Association of Hypoactive and Hyperactive Delirium With Cognitive Function After Critical Illness

Registered nurses' experiences of caring for patients with hypoactive delirium after cardiac surgery - A qualitative study

OBJECTIVES

Delirium is a common post-cardiac surgery complication that presents as acute changes in mental abilities with confused thinking and a lack of awareness of the surroundings. Delirium symptoms present in hyperactive- and hypoactive forms. Hypoactive delirium is often overlooked. Although nursing interventions are important in preventing and treating hypoactive delirium, studies focusing on nurses' experiences of hypoactive delirium are scarce. This study describes registered nurses' experiences of caring for patients with hypoactive delirium after cardiac surgery.

RESEARCH METHODOLOGY/DESIGN

This was a qualitative descriptive study with an inductive approach. Data was collected through focus group interviews with 12 registered nurses with experience in caring for cardiac surgery patients with hypoactive delirium. The study complied with the Consolidated Criteria for Reporting Qualitative Research.

SETTING

A cardiac surgery department at a Swedish University Hospital.

FINDINGS

The analysis resulted in one main category; "Navigating the complexities of care when caring for patients with hypoactive delirium" and three sub-categories: "Challenges, "Nursing interventions" and "Promoting a team approach".

CONCLUSION

Delirium assessment and nursing interventions are perceived as essential yet demanding. when caring for patients with hypoactive delirium. Nursing interventions like maintaining the circadian rhythm and offering emotional support need to be prioritised by the nurses, in line with the autonomy of the registered nurse's profession. Moreover, the team around the patient is crucial for detecting and treating hypoactive delirium, and it is important to involve other professionals as well as the patient's relatives. Future research is needed to develop assessment instruments that more accurately capture hypoactive delirium in the postoperative setting.

IMPLICATIONS FOR CLINICAL PRACTICE

Despite the use of screening tools, nurses still experience challenges in detecting the symptoms of hypoactive delirium, indicating a need for more clinically effective screening tools for hypoactive delirium. Nursing interventions are emphasised in the care of patients with hypoactive delirium.

Exploration of the factors affecting different delirium subtypes in hospitalized COVID-19 patients: a multicentre cross-sectional study

During the COVID-19 pandemic, delirium became a major complication that worsened patient outcomes. However, the factors influencing the severity of delirium in patients with COVID-19 have not been determined. We conducted this study to detect influencing factors associated with subtypes of delirium in patients with COVID-19. We included 1774 adult inpatients with COVID-19 from January to February 2023 at 7 sites in China. And used the 3 min Confusion Assessment Method and the Richmond Agitation-Sedation Scale for site assessment to identify and classify subtypes of delirium. Laboratory data were obtained from the Hospital Information System. After multivariate analysis, hypoactive delirium was significantly associated with age, the serum albumin concentration, frailty and sarcopenia, and health and nutritional status. Mixed delirium was significantly associated with age, D-dimer level, sarcopenia, health status and nutritional status. Additionally, hyperactive delirium was significantly associated with age, procalcitonin levels, frailty status and health status. Our findings suggest that poor nutritional status and low serum albumin concentration can help detect patients at high risk of developing hypoactive and mixed delirium. Additionally, clinical staff should pay more attention to patients with inflammatory conditions to assess and detect delirium because many influencing factors are involved in the common pathological mechanism of inflammation.

Patient Outcomes and Management Strategies for Intensive Care Unit (ICU)-Associated Delirium: A Literature Review

Delirium is a significant public health concern, with tremendous implications for patient outcomes. Intensive care unit (ICU)-related delirium is gaining attention due to the higher prevalence of delirium in ICU-admitted patients. The most common negative outcomes of ICU delirium include cognitive impairments, functional dependence, high incidence of mortality, extended stay in the ICU, and high costs. So far, no single etiological factor has been identified as the sole cause of delirium. Several functional, neurotransmitter, or injury-causing hypotheses have been proposed for ICU delirium. Several risk factors contribute to the development of delirium in patients admitted to the ICU. These are age, gender, types of sedation, physical restraints, medical and surgical interventions, pain, and extended stay in the ICU. The most commonly used assessment modules for ICU delirium are the PREdiction of DELIRium in ICu patients (PRE-DELIRIC), Early PREdiction model for DELIRium in ICu patients (E-PRE-DELERIC), and Lanzhou Model, Confusion Assessment Method for the Intensive Care Unit (CAM-ICU), Intensive Care Delirium Screening Checklist (ICDSC), and Delirium Rating Scale (DRS). There is no proper treatment for ICU delirium; however, it can be managed through various pharmacological and non-pharmacological interventions. Healthcare providers should receive constant education and training on delirium recognition, prevention, and management to enhance patient care and outcomes in the ICU. Further research is needed on the effective prevention and management of ICU delirium.

Post-Intensive Care Syndrome in Neurocritical Care Patients

Post-intensive care syndrome (PICS) refers to unintended consequences of critical care that manifest as new or worsening impairments in physical functioning, cognitive ability, or mental health. As intensive care unit (ICU) survival continues to improve, PICS is becoming increasingly recognized as a public health problem. Studies that focus on PICS have typically excluded patients with acute brain injuries and chronic neurodegenerative problems. However, patients who require neurocritical care undoubtedly suffer from impairments that overlap substantially with those encompassed by PICS. A major challenge is to distinguish between impairments related to brain injury and those that occur as a consequence of critical care. The general principles for the prevention and management of PICS and multidomain impairments in patients with moderate and severe neurological injuries are similar including the ICU liberation bundle, multidisciplinary team-based care throughout the continuum of care, and increasing awareness regarding the challenges of critical care survivorship among patients, families, and multidisciplinary team members. An extension of this concept, PICS-Family (PICS-F) refers to the mental health consequences of the intensive care experience for families and loved ones of ICU survivors. A dyadic approach to ICU survivorship with an emphasis on recognizing families and caregivers that may be at risk of developing PICS-F after neurocritical care illness can help improve outcomes for ICU survivors. In this review, we will summarize our current understanding of PICS and PICS-F, emerging literature on PICS in severe acute brain injury, strategies for preventing and treating PICS, and share our recommendations for future directions.

Prophylactic Minocycline for Delirium in Critically Ill Patients: A Randomized Controlled Trial

BACKGROUND

Delirium is a potentially severe form of acute encephalopathy. Minocycline has neuroprotective effects in animal models of neurologic diseases; however, data from human studies remain scarce.

RESEARCH QUESTION

Does the neuroprotective effect of minocycline prevent delirium occurrence in critically ill patients?

STUDY DESIGN AND METHODS

This study was a randomized, placebo-controlled, double-anonymized trial conducted in four ICUs. Patients aged 18 years or older were eligible and randomized to receive minocycline (100 mg, twice daily) or placebo. The primary outcome was delirium incidence within 28 days or before ICU discharge. Secondary outcomes included days in delirium during ICU stay, delirium/coma-free days, length of mechanical ventilation, ICU length of stay, ICU mortality, and hospital mortality. The kinetics of various inflammatory (IL-1β, IL-6, IL-10, and C-reactive protein) and brain-related biomarkers (brain-derived neurotrophic factor and S100B) were used as exploratory outcomes.

RESULTS

A total of 160 patients were randomized, but one patient in the placebo group died before treatment; thus the data from 159 patients were analyzed (minocycline, n = 84; placebo, n = 75). After the COVID-19 pandemic it was decided to stop patient inclusion early. There was a small but significant decrease in delirium incidence: 17 patients (20%) in the minocycline arm compared with 26 patients (35%) in the placebo arm (P = .043). No other delirium-related outcomes were modified by minocycline treatment. Unexpectedly, there was a significant decrease in hospital mortality (39% vs. 23%; P = .029). Among all analyzed biomarkers, only plasma levels of C-reactive protein decreased significantly after minocycline treatment (F = 0.75, P = .78, within time; F = 4.09, P = .045, group × time).

INTERPRETATION

Our findings in this rather small study signal a possible positive effect of minocycline on delirium incidence. Further studies are needed to confirm the benefits of this drug as a preventive measure in critically ill patients.

CLINICAL TRIAL REGISTRATION

ClinicalTrials.gov; No.: NCT04219735; URL: www.

CLINICALTRIALS

gov.

Exposure to Sedation and Analgesia Medications: Short-term Cognitive Outcomes in Pediatric Critical Care Survivors With Acquired Brain Injury

Background/Objective: Pediatric intensive care unit (PICU) survivors risk significant cognitive morbidity, particularly those with acquired brain injury (ABI) diagnoses. Studies show sedative and analgesic medication may potentiate neurologic injury, but few studies evaluate impact on survivor outcomes. This study aimed to evaluate whether exposures to analgesic and sedative medications are associated with worse neurocognitive outcome. Methods: A retrospective cohort study was conducted of 91 patients aged 8 to 18 years, undergoing clinical neurocognitive evaluation approximately 1 to 3 months after PICU discharge. Electronic health data was queried for sedative and analgesic medication exposures, including opioids, benzodiazepines, propofol, ketamine, and dexmedetomidine. Doses were converted to class equivalents, evaluated by any exposure and cumulative dose exposure per patient weight. Cognitive outcome was derived from 8 objective cognitive assessments with an emphasis on executive function skills using Principal Components Analysis. Then, linear regression was used to control for baseline cognitive function estimates to calculate a standardized residualized neurocognitive index (rNCI) z-score. Multivariable linear regression evaluated the association between rNCI and medication exposure controlling for covariates. Significance was defined as P < .05. Results: Most (n = 80; 88%) patients received 1 or more study medications. Any exposure and higher cumulative doses of benzodiazepine and ketamine were significantly associated with worse rNCI in bivariate analyses. When controlling for Medicaid, preadmission comorbid conditions, length of stay, delirium, and receipt of other medication classes, receipt of benzodiazepine was associated with significantly worse rNCI (β-coefficient = -0.48, 95% confidence interval = -0.88, -0.08). Conclusions: Exposure to benzodiazepines was independently associated with worse acute phase cognitive outcome using objective assessments focused on executive function skills when controlling for demographic and illness characteristics. Clinician decisions regarding medication regimens in the PICU may serve as a modifiable factor to improve outcomes. Additional inquiry into associations with long-term cognitive outcome and optimal medication regimens is needed.

Acute encephalopathy in the ICU: a practical approach

PURPOSE OF REVIEW

Acute encephalopathy (AE) - which frequently develops in critically ill patients with and without primary brain injury - is defined as an acute process that evolves rapidly and leads to changes in baseline cognitive status, ranging from delirium to coma. The diagnosis, monitoring, and management of AE is challenging. Here, we discuss advances in definitions, diagnostic approaches, therapeutic options, and implications to outcomes of the clinical spectrum of AE in ICU patients without primary brain injury.

RECENT FINDINGS

Understanding and definitions of delirium and coma have evolved. Delirium is a neurocognitive disorder involving impairment of attention and cognition, usually fluctuating, and developing over hours to days. Coma is a state of unresponsiveness, with absence of command following, intelligible speech, or visual pursuit, with no imaging or neurophysiological evidence of cognitive motor dissociation. The CAM-ICU(-7) and the ICDSC are validated, guideline-recommended tools for clinical delirium assessment, with identification of clinical subtypes and stratification of severity. In comatose patients, the roles of continuous EEG monitoring and neuroimaging have grown for the early detection of secondary brain injury and treatment of reversible causes.

SUMMARY

Evidence-based pharmacologic treatments for delirium are limited. Dexmedetomidine is effective for mechanically ventilated patients with delirium, while haloperidol has minimal effect of delirium but may have other benefits. Specific treatments for coma in nonprimary brain injury are still lacking.

Delirium in long-term care and the myth of Proteus

This editorial comments on the article by Webber et al. in this issue.

Non-pharmacological interventions for delirium in the pediatric population: a systematic review with narrative synthesis

BACKGROUND

Delirium is a serious complication experienced by hospitalized children. Therefore, preventive management strategies are recommended for these patients. However, comprehensive analyses of delirium interventions in children remain insufficient. Specifically, this systematic review aimed to summarize non-pharmacological interventions for pediatric delirium, addressing the urgent need for a comprehensive understanding of effective strategies. We also explored frequently measured outcome variables to contribute evidence for future research on delirium outcomes in children.

METHODS

This systematic review searched articles from PubMed, Web of Science, Cumulative Index to Nursing and Allied Health Literature, and Excerpta Medica databases. The eligibility criteria were formed under the population, intervention, comparator, outcome, and study design framework. Studies were included if they involved (1) children aged under 18 years receiving hospital care, (2) non-pharmacological delirium interventions, (3) comparators involving no intervention or pharmacological delirium interventions, and (4) outcomes measuring the effectiveness of non-pharmacological delirium interventions. Only peer-reviewed articles published in English were included.

RESULTS

Overall, 16 studies were analyzed; of them, 9 assessed non-pharmacological interventions for emergence delirium and 7 assessed interventions for pediatric delirium. The intervention types were grouped as follows: educational (n = 5), multicomponent (n = 6), and technology-assisted (n = 5). Along with pediatric and emergence delirium, the most frequently measured outcome variables were pain, patient anxiety, parental anxiety, pediatric intensive care unit length of stay, agitation, analgesic consumption, and postoperative maladaptive behavior.

CONCLUSIONS

Non-pharmacological interventions for children are effective treatments without associated complications. However, determining the most effective non-pharmacological delirium intervention for hospitalized children based on current data remains challenging.

Data-derived subtypes of delirium during critical illness

BACKGROUND

To understand delirium heterogeneity, prior work relied on psychomotor symptoms or risk factors to identify subtypes. Data-driven approaches have used machine learning to identify biologically plausible, treatment-responsive subtypes of other acute illnesses but have not been used to examine delirium.

METHODS

We conducted a secondary analysis of a large, multicenter prospective cohort study involving adults in medical or surgical ICUs with respiratory failure or shock who experienced delirium per the Confusion Assessment Method for the ICU. We used data collected before delirium diagnosis in an unsupervised latent class model to identify delirium subtypes and then compared demographics, clinical characteristics, and outcomes between subtypes in the final model.

FINDINGS

The 731 patients who developed delirium during critical illness had a median age of 63 [IQR, 54-72] years, a median Sequential Organ Failure Assessment score of 8.0 [6.0-11.0] and 613 [83.4%] were mechanically ventilated at delirium identification. A four-class model best fit the data with 50% of patients in subtype (ST) 1, 18% in subtype 2, 17% in subtype 3, and 14% in subtype 4. Subtype 2-which had more shock and kidney impairment-had the highest mortality (33% [ST2] vs. 17% [ST1], 25% [ST3], and 17% [ST4], p = 0.003). Subtype 4-which received more benzodiazepines and opioids-had the longest duration of delirium (6 days [ST4] vs. 3 [ST1], 4 [ST2], and 3 days [ST3], p < 0.001) and coma (4 days [ST4] vs. 2 [ST1], 1 [ST2], and 2 days [ST3], p < 0.001). Each of the four data-derived delirium subtypes was observed within previously identified psychomotor and risk factor-based delirium subtypes. Clinically significant cognitive impairment affected all subtypes at follow-up, but its severity did not differ by subtype (3-month, p = 0.26; 12-month, p = 0.80).

INTERPRETATION

The four data-derived delirium subtypes identified in this study should now be validated in independent cohorts, examined for differential treatment effects in trials, and inform mechanistic work evaluating treatment targets.

FUNDING

National Institutes of Health (T32HL007820, R01AG027472).

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

PURPOSE

Describe the incidence and factors associated with recurrent delirium in the intensive care unit (ICU).

MATERIALS AND METHODS

Retrospective 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.

RESULTS

Among 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]).

CONCLUSIONS

Over 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.

Online interpretable dynamic prediction models for postoperative delirium after cardiac surgery under cardiopulmonary bypass developed based on machine learning algorithms: A retrospective cohort study

OBJECTIVE

Postoperative delirium (POD) is strongly associated with poor early and long-term prognosis in cardiac surgery patients with cardiopulmonary bypass (CPB). This study aimed to develop dynamic prediction models for POD after cardiac surgery under CPB using machine learning (ML) algorithms.

METHODS

From July 2021 to June 2022, clinical data were collected from patients undergoing cardiac surgery under CPB at Nanjing First Hospital. A dataset from the same center (October 2022 to November 2022) was also used for temporal external validation. We used ML and deep learning to build models in the training set, optimized parameters in the test set, and finally validated the best model in the validation set. The SHapley Additive exPlanations (SHAP) method was introduced to explain the best models.

RESULTS

Of the 885 patients enrolled, 221 (25.0%) developed POD. 22 (22.0%) of 100 validation cohort patients developed POD. The preoperative and postoperative artificial neural network (ANN) models exhibited optimal performance. The validation results demonstrated satisfactory predictive performance of the ANN model, with area under the receiver operator characteristic curve (AUROC) values of 0.776 and 0.684 for the preoperative and postoperative models, respectively. Based on the ANN algorithm, we constructed dynamic, highly accurate, and interpretable web risk calculators for POD.

CONCLUSIONS

We successfully developed online interpretable dynamic ANN models as clinical decision aids to identify patients at high risk of POD before and after cardiac surgery to facilitate early intervention or care.

Delirium During Critical Illness and Subsequent Change of Treatment in Patients With Cancer: A Mediation Analysis

OBJECTIVES

To assess whether delirium during ICU stay is associated with subsequent change in treatment of cancer after discharge.

DESIGN

Retrospective cohort study.

SETTING

A 50-bed ICU in a dedicated cancer center.

PATIENTS

Patients greater than or equal to 18 years old with a previous proposal of cancer treatment (chemotherapy, target therapy, hormone therapy, immunotherapy, radiotherapy, oncologic surgery, and bone marrow transplantation).

INTERVENTIONS

None.

MEASUREMENTS AND MAIN RESULTS

We considered delirium present if Confusion Assessment Method for the ICU was positive. We assessed the association between delirium and modification of the treatment after discharge. We also performed a mediation analysis to assess both the direct and indirect (i.e., mediated by the development of functional dependence after discharge) of delirium on modification of cancer treatment and whether the modification of cancer treatment was associated with mortality at 1 year. We included 1,134 patients, of whom, 189 (16.7%) had delirium. Delirium was associated with the change in cancer treatment (adjusted odds ratio [OR], 3.80; 95% CI, 2.72-5.35). The association between delirium in ICU and change of treatment was both direct and mediated by the development of functional dependence after discharge. The proportion of the total effect of delirium on change of treatment mediated by the development of functional dependence after discharge was 33.0% (95% CI, 21.7-46.0%). Change in treatment was associated with increased mortality at 1 year (adjusted OR, 2.68; 95% CI, 2.01-3.60).

CONCLUSIONS

Patients who had delirium during ICU stay had a higher rate of modification of cancer treatment after discharge. The effect of delirium on change in cancer treatment was only partially mediated by the development of functional dependence after discharge. Change in cancer treatment was associated with increased 1-year mortality.

Functional independence, frailty and perceived quality of life in patients who developed delirium during ICU stay: a prospective cohort study

BACKGROUND

Survivors of critical illness are frequently left with a long-lasting disability. We hypothesised that patients who developed delirium during ICU stay, compared with patients who did not, would have worse health-related quality of life following a critical illness.

METHODS

Prospective longitudinal observational and analytical study assessing functional independence, frailty and perceived quality of life measured with the Barthel Index, the Clinical Frailty Scale, and the SF-36, comparing patients who developed delirium during ICU stay and patients who did not. The questionnaires were used at different times during the follow-up (upon ICU admission, at ICU discharge, at hospital discharge and 2 years after hospital discharge).

RESULTS

In a cohort of 1462 patients, we matched 93 patients who developed delirium (delirium group) with 93 patients who did not develop delirium (no-delirium group). Of 156 completed questionnaires (84.7%), we observed that (a) in each of the two groups of patients, the scores related to functional independence (Barthel Index) and frailty (Clinical Frailty Scale) tended to improve over time (p < 0.001), being consistently less favourable in the delirium group compared to the no-delirium group (p < 0.001); (b) the patients who developed delirium also presented lower scores on the SF-36 scale, these differences being statistically significant, and therefore evidencing a worse quality of life, with impact on both the psychological and social spheres (p < 0.001).

CONCLUSIONS

Patients who developed delirium had significantly lower scores 2 years after hospital discharge on the three used questionnaires, displaying a clear negative impact on the physical, psychological, and social dimensions. The study's results reinforce the need to support and strengthen the care of ICU survivors.

Delirium in older adults after percutaneous coronary intervention: Prevalence, risks, and clinical phenotypes

INTRODUCTION

In-hospital delirium is more common among older adults and is associated with increased mortality and adverse health-related outcomes. We aim to establish the contemporary prevalence of delirium among older adults undergoing percutaneous coronary intervention (PCI) and the impact of delirium on in-hospital complications.

METHODS

We identified older adults aged ≥75 years in the National Inpatient Sample who underwent inpatient PCI for any reason from 2016 to 2020 and stratified them into those with and without delirium. The primary outcome was in-hospital mortality, and secondary outcomes encompassed post-procedural complications.

RESULTS

Delirium occurred in 14,130 (2.6 %) hospitalizations in which PCI was performed. Patients who developed delirium were older and had more comorbidities. Patients with in-hospital delirium had higher odds of in-hospital mortality (adjusted odds ratio [aOR] 1.27, p = 0.002) and non-home discharge (aOR 3.17, p < 0.001). Delirium was also associated with higher odds of intracranial hemorrhage (aOR 2.49, p < 0.001), gastrointestinal hemorrhage (aOR 1.25, p = 0.030), need for blood transfusion (aOR 1.52, p < 0.001), acute kidney injury (aOR 1.62, p < 0.001), and fall in hospital (aOR 1.97, p < 0.001).

CONCLUSION

Delirium among older adults undergoing PCI is relatively common and associated with higher odds of in-hospital mortality and adverse events. This highlights the importance of vigilant delirium prevention and early recognition in the peri-procedural setting, especially for older adults.

Suffering in silence - Cardiac surgery patients recalling hypoactive delirium a qualitative descriptive study

OBJECTIVES

Postoperative delirium affects up to 50% of patients undergoing cardiac surgery. Delirium phenotypes are commonly divided into hyperactive and hypoactive, with hypoactive symptoms (reduced motor activity and withdrawal) often being overlooked due to their discreet character. Although the consequences of hypoactive delirium are severe, studies focusing on patients' experiences of hypoactive delirium are scarce. The aim of the study was to describe cardiac surgery patients' experiences of hypoactive delirium.

RESEARCH METHODOLOGY/DESIGN

We used qualitative descriptive semi-structured interviews with an inductive, latent approach. Twelve patients with hypoactive symptoms of delirium after cardiac surgery were purposefully selected. Interview data were analysed by qualitative content analysis.

FINDINGS

Two themes based on eight sub-themes emerged. "Dream or reality in parallel worlds" included disturbing experiences of existing in parallel realities with cognitive effects, residual nightmares, and illusions that occasionally persisted after hospital discharge. "Managing the state of hypoactive delirium" included experiences of intellectually dealing with hypoactive delirium with assumptions of causes and cures, and through interactions like communicating with others.

CONCLUSION

Participants experienced hypoactive delirium as extensive and long-lasting with perceptions of existing in parallel realities. The findings emphasize the need for healthcare professionals to have expertise in hypoactive delirium and its fluctuating course, as the delirium of many patients may be undetected and undiagnosed. Improving the use of screening tools for clinical practice is essential for the detection of hypoactive delirium, and a person-centred approach is needed to properly care for this group of patients.

IMPLICATIONS FOR CLINICAL PRACTICE

The challenges in the recognition of hypoactive delirium need to be emphasized because the syndrome is still overlooked. The use of screening tools in clinical practice is essential. A person-centred approach supports relationships between delirious patients and healthcare professionals.

Natural language processing diagnosed behavioural disturbance phenotypes in the intensive care unit: characteristics, prevalence, trajectory, treatment, and outcomes

BACKGROUND

Natural language processing (NLP) may help evaluate the characteristics, prevalence, trajectory, treatment, and outcomes of behavioural disturbance phenotypes in critically ill patients.

METHODS

We obtained electronic clinical notes, demographic information, outcomes, and treatment data from three medical-surgical ICUs. Using NLP, we screened for behavioural disturbance phenotypes based on words suggestive of an agitated state, a non-agitated state, or a combination of both.

RESULTS

We studied 2931 patients. Of these, 225 (7.7%) were NLP-Dx-BD positive for the agitated phenotype, 544 (18.6%) for the non-agitated phenotype and 667 (22.7%) for the combined phenotype. Patients with these phenotypes carried multiple clinical baseline differences. On time-dependent multivariable analysis to compensate for immortal time bias and after adjustment for key outcome predictors, agitated phenotype patients were more likely to receive antipsychotic medications (odds ratio [OR] 1.84, 1.35-2.51, p < 0.001) compared to non-agitated phenotype patients but not compared to combined phenotype patients (OR 1.27, 0.86-1.89, p = 0.229). Moreover, agitated phenotype patients were more likely to die than other phenotypes patients (OR 1.57, 1.10-2.25, p = 0.012 vs non-agitated phenotype; OR 4.61, 2.14-9.90, p < 0.001 vs. combined phenotype). This association was strongest in patients receiving mechanical ventilation when compared with the combined phenotype (OR 7.03, 2.07-23.79, p = 0.002). A similar increased risk was also seen for patients with the non-agitated phenotype compared with the combined phenotype (OR 6.10, 1.80-20.64, p = 0.004).

CONCLUSIONS

NLP-Dx-BD screening enabled identification of three behavioural disturbance phenotypes with different characteristics, prevalence, trajectory, treatment, and outcome. Such phenotype identification appears relevant to prognostication and trial design.

Long-term mortality of critically ill patients with cancer and delirium who survived to discharge: a retrospective cohort study

PURPOSE

Delirium is common in critically ill patients and has been associated with lower short-term survival; however, its association with long-term survival has been scarcely evaluated and few studies have shown divergent results.

METHODS

We conducted a retrospective cohort study of adult patients with cancer admitted to the intensive care unit (ICU) and discharged from hospital from January 2015 to December 2018. We considered delirium present if the Confusion Assessment Method for Intensive Care Unit (CAM-ICU) result was positive. We assessed the association between delirium during ICU stay and long-term mortality (up to three years after discharge). We also assessed the association between delirium type (hypoactive, hyperactive, and mixed) with long-term mortality.

RESULTS

We included 3,079 patients. Of these, 430 (14%) were considered delirious at some point during their ICU stay. Delirium was associated with one-year mortality after hospital discharge (hazard ratio [HR], 1.58; 95% confidence interval [CI], 1.36 to 1.83) after adjustment for potential confounders, but not with one to three year-mortality (HR, 0.92; 95% CI, 0.61 to 1.39). Hypoactive and mixed delirium were associated with one-year mortality (HR, 1.77; 95% CI, 1.46 to 2.14 and HR, 1.56; 95% CI, 1.21 to 2.00, respectively), but none of the delirium motor types was associated with one to three-year mortality.

CONCLUSIONS

We observed that delirium during ICU stay was associated with increased one-year mortality, but was not with mortality after one year. This association was observed in hypoactive and mixed delirium types but not with hyperactive delirium.

Inclusion of frailty improved performance of delirium prediction for elderly patients in the cardiac intensive care unit (D-FRAIL): A prospective derivation and external validation study

BACKGROUND

The elderly patients admitted to cardiac intensive care unit (CICU) are at relatively high risk for developing delirium. A simple and reliable predictive model can benefit them from early recognition of delirium followed by timely and appropriate preventive strategies.

OBJECTIVE

To explore the role of frailty in delirium prediction and develop and validate a delirium predictive model including frailty for elderly patients in CICU.

DESIGN

A prospective, observational cohort study.

SETTINGS

CICU at China-Japan Friendship Hospital from March 1, 2022 to August 25, 2022 (derivation cohort); CICU at Beijing Anzhen Hospital affiliated to Capital Medical University from March 14, 2023 to May 8, 2023 (external validation cohort).

PARTICIPANTS

A total of 236 and 90 participants were enrolled in the derivation and external validation cohorts, respectively. Participants in the derivation cohort were assigned into either the delirium (n = 70) or non-delirium group (n = 166) based on the occurrence of delirium.

METHODS

The simplified Chinese version of the Confusion Assessment Method for the Diagnosis of Delirium in the Intensive Care Unit was used to assess delirium twice a day at 8:00-10:00 and 18:00-20:00 until the onset of delirium or discharge from the CICU. Frailty was assessed using the FRAIL scale during the first 24 h in the CICU. Other possible risk factors were collected prospectively through patient interviews and medical records review. After processing missing data via multiple imputations, univariate analysis and bootstrapped forward stepwise logistic regression were performed to select optimal predictors and develop the models. The models were internally validated using bootstrapping and evaluated comprehensively via discrimination, calibration, and clinical utility in both the derivation and external validation cohorts.

RESULTS

The study developed D-FRAIL predictive model using FRAIL score, hearing impairment, Acute Physiology and Chronic Health Evaluation-II score, and fibrinogen. The area under the receiver operating characteristic curve (AUC) was 0.937 (95% confidence interval [CI]: 0.907-0.967) and 0.889 (95%CI: 0.840-0.938) even after bootstrapping in the derivation cohort. Inclusion of frailty was demonstrated to improve the model performance greatly with the AUC increased from 0.851 to 0.937 (p < 0.001). In the external validation cohort, the AUC of D-FRAIL model was 0.866 (95%CI: 0.782-0.907). Calibration plots and decision curve analysis suggested good calibration and clinical utility of the D-FRAIL model in both the derivation and external validation cohorts.

CONCLUSIONS

For elderly patients in the CICU, FRAIL score is an independent delirium predictor and the D-FRAIL model demonstrates superior performance in predicting delirium.

Validity and predictability of the confusion assessment method for the intensive care unit for delirium among critically ill patients in the intensive care unit: A systematic review and meta-analysis

OBJECTIVE

To identify the validity and predictability of the confusion assessment method for the intensive care unit (CAM-ICU) for delirium in critically ill patients in the ICU.

METHODS

In this systematic review, PubMed, Embase, Cochrane Central Register of Controlled Trials, and MEDLINE databases were searched for observational studies investigating delirium screening tools for ICU patients. In the meta-analysis, we combined the sensitivity, specificity, positive likelihood ratio, negative likelihood ratio, diagnostic odds ratio, and area under the curve (AUC) of SROC to analysis the predictive value of CAM-ICU.

RESULTS

Twenty-nine articles met the inclusion criteria. The pooled sensitivity and specificity values were 0.82 (95% confidence interval [CI]: 0.75-0.87) and 0.95 (95% CI: 0.93-0.97), respectively. The AUC point estimate of the SROC curve was 0.96 (95% CI: 0.94-0.97). Race (Asian or Others) could affect the pooled sensitivity and specificity, and the analysis method (Patient- or Scan-based) and study design were not sources of heterogeneity for pooled sensitivity and specificity.

CONCLUSIONS

The CAM-ICU is a valid and reliable tool for delirium prediction among ICU patients. When introducing CAM-ICU to assess delirium, it is necessary to localize its language and content to improve its predictive efficacy in different countries and different ethnic groups.

RELEVANCE TO CLINICAL PRACTICE

In clinical practice, nurses can use CAM-ICU to evaluate delirium in critically ill patients in ICU. However, it is necessary to debug the language and content according to the application population.

Biomarkers of delirium risk in older adults: a systematic review and meta-analysis

Delirium is a neuropsychiatric syndrome associated with increased morbidity and mortality in older patients. The aim of this study was to review predictive biomarkers of delirium in older patients to gain insights into the pathophysiology of this syndrome and provide guidance for future studies. Two authors independently and systematically searched MEDLINE, Embase, Cochrane Library, Web of Science and Scopus databases up to August 2021. A total of 32 studies were included. Only 6 studies were eligible for the meta-analysis, pooled results showed a significant increase in some serum biomarkers (C-reactive protein [CRP], tumour necrosis factor alpha [TNF-α] and interleukin-6 [IL-6]) among patients with delirium (odds ratio = 1.88, 95% CI 1.01 to 1.637; I2 = 76.75%). Although current evidence does not favour the use of any particular biomarker, serum CRP, TNF-α, and IL-6 were the most consistent biomarkers of delirium in older patients.

Biomarkers of neuropsychiatric dysfunction in intensive care unit survivors: a prospective cohort study

OBJECTIVE

To assess factors associated with long-term neuropsychiatric outcomes, including biomarkers measured after discharge from the intensive care unit.

METHODS

A prospective cohort study was performed with 65 intensive care unit survivors. The cognitive evaluation was performed through the Mini-Mental State Examination, the symptoms of anxiety and depression were evaluated using the Hospital Anxiety and Depression Scale, and posttraumatic stress disorder was evaluated using the Impact of Event Scale-6. Plasma levels of amyloid-beta (1-42) [Aβ (1-42)], Aβ (1-40), interleukin (IL)-10, IL-6, IL-33, IL-4, IL-5, tumor necrosis factor alpha, C-reactive protein, and brain-derived neurotrophic factor were measured at intensive care unit discharge.

RESULTS

Of the variables associated with intensive care, only delirium was independently related to the occurrence of long-term cognitive impairment. In addition, higher levels of IL-10 and IL-6 were associated with cognitive dysfunction. Only IL-6 was independently associated with depression. Mechanical ventilation, IL-33 levels, and C-reactive protein levels were independently associated with anxiety. No variables were independently associated with posttraumatic stress disorder.

CONCLUSION

Cognitive dysfunction, as well as symptoms of depression, anxiety, and posttraumatic stress disorder, are present in patients who survive a critical illness, and some of these outcomes are associated with the levels of inflammatory biomarkers measured at discharge from the intensive care unit.

Differences in long-term outcomes between ICU patients with persistent delirium, non-persistent delirium and no delirium: A longitudinal cohort study

PURPOSE

Determine differences in physical, mental and cognitive outcomes 1-year post-ICU between patients with persistent delirium (PD), non-persistent delirium (NPD) and no delirium (ND).

MATERIALS AND METHODS

A longitudinal cohort study was performed in adult ICU patients of two hospitals admitted between July 2016-February 2020. Questionnaires on physical, mental and cognitive health, frailty and QoL were completed regarding patients' pre-ICU health status and 1-year post-ICU. Delirium data were from patients' total hospital stay. Patients were divided in PD (≥14 days delirium), NPD (<14 days delirium) or ND patients.

RESULTS

2400 patients completed both questionnaires, of whom 529 (22.0%) patients developed delirium; 35 (6.6%) patients had PD and 494 (93.4%) had NPD. Patients with delirium (PD or NPD) had worse outcomes in all domains compared to ND patients. Compared to NPD, more PD patients were frail (34.3% vs. 14.6%, p = 0.006) and fatigued (85.7% vs. 61.1%, p = 0.012). After adjustment, PD was significantly associated with long-term cognitive impairment only (aOR 3.90; 95%CI 1.31-11.63).

CONCLUSIONS

Patients with PD had a higher likelihood to develop cognitive impairment 1-year post-ICU compared to NPD or ND. Patients with PD and NPD were more likely to experience impairment on all health domains (i.e. physical, mental and cognitive), compared to ND patients.

Delirium-related psychiatric and neurocognitive impairment and the association with post-intensive care syndrome-A narrative review

INTRODUCTION

Delirium is common among patients admitted to the intensive care unit (ICU) and its impact on the neurocognitive and psychiatric state of survivors is of great interest. These new-onset or worsening conditions, together with physical alterations, are called post-intensive care syndrome (PICS). Our aim is to update on the latest screening and follow-up options for psychological and cognitive sequelae of PICS.

METHOD

This narrative review discusses the occurrence of delirium in ICU settings and the relatively new concept of PICS. Psychiatric and neurocognitive morbidities that may occur in survivors of critical illness following delirium are addressed. Future perspectives for practice and research are discussed.

RESULTS

There is no "gold standard" for diagnosing delirium in the ICU, but two extensively validated tools, the confusion assessment method for the ICU and the intensive care delirium screening checklist, are often used. PICS complaints are frequent in ICU survivors who have suffered delirium and have been recognized as an important public health and socio-economic problem worldwide. Depression, anxiety, post-traumatic stress disorder, and long-term cognitive impairment are recurrently exhibited. Screening tools for these deficits are discussed, as well as the suggestion of early assessment after discharge and at 3 and 12 months.

CONCLUSIONS

Delirium is a complex but common phenomenon in the ICU and a risk factor for PICS. Its diagnosis is challenging with potential long-term adverse outcomes, including psychiatric and cognitive difficulties. The implementation of screening and follow-up protocols for PICS sequelae is warranted to ensure early detection and appropriate management.

Assessment of the Delirium Prevalence among Pediatric Patients Admitted to the Pediatric Intensive Care Unit in West of Iran

Background: Delirium is often not diagnosed or treated in pediatric intensive care unit (PICU). Delirium leads to a longer hospital stay period, which in turn can result in an increase in hospital treatment costs and an increase in the risk of nosocomial infections. Objectives: The present study aimed to determine the prevalence of delirium and its risk factors in PICU pediatric. Methods: This cross-sectional study was conducted in 2021 - 2022 in hospitals affiliated to Kermanshah University of Medical Sciences. The data collection instruments included the Richmond Agitation-Sedation Scale (RASS) and the Cornell Assessment of Pediatric Delirium (CAPD) questionnaire. Delirium was assessed by the researcher twice a day, in the morning and the evening. The assessment was carried out by a trained person, and the examination results were confirmed by an anesthesiologist who was a member of the research team. Data analysis was carried out using SPSS ver. 16. Results: According to our study results, the majority of the 89 examined patients were male (n = 52 cases, 59.8%), aged 13 - 16 years (n = 37 cases, 42.5%), and were admitted due to pneumonia (n = 24 cases, 27.6%). The prevalence of delirium was higher in patients with pain and those requiring oxygen therapy (P < 0.05). Furthermore, the overall prevalence of delirium in PICU patients was 25.3% (n = 22 cases). Conclusions: Investigating the prevalence of delirium in all age groups – pediatric and adolescents, in particular – was found to be extremely important. It was also found that the prevalence of delirium in PICU patients was significant; therefore, it was recommended that necessary preventive and medical interventions should be made to deal with these patients.

Delirium in a surgical context from a nursing perspective: A hybrid concept analysis

Background

The term delirium has been defined in medical diagnosis criteria as a multidimensional disorder, and the term acute confusion is included in nursing classifications. Delirium can be a serious complication assessed in a patient after a surgical procedure. Still, the patient's delirium frequently remains unrecognised. Care of patients with delirium after surgical procedure is complex, and it challenges nursing expertise. From the nurses' viewpoint, delirium is associated with ambiguity of concepts and lack of knowledge. Therefore, reseach on how nurses perceive patients with delirium in a surgical context is needed.

Objective

The aim of this study was to describe the concepts of delirium and acute confusion, as well as the associated dimensions, in adult patients in a surgical context from the nursing perspective.

Design

The study used Schwartz and Barcott's hybrid concept analysis with theoretical, fieldwork, and final analytical phases.

Settings

Surgical wards, surgical intensive care units, and post-anaesthesia care units.

Data sources

A systematic literature search was performed through Pubmed (Medline), Cinahl, PsycInfo, and Embase.

Participants

Registered nurses and licensed practical nurses (n = 105) participated in the fieldwork phase.

Methods

In the theoretical phase, the concepts' working definitions were formulated based on a systematic literature search with the year limitations from 2000 until February 2021. At the fieldwork phase, the nurses' descriptions of patients with delirium were analysed using the deductive content analysis method. At the final analytical phase, findings were combined and reported.

Results

The concepts of delirium, subsyndromal delirium, and acute confusion are well defined in the literature. From the perspective of the nurses in the study, concepts were seen as a continuum not as individual diagnoses. Nurses described the continuum of delirium as a process with acute onset, duration, and recovery with the associated dimensions of symptoms, symptom severity, risk factors, and early signs. The acute phase of delirium was emphasised, and preoperative or prolonged disturbance did not seem to be relevant in the surgical care context. Patients' compliance with care may be decreased with the continuum of delirium, which might challenge both patients' recovery from surgery and the quality of nursing care.

Conclusions

In clinical practice the nurses used term confusion inaccurately. The term acute confusion might be used when illustrating an early stage of delirium. Nurses could benefit from further education where the theoretical knowledge is combined with the clinical practice. The discussion about the delirium, which covers the time both before surgery and after the acute phase should be increased.

New onset delirium prediction using machine learning and long short-term memory (LSTM) in electronic health record

OBJECTIVE

To develop and test an accurate deep learning model for predicting new onset delirium in hospitalized adult patients.

METHODS

Using electronic health record (EHR) data extracted from a large academic medical center, we developed a model combining long short-term memory (LSTM) and machine learning to predict new onset delirium and compared its performance with machine-learning-only models (logistic regression, random forest, support vector machine, neural network, and LightGBM). The labels of models were confusion assessment method (CAM) assessments. We evaluated models on a hold-out dataset. We calculated Shapley additive explanations (SHAP) measures to gauge the feature impact on the model.

RESULTS

A total of 331 489 CAM assessments with 896 features from 34 035 patients were included. The LightGBM model achieved the best performance (AUC 0.927 [0.924, 0.929] and F1 0.626 [0.618, 0.634]) among the machine learning models. When combined with the LSTM model, the final model's performance improved significantly (P = .001) with AUC 0.952 [0.950, 0.955] and F1 0.759 [0.755, 0.765]. The precision value of the combined model improved from 0.497 to 0.751 with a fixed recall of 0.8. Using the mean absolute SHAP values, we identified the top 20 features, including age, heart rate, Richmond Agitation-Sedation Scale score, Morse fall risk score, pulse, respiratory rate, and level of care.

CONCLUSION

Leveraging LSTM to capture temporal trends and combining it with the LightGBM model can significantly improve the prediction of new onset delirium, providing an algorithmic basis for the subsequent development of clinical decision support tools for proactive delirium interventions.

How do predisposing factors differ between delirium motor subtypes? A systematic review and meta-analysis

BACKGROUND

Delirium is a common neurocognitive disorder in hospitalised older adults with vast negative consequences. The predominant method of subtyping delirium is by motor activity profile into hypoactive, hyperactive and mixed groups.

OBJECTIVE

This systematic review and meta-analysis investigated how predisposing factors differ between delirium motor subtypes.

METHODS

Databases (Medline, PsycINFO, Embase) were systematically searched for studies reporting predisposing factors (prior to delirium) for delirium motor subtypes. A total of 61 studies met inclusion criteria (N = 14,407, mean age 73.63 years). Random-effects meta-analyses synthesised differences between delirium motor subtypes relative to 22 factors.

RESULTS

Hypoactive cases were older, had poorer cognition and higher physical risk scores than hyperactive cases and were more likely to be women, living in care homes, taking more medications, with worse functional performance and history of cerebrovascular disease than all remaining subtypes. Hyperactive cases were younger than hypoactive and mixed subtypes and were more likely to be men, with better cognition and lower physical risk scores than all other subtypes. Those with no motor subtype (unable to be classified) were more likely to be women and have better functional performance. Effect sizes were small.

CONCLUSIONS

Important differences in those who develop motor subtypes of delirium were shown prior to delirium occurrence. We provide robust quantitative evidence for a common clinical assumption that indices of frailty (institutional living, cognitive and functional impairment) are seen more in hypoactive patients. Motor subtypes should be measured across delirium research. Motor subtyping has great potential to improve the clinical risk assessment and management of delirium.

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.

Development and Validation of a Nomogram for Predicting Postoperative Delirium in Patients With Elderly Hip Fracture Based on Data Collected on Admission

Delirium is a common postoperative complication in elderly hip fracture patients that seriously affects patients’ lives and health, and early delirium risk prediction, and targeted measures can significantly reduce the incidence of delirium. The purpose of this study was to develop and validate a nomogram for the prediction of postoperative delirium (POD) in elderly hip fracture patients. A total of 328 elderly patients with hip fractures enrolled retrospectively in department 1 of our hospital were randomly divided into the training set (n = 230) and the internal validation set (n = 98). The least absolute shrinkage and selection operator (LASSO) regression analysis was used for feature variable selection, and multivariate logistic regression with a backward stepwise method was used to construct a nomogram in the training set. The discrimination efficacy and calibration efficacy of the nomogram were evaluated through the receiver operating characteristic (ROC) curve and calibration curve, respectively. The clinical usefulness was estimated through decision curve analysis (DCA) and clinical impact curve (CIC) analysis. Another validation set from department 2 of our hospital, containing 76 elderly patients with hip fractures, was used for external validation of the nomogram. A total of 43 (13.1%) and 12 (15.8%) patients had POD in department 1 and department 2, respectively. The nomogram was constructed by three predictors, including dementia, chronic obstructive pulmonary disease (COPD), and albumin level. The nomogram showed good discrimination efficacy and calibration efficacy, with the AUC of 0.791 (95% CI, 0.708–0.873), 0.820 (95% CI, 0.676–0.964), and 0.841 (95% CI, 0.717–0.966) in the training set, the internal validation set, and the external validation set, respectively. Both DCA and CIC demonstrated that this nomogram has good clinical usefulness. The nomogram constructed by dementia, COPD, and albumin level can be conveniently used to predict POD in patients with elderly hip fractures.

Monitoring of sedation in mechanically ventilated patients using remote technology

PURPOSE OF REVIEW

Two years of coronavirus disease 2019 (COVID-19) pandemic highlighted that excessive sedation in the ICU leading to coma and other adverse outcomes remains pervasive. There is a need to improve monitoring and management of sedation in mechanically ventilated patients. Remote technologies that are based on automated analysis of electroencephalogram (EEG) could enhance standard care and alert clinicians real-time when severe EEG suppression or other abnormal brain states are detected.

RECENT FINDINGS

High rates of drug-induced coma as well as delirium were found in several large cohorts of mechanically ventilated patients with COVID-19 pneumonia. In patients with acute respiratory distress syndrome, high doses of sedatives comparable to general anesthesia have been commonly administered without defined EEG endpoints. Continuous limited-channel EEG can reveal pathologic brain states such as burst suppression, that cannot be diagnosed by neurological examination alone. Recent studies documented that machine learning-based analysis of continuous EEG signal is feasible and that this approach can identify burst suppression as well as delirium with high specificity.

SUMMARY

Preventing oversedation in the ICU remains a challenge. Continuous monitoring of EEG activity, automated EEG analysis, and generation of alerts to clinicians may reduce drug-induced coma and potentially improve patient outcomes.

Early Clinical and Electrophysiological Brain Dysfunction Is Associated With ICU Outcomes in COVID-19 Critically Ill Patients With Acute Respiratory Distress Syndrome: A Prospective Bicentric Observational Study

OBJECTIVES:

Describe the prevalence of acute cerebral dysfunction and assess the prognostic value of an early clinical and electroencephalography (EEG) assessment in ICU COVID-19 patients.

DESIGN:

Prospective observational study.

SETTING:

Two tertiary critical care units in Paris, France, between April and December 2020.

PATIENTS:

Adult critically ill patients with COVID-19 acute respiratory distress syndrome.

INTERVENTIONS:

Neurologic examination and EEG at two time points during the ICU stay, first under sedation and second 4–7 days after sedation discontinuation.

MEASUREMENTS AND MAIN RESULTS:

Association of EEG abnormalities (background reactivity, continuity, dominant frequency, and presence of paroxystic discharges) with day-28 mortality and neurologic outcomes (coma and delirium recovery). Fifty-two patients were included, mostly male (81%), median (interquartile range) age 68 years (56–74 yr). Delayed awakening was present in 68% of patients (median awakening time of 5 d [2–16 d]) and delirium in 74% of patients who awoke from coma (62% of mixed delirium, median duration of 5 d [3–8 d]). First, EEG background was slowed in the theta-delta range in 48 (93%) patients, discontinuous in 25 patients (48%), and nonreactive in 17 patients (33%). Bifrontal slow waves were observed in 17 patients (33%). Early nonreactive EEG was associated with lower day-28 ventilator-free days (0 vs 16; p = 0.025), coma-free days (6 vs 22; p = 0.006), delirium-free days (0 vs 17; p = 0.006), and higher mortality (41% vs 11%; p = 0.027), whereas discontinuous background was associated with lower ventilator-free days (0 vs 17; p = 0.010), coma-free days (1 vs 22; p < 0.001), delirium-free days (0 vs 17; p = 0.001), and higher mortality (40% vs 4%; p = 0.001), independently of sedation and analgesia.

CONCLUSIONS:

Clinical and neurophysiologic cerebral dysfunction is frequent in COVID-19 ARDS patients. Early severe EEG abnormalities with nonreactive and/or discontinuous background activity are associated with delayed awakening, delirium, and day-28 mortality.

DelIrium VULnerability in GEriatrics (DIVULGE) study: a protocol for a prospective observational study of electroencephalogram associations with incident postoperative delirium

INTRODUCTION

Delirium is a neurocognitive disorder common in older adults in acute care settings. Those who develop delirium are at an increased risk of dementia, cognitive decline and death. Electroencephalography (EEG) during delirium in older adults is characterised by slowing and reduced functional connectivity, but markers of vulnerability are poorly described. We aim to identify EEG spectral power and event-related potential (ERP) markers of incident delirium in older adults to understand neural mechanisms of delirium vulnerability. Characterising delirium vulnerability will provide substantial theoretical advances and outcomes have the potential to be translated into delirium risk assessment tools.

METHODS AND ANALYSIS

We will record EEG in 90 participants over 65 years of age prior to elective coronary artery bypass grafting (CABG) or transcatheter aortic valve implantation (TAVI). We will record 4-minutes of resting state (eyes open and eyes closed) and a 5-minute frequency auditory oddball paradigm. Outcome measures will include frequency band power, 1/f offset and slope, and ERP amplitude measures. Participants will undergo cognitive and EEG testing before their elective procedures and daily postoperative delirium assessments. Group allocation will be done retrospectively by linking preoperative EEG data according to postoperative delirium status (presence, severity, duration and subtype).

ETHICS AND DISSEMINATION

This study is approved by the Human Research Ethics Committee of the Royal Adelaide Hospital, Central Adelaide Local Health Network and the University of South Australia Human Ethics Committee. Findings will be disseminated through peer-reviewed journal articles and presentations at national and international conferences.

TRIAL REGISTRATION NUMBER

ACTRN12618001114235 and ACTRN12618000799257.

Postoperative delirium and neurocognitive disorders

PURPOSE OF REVIEW

Postoperative neurocognitive disorders (NCD) are significant causes of morbidity and mortality. In this paper, we will review our understanding and potential management of postoperative NCD.

RECENT FINDINGS

Postoperative delirium, delayed neurocognitive recovery and postoperative cognitive dysfunction (POCD) are recognized as a part of the continuous spectrum of postoperative NCD. Although the pathophysiology is still poorly understood, there is renewed focus on improving neurocognitive outcomes of aging surgical population. Novel methods of neurocognitive screening are developed and research in the prevention and management of NCD has gained traction.

SUMMARY

A spectrum of NCD exists in surgical patients ranging from postoperative delirium, delayed neurocognitive recovery, and POCD. Identification of patients at-risk for developing NCD can help target appropriate perioperative intervention. Also, specialized care teams and the implementation of standardized protocols are crucial for the successful management perioperative NCD. Finally, large, randomized, multicenter studies are needed to confirm benefits of preventive and treatment strategies.

Diagnosis and Risk Factors for Delirium in Elderly Patients in the Emergency Rooms and Intensive Care Unit of the National Geriatric Hospital Emergency Department: A Cross-Sectional Observational Study

Purpose

To diagnose delirium and identify risk factors for its development in elderly patients in the emergency department (ED) and intensive care units (ICU) at the National Geriatric Hospital (Vietnam).

Patients and Methods

A cross-sectional observational study was conducted with a convenience sample of non-surgical patients admitted to ED and ICU at Hanoi National Geriatric Hospital in Vietnam. In total, 163 patients met the selection criteria and were included in the study. Screening involved using the Confusion Assessment Method (CAM) and the Confusion Assessment Method for the Intensive Care Unit (CAM-ICU). The diagnosis was established according to the DSM-5 and ICD-10 codes.

Results

Delirium was found in a total of 106 (63.1%) patients. The factors significantly affecting its development were vision impairment (OR, 3.3; 95% CI, 1.5 to 7.4, P=0.003), hearing impairment (OR, 3.6; 95% CI, 1.77 to 7.36, P=0.0001), acute or chronic kidney failure (OR, 7.1; 95% CI, 2.05 to 6.39, P<0.001), respiratory disorders (OR, 2.7; 95% CI, 1.4 to 5.2, P=0.004), and malnutrition (OR, 9.17; 95% CI, 3.43–24.5, P=0.0001). The list also include the fall risk factors (OR, 12.2; 95% CI, 4.1–36.3, P=0.0001), frailty (OR, 8.35; 95% CI, 3.4–20.6, P=0.0001), activities of daily living (OR, 8.35; 95% CI, 3.4–20.6, P=0.0001), hyponatremia (OR, 2.48; 95% CI, 1.07 to 5.75, P=0.001), hypernatremia (OR, 13.1; 95% CI, 1.67 to 2.5, P=0.001), and treatment interventions. In addition, delirium was linked to the duration of ICU admission (OR, 6.53; 95% CI, 4.5–25.5, P < 0.0001).

Conclusion

The CAM/CAM-ICU diagnostic algorithm makes it possible to diagnose delirium successfully. The present study confirmed the role of several premorbid and triggering factors in the occurrence of delirium in elderly patients in ED and ICU. There is a need for further research into risk factors for delirium in elderly patients.

Subtypes of delirium after ischaemic stroke-predisposing factors and outcomes: a prospective observational study (PROPOLIS)

BACKGROUND AND PURPOSE

Delirium is a serious complication after stroke. It remains unclear whether different motor subtypes of delirium are associated with diverse risk factors and outcomes. The aim was to investigate if delirium subtypes differ in predisposing factors, clinical characteristics and outcomes.

METHODS

In all, 698 patients with ischaemic stroke or transient ischaemic attack (median age 73 years; 53.7% female) were prospectively included. Core features of delirium during the first 7 days after admission were examined. The Diagnostic and Statistical Manual of Mental Disorders (DSM-5) criteria for delirium were used. Pre-stroke characteristics were compared between different delirium subtypes and logistic regression and Cox proportional hazard models were used to explore the association between delirium, functional outcome and death.

RESULTS

Hyperactive, hypoactive and mixed delirium were diagnosed in 28, 75 and 66 patients, respectively. Patients with hyperactive delirium had less severe neurological deficit on admission and more often had transient ischaemic attack compared with patients with hypoactive and mixed delirium. Compared with patients with hypoactive delirium, those with hyperactive delirium more often suffered from irritability/lability prior to stroke. Hyperactive and hypoactive delirium did not differ in age, sex, comorbidities, pre-stroke dependency, cognitive decline and severity of delirium. Hyperactive, hypoactive and mixed delirium were associated with an increased risk of poor 3- and 12-month functional outcome compared with patients without delirium. Moreover, patients with hypoactive and mixed delirium had an elevated risk of death.

CONCLUSIONS

Hyperactive delirium is associated with less severe stroke and higher scores of pre-existing irritability/lability. All three motor subtypes of delirium are associated with poor outcome, although hyperactive delirium seems to have a less unfavourable prognosis.

Phenotypes and subphenotypes of delirium: a review of current categorisations and suggestions for progression

Delirium is a clinical syndrome occurring in heterogeneous patient populations. It affects 45-87% of critical care patients and is often associated with adverse outcomes including acquired dementia, institutionalisation, and death. Despite an exponential increase in delirium research in recent years, the pathophysiological mechanisms resulting in the clinical presentation of delirium are still hypotheses. Efforts have been made to categorise the delirium spectrum into clinically meaningful subgroups (subphenotypes), using psychomotor subtypes such as hypoactive, hyperactive, and mixed, for example, and also inflammatory and non-inflammatory delirium. Delirium remains, however, a constellation of symptoms resulting from a variety of risk factors and precipitants with currently no successful targeted pharmacological treatment. Identifying specific clinical and biological subphenotypes will greatly improve understanding of the relationship between the clinical symptoms and the putative pathways and thus risk factors, precipitants, natural history, and biological mechanism. This will facilitate risk factor mitigation, identification of potential methods for interventional studies, and informed patient and family counselling. Here, we review evidence to date and propose a framework to identify subphenotypes. Endotype identification may be done by clustering symptoms with their biological mechanism, which will facilitate research of targeted treatments. In order to achieve identification of delirium subphenotypes, the following steps must be taken: (1) robust records of symptoms must be kept at a clinical level. (2) Global collaboration must facilitate large, heterogeneous research cohorts. (3) Patients must be clustered for identification, validation, and mapping of subphenotype stability.

Delirium in critical illness: clinical manifestations, outcomes, and management

Delirium is the most common manifestation of brain dysfunction in critically ill patients. In the intensive care unit (ICU), duration of delirium is independently predictive of excess death, length of stay, cost of care, and acquired dementia. There are numerous neurotransmitter/functional and/or injury-causing hypotheses rather than a unifying mechanism for delirium. Without using a validated delirium instrument, delirium can be misdiagnosed (under, but also overdiagnosed and trivialized), supporting the recommendation to use a monitoring instrument routinely. The best-validated ICU bedside instruments are CAM-ICU and ICDSC, both of which also detect subsyndromal delirium. Both tools have some inherent limitations in the neurologically injured patients, yet still provide valuable information about delirium once the sequelae of the primary injury settle into a new post-injury baseline. Now it is known that antipsychotics and other psychoactive medications do not reliably improve brain function in critically ill delirious patients. ICU teams should systematically screen for predisposing and precipitating factors. These include exacerbations of cardiac/respiratory failure or sepsis, metabolic disturbances (hypoglycemia, dysnatremia, uremia and ammonemia) receipt of psychoactive medications, and sensory deprivation through prolonged immobilization, uncorrected vision and hearing deficits, poor sleep hygiene, and isolation from loved ones so common during COVID-19 pandemic. The ABCDEF (A2F) bundle is a means to facilitate implementation of the 2018 Pain, Agitation/Sedation, Delirium, Immobility, and Sleep Disruption in Adult Patients in the ICU (PADIS) Guidelines. In over 25,000 patients across nearly 100 institutions, the A2F bundle has been shown in a dose-response fashion (i.e., greater bundle compliance) to yield improved survival, length of stay, coma and delirium duration, cost, and less ICU bounce-backs and discharge to nursing homes.

Cognitive Dysfunction After Analgesia and Sedation: Out of the Operating Room and Into the Pediatric Intensive Care Unit

In the midst of concerns for potential neurodevelopmental effects after surgical anesthesia, there is a growing awareness that children who require sedation during critical illness are susceptible to neurologic dysfunctions collectively termed pediatric post-intensive care syndrome, or PICS-p. In contrast to healthy children undergoing elective surgery, critically ill children are subject to inordinate neurologic stress or injury and need to be considered separately. Despite recognition of PICS-p, inconsistency in techniques and timing of post-discharge assessments continues to be a significant barrier to understanding the specific role of sedation in later cognitive dysfunction. Nonetheless, available pediatric studies that account for analgesia and sedation consistently identify sedative and opioid analgesic exposures as risk factors for both in-hospital delirium and post-discharge neurologic sequelae. Clinical observations are supported by animal models showing neuroinflammation, increased neuronal death, dysmyelination, and altered synaptic plasticity and neurotransmission. Additionally, intensive care sedation also contributes to sleep disruption, an important and overlooked variable during acute illness and post-discharge recovery. Because analgesia and sedation are potentially modifiable, understanding the underlying mechanisms could transform sedation strategies to improve outcomes. To move the needle on this, prospective clinical studies would benefit from cohesion with regard to datasets and core outcome assessments, including sleep quality. Analyses should also account for the wide range of diagnoses, heterogeneity of this population, and the dynamic nature of neurodevelopment in age cohorts. Much of the related preclinical evidence has been studied in comparatively brief anesthetic exposures in healthy animals during infancy and is not generalizable to critically ill children. Thus, complementary animal models that more accurately "reverse translate" critical illness paradigms and the effect of analgesia and sedation on neuropathology and functional outcomes are needed. This review explores the interactive role of sedatives and the neurologic vulnerability of critically ill children as it pertains to survivorship and functional outcomes, which is the next frontier in pediatric intensive care.

Does rocking motion calm delirious patients in ICU? A multicentre randomised clinical trial protocol (RockingICU)

BACKGROUND

Rocking chair therapy has been explored in patients with dementia to promote the feeling of relaxation, but not in Intensive Care Unit (ICU) patients with delirium.

AIM

The aim is to investigate the effect of a chair with or without rocking motion on the duration of delirium and intensity of agitation in critically ill patients admitted to the ICU.

DESIGN

This is an investigator-initiated pragmatic, multicentre, parallel-grouped, centrally randomised, stratified, data analyst-blinded trial.

METHOD

We will include patients for 1:1 web-based randomisation, stratified by site in patients 18 y or older with a positive delirium score identified by a validated tool. We will exclude patients mainly due to mobilisation restrictions, body weight exceeding 130 kg, inability to provide consent, and presence of multiresistant bacteria or viral droplet infections. The intervention group will receive a minimum of 20 min of rocking therapy daily. The control group will be transferred to the same type of chair but without rocking therapy daily. A power calculation with a risk reduction of 20%, a power of 80% with an alpha cut-off on 5% and further 20% inclusion gives 76 patients in intervention and control group reaching a total of n = 152 inclusion in the trial.

CONCLUSION

The RockingICU trial will provide important new knowledge and raise research questions regarding nonpharmacological interventions to alleviate delirium in ICU patients.

Delirium Variability is Influenced by the Sound Environment (DEVISE Study): How Changes in the Intensive Care Unit soundscape affect delirium incidence

Quantitative data on the sensory environment of intensive care unit (ICU) patients and its potential link to increased risk of delirium is limited. We examined whether higher average sound and light levels in ICU environments are associated with delirium incidence. Over 111 million sound and light measurements from 143 patient stays in the surgical and trauma ICUs were collected using Quietyme® (Neshkoro, Wisconsin) sensors from May to July 2018 and analyzed. Sensory data were grouped into time of day, then normalized against their ICU environments, with Confusion Assessment Method (CAM-ICU) scores measured each shift. We then performed logistic regression analysis, adjusting for possible confounding variables. Lower morning sound averages (8 am-12 pm) (OR = 0.835, 95% OR CI = [0.746, 0.934], p = 0.002) and higher daytime sound averages (12 pm-6 pm) (OR = 1.157, 95% OR CI = [1.036, 1.292], p = 0.011) were associated with an increased odds of delirium incidence, while nighttime sound averages (10 pm-8 am) (OR = 0.990, 95% OR CI = [0.804, 1.221], p = 0.928) and the ICU light environment did not show statistical significance. Our results suggest an association between the ICU soundscape and the odds of developing delirium. This creates a future paradigm for studies of the ICU soundscape and lightscape.

Neuroanesthesiology Update

This review summarizes the literature published in 2020 that is relevant to the perioperative care of neurosurgical patients and patients with neurological diseases as well as critically ill patients with neurological diseases. Broad topics include general perioperative neuroscientific considerations, stroke, traumatic brain injury, monitoring, anesthetic neurotoxicity, and perioperative disorders of cognitive function.

Delirium

Delirium, a syndrome characterized by an acute change in attention, awareness and cognition, is caused by a medical condition that cannot be better explained by a pre-existing neurocognitive disorder. Multiple predisposing factors (for example, pre-existing cognitive impairment) and precipitating factors (for example, urinary tract infection) for delirium have been described, with most patients having both types. Because multiple factors are implicated in the aetiology of delirium, there are likely several neurobiological processes that contribute to delirium pathogenesis, including neuroinflammation, brain vascular dysfunction, altered brain metabolism, neurotransmitter imbalance and impaired neuronal network connectivity. The Diagnostic and Statistical Manual of Mental Disorders, 5th edition (DSM-5) is the most commonly used diagnostic system upon which a reference standard diagnosis is made, although many other delirium screening tools have been developed given the impracticality of using the DSM-5 in many settings. Pharmacological treatments for delirium (such as antipsychotic drugs) are not effective, reflecting substantial gaps in our understanding of its pathophysiology. Currently, the best management strategies are multidomain interventions that focus on treating precipitating conditions, medication review, managing distress, mitigating complications and maintaining engagement to environmental issues. The effective implementation of delirium detection, treatment and prevention strategies remains a major challenge for health-care organizations globally.

Pathomechanisms of Non-Traumatic Acute Brain Injury in Critically Ill Patients

Delirium, an acute alteration in mental status characterized by confusion, inattention and a fluctuating level of arousal, is a common problem in critically ill patients. Delirium prolongs hospital stay and is associated with higher mortality. The pathophysiology of delirium has not been fully elucidated. Neuroinflammation and neurotransmitter imbalance seem to be the most important factors for delirium development. In this review, we present the most important pathomechanisms of delirium in critically ill patients, such as neuroinflammation, neurotransmitter imbalance, hypoxia and hyperoxia, tryptophan pathway disorders, and gut microbiota imbalance. A thorough understanding of delirium pathomechanisms is essential for effective prevention and treatment of this underestimated pathology in critically ill patients.