Independent Risk Factors For Delirium Research Articles

#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.

Risk factors and prediction model of delirium in elderly patients after hip arthroplasty

Objective: To analyze the risk factors of delirium in elderly patients after hip arthroplasty and to construct a prediction model. Methods: Clinical data of 248 elderly patients who underwent hip arthroplasty in the Department of Traumatology and Orthopedics at Wuhan Fourth Hospital were retrospectively collected from November 2021 to February 2023. Logistic regression analysis was used to identify the risk factors of delirium after hip arthroplasty, and a nomogram prediction model was constructed using the RMS package of R4.1.2 software. The accuracy and stability of the model was evaluated based on the Hosmer-Lemeshow goodness-of-fit test and the receiver operating characteristic (ROC) curve. Results: Age, nighttime sleep, anesthesia method, intraoperative blood loss, hypoxemia, and C-reactive protein (CRP) level were all risk factors of delirium after the hip arthroplasty (P<0.05). These factors were used to construct a nomogram prediction model that was internally validated using the Bootstrap method. The prediction model had the area under ROC curve (AUC) of 0.980 (95% CI: 0.964-0.996), indicating that it has certain predictive value for postoperative delirium. When the optimal cut off value was selected, the sensitivity and specificity were 92.7% and 92.3%, respectively, indicating that the prediction model is effective. Conclusions: Age, short nighttime sleep, general anesthesia, high intraoperative blood loss, hypoxemia, and high CRP levels are independent risk factors for delirium after hip arthroplasty. The nomogram prediction model constructed based on these risk factors can effectively predict delirium in elderly patients after hip arthroplasty. doi: https://doi.org/10.12669/pjms.40.6.9306 How to cite this: Duan Y, Zhang R. Risk factors and prediction model of delirium in elderly patients after hip arthroplasty. Pak J Med Sci. 2024;40(6):1077-1082. doi: https://doi.org/10.12669/pjms.40.6.9306 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Incidence and Risk Factors for ICU-Associated Delirium in the Alert Geriatric Trauma Population.

This study analyzed the overall incidence of delirium, comorbid conditions, injury patterns, and pharmacological risk factors for the development of delirium in an alert, geriatric trauma population. IRB-approved, prospective, consecutive cohort series at two Southeastern Level 1 trauma centers from June 11 to August 15, 2023. Delirium was assessed using the Confusion Assessment Method (CAM) score. Comorbidities and medications were detailed from electronic medical records. Inclusion criteria: age ≥55, GCS ≥14, and ICU admission for trauma. Patients on a ventilator were excluded. Data was analyzed using SPSS version 28 (Armonk, NY: IBM Corp). In total, 196 patients met inclusion criteria. Incidences of delirium for Hospital 1 (n = 103) and Hospital 2 (n = 93) were 15.5% and 12.9%, respectively, with an overall incidence of 14.3% and with no statistical differences between hospitals (P = .599). CAD, CKD, dementia, stroke history, and depression were statistically significant risk factors for developing delirium during ICU admission. Inpatient SSRI/SNRIs, epinephrine/norepinephrine, and lorazepam were significant risk factors. Injury patterns, operative intervention, and use of lidocaine infusions and gabapentin were not statistically significant in delirium development. Using binary linear regression (BLR) analysis, independent risk factors for delirium were dementia, any stage CKD, home SSRI/SRNI prescription, any spine injury and cerebrovascular disease, or injury. Comorbidities of CAD, CHF, CKD, and depression, and these medications: home lorazepam and ICU epinephrine/norepinephrine statistically are more common in patients developing delirium. Dementia, CKD, home SSRI/SRNI and stroke/cerebrovascular disease/injury, and spine injuries are independent predictors by BLR.

Former smoking, but not active smoking, is associated with delirium in postoperative ICU patients: a matched case-control study.

To examine the relationship between current and former smoking and the occurrence of delirium in surgical Intensive Care Unit (ICU) patients. We conducted a single center, case-control study involving 244 delirious and 251 non-delirious patients that were admitted to our ICU between 2018 and 2022. Using propensity score analysis, we obtained 115 pairs of delirious and non-delirious patients matched for age and Simplified Acute Physiology Score II (SAPS II). Both groups of patients were further stratified into non-smokers, active smokers and former smokers, and logistic regression was performed to further investigate potential confounders. Our study revealed a significant association between former smoking and the incidence of delirium in ICU patients, both in unmatched (adjusted odds ratio (OR): 1.82, 95% confidence interval (CI): 1.17-2.83) and matched cohorts (OR: 3.0, CI: 1.53-5.89). Active smoking did not demonstrate a significant difference in delirium incidence compared to non-smokers (unmatched OR = 0.98, CI: 0.62-1.53, matched OR = 1.05, CI: 0.55-2.0). Logistic regression analysis of the matched group confirmed former smoking as an independent risk factor for delirium, irrespective of other variables like surgical history (p = 0.010). Notably, also respiratory and vascular surgeries were associated with increased odds of delirium (respiratory: OR: 4.13, CI: 1.73-9.83; vascular: OR: 2.18, CI: 1.03-4.59). Medication analysis showed that while Ketamine and Midazolam usage did not significantly correlate with delirium, Morphine use was linked to a decreased likelihood (OR: 0.27, 95% CI: 0.13-0.55). Nicotine's complex neuropharmacological impact on the brain is still not fully understood, especially its short-term and long-term implications for critically ill patients. Although our retrospective study cannot establish causality, our findings suggest that smoking may induce structural changes in the brain, potentially heightening the risk of postoperative delirium. Intriguingly, this effect seems to be obscured in active smokers, potentially due to the recognized neuroprotective properties of nicotine. Our results motivate future prospective studies, the results of which hold the potential to substantially impact risk assessment procedures for surgeries.

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.

Incidence and risk factors for delirium after open heart surgery with cardiopulmonary bypass

Background & objectives: Postoperative delirium is a prevalent complication, particularly following cardiac surgery, and has detrimental effects on patient outcomes, including increased morbidity and mortality and prolonged stays in the intensive care unit. This study aims to estimate the incidence and identify the risk factors for delirium.
 Methodology: This prospective observational study was conducted on adult patients undergoing open-heart surgery with cardiopulmonary bypass at the Cardiovascular Surgery Unit at Bachmai Hospital, Vietnam. The Confusion Assessment Method for the ICU (CAM-ICU) was utilized to assess delirium twice daily during the initial four days post-surgery. Perioperative variables were analyzed by univariable and multivariable logistic regression.
 Results: Among the 285 patients included in this study, 56 were diagnosed with delirium using the CAM-ICU, representing a prevalence rate of 19.6%. Multivariate regression analysis revealed several independent risk factors for delirium, including advanced age (odd ratio - OR; 95% confidence interval-CI) (1.07; 1.03-1.10), a history of cerebrovascular accident (3.95; 1.31-11.84), prolonged cardiopulmonary bypass duration (1.02; 1.00-1.03), postoperative atrial fibrillation (2.47; 1.15-5.28), and opioid use time (13.65; 5.69-32.75).
 Conclusion: The incidence of delirium after open heart surgery with cardiopulmonary bypass was 19.6%. Advanced age and a history of cerebrovascular accidents were identified as non-modifiable risk factors for postoperative delirium. Meanwhile, there were three modifiable risk factors, including cardiopulmonary bypass duration, atrial fibrillation, and the time of opioid administration.
 Abbreviations: CAM-ICU: Confusion Assessment Method for the Intensive Care Unit
 Key words: Postoperative Delirium; Risk Factors; Incidence; Open-Heart Surgery; Cardiac Surgery
 Citation: Nguyen TT, Ta DD, Ho HS, Duong HD. Incidence and risk factors for delirium after open heart surgery with cardiopulmonary bypass. Anaesth. pain intensive care 2023;27(6):639−645; DOI: 10.35975/apic.v27i6.2354
 Received: Oct 04, 2023; Revised: Oct 28, 2023; Accepted: Oct 31, 2023

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.

Correlation between malnutrition and delirium in elderly patients with severe pneumonia undergoing invasive mechanical ventilation

To investigate the relationship between malnutrition and delirium and its effect on prognosis in elderly patients with severe pneumonia undergoing invasive mechanical ventilation. A prospective observational study was conducted. Patients with severe pneumonia aged ≥ 60 years old who underwent invasive mechanical ventilation admitted to department of critical care medicine of the Second People's Hospital of Lianyungang from January 2021 to December 2022 were enrolled. The confusion assessment method (CAM) was used to evaluate the delirium of the patients in intensive care unit (ICU). The score of CAM ≥ 1 was defined as delirium. Mini nutritional assessment short-form (MNA-SF) was used to assess the nutritional status of patients, and MNA-SF score ≤ 7 was defined as malnutrition. Patients were divided into delirium group and non-delirium group according to whether delirium occurred. The differences in clinical indicators, length of ICU stay, duration of mechanical ventilation and wake-up time after drug withdrawal were compared between the two groups. After 28 days of short-term follow-up, the patients were divided into death group and survival group, and the differences in the incidence of delirium and malnutrition between the two groups were compared. Binary multivariate Logistic regression analysis was used to screen the risk factors for delirium in elderly patients with severe pneumonia undergoing invasive mechanical ventilation. Kaplan-Meier survival curve was used to analyze the effect of delirium on prognosis. A total of 132 elderly patients with severe pneumonia undergoing invasive mechanical ventilation were enrolled, of whom 98 survived and 34 died within 28 days, with a mortality of 25.76%. The incidence of malnutrition and delirium in the death group was significantly higher than that in the survival group (61.76% vs. 37.76%, 64.71% vs. 26.53%, both P < 0.05), and the MNA-SF score was significantly lower than that in the survival group (6.32±1.80 vs. 8.72±2.23, P < 0.01). Procalcitonin (PCT), interleukin-6 (IL-6) and blood lactic acid (Lac) in the death group were significantly higher than those in the survival group [PCT (μg/L): 4.47 (2.69, 10.39) vs. 2.77 (1.28, 5.94), IL-6 (ng/L): 204.08 (126.12, 509.85) vs. 120.46 (60.67, 290.99), Lac (mmol/L): 5.14 (2.75, 8.60) vs. 3.13 (2.16, 4.30), all P < 0.05], and the wake-up time after drug withdrawal was significantly longer than that in the survival group (minutes: 33.94±8.51 vs. 28.92±7.03, P < 0.01). Among 132 elderly patients with severe pneumonia undergoing invasive mechanical ventilation, 48 patients had delirium during ICU stay, and 84 patients did not have delirium. The incidence of delirium was 36.36%. The 28-day mortality in the delirium group was significantly higher than that in the non-delirium group (45.83% vs. 14.29%, P < 0.01), and the MNA-SF score was significantly lower than that in the non-delirium group (6.46±1.77 vs. 9.05±2.15, P < 0.01), the length of ICU stay, duration of mechanical ventilation, and wake-up time after drug withdrawal were also significantly longer than those in the non-delirium group [length of ICU stay (days): 13.40±9.59 vs. 10.06±7.81, duration of mechanical ventilation (hours): 197.06±89.80 vs. 138.81±82.30, wake-up time after drug withdrawal (minutes): 35.85±7.01 vs. 26.99±6.12, all P < 0.05]. Binary multivariate Logistic regression analysis showed that malnutrition [odds ratio (OR) = 7.527, 95% confidence interval (95%CI) was 2.585-21.917], Lac (OR = 5.345, 95%CI was 1.733-16.483), wake-up time after drug withdrawal (OR = 6.653, 95%CI was 2.021-21.904) were independent risk factors for delirium during ICU stay in elderly patients with severe pneumonia undergoing invasive mechanical ventilation (all P < 0.01). Kaplan-Meier survival analysis showed that the 28-day cumulative survival rate of patients in the delirium group was significantly lower than that in the non-delirium group (54.17% vs. 85.71%), and the difference was statistically significant (Log-Rank test: χ2 = 16.780, P < 0.001). The risk factors for delirium in elderly patients with severe pneumonia undergoing invasive mechanical ventilation during ICU stay include malnutrition, Lac, and wake-up time after drug withdrawal. The occurrence of delirium is closely related to poor prognosis.

Opioids increase the risk of delirium in critically ill patients: A propensity score analysis.

Medications are biologically plausible and potentially modifiable risk factors for delirium. Therapies for delirium might involve more specific strategies such as avoiding the use of delirium-inducing drugs to reduce the incidence of delirium. The association between opioid exposure within 24 hours prior to delirium assessment and the risk of delirium was studied. Using three large databases, the MIMIC III v1.4, MIMIC-IV v0.4 and eICU Collaborative Research, we performed a multicenter, observational cohort study with two cohorts to estimate the relative risks of outcomes among patients administered opioids within 24 hours prior to delirium assessment. Propensity score matching was performed to generate a balanced 1:1 matched cohort and to identify potential prognostic factors. The outcomes included mortality, length of intensive care unit (ICU) stay, length of hospitalization, and odds of being discharged home. Propensity matching successfully balanced the covariates for the 9,529 patients in each group. Opioid use was associated with a significantly higher risk for delirium than not using opioids (p<0.001). Additionally, treatment with opioids was associated with higher mortality and a longer ICU stay (p<0.001) than treatment without opioids. However, patients treated with opioids were more likely to be discharged home (p<0.001). Opioids may be an independent risk factor for delirium in critically ill patients.

Delirium in Medically Hospitalized Patients: Prevalence, Recognition and Risk Factors: A Prospective Cohort Study.

Delirium is a common neuropsychiatric syndrome in hospitalized elderly patients and is associated with poor clinical outcomes. We aimed to determine the prevalence, recognition, risk factors, and course of delirium among hospitalized elderly (65 years of age or older) patients at Sultan Qaboos University Hospital (SQUH). A prospective cohort study included 327 elderly patients (65 years of age or older) admitted to the medical wards at SQUH. Patients were screened for delirium using the 3-Minute Diagnostic Confusion Assessment Method (3D-CAM). Additionally, medical records were reviewed to identify possible associated factors. The prevalence of delirium was 55.4% (95% CI 49.9-60.7), and 35.4% of patients with delirium were not recognized by the treating team. Hypoactive delirium is the most common type of delirium. The logistic regression analyzes demonstrated that pre-existing cognitive impairment (OR = 4.0); poor functional status (OR = 1.9); the use of medications that are known to precipitate delirium (OR = 2.3); polypharmacy (OR = 5.7); urinary catheterization (OR = 2.2); dehydration (OR = 3.1); and electrolytes derangements (OR = 2.0) were independent risk factors for delirium. Furthermore, 56.9% of patients with delirium continued to have delirium upon discharge from the hospital. Delirium is common among elderly patients hospitalized in general medical wards. Implementing effective preventive strategies for delirium during the hospital stay, including early recognition using standard sensitive and specific screening tools (i.e., 3D-CAM) and developing geriatric wards, is crucial.

The relationship between major depression and delirium: A two-sample Mendelian randomization analysis

BackgroundMajor depression (MD) is a well-recognized risk factor for delirium. However, observational studies cannot provide direct evidence of causality between MD and delirium. MethodsThis study explored the genetic causal association between MD and delirium using two-sample Mendelian randomization (MR). Genome-wide association study (GWAS) summary data for MD were obtained from the UK Biobank. GWAS summary data for delirium were obtained from the FinnGen Consortium. Inverse-variance weighted (IVW), MR Egger, weighted median, simple mode, and weighted mode were used to perform the MR analysis. In addition, the Cochrane's Q test was used to detect heterogeneity in the MR results. Horizontal pleiotropy was detected using the MR-Egger intercept test and MR pleiotropy residual sum and outliers (MR-PRESSO) test. Leave-one-out analysis was used to investigate the sensitivity of this association. ResultsThe IVW method showed that MD was an independent risk factor for delirium (P = 0.013). Horizontal pleiotropy was unlikely to bias causality (P > 0.05), and no evidence of heterogeneity was found between the genetic variants (P > 0.05). Finally, a leave-one-out test showed that this association was stable and robust. LimitationsAll participants included in the GWAS were of European ancestry. Due to database limitations, the MR analysis did not conduct stratified analyses for different countries, ethnicities, or age groups. ConclusionWe conducted a two-sample MR analysis and found the evidence of genetic causal association between MD and delirium.

Association of insulin resistance with delirium and CSF biomarkers of Alzheimer's disease in elderly patients with hip fracture.

Delirium is associated with dementia, which shares symptoms of cognitive dysfunctions. Notably, pathological mechanisms of Alzheimer's disease (AD) appear involved in both conditions. Insulin resistance has been reported to be a risk factor for AD, leading to neurodegeneration and cognitive impairment by affecting amyloid-beta (Aβ) metabolism, tau phosphorylation, and neuro-inflammation. Thus, insulin resistance may provide pathophysiological clues to the occurrence of delirium. To investigate the relationship between preoperative insulin resistance, insulin concentrations in the cerebrospinal fluid (CSF), and delirium in elderly patients with hip fracture. The study included 138 elderly patients with or without pre-existing dementia who underwent hip fracture surgery. Delirium was diagnosed with the confusion assessment method performed daily from pre-operation to 5days post-operation. CSF and blood samples were collected at the beginning of spinal anesthesia. The concentrations of insulin, amyloid-beta1-42 (Aβ42), total tau (t-tau), and phosphorylated tau (p-tau)181 were determined by ELISA. Homeostasis model assessment (HOMA-IR) was used to assess insulin resistance. Sixty-one (44%) of 138 hip fracture patients developed delirium peri-operatively. Compared to non-delirium group, the preoperative HOMA-IR index in delirium was much higher (median 3.3 vs 2.8, p = 0.001), but the CSF insulin concentration was significantly decreased (median 1.5 vs 2.2mU/L, p < 0.001). Binary logistic regression analysis showed that HOMA-IR index and CSF insulin concentration were independent risk factors for delirium (p < 0.05). HOMA-IR index was negatively correlated with CSF insulin concentrations (rho = - 0.55, p < 0.001). Multiple linear regression analysis showed that AD core biomarkers were significantly correlated with HOMA-IR index and CSF insulin level (p < 0.05). This study innovatively examined insulin concentrations in serum and cerebrospinal fluid in patients with delirium. Our findings suggest that preoperative insulin resistance may affect the occurrence of delirium. The potential association between insulin resistance and delirium may be related to insulin resistance affecting the metabolism of AD biomarkers.

Identifying hormones and other perioperative risk factors for postoperative delirium after endoscope-assisted transsphenoidal pituitary adenoma resection: A retrospective, matched cohort study.

As a complex and acute brain dysfunction, if postoperative delirium (POD) occurs in the postoperative period, it will lead to a prolonged length of stay in the critical care unit, with increased hospitalization costs and higher mortality. A few case reports inspired us to pay close attention to pituitary tumor-associated delirium. We hypothesized that the changes in hormone levels after pituitary tumor resection might be associated with POD occurrence. Retrospective analysis was performed on data from a single-center cohort study conducted at Southwest Hospital between January 2018 and May 2022. A total of 360 patients with pituitary tumors who underwent endoscope-assisted transsphenoidal pituitary tumor resection were divided into two groups at a 1:3 ratio, with 36 patients in the POD group and 108 patients in the non-POD group matched by propensity score, age, sex, and tumor size. Basic characteristics, pituitary adenoma features, endocrine levels and other biochemical indicators, and Confusion Assessment Method for the Intensive Care Unit (CAM-ICU) for postoperative delirium were documented for further analysis. Lower insulin-like growth factor-1 (IGF-1, p=.024) and corticotropin-releasing hormone (CRH, p=.005) levels were closely associated with postoperative delirium and with high levels of blood glucose (GLU, p=.023) after surgery. Subsequent analysis indicated that serum potassium (OR: 0.311, 95% CI 0.103-0.935), sodium (OR: 0.991, 95% CI 0.983-1.000), CRH (OR: 0.964, 95% CI 0.936-0.994), and GLU (OR: 1.654, 95% CI 1.137-2.406) levels in the perioperative period were independent risk factors for delirium. Our study indicated that lower serum CRH, potassium, sodium, and GLU levels may be associated with the occurrence of POD after endoscopic-assisted transsphenoidal surgery. These data provide preliminary evidence for the management of POD in pituitary adenoma patients after surgery. Further studies are needed to identify pharmacological and nonpharmacological multicomponent treatment strategies.

Risk Factors and Prognosis of Delirium After Liver Transplantation

To analyze the incidence, the onset time, and the risk factors of delirium after liver transplantation (LT). The clinical data of 211 patients who underwent LT at Third Xiangya Hospital, Central South University between January 2019 and December 2021 were collected to investigate the incidence and the onset time of postoperative delirium. Univariate analysis and multivariate logistic regression analysis were conducted to analyze the risk factors of delirium and to analyze the effect of delirium on clinical outcomes. The incidence of delirium was 20.4% (43/211) and the median interval between LT and the onset of delirium was 19 hours. Univariate analysis showed that the preoperative Model for End-Stage Liver Disease (MELD) score≥22, preoperative length-of-stay≥7, liver cancer, preoperative hepatic encephalopathy, infections within 2 months before LT, preoperative lymphocyte value<0.5×10 9 L －1, massive amount of intraoperative red blood cell infusion, and carbapenem antibiotics use for 3 days or longer were associated with postoperative delirium. Multivariate logistic regression analysis showed that preoperative infections within 2 months before LT (odds ratio [ OR]=2.597, 95% confidence interval [ CI]: 1.135-5.944, P=0.024), preoperative MELD score≥22 ( OR=2.967, 95% CI: 1.104-7.975, P=0.031), and preoperative hepatic encephalopathy ( OR=4.700, 95% CI: 2.043-10.602, P<0.001) were independent risk factors for delirium after LT, while carbapenems antibiotics use for 3 days or longer ( OR=0.192, 95% CI: 0.083-0.441, P<0.001) was a protective factor for postoperative delirium among LT recipients. Regarding clinical outcomes, patients with delirium had longer postoperative ICU length-of-stays than those without delirium did ( P=0.025). There is a high incidence of postoperative delirium among patients who undergo LT and the onset time of delirium after LT is early. Risk factors include preoperative infections, high MELD score, and hepatic encephalopathy. On the other hand, the use of carbapenems can help prevent delirium.

Risk Factors for Delirium Superimposed on Dementia in Elderly Patients in Comprehensive Ward.

To investigate the incidence of delirium and its related risk factors in patients with senile dementia during hospitalization. A retrospective analysis of clinical data of 157 patients over 65 with cognitive impairment who were hospitalized in the comprehensive ward from October 2019 to February 2023 was conducted. Patients were assigned into delirium and non-delirium groups according to whether they exhibited delirium during hospitalization. General information about the patients and Visual Analogue Scale (VAS) score, blood C-reactive protein level, and blood superoxide dismutase (SOD) level were recorded. Univariate analysis was used to identify potential risk factors for delirium, and factors with statistical significance were subjected to multivariate logistic regression analysis. A prediction line chart for delirium in elderly dementia patients was constructed using R 4.03 software, and the model was validated. Among the 157 patients with senile dementia, 42 patients exhibited delirium and 115 patients exhibited non-delirium. Multivariate logistic regression analysis showed that diabetes, cerebrovascular disease, VAS score ≥4 points, use of sedative drugs, and blood SOD <129 U/mL were independent risk factors for delirium during hospitalization in elderly dementia patients. A prediction nomogram was plotted based on the five risk factors, and receiver operating characteristic curve analysis presented an area under the curve of .875 (95% CI: .816-.934). The nomogram model was internally validated by the Bootstrap method, and the calibration curve showed good agreement between predicted and actual results. Hosmer-Lemeshow test demonstrated that the model had a good fit and high predictive ability. Diabetes, cerebrovascular disease, VAS ≥4 points, use of sedative drugs, and blood SOD <129 U/mL were independent risk factors for delirium in patients with senile dementia during hospitalization. The nomogram model had good accuracy and clinical application value for predicting delirium in this study.

Relationship between body mass index and risk of delirium in an intensive care unit

ObjectiveDelirium in the intensive care unit (ICU) is a common and critical condition that leads to poor prognosis in older patients, but the association between body mass index (BMI) and the incidence of delirium remains unclear. MethodsWe retrospectively analyzed 5,622 patients admitted to the ICU of a tertiary referral hospital between 2013 and 2022. We collected sociodemographic data, vital signs, laboratory results, and delirium scale scores. We subdivided the patients into four categories: underweight (<18.5 kg/m2), normal weight (18.5–22.9 kg/m2), overweight (23–24.9 kg/m2), and obese (>25 kg/m2). The primary outcome was the incidence of delirium according to the BMI categories. We performed multivariable logistic regression analysis, adjusted for sex, age, past smoking and alcohol history, benzodiazepine use, and laboratory abnormalities. ResultsAmong the 5,622 patients in the ICU (mean age, 72.9 years; male, 60.1%; mean BMI, 24.2 kg/m2), the incidence of delirium was 19.0% (1,069 patients). The mean modified incidence of delirium was higher among underweight patients (odds ratio [OR]=1.51, confidence interval [CI]=1.07–2.12, p = 0.02) than among normal-weight patients. Overweight and obese status were not independently associated with delirium (OR=0.90, CI=0.70–1.17, p = 0.43; OR= 0.97; CI=0.77–1.21, p = 0.78, respectively). The area under the receiver-operating characteristic curve of the multivariable logistic regression model was 0.71 (95% CI=0.69–0.73). ConclusionsUnderweight status is an independent risk factor for delirium in the ICU. Additional caution is required when evaluating underweight patients for delirium. Obese or overweight status are not associated with delirium, providing evidence for the obesity paradox.

Risk Factors for Delirium after Deep Brain Stimulation Surgery under Total Intravenous Anesthesia in Parkinson's Disease Patients.

Postoperative delirium (POD) is associated with perioperative complications and mortality. Data on the risk factors for delirium after subthalamic nucleus deep brain stimulation (STN-DBS) surgery is not clarified in Parkinson's disease (PD) patients receiving total intravenous anesthesia. We aimed to investigate the risk factors for delirium after STN-DBS surgery in PD patients. The retrospective cohort study was conducted, including 131 PD patients who underwent STN-DBS for the first time under total intravenous anesthesia from January to December 2021. Delirium assessments were performed twice daily for 7 days after surgery or until hospital discharge using the confusion assessment method for the intensive care unit. Multivariate logistic regression analysis was used to determine the risk factor of POD. In total, 22 (16.8%) of 131 patients were in the POD group, while the other 109 patients were in the Non-POD group. Multivariate logistic regression analysis showed that preoperative Mini-mental State Examination score [odds ratio = 0.855, 95% confidence interval = 0.768-0.951, p = 0.004] and unified Parkinson's disease rating scale part 3 (on state) score (odds ratio = 1.061, 95% confidence interval = 1.02-1.104, p = 0.003) were independently associated with delirium after surgery. In this retrospective cohort study of PD patients, a lower Mini-mental State Examination score and a higher unified Parkinson's disease rating scale part 3 (on state) score were the independent risk factors for delirium after STN-DBS surgery in PD patients under total intravenous anesthesia.

Early alteration of peripheral blood lymphocyte subsets as a risk factor for delirium in critically ill patients after cardiac surgery: A prospective observational study.

ObjectiveThere is a high incidence of delirium among patients with organ dysfunction undergoing cardiac surgery who need critical care. This study aimed to explore the risk factors for delirium in critically ill patients undergoing cardiac surgery and the predictive value of related risk factors.MethodsWe conducted a prospective observational study on adult critically ill patients who underwent cardiac surgery between January 2019 and August 2021. Patients were consecutively assigned to delirium and non-delirium groups. Univariate analysis and multivariate logistic analysis were used to determine the risk factors for delirium. Receiver operating characteristic curves and a nomogram were used to identify the predictive value of related risk factors.ResultsDelirium developed in 242 of 379 (63.9%) participants. Acute Physiology and Chronic Health Evaluation II (APACHE II) and Sequential Organ Failure Assessment (SOFA) scores were 14.2 ± 5.6 and 18 ± 8.4, respectively. Patients with delirium had longer cardiopulmonary bypass time (149.6 ± 59.1 vs. 126.7 ± 48.5 min, p < 0.001) and aortic cross-clamp time (98.7 ± 51.5 vs. 86.1 ± 41.6 min, p = 0.010) compared with the non-delirium group. The area under the curve was 0.824 for CD4+ T cell count and 0.862 for CD4/CD8 ratio. Multivariate analysis demonstrated that age [odds ratio (OR) 1.030, p = 0.038], duration of physical restraint (OR 1.030, p < 0.001), interleukin-6 (OR 1.001, p = 0.025), CD19+ B cell count (OR 0.996, p = 0.016), CD4+ T cell count (OR 1.005, p < 0.001) and CD4/CD8 ratio (OR 5.314, p < 0.001) were independent risk factors for delirium. A nomogram revealed that age, cardiopulmonary bypass duration, CD4+ T cell count and CD4/CD8 ratio were independent predictors of delirium.ConclusionAge, duration of physical restraint, CD4+ T cell count and CD4/CD8 ratio were reliable factors for predicting delirium in critically ill patients after cardiac surgery. The receiver operating characteristic curves and nomogram suggested a potential role for CD4+ T cells in mediating potential neuroinflammation of delirium.

Risk factors for delirium after surgery for craniocerebral injury in the neurosurgical intensive care unit

BACKGROUNDPostoperative delirium is common in patients who undergo neurosurgery for craniocerebral injury. However, there is no specific medical test to predict postoperative delirium to date.AIMTo explore risk factors for postoperative delirium in patients with craniocerebral injury in the neurosurgery intensive care unit (ICU). METHODSA retrospective analysis was performed in 120 patients with craniocerebral injury admitted to Hainan People’s Hospital/Hainan Hospital Affiliated to Hainan Medical University, The First Affiliated Hospital of Hainan Medical University, and The Second Affiliated Hospital of Hainan Medical University between January 2018 and January 2020. The patients were categorized into groups based on whether delirium occurred. Of them, 25 patients with delirium were included in the delirium group, and 95 patients without delirium were included in the observation group. Logistic regression analysis was used to explore the association between sex, age, educational level, Glasgow coma scale (GCS), complications (with or without concussion, cerebral contusion, hypoxemia and ventricular compression) and site of injury and delirium. RESULTSThe GCS score above 8 and concomitant disease of cerebral concussion, cerebral contusion, hypoxemia and ventricular compression, and damage to the frontal lobe were associated with delirium in patients admitted to neurosurgical intensive care unit (ICU) (all P < 0.05). However, age, sex, administration more than three medicines, and educational level were not significantly associated with the onset of delirium in patients with craniocerebral injury in the neurosurgical ICU (P < 0.05). Multivariate logistic regression analysis showed that GCS score above 8, cerebral concussion, cerebral contusion, hypoxemia, ventricle compression, and frontal lobe disorders were independent risk factors for delirium in patients with craniocerebral injury in the neurosurgical ICU (P < 0.05).CONCLUSIONGCS score, concussive concussion, cerebral contusion, hypoxemia, ventricle compression, and damage to frontal lobe are risk factors of postoperative delirium.

Risk factors of delirium in paediatric intensive care units: A meta-analysis.

BackgroundDelirium is a brain dysfunction syndrome, which children have a higher incidence. At present, there have been more and more studies and reports on delirium in paediatric intensive care unit, but there are some differences in the risk factor results among different studies. To better manage delirium, this study was performed.ObjectiveTo integrate and clarify the risk factors for delirium in paediatric intensive care unit.MethodsCNKI, CBMdisc, Wanfang Data Knowledge Service Platform, VIP, PubMed, Embase, Cochrane Library, JBI and PsycInfo were searched for relevant literature. The study subjects were patients in PICU and literature was included according to the PICOS principle. Literature screening and risk of bias assessment were mainly completed by two researchers, and RevMan 5.3 software and Stata software were used for data analysis. The GRADE systerm was used to assess the quality of evidence.ResultsA total of 10 studies were included, all in English, involving 4343 children. Within the GRADE system, 4 indicators were scored A, 1 indicators were scored B, and 3 indicators were scored C regarding evidence levels. Three studies analysed the influence of developmental delay on the occurrence of delirium in PICU, total sample size of which was 1823, and the results showed that the combined effect was statistically significant [OR = 3.34, 95%CI(2.46–4.53), Z = 7.75, P<0.001]; Five studies analysed the effects of mechanical ventilation on the occurrence of delirium in PICU, sample size of which was 1562, and the results showed that the combined effect was statistically significant [OR = 4.11, 95%CI(3.13–5.40), Z = 10.16, P<0.001]; Two studies analysed the effects of benzodiazepines on children developing delirium, sample size of which was 1635, and the results showed that the combined effect was statistically significant [OR = 5.05, 95%CI(3.65–6.97), Z = 9.83, P<0.001]; Two studies analysed the effects of anticholinergic drug use on children developing delirium in PICU, sample size of which was 1703, and the results suggested the combined effect was statistically significant [OR = 5.04, 95%CI (3.62–7.00), Z = 9.63, P<0.001]; Two studies compared the same age period, sample size of which was 1724 and the results showed that children 2–5 years old has a 48% incidence rate of delirium relative to children younger than 2 years old, and the combined effect was statistically significant [OR = 0.48, 95%CI(0.25–0.92), Z = 2.22, P = 0.030], children 5–13 years old has a 39% incidence rate of delirium relative to children younger than 2 years old, and the combined effect was statistically significant [OR = 0.39, 95%CI(0.26–0.59), Z = 4.43, P<0.001]. Two studies analysed the effects of PICU LOS on children developing delirium and the combined effect of PICU LOS on the occurrence of delirium in children in PICU was statistically significant [OR = 1.10, 95%CI(1.05–1.15), Z = 4.07, P<0.001].ConclusionDevelopmental delay, mechanical ventilation, benzodiazepine use, anticholinergic use, age and PICU length of stay are independent risk factors for delirium in children in PICU. However, only a few articles were included in this study, which may lead to a certain bias and affect the analysing results. More large-sample, multicentre studies should be conducted to further explore and clarify the independent influencing factors of delirium in children in PICU and to provide guidance for clinical practice.