Delirium In Intensive Care Unit Patients Research Articles

Intensive care nurses' perceptions and awareness of delirium and delirium prevention guidelines.

Delirium is an acute and fluctuating disturbance of cognition and is a common occurrence in critically ill patients. It is a manifestation of an acute brain dysfunction often attributed to higher survival rates and a subsequently aging population. Intensive Care Unit (ICU) treatment and survival often contributes towards development of delirium, and lack of or inappropriate management can translate into the development of long-term psychological effects that last even after discharge. While a lot is already known about this topic, and several assessment tools exist, these are not being consistently used by ICU nurses and as a result delirium often goes unrecognized, with unwarranted consequences. The study aimed to explore the perception of delirium among ICU nurses, and the extent of their awareness about guidelines to assess and prevent delirium in ICU patients. It also sought to understand the application of delirium guidelines in ICU practice. A quantitative, exploratory, self-reporting survey was conducted among 145 ICU nurses from one critical care unit in the Republic of Ireland. The overall response rate was 71% (103/145). Most nurses (85%) who participated in this survey believed delirium was expected. However, only 45% acknowledged it is a complication. Only 31% of nurses monitored delirium using a validated scale and few observed this as a part of routine care. Most nurses had received education; however, this did not translate to their clinical practice. Guidelines on managing delirium may not be routinely implemented in the ICU settings of hospitals in the Republic of Ireland. As the findings suggest, a gap exists between theory and practice, necessary revision of policy or creating a new policy, supplemental educational sessions such as bedside sessions, e-learning module, study day or seminars need to be organized to improve nurses' awareness related to delirium and delirium prevention guidelines.

Restrictive use of Restraints and Delirium Duration in the Intensive Care Unit (R2D2-ICU): protocol for a French multicentre parallel-group open-label randomised controlled trial

IntroductionPhysical restraint (PR) is prescribed in patients receiving invasive mechanical ventilation in the intensive care unit (ICU) to avoid unplanned removal of medical devices. However, it is associated with an...

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

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

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.

Does ICU admission dysphagia independently contribute to delirium risk in ischemic stroke patients? Results from a cohort study

BackgroundDelirium is prevalent in ischemic stroke patients, particularly those in the intensive care unit (ICU), and it poses a significant burden on patients and caregivers, leading to increased mortality rates, prolonged hospital stays, and impaired cognitive function. Dysphagia, a common symptom in critically ill patients with ischemic stroke, further complicates their condition. However, the association between dysphagia and delirium in this context remains unclear. The objective of this study was to investigate the correlation between dysphagia and delirium in ICU patients with ischemic stroke.MethodsA retrospective analysis was conducted on adult patients diagnosed with ischemic stroke at a medical center in Boston. Ischemic stroke cases were identified using the ninth and tenth revisions of the International Classification of Diseases. Dysphagia was defined as a positive bedside swallowing screen performed by medical staff on the day of ICU admission, while delirium was assessed using the ICU Confusion Assessment Method and review of nursing notes. Logistic regression models were used to explore the association between dysphagia and delirium. Causal mediation analysis was employed to identify potential mediating variables.ResultsThe study comprised 1838 participants, with a median age of approximately 70 years, and 50.5% were female. Among the total study population, the prevalence of delirium was 43.4%, with a higher prevalence observed in the dysphagia group (60.7% vs. 40.8%, p < 0.001) compared to the non-dysphagia group. After adjusting for confounding factors including age, sex, race, dementia, depression, sedative medications, history of falls, visual or hearing deficit, sequential organ failure score, and Glasgow coma score, multifactorial logistic regression analysis demonstrated a significant association between dysphagia and an increased likelihood of delirium (odds ratio [OR]: 1.48; 95% confidence interval [CI]: 1.07–2.05; p = 0.018; E-value = 1.73). Causal mediation analysis revealed that serum albumin levels partially mediated the association between dysphagia and delirium in critically ill patients with ischemic stroke (average causal mediated effect [ACME]: 0.02, 95% CI: 0.01 to 0.03; p < 0.001).ConclusionICU admission dysphagia may independently contribute to the risk of delirium in patients with ischemic stroke. Early identification and intervention in ischemic stroke patients with dysphagia may help mitigate the risk of delirium and improve patient prognosis.

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.

Assessing the impact of creating virtual windows on the incidence of delirium in a surgical intensive care unit: a before and after study

Introduction: Delirium is a frequent and important problem in the intensive care unit (ICU), and non-pharmacological means of prevention are limited. The importance of the physical environment in the occurrence of delirium in intensive care has been reported, particularly the presence of windows and daylight. We organized a trial to evaluate if the installation of virtual windows in the form of paintings in rooms without an actual window can limit the occurrence of delirium in ICU patients. Methods: We conducted a retrospective pre and post cohort study in a surgical ICU of a university-affiliated hospital. Patients residing for more than 48 hours in a windowless room before and after the installation of virtual windows were included in the trial. The primary endpoint was the incidence of a positive screening test for delirium during their time in the ICU. The Intensive Care Delirium Screening Checklist (ICDSC) was used as an objective screening tool to assess the occurrence of delirium. Results: A total of 400 patients were included in this trial (pre group: n = 200; post group: n = 200). The groups were well balanced except for the score APACHE II who was significantly higher in the post intervention group. The incidence of a positive screening test for delirium was similar in both groups after correction for confounding factors (29% vs 27%; OR 0,906 [0,584-1,402], p=0,656). Conclusion: The installation of virtual windows did not reduce the incidence of delirium in a surgical intensive care unit. Keywords Critical care, delirium, windows, prevention, circadian cycle.

Calibration of the PREdiction of DELIRium in ICu Patients (PRE-DELIRIC) Score in a Cohort of Critically Ill Patients: A Retrospective Cohort Study.

To predict delirium in intensive care unit (ICU) patients, the Prediction of Delirium in ICU Patients (PRE-DELIRIC) score may be used. This model may help nurses to predict delirium in high-risk ICU patients. The aims of this study were to externally validate the PRE-DELIRIC model and to identify predictive factors and outcomes for ICU delirium. All patients underwent delirium risk assessment by the PRE-DELIRIC model at admission. We used the Intensive Care Delirium Screening Check List to identify patients with delirium. The receiver operating characteristic curve measured discrimination capacity among patients with or without ICU delirium. Calibration ability was determined by slope and intercept. The prevalence of ICU delirium was 55.8%. Discrimination capacity (Intensive Care Delirium Screening Check List score ≥4) expressed by the area under the receiver operating characteristic curve was 0.81 (95% confidence interval, 0.75-0.88), whereas sensitivity was 91.3% and specificity was 64.4%. The best cut-off was 27%, obtained by the max Youden index. Calibration of the model was adequate, with a slope of 1.03 and intercept of 8.14. The onset of ICU delirium was associated with an increase in ICU length of stay (P < .0001), higher ICU mortality (P = .008), increased duration of mechanical ventilation (P < .0001), and more prolonged respiratory weaning (P < .0001) compared with patients without delirium. The PRE-DELIRIC score is a sensitive measure that may be useful in early detection of patients at high risk for developing delirium. The baseline PRE-DELIRIC score could be useful to trigger use of standardized protocols, including nonpharmacologic interventions.

Circadian rhythm disturbance and delirium in ICU patients: a prospective cohort study

BackgroundPatients treated in the intensive care unit (ICU) may experience a reversal of day and night. The circadian rhythm in ICU patients can be disturbed.MethodsTo explore the relationship between ICU delirium and the circadian rhythms of melatonin, cortisol and sleep. A prospective cohort study was carried out in a surgical ICU of a tertiary teaching hospital. Patients who were conscious during the ICU stay after surgery and were scheduled to stay in the ICU for more than 24 h were enrolled. Serum melatonin and plasma cortisol levels were measured three times a day by drawing arterial blood on the first three days after ICU admission. Daily sleep quality was assessed by the Richard-Campbell Sleep Questionnaire (RCSQ). The Confusion Assessment Method for the Intensive Care Unit (CAM-ICU) was performed twice a day to screen for ICU delirium.ResultsA total of 76 patients were included in this study, and 17 patients developed delirium during their ICU stay. Melatonin levels were different at 8:00 (p = 0.048) on day 1, at 3:00 (p = 0.002) and at 8:00 (p = 0.009) on day 2, and at all three time points on day 3 (p = 0.032, 0.014, 0.047) between delirium and non-delirium patients. The plasma cortisol level in the delirium patients was significantly lower than that in the non-delirium patients at 16:00 on day 1 (p = 0.025). The changes in melatonin and cortisol secretion levels exhibited obvious biological rhythmicity in non-delirium patients (p < 0.001 for melatonin, p = 0.026 for cortisol), while no rhythmicity was found in melatonin and cortisol secretion levels in the delirium group (p = 0.064 for melatonin, p = 0.454 for cortisol). There was no significant difference in RCSQ scores in the first three days between the two groups.ConclusionsThe disturbance of the circadian rhythm of melatonin and cortisol secretion was associated with the development of delirium in ICU patients. Clinical staff should pay more attention to the importance of maintaining patients’ normal circadian rhythms in the ICU.Trial registrationThe study was registered with the US National Institutes of Health ClinicalTrials.gov(NCT05342987) (25/04/2022).

Factors Affecting Delirium in ICU Patients.

This study examined delirium severity using a delirium screening tool and analyzed the predictors, including pain, acuity, level of consciousness, fall risk, and pain score, to increase understanding of delirium and present foundational data for developing nursing interventions for delirium prevention. This was a retrospective study of 165 patients admitted to three intensive care units (ICUs). the Nursing Delirium Screening Scale (Nu-DESC) was used as a research tool to screen for delirium and measure the degree of delirium. The incidence of delirium in patients was 53.3%, and the average delirium score in the delirium group was 2.40 ± 0.56. Nu-DESC scores were significantly correlated with ICU days, ventilator days, restraint applications, the number of catheters inserted, sedative medication use, the Simplified Acute Physiology Score (SAPS III), the Morse Fall Scale (MFS), the Glasgow Coma Scale (GCS) scores, pain scores, and blood urea nitrogen (BUN). Stepwise multiple linear regression showed that the number of restraint applications, GCS score, ICU days, and BUN levels were factors influencing delirium. Based on the findings, ICU nurses should use delirium screening tools to ensure accurate delirium screening and work to reduce the incidence and degree of delirium by observing factors affecting delirium in patients.

Deficient vitamin B12 levels are associated with increased delirium incidence in critically ill patients

In intensive care unit (ICU) patients, deficiency of vitamin B12 (cobalamin) occur often and may be associated with significant neurologic syndromes. Therefore, this study aimed to investigate the association between cobalamin (cbl) serum levels and the incidence of delirium in ICU patients. In this multi-center, cross-sectional clinical study, adult patients with GCS (Glasgow Coma Scale)≥8 and RASS (The Richmond Agitation-Sedation Scale)≥-3, without a history of mood disorders before ICU admission, were eligible for inclusion. After informed consent was obtained, clinical and biochemical characteristics of eligible patients were recorded on the first day and then daily during follow-up for seven days or until delirium was developed. The CAM-ICU tool was used to evaluate delirium. Moreover, the cbl level was measured at the end of the study to assess its association with the incidence of delirium. Among 560 patients screened for eligibility, 152 could be analyzed. Logistic regression results indicated a high cbl level (>900pg/ml) was independently associated with lower delirium incidence (P<0.001). Further analysis revealed that the delirium rate was significantly higher in patients with deficient and sufficient cbl compared to the high cbl group (P=0.002 and 0.017, respectively). In addition, surgical and medical patients and pre-deliric scores were negatively associated with high cbl (P=0.006, 0.003, and 0.031, respectively). We have shown that deficient and sufficient compared to the high cbl group were significantly associated with a higher delirium incidence in critically ill patients. Further controlled clinical studies are required to evaluate the safety and efficacy of high-dose cbl to prevent delirium in critically ill patients.

Delirium in the intensive care unit: a narrative review

Critically ill patients frequently suffer from various acute organ dysfunctions. The most common clinical manifestation of central nervous system dysfunction defined as acute encephalopathy is delirium. Since delirium in intensive care unit (ICU) patients has been associated with worse outcomes, its early diagnosis, prevention, and appropriate treatments are strongly recommended. The PADIS guidelines recommend routine monitoring of delirium with the CAM-ICU or ICDSC, which should be performed at least once during each nursing shift and whenever patients show a change in the level of consciousness. Neuroimaging is useful for studying the pathophysiology of delirium, and it might be helpful in the differential diagnosis, although various and non-specific patterns can be observed in both MRI and functional MRI. Also, the electroencephalogram (EEG) showed different non-specific patterns associated with delirium and its role in the differential diagnosis of neurological complications of the critical patient is still uncertain. This narrative review presents the epidemiology and risk factors of delirium in ICU patients, the different diagnostic tools and procedures useful for its early detection, and the pharmacological and non-pharmacological treatments required for its management.

The Impact of a Pharmacist-Driven Multicomponent Sleep-Promoting Protocol on Delirium in Critically Ill Patients

Background: Sleep deprivation is reported in 80% of patients in the intensive care unit (ICU) and is associated with delirium. Guidelines recommend implementing a sleep-promoting protocol in critically ill patients which may increase the quantity and quality of sleep and may decrease delirium. Our objective was to implement a pharmacist-led interdisciplinary sleep-promoting protocol and analyze its impact on delirium in ICU patients receiving mechanical ventilation (MV). Methods: The study involved pre-implementation education, protocol development, and post-implementation analysis. ICU pharmacists completed prospective patient chart reviews to reduce exposure to deliriogenic medications and assess the need for a pharmacologic sleep aid. The primary outcome was the incidence of delirium and delirium-free days. Secondary outcomes included ICU length of stay (LOS), incidence of MV, and pharmacist medication interventions. Results: Post-protocol patients (n = 185) had a higher incidence of delirium compared to pre-protocol patients (n = 237) (51.3% vs 39.0%; P = .01). Post-protocol patients had a higher average APACHE III score (P = <.001). Delirium-free days were not significantly different between groups (P = .97). Difference in ICU LOS was not significant (P = .80). More patients received MV post-protocol implementation (55.7% vs 36.1%; P < .001). Pharmacists documented a total of 113 medication interventions. Conclusion and Relevance: A pharmacist-led, ICU sleep-promoting protocol was successfully implemented but did not reduce the incidence of delirium or the administration of insomnia agents. Post-protocol patients had higher disease severity and were more likely to receive MV. Incidence of delirium was consistent with the national reported prevalence of ICU delirium. ICU pharmacists on all shifts had an active role in optimizing sleep.

Discussion Guide for the van Nieuw Amerongen Article.

Discussion Guide for the van Nieuw Amerongen Article.

Incidence, prevalence and risk factors of delirium in ICU patients: A systematic review and meta‐analysis

AbstractBackgroundDelirium is one of the most common problems in intensive care units (ICU), and it has a detrimental influence on the patients' health. Estimating the prevalence of delirium in ICU patients and understanding the risk factors for delirium are crucial tasks.AimTo offer empirical support for early detection of the risk of delirium in ICU patients, we conducted a systematic review and meta‐analysis to analyse the incidence, prevalence and risk factors of delirium in ICU patients.Study DesignFrom inception to 19th December 2021, PubMed, Embase, Cochrane Library, Web of Science, China Knowledge Resource Integrated Database (CNKI), Wanfang Database, Chinese Biomedical Database (CBM) and Weipu Database (VIP) were searched for inclusion to the study. The quality of the included studies was assessed by two investigators independently. The outcomes of the meta‐analysis, which was conducted using the Stata 12.0 software, were reported using odds ratios (OR) and 95 percent confidence intervals (CI). Heterogeneity was determined using the I2 statistic.ResultsIn this meta‐analysis, 51 studies with a total of 39 076 patients were evaluated. The incidence and prevalence of delirium in ICU patients were 31 per 1000 and 33%, respectively. A total of 28 risk factors were identified. Of these 28 risk factors, the top five modifiable risk factors were pain (OR = 19.74, 95% CI [8.86–30.61]), use of physical restraints (OR = 15.46, 95% CI [3.68–27.25]), respiratory diseases (OR = 14.3, 95% CaI [8.42–20.19]), sleep deprivation (OR = 9.4, 95% CI [6.8–12.1]) and surgery (OR = 8.98, 95% CI [7–15.27]). Non‐modifiable risk factors included age (OR = 1.06, 95% CI[1.04, 1.07]) and gender (OR = 1.45, 95% CI[1.13, 1.77]). Of these 51 studies included in this analysis, 30 studies were shown with a low risk of bias while 21 studies were shown with a moderate risk of bias. Our results also demonstrated that 21 studies and 30 studies with intermediate methodological quality and low methodological quality respectively.ConclusionDelirium was shown to be prevalent among ICU patients. There are 28 risk factors for delirium that we discovered. These risk factors can assist physicians, nurses and other health care professionals prevent delirium in ICU patients.Relevance to practiceDelirium in ICU patients can potentially be prevented through appropriate prevention strategies by intensive care staff.

Prophylactic melatonin for delirium in critically ill patients: A systematic review and meta-analysis with trial sequential analysis.

Up to 80% of patients in the intensive care unit (ICU) suffer from delirium. Studies on the preventative use of melatonin in the ICU have produced mixed results. We performed a systematic review and meta-analysis to evaluate whether early administration of melatonin reduces the prevalence of delirium in critically ill patients. We searched Medline, Embase, and the Cochrane Library for randomized controlled trials comparing melatonin or melatonin agonists to placebo in ICU setting. The population included adult patients in the ICU. The primary outcome was the prevalence of delirium. Secondary outcomes included duration of delirium, delirium-free day, serum melatonin concentration, need for sedation, duration of mechanical ventilation, hospital and ICU length of stay (LOS), all-cause mortality, sleep quality, and adverse events. Trial sequential analysis (TSA) was performed on the primary outcome to prevent the risk of random error and multiplicity phenomenon as a result of repeated significance testing across all the included trials. Twelve trials with a total of 2538 patients were analyzed. When all trials were pooled, the incidence of delirium in ICU patients who received melatonin was significantly lower than in those who received placebo (risk ratio, 0.77; 95% confidence interval: 0.61-0.96; I2 = 56%). There were no significant differences in secondary outcomes including duration of delirium, duration of mechanical ventilation, ICU LOS, hospital LOS, and mortality. TSA indicated that Z-curve crossed the traditional boundary, but did not cross the monitoring boundary for benefit, which indicated that it is still inconclusive that melatonin affects the incidence of delirium. This meta-analysis found that early administration of melatonin may result in a decreased delirium prevalence in critically ill patients. However, the sensitivity analysis of high-quality studies did not support this finding. In addition, TSA demonstrated that the result may have false-positive error. Therefore, this finding should be interpreted with caution. Further studies are needed to examine the effectiveness of prophylactic melatonin on the prevalence and duration of ICU delirium in the future.

Haloperidol for the Treatment of Delirium in ICU Patients

BackgroundHaloperidol is frequently used to treat delirium in patients in the intensive care unit (ICU), but evidence of its effect is limited.MethodsIn this multicenter, blinded, placebo-controlled trial, we randomly assigned adult patients with delirium who had been admitted to the ICU for an acute condition to receive intravenous haloperidol (2.5 mg 3 times daily plus 2.5 mg as needed up to a total maximum daily dose of 20 mg) or placebo. Haloperidol or placebo was administered in the ICU for as long as delirium continued and as needed for recurrences. The primary outcome was the number of days alive and out of the hospital at 90 days after randomization.ResultsA total of 1000 patients underwent randomization; 510 were assigned to the haloperidol group and 490 to the placebo group. Among these patients, 987 (98.7%) were included in the final analyses (501 in the haloperidol group and 486 in the placebo group). Primary outcome data were available for 963 patients (97.6%). At 90 days, the mean number of days alive and out of the hospital was 35.8 (95% confidence interval [CI], 32.9 to 38.6) in the haloperidol group and 32.9 (95% CI, 29.9 to 35.8) in the placebo group, with an adjusted mean difference of 2.9 days (95% CI, −1.2 to 7.0) (P=0.22). Mortality at 90 days was 36.3% in the haloperidol group and 43.3% in the placebo group (adjusted absolute difference, −6.9 percentage points [95% CI, −13.0 to −0.6]). Serious adverse reactions occurred in 11 patients in the haloperidol group and in 9 patients in the placebo group.ConclusionsAmong patients in the ICU with delirium, treatment with haloperidol did not lead to a significantly greater number of days alive and out of the hospital at 90 days than placebo. (Funded by Innovation Fund Denmark and others; AID-ICU ClinicalTrials.gov number, NCT03392376; EudraCT number, 2017-003829-15.)

Relationship between PaO2/FiO2 and delirium in intensive care: A cross-sectional study

BackgroundTo investigate the relationship between partial pressure of oxygen (PaO2)/fraction of inspired oxygen (FiO2) and the probability of delirium in intensive care units (ICUs). MethodsThe investigation was a cross-sectional study that involved the collection of data from patients admitted to the Xiang Ya Hospital Cardiothoracic Surgical Care Unit and Comprehensive Intensive Care Unit from 01 September 2016 to 10 December 2016. Delirium was diagnosed using the simplified version of the Chinese Confusion Assessment Method (CAM) for the ICU. Demographic and medical data were obtained within 24 h of each patient admitted in the ICU. The PaO2/FiO2 of each patient was recorded 24 h after admission in the ICU. The patients were divided into three groups according to PaO2/FiO2 data : normal (PaO2/FiO2 ≥300 mmHg), slightly low (200 ≥PaO2/FiO2 <300 mmHg), and severely low (PaO2/FiO2 <200 mmHg). Baseline characteristics were compared in the three groups. Results of the unadjusted model, minimally adjusted model, and fully adjusted model are presented. ResultsA total of 403 participants were included in the study, of which 184 (45.7%) developed delirium. Age (P <0.001), Sequential Organ Failure Assessment (SOFA) score (P <0.001), Acute Physiology and Chronic Health Evaluation (APACHE) II score (P <0.001), mechanical ventilation time (P <0.001), history of hypertension (P=0.040), heart disease (P=0.040), sedation (P=0.001), and PaO2/FiO2 (P=0.006) were significantly associated with delirium in univariate analysis. Multivariate regression analysis models were used to further analyze the associations between PaO2/FiO2 and delirium. In the crude model, for 1 standard deviation (SD) increase in PaO2/FiO2, the odds ratio (OR) of delirium was 0.8 (95% confidence interval [CI]: 0.6–0.9), but there was no significant correlation in the fully adjusted model. There was a non-linear relationship between the PaO2/FiO2 and delirium in a generalized additive model. A two-piecewise linear regression model was used to calculate a PaO2/FiO2 threshold of 243 mmHg. On the left side of the threshold, the OR was 0.9 and the 95% CI was 0.9–1.0 (P=0.013) when PaO2/FiO2 increased by 1 SD. ConclusionsPaO2/FiO2 was negatively associated with delirium when PaO2/FiO2 was below the identified threshold. As a readily available laboratory indicator, PaO2/FiO2 has potential value in the clinical evaluation of risk of delirium in ICU patients.

An Automated Algorithm for Determining Sleep Using Single-Channel Electroencephalography to Detect Delirium: A Prospective Observational Study in Intensive Care Units.

The relationship between polysomnography-based objective sleep and delirium in the intensive care unit (ICU) is inconsistent across studies, suggesting limitations in manually determining the sleep stage of critically ill patients. We objectively measured 24-h sleep using a single-channel electroencephalogram (SleepScope [SS]) and an under-mattress sleep monitor (Nemuri SCAN [NSCAN]), both of which have independent algorithms that automatically determine sleep and wakefulness. Eighteen patients (median age, 68 years) admitted to the ICU after valvular surgery or coronary artery bypass grafting were included, and their sleep time was measured one day after extubation. The median total sleep times (TSTs) measured by SS (TST-SS) and NSCAN were 548 (48–1050) and 1024 (462–1257) min, respectively. Two patients with delirium during the 24-h sleep measurement had very short TST-SS of 48 and 125 min, and the percentage of daytime sleep accounted for >80% in both SS and NSCAN. This preliminary case series showed marked sleep deprivation and increased rates of daytime sleeping in ICU patients with delirium. Although data accuracy from under-mattress sleep monitors is contentious, automated algorithmic sleep/wakefulness determination using a single-channel electroencephalogram may be useful in detecting delirium in ICU patients and could even be superior to polysomnography.

Potential Usefulness of Blood Urea Nitrogen to Creatinine Ratio in the Prediction and Early Detection of Delirium Motor Subtype in the Intensive Care Unit.

Prediction and early detection of delirium can improve patient outcomes. A high blood urea nitrogen to creatinine ratio (BCR), which reflects dehydration, has been reported as a risk factor for delirium. Additionally, BCR represents skeletal muscle loss in intensive care unit (ICU) patients, which can have critical implications for clinical outcomes. We investigated whether BCR could be used to predict the occurrence and motor subtype of delirium in ICU patients through a retrospective cohort study that included 7167 patients (50 years or older) admitted to the ICU. Patients were assessed daily using the Richmond Agitation-Sedation Scale and the Confusion Assessment Method for ICU and categorized according to the delirium subtype. Participants were split into 10 groups according to BCR at ICU admission and the prevalence of each delirium subtype was compared. Multivariable logistic regression was then used for analysis. A higher BCR at ICU admission was associated with the development of hypoactive delirium. Moreover, BCR > 24.9 was associated with higher rates of hypoactive delirium. Our findings showed that a high BCR at ICU admission was associated with the development of hypoactive delirium, which suggested that BCR could be a potential biomarker for hypoactive delirium in ICU patients.