D-aspartate receptors' tonic currents in the hippocampus. These further induced the abnormal activities of the hippocampal neural networks and consequently contributed to delirium-like behavior in aged mice. Notably, the intraperitoneal administration of exendin-4, a glucagon-like peptide-1 receptor agonist, downregulated A1 astrocyte activation and alleviated delirium-like behavior in aged mice, while IL-1α, TNF-α, and C1q in combination administered intracerebroventricularly upregulated A1 astrocyte activation and induced delirium-like behavior in young mice. Therefore, our study suggested that cardiac surgery increased A1 astrocyte activation which subsequently impaired the hippocampal neural networks and triggered delirium development.

Association Between Antidiabetic Drugs and Delirium: A Study Based on the Adverse Drug Event Reporting Database in Japan.

Several associations between diabetes mellitus and delirium have been reported; however, they have been inconsistent, and evidence on the effects of antidiabetic medications on delirium is also limited. This study aimed to investigate whether the use of antidiabetic drugs is a risk factor for delirium development. Using the Japanese Adverse Event Reporting Database, we analyzed 662,899 reports between 2004 and 2022. Reporting odds ratios (RORs) and 95% confidence intervals (CIs) for delirium associated with diabetes and using each antidiabetic medication were calculated after adjusting for potential confounders. Overall, 8892 of the reports analyzed were associated with delirium. A comparison of the incidence of delirium between patients with and without diabetes showed no significant difference, with 1.34% in patients without diabetes and 1.37% in those with diabetes. In each antidiabetic medication, signals for delirium were detected for sulfonylurea (crude ROR, 1.35; 95% CI 1.21-1.51) and insulin (crude ROR, 1.28; 95% CI 1.13-1.44). These results were maintained even after adjusting for factors with potential confounders (sulfonylurea: adjusted ROR, 1.75; 95% CI 1.54-2.00, insulin: adjusted ROR, 1.35; 95% CI 1.20-1.54). Our results suggest no association between diabetes and delirium; however, using sulfonylurea and insulin may be associated with delirium development. Nonetheless, these findings should be validated in future studies.

Delirium after Cardiac Surgery-A Narrative Review.

Postoperative delirium (POD) after cardiac surgery is a well-known phenomenon which carries a higher risk of morbidity and mortality. Multiple patient-specific risk factors and pathophysiologic mechanisms have been identified and therapies have been proposed to mitigate risk of delirium development postoperatively. Notably, cardiac surgery frequently involves the use of an intraoperative cardiopulmonary bypass (CPB), which may contribute to the mechanisms responsible for POD. Despite our greater understanding of these causative factors, a substantial reduction in the incidence of POD remains high among cardiac surgical patients. Multiple therapeutic interventions have been implemented intraoperatively and postoperatively, many with conflicting results. This review article will highlight the incidence and impact of POD in cardiac surgical patients. It will describe some of the primary risk factors associated with POD, as well as anesthetic management and therapies postoperatively that may help to reduce delirium.

Nurse-led ultrasound-guided femoral nerve block: A randomised controlled trial of two different patient flow systems in an emergency department

IntroductionElderly with hip fractures present complex challenges. Effective pain management is crucial for recovery and quality of life. However, pain control can be difficult and requires customized care. MethodsWe conducted an unblinded, randomised controlled trial investigating the effects of ultrasound-guided femoral nerve block in patients with hip fracture performed by specially trained nurses (Group Nurse) compared to anaesthesiologists (Group Anaesthesiologist). The hypothesis was that a single shot ultrasound-guided femoral nerve block would result in a total summarized lower dynamic numeric rating scale score for pain intensity during the first 120 min after admission for patients in Group Nurse compared to Group Anaesthesiologist measured in five timepoints. The primary outcome was measured by a cumulative numeric rating scale score for dynamic pain (with flexion of the hip until maximum 30° from bed surface) during the first 120 min after admission to the emergency department. ResultsFrom February 2020 to June 2021, 263 patients were screened, of which 42 (16.0%) consented and were randomly allocated; 21 in each arm. The primary outcome was not different between groups (p = 0.24), and displayed no substantial superiority of specially trained nurses over anaesthesiologist. No complications or adverse effects were observed in either group. The use of systemic analgesics and the development of delirium was similar between the two groups. In the Nurse Group, patients were administered their ultrasound-guided femoral nerve block earlier. ConclusionOur study did not demonstrate a statistically significant beneficial effect of specially trained nurses over anaesthesiologist on cumulative pain in performing ultrasound-guided femoral nerve blocks, while no side-effects/complications or adverse effects were observed in either group. ClinicaltrialThe trial was registered on October 31, 2019 at Clinicaltrials.gov (NCT04145752).

Possible role of gut derived metabolites in communication between systemic inflammation and CNS in delirium development.

AbstractBackgroundDementia and delirium are strongly correlated. Patients with dementia are more prone to develop delirium, while delirium can lead to accelerated cognitive decline. Biomarkers present in the CSF have been considered to belong to the pathophysiological pathways between systemic inflammation, neuroinflammation, gut microbiota and consequently, contribute to the etiology of both the cognition impairments, ie. delirium and dementia. Despite multiple studies on inflammatory biomarkers in CSF, the link with systemic inflammation has still not been deciphered. Multiple studies have indicated that inflammatory pathways in patients with cognitive decline are mediated by gut microbiota.MethodIn this narrative review we screened PubMed for studies, where neuroinflammatory biomarkers detected in CSF were investigated in relation to delirium. We will explain the link to microbiome by comparing these delirium studies to microbiome studies in dementia. These studies were published in English till January 2023.ResultWe found that in patients with Alzheimer’s disease (AD) and delirium altered levels of at least 70 different neuroinflammatory biomarkers in CSF were found. Also altered microbiome has been identified in AD and its correlation with the CNS inflammation was shown. Interestingly, in case of AD, a recent study demonstrated that a microbial‐derived metabolite, trimethylamine N‐oxide (TMAO), reaches the CNS and that its elevated levels are present in AD patients.In case of delirium, we found two studies indicating contribution of disbalanced gut microbiota in acute CNS inflammation in human. It has been shown that preoperative status of gut microbiota can allow prediction of postoperative delirium in patients with gastric cancer. Interestingly, there was already one case described where fecal microbiota transplantation ameliorated patient’s infection and delirium. No studies on microbiome‐derived metabolites, which could constitute a possible link with the acute inflammation of CNS in delirium, have been found.ConclusionThere is irrefutable evidence that altered levels of neuroinflammatory biomarkers in CSF are associated with pathology of both AD and delirium. Implication of the microbiome, and microbial‐derived metabolite TMAO in inflammatory processes and in pathophysiology of AD has already been found. This has encouraged us to investigate the role of TMAO in the acute CNS inflammatory condition, i.e. delirium.

Mechanisms of sepsis‐induced inflammation in the aging brain

AbstractBackgroundSepsis affects millions worldwide with adults over the age of 65 at particularly high risk. Up to 70% of sepsis patients develop delirium and the severity and length of delirium are strong predictors of acquisition of Alzheimer’s Disease and Related Dementias (AD, ADRD). We hypothesize that older adults and those at risk for AD have augmented neuroinflammation during sepsis that correlates development of delirium and persistence of long‐term cognitive impairment.MethodMale and female wild‐type (young‐3 months and aged‐18 months) and 4 month old Tau P301S transgenic AD mice were used to test the effects of polymicrobial sepsis on markers of neuroimflammation and behavior. Sepsis was induced by intraperitoneal injection of a slurry of cecal contents. Plasma and brain were collected from 8 hours to 7 days post infection for measurement of pro‐inflammatory cytokines (IL‐6, CXCL‐1, TNF‐a) and markers of neuroinflammation (GFAP, IBA1 and s100B) using a combination of protein quantification, multiplex and immunohistochemical approaches. Behavior, including measures of locomotor activity, motor learning (rotarod) and cognition (Y‐maze, nest building) were tested up to 7 days post infection.ResultSepsis increases plasma markers of acute neuroinflammation between 8 and 48 hours that resolves by 7 days. Despite this, mice who have recovered from sepsis have persistent microglial activation in the hippocampus at least 7 days later suggesting prolonged damage. Some recovered mice also have persistent deficits in behavioral tasks including activity and nest building despite appearing healthy and fully recovered. Older WT mice are more susceptible to sepsis as measured by severity of illness (Figure) and mortality and mice genetically predisposed to AD have greater deficits in behavioral measures compared to their WT counterparts following infection.ConclusionSepsis is accompanied acutely by marked neuroinflammation and chronically by microglial activation and behavior deficits. Older age and presence of even early stages of AD‐relevant pathology augment these deficits. Persistent microglial activation may underlie this pathology and prime the aged brain to develop an ADRD‐like syndrome.

Geriatric nutritional risk index independently predicts delirium in older patients in intensive care units: A multicenter cohort study

BackgroundMalnutrition is associated with clinical outcomes in several diseases. However, the role of malnutrition in the risk of delirium in elderly patients in intensive care units (ICU) remains unclear. This study aimed to elucidate the association between the Geriatric Nutritional Risk Index (GNRI) and the risk of delirium in elderly patients in the ICU. MethodsElderly patients from the Medical Information Mart for Intensive Care IV (MIMIC-IV) and the eICU Collaborative Research Database (eICU-CRD) were included in this study, totaling 11,310 and 5,627, respectively. All subjects were stratified according to their GNRI score: those with no nutritional risk (GNRI > 98), mild nutritional risk (92 ≤ GNRI ≤ 98), moderate nutritional risk (82 ≤ GNRI ≤ 92), and severe nutritional risk (GNRI < 82). The primary outcome was delirium. ResultsThe GNRI in MIMIC-IV and eICU-CRD were 93.82 (84.88, 101.26) and 83.39 (75.95, 89.35), respectively. Compared to the cohort without nutritional risk, there was an increased risk of delirium in patients with mild nutritional risk (OR: 1.39, 95 % CI: 1.23–1.58), moderate nutritional risk (OR: 1.72, 95 % CI: 1.52–1.95), and severe nutritional risk (OR: 2.07, 95 % CI: 1.79–2.39). Inclusion of the GNRI score in the multivariate models improved the prediction of delirium. Similar results were found in the eICU-CRD database. ConclusionsNutritional assessment using the GNRI may be an independent predictor of the development of delirium in elderly patients in the ICU. The addition of the GNRI score to the delirium prediction model improves its predictive accuracy.

Recurrent delirium episodes within the intensive care unit: Incidence and associated factors

PurposeDescribe the incidence and factors associated with recurrent delirium in the intensive care unit (ICU). Materials and methodsRetrospective study of ICU patients diagnosed with delirium. Delirium clearance defined as 48 h of negative delirium assessments following initial episode and recurrent delirium as any positive delirium assessment following clearance. Multivariable logistic regression model assessed independent association of patient and hospital factors on development of recurrent delirium, adjusting for pre-defined covariates. ResultsAmong 8591 ICU admissions identified with delirium, 1067 (12.4%) had recurrent symptoms. Factors associated with increased odds of recurrent delirium were age (nonlinear; p = 0.02), shock (OR 1.45, 95% CI [1.20, 1.75]), admission to medical (OR 3.25, 95% CI [2.42, 4.37]), surgical (OR 3.00, 95% CI [2.21, 4.06]), or trauma (OR 2.17, 95% CI [1.58, 3.00]) ICU vs. cardiovascular ICU, increased duration of mechanical ventilation (OR 2.43, 95% CI [2.22, 2.65]), propofol use (OR 1.35, 95% CI [1.02, 1.80]), and antipsychotic medications (haloperidol OR 1.53, 95% CI [1.26, 1.86]; quetiapine OR 2.45, 95% CI [1.98, 3.02]; and olanzapine OR 1.54, 95% CI [1.25, 1.88]). ConclusionsOver 10% of delirious ICU patients had recurrent symptoms. Factors associated with recurrence included age, duration of mechanical ventilation and medication exposure.Clinical Trial Number: Not applicable.

Exploration of key drug target proteins highlighting their related regulatory molecules, functional pathways and drug candidates associated with delirium: evidence from meta-data analyses

BackgroundDelirium is a prevalent neuropsychiatric medical phenomenon that causes serious emergency outcomes, including mortality and morbidity. It also increases the suffering and the economic burden for families and carers. Unfortunately, the pathophysiology of delirium is still unknown, which is a major obstacle to therapeutic development. The modern network-based system biology and multi-omics analysis approach has been widely used to recover the key drug target biomolecules and signaling pathways associated with disease pathophysiology. This study aimed to identify the major drug target hub-proteins associated with delirium, their regulatory molecules with functional pathways, and repurposable drug candidates for delirium treatment.MethodsWe used a comprehensive proteomic seed dataset derived from a systematic literature review and the Comparative Toxicogenomics Database (CTD). An integrated multi-omics network-based bioinformatics approach was utilized in this study. The STRING database was used to construct the protein-protein interaction (PPI) network. The gene set enrichment and signaling pathways analysis, the regulatory transcription factors and microRNAs were conducted using delirium-associated genes. Finally, hub-proteins associated repurposable drugs were retrieved from CMap database.ResultsWe have distinguished 11 drug targeted hub-proteins (MAPK1, MAPK3, TP53, JUN, STAT3, SRC, RELA, AKT1, MAPK14, HSP90AA1 and DLG4), 5 transcription factors (FOXC1, GATA2, YY1, TFAP2A and SREBF1) and 6 microRNA (miR-375, miR-17-5, miR-17-5p, miR-106a-5p, miR-125b-5p, and miR-125a-5p) associated with delirium. The functional enrichment and pathway analysis revealed the cytokines, inflammation, postoperative pain, oxidative stress-associated pathways, developmental biology, shigellosis and cellular senescence which are closely connected with delirium development and the hallmarks of aging. The hub-proteins associated computationally identified repurposable drugs were retrieved from database. The predicted drug molecules including aspirin, irbesartan, ephedrine-(racemic), nedocromil, and guanidine were characterized as anti-inflammatory, stimulating the central nervous system, neuroprotective medication based on the existing literatures. The drug molecules may play an important role for therapeutic development against delirium if they are investigated more extensively through clinical trials and various wet lab experiments.ConclusionThis study could possibly help future research on investigating the delirium-associated therapeutic target biomarker hub-proteins and repurposed drug compounds. These results will also aid understanding of the molecular mechanisms that underlie the pathophysiology of delirium onset and molecular function.

Effect of preoperative sleep disorders on delirium in proximal femoral surgery patients aged 60 or older

ObjectiveTo examine the effect of preoperative sleep disorders on delirium in patients older than 60 years of age who underwent surgery for proximal femoral fracture.MethodsThis is a prospective observational study. We prospectively selected 143 patients with proximal femoral fracture who underwent surgery between April 2021 and April 2022. The primary outcome was postoperative delirium (PD). Multiple logistic regression analyses were performed and a receiver operating characteristic (ROC) curve was generated. The preoperative sleep quality of all eligible participants was assessed through the Pittsburgh Sleep Quality Index (PSQI). The Confusion Assessment Method (CAM) was used to assess PD from the first to the seventh day postoperatively. Patients were divided into two groups according to the PD diagnosis: (1) the no PD (NPD) group and (2) the PD (PD) group.ResultsOf 143 eligible patients, 43 (30.1%) were diagnosed with PD. Multiple logistic regression analysis demonstrated that postoperative ICU admissions (OR = 2.801, p = 0.049) and preoperative sleep disorders (OR = 1.477 p < 0.001) were independently associated with PD. A receiver operating characteristic (ROC) curve demonstrated that the preoperative PSQI score was predictive of PD (AUC 0.808, 95% CI 0.724 ~ 0.892, p < 0.001).ConclusionPreoperative sleeping disorders may be an independent risk factor leading to PD and an independent predictive factor for the development of delirium in proximal femoral surgery patients aged 60 or older.

Development of a complex intervention to prevent delirium in older hospitalized patients by optimizing discharge and transfer processes and involving caregivers: A multi-method study

BackgroundDelirium is a common yet challenging condition in older hospitalized patients, associated with various adverse outcomes. Environmental factors, such as room changes, may contribute to the development or severity of delirium. Most previous research has focused on preventing and reducing this condition by addressing risk factors and facilitating reorientation during hospital stay. ObjectiveWe aimed to systematically develop a complex intervention to prevent delirium in older hospitalized patients by optimizing discharge and transfer processes and involving caregivers during and after these procedures. The intervention combines stakeholder and expert opinions, evidence, and theory. This article provides guidance and inspiration to research groups in developing complex interventions according to the recommendations in the Medical Research Council framework for complex interventions. Design and methodsA stepwise multi-method study was conducted. The preparation phase included analysis of the context and current practice via focus groups. Based on these results, an expert workshop was organized, followed by a Delphi survey. Finally, the intervention was modeled and a program theory was developed, including a logic model. ResultsA complex intervention was developed in an iterative process, involving healthcare professionals, delirium experts, researchers, as well as caregiver and patient representatives. The key intervention component is an 8-point-program, which provides caregivers with recommendations for preventing delirium during the transition phase and in the post-discharge period. Information materials (flyers, handbook, videos, posters, defined “Dos and Don'ts”, discharge checklist), training for healthcare professionals, and status analyses are used as implementation strategies. In addition, roles were established for gatekeepers to act as leaders, and champions to serve as knowledge multipliers and trainers for the multi-professional team in the hospitals. ConclusionsThis study serves as an example of how to develop a complex intervention. In an additional step, the intervention and implementation strategies will be investigated for feasibility and acceptability in a pilot study with an accompanying process evaluation. Tweetable abstractDelirium prevention can benefit from optimizing discharge and transfer processes and involving caregivers of older patients in these procedures. Study registrationDRKS00017828, German Register of Clinical Studies, date of registration 17.09.2019.