Recent Insights on Prevalence and Corelations of Hypoactive Delirium

Point prevalence and clinical profile of patients with delirium admitted in internal medicine department at tertiary care centre in eastern Nepal: a descriptive cross-sectional study

Introduction

Delirium, marked by acute disturbances in consciousness and cognition, remains underdiagnosed despite its significant impact on morbidity and mortality. This study investigates the point prevalence and clinical profile of delirium in patients at an eastern Nepal tertiary care centre.

Methods

A 1-month descriptive cross-sectional study involved 152 Internal Medicine Department patients at BPKIHS, Dharan. Data, collected through face-to-face interviews and the Confusion Assessment Method (CAM), analyzed demographic details, clinical history, and laboratory findings. Ethical clearance and informed consent were obtained.

Results

Among 152 participants, 13.2% exhibited delirium, with notable risk factors identified. Elderly patients (≥65 years) and those with nasogastric tubes faced higher risks. Significant associations were found with cardiovascular diseases (P=0.002), central nervous system diseases (P=0.015), and alcoholism (P=0.003). Laboratory findings revealed correlations with elevated creatinine, hyperuremia, and abnormal aspartate aminotransferase levels. The study emphasizes key contributors to delirium, providing valuable insights for clinicians in identifying, preventing, and managing delirium in a hospital setting.

Conclusions

This study provides critical insights into delirium prevalence and profiles in Eastern Nepal. Identified risk factors underscore the importance of routine screenings and targeted interventions for at-risk populations. Study limitations, including sample size and single-centre focus, call for further research to validate findings and enhance our understanding of delirium's management across diverse healthcare settings. Overall, the study informs clinical practices and prompts broader exploration of delirium in healthcare contexts.

Knowledge, attitude and practice regarding hypoactive delirium among ICU nurses: A nationwide cross-sectional study

AIMS AND OBJECTIVES

This study aimed to assess the knowledge, attitude and practice (KAP) of intensive care unit (ICU) nurses in patients with hypoactive delirium in China.

BACKGROUND

The presentation of hypoactive delirium is not obvious and tends to be ignored. However, it has a high incidence and can cause critical impairment. Although nurses are the primary caregivers of patients, the evidence of the current status of KAP of hypoactive delirium among ICU nurses is insufficient in China.

DESIGN

The study participants were 2835 ICU nurses from 201 hospitals in 69 cities from 31 provinces in China.

METHODS

The current status of KAP of hypoactive delirium among ICU nurses was determined using a self-reported structured questionnaire, including 52 questions covering general personal information; three dimensions of KAP; and relevant issues. Descriptive analyses of the sample distribution were reported as percentages and medians. The factors were detected using univariate and multivariate analyses. To guide the reporting of the research, a STROBE checklist of cross-sectional studies was used.

RESULTS

Of the 3101 returned questionnaires, 2835 were analyzed. Approximately 64. 94 % and 53. 30 % of them were identified with a positive attitude and appropriate practice, respectively, whereas only 1. 48 % showed a good level of knowledge. The regression analysis showed that age, years of working in the ICU, educational background, professional title, caring for patients with delirium, attending training on hypoactive delirium and hospital grading were significantly associated with their KAP status(P＜005).

CONCLUSIONS

Hypoactive delirium is an ignored entity by nursing professionals, with no definite nursing procedure. This study shows that receiving relevant training is a factor affecting KAP status, indicating that training should be strengthened. Additionally, appropriate screening and nursing procedures should be developed to standardize the behavior of ICU nurses and improve the quality of care.

RELEVANCE TO CLINICAL PRACTICE

ICU nurses have poor knowledge of hypoactive delirium and related training should be strengthened, especially for middle-aged nurses. Screening and nursing procedures should be set up, which is critical to promote nursing practice.

NO PATIENT OR PUBLIC CONTRIBUTION

None.

Prevalence of delirium in gastroenterology/hepatology units: A cross-sectional study

Prevalence rates of delirium amount to 22.0% within acute-care settings. In contrast, 30-40% of patients with liver cirrhosis may develop hepatic encephalopathy, a condition that has been classified as a syndrome of delirium, based on recent pathophysiology findings. However, the prevalence of delirium in gastroenterology and hepatology units is unknown.The aims of the study were (i) to identify delirium prevalence rates in inpatients of gastroenterology/hepatology wards, (ii) to analyze the delirium motor subtype, and (iii) to assess associations between delirium and patient characteristics.In this monocentric, cross-sectional, epidemiological study, point prevalence was assessed at six time points in three gastroenterology/hepatology units within a German university hospital. Delirium was assessed using the 4 'As' Test (4AT) and delirium subtype by the delirium motor subtype scale. Patient characteristics were collected from patient charts.The sample consisted of 188 patients, aged 18 to 98 years (mean age 64, n=110 male). Of them, 18.1% of patients showed delirium symptoms (61.8% hypoactive, 29.4% mixed, and 8.8% hyperactive). For the participants aged ≥65 years (n=96), prevalence of delirium amounted to 26.0%. Significant associations were observed between delirium and the following characteristics: age (p=0.001), length of hospital stay until assessment (p=0.043), cerebrovascular disease (p=0.002), dementia (p=0.010), diabetes mellitus with chronic complications (p=0.012), and gender (nonsignificant trend, p=0.050), while no association was detected between moderate or severe liver disease and delirium (p=0.414).In conclusion, overall prevalence rates of delirium were rather low and did not increase in patients with liver disease.

Heterogeneity in the definition of delirium in ICUs and association with the intervention effect in randomized controlled trials: a meta-epidemiological study

PURPOSE

To evaluate the heterogeneity in the definition of delirium in randomized controlled trials (RCTs) included in meta-analyses of delirium in intensive care units (ICUs) and to explore whether intervention effect depends on the definition used.

METHODS

We searched PubMed for meta-analyses including RCTs evaluating prevention or treatment strategies of delirium in ICU. The definition of delirium was collected from RCTs and classified as validated (DSM criteria, CAM-ICU, ICDSC, NEECHAM, DRS-R98) or non-validated (non-validated scales, set of symptoms, physician appreciation or not reported). We conducted a meta-epidemiological analysis to compare intervention effects between trials using or not a validated definition by a two-step method as primary analysis and a multilevel model as secondary analysis. A ratio of odds ratios (ROR) < 1 indicated larger intervention effects in trials using a non-validated definition.

RESULTS

Of 149 RCTs (41 meta-analyses), 109 (73.1%) used a validated definition and 40 (26.8%) did not (including 31 [20.8%] not reporting the definition). The primary analysis of 7 meta-analyses (30 RCTs) found no significant difference in intervention effects between trials using a validated definition and the others (ROR = 0.54, 95% CI 0.27-1.08), whereas the secondary multilevel analysis including 12 meta-analyses (67 RCTs) found significantly larger effects for trials using a non-validated versus a validated definition (ROR = 0.36, 95% CI 0.21-0.62).

CONCLUSION

The definition of delirium was heterogeneous across RCTs, with one-fifth not reporting how they evaluated delirium. We did not find a significant association with intervention effect in the primary analysis. The secondary analysis including more studies revealed significantly larger intervention effects in trials using a non-validated versus a validated definition.

Catatonia Due to General Medical Conditions in Psychiatric Patients: Implications for Clinical Practice

Catatonic syndrome is frequently observed over the course of severe mental disorders and general medical conditions, but when catatonia occurs in psychiatric patients with co-morbid medical or neurologic conditions, diagnosis and management may be challenging. Several medical conditions may cause catatonia in psychiatric patients, but some, such as brain injury, infections, hyponatremia and critical illness, may be most relevant in this population. Alongside appropriate etiologic treatment, benzodiazepines and electroconvulsive therapy in refractory cases are effective and safe, and may resolve catatonic syndrome rapidly. When newly-onset psychotic symptoms in catatonic patients with established psychotic disorders occur, delirium should be suspected and appropriately managed. An extensive clinical and laboratory diagnostic workup to determine the underlying etiology of catatonic syndrome should be carried out. In cases of acute multi-morbidity, the exact cause of catatonic syndrome in psychiatric patients may be unclear. It is recommended to avoid antipsychotic drugs in acutely catatonic patients, because they may exacerbate the catatonic symptoms. The akinetic type of catatonia should be differentiated from hypoactive delirium, as treatments for these syndromes differ substantially. When a psychiatric patient presents with symptomatology of both catatonia and delirium, treatment is particularly challenging.

Nurses’ competence in recognition and management of delirium in older patients: development and piloting of a self-assessment tool

Background

Delirium is a common condition in elderly inpatients. Health care professionals play a crucial role in recognizing delirium, initiating preventive measures and implementing a multicomponent treatment strategy. Yet, delirium often goes unrecognized in clinical routine. Nurses take an important role in preventing and managing delirium. This study assesses clinical reasoning of nurses using case vignettes to explore their competences in recognizing, preventing and managing delirium.

Methods

The study was conducted as an online survey. The questionnaire was based on five case vignettes presenting cases of acutely ill older patients with different subtypes of delirium or diseases with overlapping symptoms. In a first step, case vignettes were developed and validated through a multidisciplinary expert panel. Scoring of response options were summed up to a Geriatric Delirium Competence Questionnaire (GDCQ) score including recognition and management tasks The questionnaire was made available online. Descriptive analyses and group comparisons explores differences between nurses from different settings. Factors explaining variance in participants’ score were evaluated using correlations and linear regression models.

Results

The questionnaire demonstrated good content validity and high reliability (kappa = 0.79). The final sample consisted of 115 nurses. Five hundred seventy-five case vignettes with an accuracy of 0.71 for the correct recognition of delirium presence or absence were solved. Nurses recognized delirium best in cases describing hyperactive delirium (79%) while hypoactive delirium was recognized least (44%). Nurses from geriatric and internal medicine departments had significantly higher GDCQ-score than the other subgroups. Management tasks were correctly identified by most participants.

Conclusions

Overall, nurses’ competence regarding hypoactive delirium should be strengthened. The online questionnaire might facilitate targeting training opportunities to nurses’ competence.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12877-022-03573-8.

Stroke, Seizures, Hallucinations and Postoperative Delirium as Neurological Complications after Cardiac Surgery and Percutaneous Valve Replacement

(1) Background: Neurological complications such as acute ischemic stroke or postoperative delirium are frequent after cardiac surgery or percutaneous valve replacement. This study aimed to identify corresponding risk factors. (2) Methods: 297 patients with percutaneous valve replacement or cardiac surgery were postoperatively screened for neurological complications such as delirium, stroke, seizures and hallucinations twice daily for three days. Pre- and perioperative risk factors were evaluated in a multivariate model. (3) Results: Neurological complications occurred in 43.8% (n = 130) as composed of delirium (43.43%, n = 129), stroke (2.7%, n = 8), seizures (1.35%, n = 4) and real hallucinations (3.36%, n = 10). Multiple logistic regression revealed an association of neurological complications with lower Montreal Cognitive Assessment scores (Exp(B) 2.042; 95% CI, 1.183−3.525, p = 0.010), older age (Exp(B) 1.071; 95% CI, 1.036−1.107, p < 0.001), red blood cell transfusions until postoperative day 3 (Exp(B) 1.157; 95% CI, 1.030−1.300, p = 0.014), history of heart failure (Exp(B) 1.985; 95% CI, 1.130−3.487, p = 0.017) and increased CRP levels (Exp(B) 1.004; 95% CI, 1.000−1.008, p = 0.037). (4) Conclusions: Postoperative delirium remains a frequent complication after cardiac surgery, while stroke and seizures occur rarely. A preoperative risk profile including older age, history of heart failure and cognitive impairment was identified for a complicated postoperative course. However, the impact of an intense inflammatory response must not be neglected.

Outcomes of critically ill COVID-19 survivors and caregivers: a case study-centred narrative review

PURPOSE

Critical illness is a transformative experience for both patients and their family members. For COVID-19 patients admitted to the intensive care unit (ICU), survival may be the start of a long road to recovery. Our knowledge of the post-ICU long-term sequelae of acute respiratory distress syndrome (ARDS) and severe acute respiratory syndrome (SARS) may inform our understanding and management of the long-term effects of COVID-19.

SOURCE

We identified international and Canadian epidemiologic data on ICU admissions for COVID-19, COVID-19 pathophysiology, emerging ICU practice patterns, early reports of long-term outcomes, and federal support programs for survivors and their families. Centred around an illustrating case study, we applied relevant literature from ARDS and SARS to contextualize knowledge within emerging COVID-19 research and extrapolate findings to future long-term outcomes.

PRINCIPAL FINDINGS

COVID-19 is a multisystem disease with unknown long-term morbidity and mortality. Its pathophysiology is distinct and unique from ARDS, SARS, and critical illness. Nevertheless, based on initial reports of critical care management for COVID-19 and the varied injurious supportive practices employed in the ICU, patients and families are at risk for post-intensive care syndrome. The distinct incremental risk of COVID-19 multiple organ dysfunction is unknown. The risk of mood disorders in family members may be further exacerbated by imposed isolation and stigma.

CONCLUSION

Emerging literature on COVID-19 outcomes suggests some similarities with those of ARDS/SARS and prolonged mechanical ventilation. The pathophysiology of COVID-19 is presented here in the context of early outcome data and to inform an agenda for longitudinal research for patients and families.

Intraoperative Glycemic Variability and Mean Glucose are Predictors for Postoperative Delirium After Cardiac Surgery: A Retrospective Cohort Study

Purpose

Postoperative delirium (POD) is a common but serious complication after cardiac surgery and is associated with various short- and long-term outcomes. In this study, we investigated the effects of intraoperative glycemic variability (GV) and other glycemic variables on POD after cardiac surgery.

Patients and Methods

A retrospective single-center cohort analysis was conducted using data from electronic medical record from 2018 to 2020. A total of 705 patients undergoing coronary artery bypass graft surgery and/or valve surgery, and/or aortic replacement surgery were included in the analysis. Intraoperative GV was assessed with a coefficient of variation (CV), which was defined as the standard deviation of five intraoperative blood glucose measurements divided by the mean. POD assessment was performed three times a day in the ICU and twice a day in the ward until discharge by trained medical staff. POD was diagnosed if any of the Confusion Assessment Method for the Intensive Care Unit was positive in the ICU, and the Confusion Assessment Method was positive in the ward. Multivariable logistic regression was used to identify associations between intraoperative GV and POD.

Results

POD occurred in 306 (43.4%) patients. When intraoperative glycemic CV was compared as a continuous variable, the delirium group had higher intraoperative glycemic CV than the non-delirium group (22.59 [17.09, 29.68] vs 18.19 [13.00, 23.35], p < 0.001), and when intraoperative glycemic CV was classified as quartiles, the incidence of POD increased as intraoperative glycemic CV quartiles increased (first quartile 29.89%; second quartile 36.67%; third quartile 44.63%; and fourth quartile 62.64%, p < 0.001). In the multivariable logistic regression model, patients in the third quartile of intraoperative glycemic CV were 1.833 times (OR 1.833, 95% CI: 1.132–2.967, p = 0.014), and patients in the fourth quartile of intraoperative glycemic CV were 3.645 times (OR 3.645, 95% CI: 2.235–5.944, p < 0.001) more likely to develop POD than those in the first quartile of intraoperative glycemic CV.

Conclusion

Intraoperative blood glucose fluctuation, manifested by intraoperative GV, is associated with POD after cardiac surgery. Patients with a higher intraoperative GV have an increased risk of POD.

Delirium and Associated Factors in a Cohort of Hospitalized Patients With Coronavirus Disease 2019

BACKGROUND

The coronavirus disease 2019 (COVID-19) pandemic dramatically increased the number of patients requiring treatment in an intensive care unit or invasive mechanical ventilation worldwide. Delirium is a well-known neuropsychiatric complication of patients with acute respiratory diseases, representing the most frequent clinical expression of acute brain dysfunction in critically ill patients, especially in those undergoing invasive mechanical ventilation. Among hospitalized patients with COVID-19, delirium incidence ranges from 11% to 80%, depending on the studied population and hospital setting.

OBJECTIVE

To determine risk factors for the development of delirium in hospitalized patients with COVID-19 pneumonia.

METHODS

We retrospectively studied consecutive hospitalized adult (≥18 y) patients with confirmed COVID-19 pneumonia from March 15 to July 15, 2020, in a tertiary-care hospital in Mexico City. Delirium was assessed by the attending physician or trained nurse, with either the Confusion Assessment Method for the Intensive Care Unit or the Confusion Assessment Method brief version, according to the appropriate diagnostic tool for each hospital setting. Consultation-liaison psychiatrists and neurologists confirmed all diagnoses. We calculated adjusted hazard ratios (aHR) with 95% confidence interval (CI) using a Cox proportional-hazards regression model.

RESULTS

We studied 1017 (64.2% men; median age, 54 y; interquartile range 44-64), of whom 166 (16.3%) developed delirium (hyperactive in 75.3%); 78.9% of our delirium cases were detected in patients under invasive mechanical ventilation. The median of days from admission to diagnosis was 14 (interquartile range 8-21) days. Unadjusted mortality rates between delirium and no delirium groups were similar (23.3% vs. 24.1; risk ratio 0.962, 95% CI 0.70-1.33). Age (aHR 1.02, 95% CI 1.01-1.04; P = 0.006), an initial neutrophil-to-lymphocyte ratio ≥9 (aHR 1.81, 95% CI 1.23-2.65; P = 0.003), and requirement of invasive mechanical ventilation (aHR 3.39, 95% CI 1.47-7.84; P = 0.004) were independent risk factors for in-hospital delirium development.

CONCLUSIONS

Delirium is a common in-hospital complication of patients with COVID-19 pneumonia, associated with disease severity; given the extensive number of active COVID-19 cases worldwide, it is essential to detect patients who are most likely to develop delirium during hospitalization. Improving its preventive measures may reduce the risk of the long-term cognitive and functional sequelae associated with this neuropsychiatric complication.

Delirium in Intensive Care Units: Perceptions of Physicians and Nurses

Delirium is an indicator of morbidity and mortality in intensive care unit (ICU) patients. It can lead to negative outcomes and longer hospital stays, thus increasing hospital costs. Despite national recommendations for daily assessment of delirium, it remains underdiagnosed. Many studies point to a lack of knowledge among health care professionals to accurately detect and manage ICU delirium. The aim of our study was to assess the knowledge, attitudes, and practices of Palestinian health care professionals regarding ICU delirium. The results of a cross-section observational study revealed that delirium appears to be often underrecognized or misdiagnosed in ICUs in Palestine. Therefore, it is critical to further educate the medical and nursing teams and to promote the use of validated tools that can aid in the assessment of this condition. In this way, the length of hospital stays and related health care costs can be reduced.

A Systematic Review and Pooled Prevalence of Delirium in Critically Ill Children

OBJECTIVES

Pediatric delirium is a neuropsychiatric disorder with disrupted cerebral functioning due to underlying disease and/or critical care treatment. Pediatric delirium can be classified as hypoactive, hyperactive, and mixed. This systematic review was conducted to estimate the pooled prevalence of pediatric delirium using validated assessment tools in children (Cornell Assessment of Pediatric Delirium, Pediatric Confusion Assessment Method for the ICU, PreSchool Confusion Assessment Method for the ICU, Pediatric Confusion Assessment Method for the ICU Severity Scale, and Sophia Observation Withdrawal Symptoms Pediatric Delirium scale), identify modifiable and nonmodifiable risk factors, and explore the association of pediatric delirium with clinical outcomes.

DATA SOURCES

A systematic search of PubMed, EMBASE, and CINAHL databases was undertaken for full articles pertaining to pediatric delirium prevalence.

STUDY SELECTION

No language or date barriers were set. Studies were included where the following eligibility criteria were met: study design aimed to estimate pediatric delirium prevalence arising from treatment in the intensive care setting, using a validated tool. Only randomized controlled trials, cross-sectional studies, or cohort studies allowing an estimate of the prevalence of pediatric delirium were included.

DATA EXTRACTION

Data were extracted by the primary researcher (D.S.) and accuracy checked by coauthors.

DATA SYNTHESIS

A narrative synthesis and pooled prevalence meta-analysis were undertaken.

CONCLUSIONS

Pediatric delirium, as determined by the Cornell Assessment of Pediatric Delirium score, is estimated to occur in 34% of critical care admissions. Eight of 11 studies reporting on subtype identified hypoactive delirium as most prevalent (46-81%) with each of the three remaining reporting either hyperactive (44%), mixed (57%), or equal percentages of hypoactive and mixed delirium (43%) as most prevalent. The development of pediatric delirium is associated with cumulative doses of benzodiazepines, opioids, the number of sedative classes used, deep sedation, and cardiothoracic surgery. Increased time mechanically ventilated, length of stay, mortality, healthcare costs, and associations with decreased quality of life after discharge were also found. Multi-institutional and longitudinal studies are required to better determine the natural history, true prevalence, long-term outcomes, management strategies, and financial implications of pediatric delirium.

Prevalence and risk factors of delirium and subsyndromal delirium in older adults

Background

Delirium is a common geriatric problem associated with poor outcomes. Subsyndromal delirium (SSD) is characterized by the presence of certain symptoms of delirium yet, not satisfying the definition of full-blown delirium, defined by categorical elements, and is usually referred to as the presence of one or more symptoms in the confusion assessment method (CAM). This study aimed to investigate the prevalence and risk factors of delirium and SSD in older adults admitted to the hospital. Five hundred eighty-eight elderly (above 65 years) Egyptian patients were recruited from January 2019 to February 2020. After explaining the purpose of the study and assuring the confidentiality of all participants, an informed consent was obtained from the participant or a responsible care giver for those who were not able to give consent. All patients were subjected ‘on admission’ to thorough history taking, clinical examination, and comprehensive geriatric assessment including confusion assessment tools, mini-mental state examination, and functional assessment using Barthel index score.

Results

The current study showed that 19.6% of patients had delirium and 14.1% of patients had SSD with combined prevalence of 33.7%. Most common causes included metabolic, infection, organic brain syndrome, and dehydration. The current study reported significant proportionate relation between cognitive assessment and functional ability, so patients with a score of 23 MMSE had good functional ability, while cognitive assessment using mini-mental score shows inversed relation to delirium and SSD using CAM score.

Conclusion

Delirium is independently associated with adverse short-term and long-term outcomes, including an increase in mortality, length of hospital stay, discharge to an institution, and functional decline on discharge. Subsyndromal delirium (SSD) is characterized by the presence of certain symptoms of delirium, not yet satisfying the definition of full-blown delirium but it can identify patients with early cognitive and functional disabilities, and because of high prevalence of delirium and SSD. Efforts to prevent or early detection may identify patients who warrant clinical attention.

Risk factors of postoperative delirium after cardiac surgery: a meta-analysis

Background

Postoperative delirium is a frequent event after cardiac surgery. This meta-analysis aimed to identify relevant risk factors.

Method

In this meta-analysis, all original researches regarding patients undergoing mixed types of cardiac surgery (excluding transcatheter procedures) and postoperative delirium were evaluated for inclusion. On July 28th 2020, we searched PubMed, Embase, Web of Science and Scopus. Data about name of first author, year of publication, inclusion and exclusion criteria, research design, setting, method of delirium assessment, incidence of delirium, odds ratio (OR) and corresponding 95% confidence interval (CI) of risk factors, and other information relevant was collected. OR and 95% CI were used as metrics for summarized results. Random effects model was applied.

Results

Fourteen reports were included with a total sample size of 13,286. The incidence of delirium ranged from 4.1 to 54.9%. Eight risk factors were identified including aging, diabetes, preoperative depression, mild cognitive impairment, carotid artery stenosis, NYHA functional class III or IV, time of mechanical ventilation and length of intensive care unit stay.

Conclusion

In this study several risk factors associated with postoperative delirium after cardiac surgery were identified. Utilizing the information may allow us to identifying patients at high risk of developing postoperative delirium prior to delirium onset.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13019-021-01496-w.

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.

Delirium Superimposed on Dementia in Perioperative Period and Intensive Care

Delirium is a life-threatening condition, the causes of which are still not fully understood. It may develop in patients with pre-existing dementia. Delirium superimposed on dementia (DSD) can go completely unnoticed with routine examination. It may happen in the perioperative period and in the critical care setting, especially in the ageing population. Difficulties in diagnosing and lack of specific pharmacological and non-pharmacological treatment make DSD a seriously growing problem. Patient-oriented, multidirectional preventive measures should be applied to reduce the risk of DSD. For this reason, anesthesiologists and intensive care specialists should be aware of this interesting condition in their everyday clinical practice.

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.

Decompensated hypothyroidism: A review for the emergency clinician

BACKGROUND

Decompensated hypothyroidism, formerly known as myxedema coma, is an endocrine emergency that commonly presents with altered mental status, as well as hypothermia and depressed vital signs. The condition is often caused by an inciting event, which may lead to significant delays in the diagnosis and management of this disease. Although the incidence is low, this disease is associated with significant morbidity and mortality. Therefore, it is important for emergency clinicians to be aware of this condition.

OBJECTIVE

This narrative review evaluates the emergency medicine diagnosis and management of adult patients with decompensated hypothyroidism.

DISCUSSION

Decompensated hypothyroidism is a severe hypothyroid state associated with multiple organ failure. The diagnosis can be challenging due to similarities with more common diseases and lack of consideration of the diagnosis. Many patients may present with altered sensorium or depressed vital signs. Clinicians should obtain a thyroid stimulating hormone and free thyroxine level when considering the diagnosis. Management involves resuscitation, early steroid supplementation, thyroid hormone replacement, and treatment of the inciting event.

CONCLUSIONS

Decompensated hypothyroidism should be considered in the evaluation of patients with altered sensorium and depressed vital signs so as to not miss this critical diagnosis.

Cognitive and psychosocial outcomes of mechanically ventilated intensive care patients with and without delirium

Objective

Delirium is common in intensive care patients and is associated with short- and long-term adverse outcomes. We investigated the long-term risk of cognitive impairment and post-traumatic stress disorder (PTSD) in intensive care patients with and without delirium.

Methods

This is a prospective cohort study in ICUs in two Australian university-affiliated hospitals. Patients were eligible if they were older than 18 years, mechanically ventilated for more than 24 h and did not meet exclusion criteria. Delirium was assessed using the Confusion Assessment Method for Intensive Care Unit. Variables assessing cognitive function and PTSD symptoms were collected at ICU discharge, after 6 and 12 months: Mini-Mental State Examination, Telephone Interview for Cognitive Status, Impact of Events Scale-Revised and Informant Questionnaire for Cognitive Decline (caregiver).

Results

103 participants were included of which 36% developed delirium in ICU. Patients with delirium were sicker and had longer duration of mechanical ventilation and ICU length of stay. After 12 months, 41/60 (68.3%) evaluable patients were cognitively impaired, with 11.6% representing the presence of symptoms consistent with dementia. When evaluated by the patient’s caregiver, the patient’s cognitive function was found to be severely impaired in a larger proportion of patients (14/60, 23.3%). Delirium was associated with worse cognitive function at ICU discharge, but not with long-term cognitive function. IES-R scores, measuring PTSD symptoms, were significantly higher in patients who had delirium compared to patients without delirium. In regression analysis, delirium was independently associated with cognitive function at ICU discharge and PTSD symptoms at 12 months.

Conclusions

Intensive care survivors have significant rates of long-term cognitive decline and PTSD symptoms. Delirium in ICU was independently associated with short-term but not long-term cognitive function, and with long-term PTSD symptoms.

Trial registration Australian New Zealand Clinical Trials Registry, ACTRN12616001116415, 15/8/2016 retrospectively registered, https://www.anzctr.org.au

Post-traumatic stress disorder (PTSD) related symptoms following an experience of delirium

AIM

To evaluate the prevalence of symptoms of PTSD and its correlates after 2 weeks of recovery, among patients, who developed delirium.

METHODOLOGY

A prospective study designed was followed, in which subjects diagnosed with delirium were evaluated 2 weeks after resolution of symptoms of delirium, for PTSD symptoms by using Impact of Events Scale-Revised version (IES-R).

RESULTS

59 patients were evaluated for PTSD 2 weeks after resolution of delirium and the total mean IES-R score was 27.81 (SD-11.41). Based on the IES-cut-off scores of the scale, 30.5% of the patients (n = 18) were considered to have substantial symptoms of PTSD, 22% (n = 13) had probable symptoms of PTSD and 15.3% were considered to have partial symptoms of PTSD after resolution of delirium. None of the demographic or clinical factors were associated with development of PTSD. Those with PTSD symptoms had significantly higher prevalence of fluctuation of symptoms, while experiencing delirium and had significantly higher mean scores for the items of motor agitation, attentional deficits, higher total severity score on the Delirium Rating Scale-revised-98 version (DRS-R98) and higher DRS-R-98 total score. Higher severity of delirium as indicated by the total DRS-R98 score and the total DRS-R98 severity score were associated with higher severity of PTSD symptoms. The IES-R total score did not have any significant correlation with duration of illness, duration of delirium or Charlson Co-morbidity index.

CONCLUSIONS

This study suggests that about one-third of patients who develop delirium go on to develop symptoms of PTSD, after recovery from delirium. Development of PTSD symptoms is associated with severity of delirium. Hence, it is important to treat the delirium adequately and provide psychological support to the patients who develop delirium, after recovery from delirium.

Prediction of ICU Delirium: Validation of Current Delirium Predictive Models in Routine Clinical Practice

OBJECTIVES

To investigate the ability of available delirium risk assessment tools to identify patients at risk of delirium in an Australian tertiary ICU.

DESIGN

Prospective observational study.

SETTING

An Australian tertiary ICU.

PATIENTS

All patients admitted to the study ICU between May 8, 2017, and December 31, 2017, were assessed bid for delirium throughout their ICU stay using the Confusion Assessment Method for ICU. Patients were included in this study if they remained in ICU for over 24 hours and were excluded if they were delirious on ICU admission, or if they were unable to be assessed using the Confusion Assessment Method for ICU during their ICU stay. Delirium risk was calculated for each patient using the prediction of delirium in ICU patients, early prediction of delirium in ICU patients, and Lanzhou models. Data required for delirium predictor models were obtained retrospectively from patients medical records.

INTERVENTIONS

None.

MEASUREMENTS AND MAIN RESULTS

There were 803 ICU admissions during the study period, of which 455 met inclusion criteria. 35.2% (n = 160) were Confusion Assessment Method for ICU positive during their ICU admission. Delirious patients had significantly higher Acute Physiology and Chronic Health Evaluation III scores (median, 72 vs 54; p < 0.001), longer ICU (median, 4.8 vs 1.8 d; p < 0.001) and hospital stay (16.0 vs 8.16 d; p < 0.001), greater requirement of invasive mechanical ventilation (70% vs 21.4%; p < 0.001), and increased ICU mortality (6.3% vs 2.4%; p = 0.037). All models included in this study displayed moderate to good discriminative ability. Area under the receiver operating curve for the prediction of delirium in ICU patients was 0.79 (95% CI, 0.75-0.83); recalibrated prediction of delirium in ICU patients was 0.79 (95% CI, 0.75-0.83); early prediction of delirium in ICU patients was 0.72 (95% CI, 0.67-0.77); and the Lanzhou model was 0.77 (95% CI, 0.72-0.81).

CONCLUSIONS

The predictive models evaluated in this study demonstrated moderate to good discriminative ability to predict ICU patients' risk of developing delirium. Models calculated at 24-hours post-ICU admission appear to be more accurate but may have limited utility in practice.

Delirium Subtypes and Associated Characteristics in Older Patients With Exacerbation of Chronic Conditions

OBJECTIVE

The prevalence and prognosis of delirium motor subtypes are not yet well established. We analyzed the prevalence of motor subtypes of delirium, as well as their risk factors and outcomes, among older vulnerable patients admitted for short-term management of exacerbated chronic conditions.

METHODS

Cohort study of patients aged 65 and older who developed delirium while admitted to a subacute care unit for 12 months (N = 352). Confusion Assessment Method was used to determine the presence of delirium and the Delirium Motor Subtype Scale was used to define the motor subtype. Outcomes included discharge destination, mortality, readmission, and functional trajectories.

RESULTS

Out of 352 patients with delirium (mean age= 87.4, 73.6% with dementia), hyperactive delirium was the most prevalent subtype (40.6%), followed by mixed (31%), hypoactive (25.9%), and nonmotor (2.6%). In multivariate models, worse preadmission functional status (odds ratio [OR] [95% confidence interval {CI}] = 0.97 [0.96-0.98]) and higher comorbidity (OR [95% CI] = 1.3 [1.04-1.51]) were associated with an increased risk of hypoactive delirium. In multivariate models adjusted for different variables, including disability, hypoactive delirium was associated with mortality compared with hyperactive delirium (OR [95% CI] = 4.7 [1.6-14]) and mixed delirium (OR [95% CI] = 2.0 [1.02-3.9]) and with worse functional recovery (Beta[95% CI] = -0.2 [-12.0-(-0.4)]).

CONCLUSION

Delirium motor subtypes were associated with different patient characteristics and outcomes. Hypoactive delirium seems to affect more vulnerable patients and to be associated with worse outcomes. More research on the different delirium subtypes could help develop better preventive and management strategies.

The Motoric Types of Delirium and Estimated Blood Loss during Perioperative Period in Orthopedic Elderly Patients

Background

Delirium is a common and serious syndrome in elderly patients. The hypoactive type of delirium is known to have different characteristics, but further studies are needed to define the specificities of these characteristics. Our study aims at finding specific risk factors, especially estimated blood loss during operations of hyper- and hypoactive delirium in orthopedic elderly patients.

Methods

One hundred and seventy-five elderly patients were evaluated using the Confusion Assessment Method (CAM) and the 4^th edition text revision of the Diagnostic and Statistical Manual of Mental Disorders (DSM-IV-TR). Trained psychiatrists interviewed the subjects directly at pre- and postoperative time points. We reviewed medical records after the patients were discharged.

Results

Thirty-nine patients (22.3%) were diagnosed with multiple types of delirium, which included 17 hyperactive types (65.9%), 13 hypoactive types (33.3%), and 9 mixed types (23.1%). Although the mean estimated blood loss in patients with either hyper- or hypoactive symptoms was larger than in patients lacking these symptoms, the odds ratio was only significant in patients with hyperactive symptoms. In addition, age, preoperative daily function, and preoperative hyponatremia were found to be risk factors for hyperactive but not hypoactive symptoms.

Conclusion

Patients with hypoactive symptoms had different risk factors than patients with hyperactive symptoms of delirium. The estimated blood loss, well-known risk factors for delirium, might be risk factors for only hyperactive delirium. The acute precipitating factors seemed to show stronger correlation with the hyperactive type of delirium than with the hypoactive type.

Music intervention to prevent delirium among older patients admitted to a trauma intensive care unit and a trauma orthopaedic unit

PURPOSE

Evaluate music listening for delirium prevention among patients admitted to a Trauma Intensive Care and Trauma Orthopaedic Unit. The Roy Adaptation Model provided the theoretical framework focusing on modifying contextual stimuli.

METHODS

Randomised controlled trial, 40 patients aged 55 and older.

INTERVENTION

Participants randomly assigned to receive music listening or usual care for 60 minutes, twice a day, over three days. Pre-recorded self-selected music using an iPod and headsets, with slow tempo, low pitch and simple repetitive rhythms to alter physiologic responses.

OUTCOMES

Heart rate, respiratory rate, systolic and diastolic blood pressure, confusion assessment method.

RESULTS

Repeated measures ANOVA, F(4, 134) = 4.75, p = .001, suggested statistically significant differences in heart rate pre/post music listening, and F(1, 37) = 10.44, p = .003 in systolic blood pressure pre/post music listening. Post-hoc analysis reported changes at three time periods of statistical significance; (p = .010), (p = .005) and (p = .039) and a change in systolic blood pressure pre/post music listening; (p = .001) of statistical significance. All participants screened negative for delirium.

CONCLUSION

Music addresses pathophysiologic mechanisms that contribute to delirium; neurotransmitter imbalance, inflammation and acute physiologic stressors. Music to prevent delirium is one of few that provide support in a critical care setting.

Prevalence and risk factors for delirium diagnosis in patients followed in general practices in Germany

ABSTRACTBackground:The aim of this study is to identify the prevalence and risk factors of documented delirium in general practices in Germany.

METHODS

The present study includes 2,194 patients over the age of 65 years with delirium and 2,194 controls without delirium from a sample of 6,180,042 patients from 1,262 general practices. Multivariate logistic regression models were fitted with delirium as a dependent variable and other disorders and drugs as potential predictors.

RESULTS

A five-year-prevalence of 0.08% and an average of 0.7 (SD: 1.5) patients per practice per year were found. Among the study participants, 43.0% were men, and the mean age was 82.2 years (SD = 7.1 years). 24.2% of delirium patients and 10.3% of controls lived in nursing homes. Delirium was found to be positively associated with nursing home residence (OR: 1.69), dementia (OR = 3.45), epilepsy (OR = 2.16), stroke (OR = 1.80), Parkinson's disease (OR = 1.78), sleep disorder (OR = 1.64), renal insufficiency (OR = 1.57), fractures (OR = 1.56), and the prescription of benzodiazepines (OR = 1.62) and antiepileptics (OR = 1.53). Finally, the number of different drug classes prescribed within one year prior to the index date was positively associated with a risk of delirium. Compared to patients without medication therapy, the OR for delirium was 3.21 when more than four drug classes were prescribed.

CONCLUSIONS

In primary care, neuropsychiatric risk factors and polymedication were particularly important for the diagnosis of delirium compared to inpatient care. The methodological limitations of the analysis of data from routine care must be considered. Delirium is rarely diagnosed in primary care. Risk factors in primary care differ from those found in inpatient care. The reasons for this need to be further investigated.

Delirium is a Common and Early Finding in Patients in the Pediatric Cardiac Intensive Care Unit

OBJECTIVE

To determine incidence, associated risk factors, and characteristics of delirium in a pediatric cardiac intensive care unit (CICU). Delirium is a frequent and serious complication in adults after cardiac surgery, but there is limited understanding of its impact in children with critical cardiac disease.

STUDY DESIGN

Single-center prospective observational study of CICU patients ≤21 years old. All were screened for delirium using the Cornell Assessment for Pediatric Delirium each 12-hour shift.

RESULTS

Ninety-nine patients were included. Incidence of delirium was 57%. Median time to development of delirium was 1 day (95% CI 0, 1 days). Children with delirium were younger (geometric mean age 4 vs 46 months; P < .001), had longer periods of mechanical ventilation (mean 35.9 vs 8.8 hours; P = .002) and had longer cardiopulmonary bypass times (geometric mean 126 vs 81 minutes; P = .001). Delirious patients had longer length of CICU stay than those without delirium (median 3 (IQR 2, 12.5) vs 1 (IQR1, 2) days; P < .0001). A multivariable generalized linear mixed model showed a significant association between delirium and younger age (OR 0.35 for each additional month, 95% CI 0.19, 0.64), need for mechanical ventilation (OR 4.1, 95% CI 1.7, 9.89), and receipt of benzodiazepines (OR 3.78, 95% CI 1.46, 9.79).

CONCLUSIONS

Delirium is common in patients in the pediatric CICU and is associated with longer length of stay. There may be opportunities for prevention of delirium by targeting modifiable risk factors, such as use of benzodiazepines.

Prediction and early detection of delirium in the intensive care unit by using heart rate variability and machine learning

OBJECTIVE

Delirium is an important syndrome found in patients in the intensive care unit (ICU), however, it is usually under-recognized during treatment. This study was performed to investigate whether delirious patients can be successfully distinguished from non-delirious patients by using heart rate variability (HRV) and machine learning.

APPROACH

Electrocardiography data of 140 patients was acquired during daily ICU care, and HRV data were analyzed. Delirium, including its type, severity, and etiologies, was evaluated daily by trained psychiatrists. HRV data and various machine learning algorithms including linear support vector machine (SVM), SVM with radial basis function (RBF) kernels, linear extreme learning machine (ELM), ELM with RBF kernels, linear discriminant analysis, and quadratic discriminant analysis were utilized to distinguish delirium patients from non-delirium patients.

MAIN RESULTS

HRV data of 4797 ECGs were included, and 39 patients had delirium at least once during their ICU stay. The maximum classification accuracy was acquired using SVM with RBF kernels. Our prediction method based on HRV with machine learning was comparable to previous delirium prediction models using massive amounts of clinical information.

SIGNIFICANCE

Our results show that autonomic alterations could be a significant feature of patients with delirium in the ICU, suggesting the potential for the automatic prediction and early detection of delirium based on HRV with machine learning.

Clinical characteristics, prevalence, and factors related to delirium in children of 5 to 14 years of age admitted to intensive care

OBJECTIVE

To evaluate the clinical characteristics, prevalence and factors associated with delirium in critical patients from 5 to 14 years of age.

DESIGN

An analytical, cross-sectional observational study was made. Delirium was assessed with the Pediatric-Confusion Assessment Method for the Intensive Care Unit (pCAM-ICU) and motor classification was established with the Delirium Rating Scale Revised-98.

SETTING

A pediatric Intensive Care Unit.

PATIENTS

All those admitted over a one-year period were assessed during the first 24-72h, or when possible in deeply sedated patients.

EXCLUSION CRITERIA

Patients in stupor or coma, with severe communication difficulty, subjected to deep sedation throughout admission, and those with denied consent.

RESULTS

Twenty-nine of the 156 assessed patients suffered delirium (18.6%) and 55.2% were hypoactive. The neurocognitive alterations evaluated by the pCAM-ICU were similar in the three motor groups. Intellectual disability (OR=17.54; 95%CI: 3.23-95.19), mechanical ventilation (OR=18.80; 95%CI: 4.29-82.28), liver failure (OR=54.88; 95%CI: 4.27-705.33), neurological disease (OR=4.41; 95%CI: 1.23-15.83), anticholinergic drug use (OR=3.23; 95%CI: 1.02-10.26), different psychotropic agents (OR=4.88; 95%CI: 1.42-16.73) and tachycardia (OR=4.74; 95%CI: 1.21-18.51) were associated to delirium according to the logistic regression analysis.

CONCLUSION

The frequency of delirium and hypoactivity was high. It is therefore necessary to routinely evaluate patients with standardized instruments. All patients presented with important neurocognitive alterations. Several factors related with the physiopathology of delirium were associated to the diagnosis; some of them are modifiable through the rationalization of medical care.

Delirium during the first evaluation of children aged five to 14 years admitted to a paediatric critical care unit

OBJECTIVES

To describe the prevalence and characteristics of delirium during the initial evaluation of critically ill patients aged 5-14 years.

METHOD/DESIGN

This is a cross-sectional descriptive study in a critical care unit. For six months, all patients were evaluated within the first 24-72 hours or when sedation permitted the use of the paediatric confusion assessment method for the intensive care unit (PCAM-ICU) and the Delirium Rating Scale-Revised-98 items #7 and #8 to determine motor type. We report the characteristics of PCAM-ICU delirium (at least three of the required items scored positive) and of subthreshold score cases (two positive items).

RESULTS

Of 77 admissions, 15 (19.5%) had delirium, and 11 (14.2%) were subthreshold. A total of 53.3% of delirium and 45.5% of subthreshold cases were hypoactive. The prevalence of delirium and subthreshold PCAM-ICU was 83.3% and 16.7% in mechanically ventilated children. The most frequent combination of PCAM-ICU alterations in subthreshold cases was acute onset-fluctuation with altered alertness. The main nursing diagnoses were related to reduced cellular respiration.

CONCLUSIONS

Delirium is common in critically ill children. It is necessary to assess whether certain nursing diagnoses imply an increase in delirium. Longitudinal studies of subthreshold PCAM-ICU cases are needed to understand their importance better.

Prognostic effects of delirium motor subtypes in hospitalized older adults: A prospective cohort study

OBJECTIVES

To investigate the association between delirium motor subtypes and hospital mortality and 12-month mortality in hospitalized older adults.

DESIGN

Prospective cohort study conducted from 2009 to 2015.

SETTING

Geriatric ward of a university hospital in Sao Paulo, Brazil.

PARTICIPANTS

We included 1,409 consecutive admissions of acutely ill patients aged 60 years and over. We excluded admissions for end-of-life care, with missing data on the main variables, length of stay shorter than 48 hours, or when consent to participate was not given.

MAIN OUTCOMES AND MEASURES

Delirium was detected using the Confusion Assessment Method and categorized in hypoactive, hyperactive, or mixed delirium. Primary outcomes were time to death in the hospital, and time to death in 12 months (for the discharged sample). Comprehensive geriatric assessment was performed at admission and included socio-demographic, clinical, functional, cognitive, and laboratory variables. Further clinical data were documented upon death or discharge. Multivariate analyses used Cox proportional hazards models adjusted for possible confounders.

RESULTS

We included 1,409 admissions, with a mean age of 80 years. The proportion of in-hospital deaths was 19%, with a cumulative mortality of 38% in 12 months. Delirium occurred in 47% of the admissions. Hypoactive delirium was the predominant motor subtype (53%), followed by mixed delirium (30%) and hyperactive delirium (17%). Hospital mortality rates were respectively 33%, 34% and 15%. We verified that hypoactive and mixed delirium were independently associated with hospital mortality, with respective hazard ratios of 2.43 (95%CI = 1.64-3.59) and 2.31 (95%CI = 1.53-3.50). Delirium motor subtypes were not independently predictive of 12-month mortality.

CONCLUSIONS

One in three acutely ill hospitalized older adults who suffered hypoactive or mixed delirium died in the hospital. Clinicians should be aware that hypoactive symptoms of delirium, whether shown exclusively or in alternation with hyperactive symptoms, are indicative of a worse prognosis in this population.

Delirium in Pediatric Critical Care

Delirium occurs frequently in the critically ill child. It is a syndrome characterized by an acute onset and fluctuating course, with behaviors that reflect a disturbance in awareness and cognition. Delirium represents global cerebral dysfunction due to the direct physiologic effects of an underlying medical illness or its treatment. Pediatric delirium is strongly associated with poor outcomes, including increased mortality, prolonged intensive care unit length of stay, longer time on mechanical ventilation, and increased cost of care. With heightened awareness, the pediatric intensivist can detect, treat, and prevent delirium in at-risk children.

Delirium and Mortality in Critically Ill Children: Epidemiology and Outcomes of Pediatric Delirium

OBJECTIVES

Delirium occurs frequently in adults and is an independent predictor of mortality. However, the epidemiology and outcomes of pediatric delirium are not well-characterized. The primary objectives of this study were to describe the frequency of delirium in critically ill children, its duration, associated risk factors, and effect on in-hospital outcomes, including mortality. Secondary objectives included determination of delirium subtype, and effect of delirium on duration of mechanical ventilation, and length of hospital stay.

DESIGN

Prospective, longitudinal cohort study.

SETTING

Urban academic tertiary care PICU.

PATIENTS

All consecutive admissions from September 2014 through August 2015.

INTERVENTIONS

Children were screened for delirium twice daily throughout their ICU stay.

MEASUREMENTS AND MAIN RESULTS

Of 1,547 consecutive patients, delirium was diagnosed in 267 (17%) and lasted a median of 2 days (interquartile range, 1-5). Seventy-eight percent of children with delirium developed it within the first 3 PICU days. Most cases of delirium were of the hypoactive (46%) and mixed (45%) subtypes; only 8% of delirium episodes were characterized as hyperactive delirium. In multivariable analysis, independent predictors of delirium included age less than or equal to 2 years old, developmental delay, severity of illness, prior coma, mechanical ventilation, and receipt of benzodiazepines and anticholinergics. PICU length of stay was increased in children with delirium (adjusted relative length of stay, 2.3; CI = 2.1-2.5; p < 0.001), as was duration of mechanical ventilation (median, 4 vs 1 d; p < 0.001). Delirium was a strong and independent predictor of mortality (adjusted odds ratio, 4.39; CI = 1.96-9.99; p < 0.001).

CONCLUSIONS

Delirium occurs frequently in critically ill children and is independently associated with mortality. Some in-hospital risk factors for delirium development are modifiable. Interventional studies are needed to determine best practices to limit delirium exposure in at-risk children.

Delirium After Mechanical Ventilation in Intensive Care Units: The Cognitive and Psychosocial Assessment (CAPA) Study Protocol

Background

In the intensive care unit (ICU), critical illness delirium occurs in the context of multiple comorbidities, multi-organ failure, and invasive management techniques, such as mechanical ventilation, sedation, and lack of sleep. Delirium is characterized by an acute confusional state defined by fluctuating mental status, inattention, and either disorganized thinking or an altered level of consciousness. The long-term cognitive and psychosocial function of patients that experience delirium in the ICU is of crucial interest because preliminary data suggest a strong association between ICU-related delirium and long-term cognitive impairment.

Objective

The aim of this study is to explore the relationship between delirium in the ICU and adverse outcomes by following mechanically ventilated patients for one year following their discharge from the ICU and collecting data on their long-term cognition and psychosocial function.

Methods

This study will be conducted by enrolling patients in two tertiary ICUs in Australia. We aim to recruit 200 patients who have been mechanically ventilated for more than 24 hours. Data will be collected at the following three time points: (1) at discharge where they will be administered the Mini-Mental State Examination (MMSE); (2) at 6 months after discharge from the ICU discharge where the Impact of Events Scale Revised (IES-R) and the Telephone Inventory for Cognitive Status (TICS) tests will be administered; and (3) at 12 months after discharge from the ICU where the patients will be administered the TICS and IES-R tests, as well as the Informant Questionnaire for Cognitive Decline in the Elderly (IQCODE). The IQCODE will be administered to their “person responsible” or the significant other of the patient.

Results

Long-term cognition and psychosocial function will be the primary outcome of this study. Mortality will also be investigated as a secondary outcome. Active enrollment will take place until the end of September 2016 and data collection will conclude at the end of September 2017. The analysis and results are expected to be available by March 2018.

Conclusion

Delirium during mechanical ventilation has been linked to longer ICU and hospital stays, higher financial burdens, increased risks of long-term cognitive impairment (ie, dementia), poor functional outcomes and quality of life, and decreased survival. However, delirium during mechanical ventilation in the ICU is not well understood. This study will advance our knowledge of the comprehensive, long-term effects of delirium on cognitive and psychosocial function.

Trial Registration

Australian New Zealand Clinical Trials Registry (ANZCTR): ACTRN12616001116415; https://www.anzctr.org.au/Trial/Registration/TrialReview.aspx?id=371216 (Archived by WebCite at http://www.webcitation.org/ 6nfDkGTcW)

Delayed Recall and Working Memory MMSE Domains Predict Delirium following Cardiac Surgery

BACKGROUND

Reduced preoperative cognition is a risk factor for postoperative delirium. The significance for type of preoperative cognitive deficit, however, has yet to be explored and could provide important insights into mechanisms and prediction of delirium.

OBJECTIVE

Our goal was to determine if certain cognitive domains from the general cognitive screener, the Mini-Mental State Exam (MMSE), predict delirium after cardiac surgery.

METHODS

Patients completed a preoperative MMSE prior to undergoing elective cardiac surgery. Following surgery, delirium was assessed throughout ICU stay using the Confusion Assessment Method for ICU delirium and the Richmond Agitation and Sedation Scale.

RESULTS

Cardiac surgery patients who developed delirium (n = 137) had lower total MMSE scores than patients who did not develop delirium (n = 457). In particular, orientation to place, working memory, delayed recall, and language domain scores were lower. Of these, only the working memory and delayed recall domains predicted delirium in a regression model adjusting for history of chronic obstructive pulmonary disease, age, sex, and duration of cardiopulmonary bypass. For each word not recalled on the three-word delayed recall assessment, the odds of delirium increased by 50%. For each item missed on the working memory index, the odds of delirium increased by 36%. Of the patients who developed delirium, 47% had a primary impairment in memory, 21% in working memory, and 33% in both domains. The area under the receiver operating characteristics curve using only the working memory and delayed recall domains was 0.75, compared to 0.76 for total MMSE score.

CONCLUSION

Delirium risk is greater for individuals with reduced MMSE scores on the delayed recall and working memory domains. Research should address why patients with memory and executive vulnerabilities are more prone to postoperative delirium than those with other cognitive limitations.

Analysis of multi-dimensional contemporaneous EHR data to refine delirium assessments

Delirium is a potentially lethal condition of altered mental status, attention, and level of consciousness with an acute onset and fluctuating course. Its causes are multi-factorial, and its pathophysiology is not well understood; therefore clinical focus has been on prevention strategies and early detection. One patient evaluation technique in routine use is the Confusion Assessment Method (CAM): a relatively simple test resulting in 'positive', 'negative' or 'unable-to-assess' (UTA) ratings. Hartford Hospital nursing staff use the CAM regularly on all non-critical care units, and a high frequency of UTA was observed after reviewing several years of records. In addition, patients with UTA ratings displayed poor outcomes such as in-hospital mortality, longer lengths of stay, and discharge to acute and long term care facilities. We sought to better understand the use of UTA, especially outside of critical care environments, in order to improve delirium detection throughout the hospital. An unsupervised clustering approach was used with additional, concurrent assessment data available in the EHR to categorize patient visits with UTA CAMs. The results yielded insights into the most common situations in which the UTA rating was used (e.g. impaired verbal communication, dementia), suggesting potentially inappropriate ratings that could be refined with further evaluation and remedied with updated clinical training. Analysis of the patient clusters also suggested that unrecognized delirium may contribute to the poor outcomes associated with the use of UTA. This method of using temporally related high dimensional EHR data to illuminate a dynamic medical condition could have wider applicability.