Preventing Delirium Takes a Village: Systematic Review and Meta-analysis of Delirium Preventive Models of Care

Delirium Mediated the Association Between a History of Falls and Short-Term Mortality Risk in Critically Ill Ischemic Stroke Patients

Patients with ischemic stroke have an increased propensity to fall, resulting in significant physical and psychological distress. This study examined the association between falls in the 3 months prior to intensive care unit (ICU) admission and mortality within 28 days among 2950 adult ICU patients diagnosed with ischemic stroke from 2008 to 2019, focusing on the potential mediating role of delirium. The primary outcomes were short-term mortality (28, 60, and 90 days) and the risk of delirium. Each patient was followed for at least 1 year. Delirium was primarily assessed using the Confusion Assessment Method for the ICU and by reviewing nursing notes. Group differences between patients with and without a history of falls were compared using the Wilcoxon rank-sum test or the chi-squared test. Cox proportional risk or logistic regression models were used to explore the association between fall history and outcomes, and causal mediation analysis was performed. Results showed that patients with a recent fall history had a significantly increased risk of 28-day (hazard ratio [HR]: 1.62, 95% confidence interval [CI]: 1.35-1.94), 60-day (HR: 1.67, 95% CI: 1.42-1.98), and 90-day mortality (HR: 1.66, 95% CI: 1.41-1.95), as well as an increased risk of delirium (odds ratio: 2.00, 95% CI: 1.66-2.42). Delirium significantly mediated the association between fall history and 28-day mortality (total effect: HR: 1.77, 95% CI: 1.45-2.16; natural indirect effect: HR: 1.12, 95% CI: 1.05-1.21; proportion mediated: 24.6%). These findings suggest that ischemic stroke patients with a recent fall have an increased risk of short-term mortality, partly mediated by delirium. Strategies aimed at preventing delirium may potentially improve prognosis in this patient population.

Post-stroke delirium and challenges for the rehabilitation setting: A narrative review

INTRODUCTION

Post-stroke delirium (PSD) is a common yet underrecognized complication following stroke, with its effect on stroke rehabilitation being the subject of limited attention. The objective of this narrative review is to provide an overview of core issues in PSD including epidemiology, diagnostic challenges, and management considerations, with an emphasis on the rehabilitation phase.

METHODS

Ovid Medline and Google Scholar were searched through February 2023 using keywords related to delirium, rehabilitation, and the post-stroke period. Only studies conducted on adults (≥18 years) and written in the English language were included.

RESULTS

PSD affects approximately 25% of stroke patients, and often persists well into the post-acute phase, with a negative impact on rehabilitation outcomes including lengths of stay, function, and cognition. Certain stroke and patient characteristics can help predict risk for PSD. The diagnosis of delirium becomes more challenging when superimposed on stroke deficits (such as attentional impairment or other cognitive, psychiatric, or behavioural disorders), leading to underdiagnosis, overdiagnosis, or misdiagnosis. Particularly in patients with post-stroke language or cognitive disorders, common screening tools are less accurate. The multidisciplinary rehabilitation team should be involved in management of PSD as rehabilitative activities can be beneficial for patients who can participate safely. Addressing barriers to effective delirium care at various levels of the health care system can improve rehabilitation trajectories for these patients.

CONCLUSIONS

PSD is a disease entity commonly encountered in the rehabilitation setting, but it is challenging to diagnose and manage. New delirium screening tools and management approaches specific for the post-stroke and rehabilitation settings are needed.

The Modified and Extended Hospital Elder Life Program: A remote model of care to expand delirium prevention

BACKGROUND

Delirium is a common complication of hospitalization and is associated with poor outcomes. Multicomponent delirium prevention strategies such as the Hospital Elder Life Program (HELP) have proven effective but rely on face-to-face intervention protocols and volunteer staff, which was not possible due to restrictions during the COVID-19 pandemic. We developed the Modified and Extended Hospital Elder Life Program (HELP-ME), an innovative adaptation of HELP for remote and/or physically distanced applications.

METHODS

HELP-ME protocols were adapted from well-established multicomponent delirium prevention strategies and were implemented at four expert HELP sites. Each site contributed to the protocol modifications and compilation of a HELP-ME Operations Manual with standardized protocols and training instructions during three expert panel working groups. Implementation was overseen and monitored during seven learning sessions plus four coaching sessions from January 8, 2021, through September 24, 2021. Feasibility of implementing HELP-ME was measured by protocol adherence rates. Focus groups were conducted to evaluate the acceptability, provide feedback, and identify facilitators and barriers to implementation.

RESULTS

A total of 106 patients were enrolled across four sites, and data were collected for 214 patient-days. Overall adherence was 82% (1473 completed protocols/1798 patient-days), achieving our feasibility target of >75% overall adherence. Individual adherence rates ranged from 55% to 96% across sites for the individual protocols. Protocols with high adherence rates included the nursing delirium protocol (96%), nursing medication review (96%), vision (89%), hearing (87%), and orientation (88%), whereas lower adherence occurred with fluid repletion (64%) and range-of-motion exercises (55%). Focus group feedback was generally positive for acceptability, with recommendations that an optimal approach would be hybrid, balancing in-person and remote interventions for potency and long-term sustainability.

CONCLUSIONS

HELP-ME was fully implemented at four HELP sites, demonstrating feasibility and acceptability. Testing hybrid approaches and evaluating effectiveness is recommended for future work.

The inter-relationship between delirium and dementia: the importance of delirium prevention

Delirium and dementia are two frequent causes of cognitive impairment among older adults and have a distinct, complex and interconnected relationship. Delirium is an acute confusional state characterized by inattention, cognitive dysfunction and an altered level of consciousness, whereas dementia is an insidious, chronic and progressive loss of a previously acquired cognitive ability. People with dementia have a higher risk of developing delirium than the general population, and the occurrence of delirium is an independent risk factor for subsequent development of dementia. Furthermore, delirium in individuals with dementia can accelerate the trajectory of the underlying cognitive decline. Delirium prevention strategies can reduce the incidence of delirium and associated adverse outcomes, including falls and functional decline. Therefore, delirium might represent a modifiable risk factor for dementia, and interventions that prevent or minimize delirium might also reduce or prevent long-term cognitive impairment. Additionally, understanding the pathophysiology of delirium and the connection between delirium and dementia might ultimately lead to additional treatments for both conditions. In this Review, we explore mechanisms that might be common to both delirium and dementia by reviewing evidence on shared biomarkers, and we discuss the importance of delirium recognition and prevention in people with dementia.

In this Review, Fong and Inouye explore mechanisms that might be common to both delirium and dementia. They present delirium as a possible modifiable risk factor for dementia and discuss the importance of delirium prevention strategies in reducing this risk.

Delirium and dementia are frequent causes of cognitive impairment among older adults and have a distinct, complex and interconnected relationship.

Delirium prevention strategies have been shown to reduce not only the incidence of delirium but also the incidence of adverse outcomes associated with delirium such as falls and functional decline.

Adverse outcomes associated with delirium, such as the onset of dementia symptoms in individuals with preclinical dementia, and/or the acceleration of cognitive decline in individuals with dementia might also be delayed by the implementation of delirium prevention strategies.

Evidence regarding the association of systemic inflammatory and neuroinflammatory biomarkers with delirium is variable, possibly as a result of co-occurring dementia pathology or disruption of the blood–brain barrier.

Alzheimer disease pathology, even prior to the onset of symptoms, might have an effect on delirium risk, with potential mechanisms including neuroinflammation and gene–protein interactions with the APOE ε4 allele.

Novel strategies, including proteomics, multi-omics, neuroimaging, transcranial magnetic stimulation and EEG, are beginning to reveal how changes in cerebral blood flow, spectral power and connectivity can be associated with delirium; further work is needed to expand these findings to patients with delirium superimposed upon dementia.

Cost-effectiveness of clinical interventions for delirium: A systematic literature review of economic evaluations

OBJECTIVE

Little is known about the economic value of clinical interventions for delirium. This review aims to synthesise and appraise available economic evidence, including resource use, costs, and cost-effectiveness of interventions for reducing, preventing, and treating delirium.

METHODS

Systematic review of published and grey literature on full and partial economic evaluations. Study quality was assessed using the Consolidated Health Economic Evaluation Reporting Standards (CHEERS).

RESULTS

Fourteen economic evaluations (43% full, 57% partial) across nine multicomponent and nonpharmacological intervention types met inclusion criteria. The intervention costs ranged between US$386 and $553 per person in inpatient settings. Multicomponent delirium prevention intervention and the Hospital Elder Life Program (HELP) reported statistically significant cost savings or cost offsets somewhere else in the health system. Cost savings related to inpatient, outpatient, and out-of-pocket costs ranged between $194 and $6022 per person. The average CHEERS score was 74% (±SD 10%).

CONCLUSION

Evidence on a joint distribution of costs and outcomes of delirium interventions was limited, varied and of generally low quality. Directed expansion of health economics towards the evaluation of delirium care is necessary to ensure effective implementation that meets patients' needs and is cost-effective in achieving similar or better outcomes for the same or lower cost.

Longitudinal validation of an electronic health record delirium prediction model applied at admission in COVID-19 patients

OBJECTIVE

To validate a previously published machine learning model of delirium risk in hospitalized patients with coronavirus disease 2019 (COVID-19).

METHOD

Using data from six hospitals across two academic medical networks covering care occurring after initial model development, we calculated the predicted risk of delirium using a previously developed risk model applied to diagnostic, medication, laboratory, and other clinical features available in the electronic health record (EHR) at time of hospital admission. We evaluated the accuracy of these predictions against subsequent delirium diagnoses during that admission.

RESULTS

Of the 5102 patients in this cohort, 716 (14%) developed delirium. The model's risk predictions produced a c-index of 0.75 (95% CI, 0.73-0.77) with 27.7% of cases occurring in the top decile of predicted risk scores. Model calibration was diminished compared to the initial COVID-19 wave.

CONCLUSION

This EHR delirium risk prediction model, developed during the initial surge of COVID-19 patients, produced consistent discrimination over subsequent larger waves; however, with changing cohort composition and delirium occurrence rates, model calibration decreased. These results underscore the importance of calibration, and the challenge of developing risk models for clinical contexts where standard of care and clinical populations may shift.

Predicting Delirium Risk Using an Automated Mayo Delirium Prediction Tool: Development and Validation of a Risk-Stratification Model

OBJECTIVE

To develop a delirium risk-prediction tool that is applicable across different clinical patient populations and can predict the risk of delirium at admission to hospital.

METHODS

This retrospective study included 120,764 patients admitted to Mayo Clinic between January 1, 2012, and December 31, 2017, with age 50 and greater. The study group was randomized into a derivation cohort (n=80,000) and a validation cohort (n=40,764). Different risk factors were extracted and analyzed using least absolute shrinkage and selection operator (LASSO) penalized logistic regression.

RESULTS

The area under the receiver operating characteristic curve (AUROC) for Mayo Delirium Prediction (MDP) tool using derivation cohort was 0.85 (95% confidence interval [CI], .846 to .855). Using the regression coefficients obtained from the derivation cohort, predicted probability of delirium was calculated for each patient in the validation cohort. For the validation cohort, AUROC was 0.84 (95% CI, .834 to .847). Patients were classified into 1 of the 3 risk groups, based on their predicted probability of delirium: low (≤5%), moderate (6% to 29%), and high (≥30%). In the derivation cohort, observed incidence of delirium was 1.7%, 12.8%, and 44.8% (low, moderate, and high risk, respectively), which is similar to the incidence rates in the validation cohort of 1.9%, 12.7%, and 46.3%.

CONCLUSION

The Mayo Delirium Prediction tool was developed from a large heterogeneous patient population with good validation results and appears to be a reliable automated tool for delirium risk prediction with hospitalization. Further prospective validation studies are required.

Stratified delirium risk using prescription medication data in a state-wide cohort

OBJECTIVE

Delirium is a common condition associated with increased morbidity and mortality. Medication side effects are a possible source of modifiable delirium risk and provide an opportunity to improve delirium predictive models. This study characterized the risk for delirium diagnosis by applying a previously validated algorithm for calculating central nervous system adverse effect burden arising from a full medication list.

METHOD

Using a cohort of hospitalized adult (age 18-65) patients from the Massachusetts All-Payers Claims Database, we calculated medication burden following hospital discharge and characterized risk of new coded delirium diagnosis over the following 90 days. We applied the resulting model to a held-out test cohort.

RESULTS

The cohort included 62,180 individuals of whom 1.6% (1019) went on to have a coded delirium diagnosis. In the training cohort (43,527 individuals), the medication burden feature was positively associated with delirium diagnosis (OR = 5.75, 95% CI 4.34-7.63) and this association persisted (aOR = 1.95; 1.31-2.92) after adjusting for demographics, clinical features, prescribed medications, and anticholinergic risk score. In the test cohort, the trained model produced an area under the curve of 0.80 (0.78-0.82). This performance was similar across subgroups of age and gender.

CONCLUSION

Aggregating brain-related medication adverse effects facilitates identification of individuals at high risk of subsequent delirium diagnosis.

Delirium

Delirium is an acute confusional state that is common and costly and is associated with significant functional decline and distress. It is the manifestation of acute encephalopathy and is variably called acute brain failure, acute brain dysfunction, or altered mental status. All patients are at risk for delirium, although those with more vulnerabilities (such as advanced age, exposures to other stressors like infection, and certain medications) are at higher risk. The pathophysiologic cause of delirium is not well understood. It is important to recognize patients at risk for and those with delirium and to immediately identify and treat factors contributing to it. There is no single intervention or medication to treat delirium, making it challenging to manage. Therefore, risk mitigation and prompt treatment rely on a sophisticated strategy to address the contributing factors. Delirium may be prevented or attenuated when multimodal strategies are used, thereby improving patient outcomes.

Inter-rater reliability and validity of risk of bias instrument for non-randomized studies of exposures: a study protocol

BACKGROUND

A new tool, "risk of bias (ROB) instrument for non-randomized studies of exposures (ROB-NRSE)," was recently developed. It is important to establish consistency in its application and interpretation across review teams. In addition, it is important to understand if specialized training and guidance will improve the reliability in the results of the assessments. Therefore, the objective of this cross-sectional study is to establish the inter-rater reliability (IRR), inter-consensus reliability (ICR), and concurrent validity of the new ROB-NRSE tool. Furthermore, as this is a relatively new tool, it is important to understand the barriers to using this tool (e.g., time to conduct assessments and reach consensus-evaluator burden).

METHODS

Reviewers from four participating centers will apprise the ROB of a sample of NRSE publications using ROB-NRSE tool in two stages. For IRR and ICR, two pairs of reviewers will assess the ROB for each NRSE publication. In the first stage, reviewers will assess the ROB without any formal guidance. In the second stage, reviewers will be provided customized training and guidance. At each stage, each pair of reviewers will resolve conflicts and arrive at a consensus. To calculate the IRR and ICR, we will use Gwet's AC₁ statistic. For concurrent validity, reviewers will appraise a sample of NRSE publications using both the Newcastle-Ottawa Scale (NOS) and ROB-NRSE tool. We will analyze the concordance between the two tools for similar domains and for the overall judgments using Kendall's tau coefficient. To measure evaluator burden, we will assess the time taken to apply ROB-NRSE tool (without and with guidance), and the NOS. To assess the impact of customized training and guidance on the evaluator burden, we will use the generalized linear models. We will use Microsoft Excel and SAS 9.4, to manage and analyze study data, respectively.

DISCUSSION

The quality of evidence from systematic reviews that include NRSE depends partly on the study-level ROB assessments. The findings of this study will contribute to an improved understanding of ROB-NRSE and how best to use it.