The CAM-ICU-7 and ICDSC as measures of delirium severity in critically ill adult patients

Performance and validation of two ICU delirium assessment and severity tools; a prospective observational study

BACKGROUND

The clinical statistical performance of the Confusion Assessment Method Intensive Care Unit (CAM-ICU, including CAM-ICU-7) and Intensive Care Delirium Screening Checklist (ICDSC) have rarely been studied. Additionally, delirium severity is often not measured due to a lack of validation of delirium assessment tools.

OBJECTIVE

The aim was to determine the statistical performance of both delirium assessment tools in daily practice, and the correlation with the gold standard Delirium Rating Scale (DRS)-R98, for delirium severity.

RESEARCH METHOD

CAM-ICU-7 and ICDSC, performed by nurses were compared with the DRS-R98 assessed by delirium experts, twice weekly. Within a time-window of one hour all assessments were independently performed.

DESIGN

A prospective observational study performed between October and December 2020.

MAIN OUTCOME MEASURES

Sensitivity, specificity, positive and negative predictive value of both tools was determined. The correlation between DRS-R98 and CAM-ICU-7 and ICDSC was used for validation of delirium severity.

RESULTS

In total, 104 CAM-ICU-7 and 105 ICDSC assessments in 86 patients were compared with the DRS-R98. For the CAM-ICU-7 and ICDSC, respectively, the sensitivity was 90% and 95%, the specificity was 92.4% and 92.3%. The positive predictive value was 0.76 and 0.80, and negative predictive value was 0.77 and 0.97. Correlation of the CAM-ICU-7 score and ICDSC score with the DRS-R98 score was 0.74 (95% CI 0.64-0.81) and 0.70 (95%CI 0.59-0.79; both p < 0.001), respectively.

CONCLUSION

Both CAM-ICU-7 and ICDSC demonstrated good statistical performance and correlated well with the delirium severity tool DRS-R98.

IMPLICATIONS FOR CLINICAL PRACTICE

Nurses can either use the CAM-ICU(-7) or the ICDSC in their practice, both are accurate in delirium diagnosis. Total CAM-ICU-7 and ICDSC score reflects delirium severity well; the higher the score, the more severe the delirium. This enables nurses to gauge the impact of their interventions and enhance the well-being of patients experiencing delirium by minimizing distressing occurrences.

Role of Intraoperative Electroencephalography in Predicting Postoperative Delirium in Patients Undergoing Cardiovascular Surgeries

OBJECTIVE

To determine the utility of electroencephalography (EEG) in predicting postoperative delirium (POD) in patients who underwent cardiovascular surgeries with EEG monitoring.

METHODS

A total of 1161 patients who underwent cardiovascular surgeries with EEG monitoring were included in the study, and their data were retrospectively reviewed. POD assessment was done utilizing Intensive Care Delirium Screening Checklist (ICDSC). Patients with a score of > 4 on ICDSC were diagnosed with POD.

RESULTS

Of 1161 patients, 131 patients had EEG changes and 56 (42.74%) of 131 patients experienced POD. Of 1030 patients without EEG changes, 219 (21.26%) experienced POD. EEG showed specificity of 91.5% and negative predictive value of 78.7% in detecting POD. On multivariable analysis, EEG changes showed a strong association with POD (ORadj 1.97 CI (1.30-2.99), p = 0.001) with persistent EEG changes showing even a higher risk of developing POD (ORadj 2.65 (1.43-4.92), p = 0.002).

CONCLUSION

EEG change has specificity of 91.5% emphasizing the need for its implementation as a diagnostic tool for predicting POD. Patients with POD are two times more likely to experience significant EEG changes, especially persistent EEG changes when undergoing cardiovascular surgeries.

SIGNIFICANCE

Intraoperative EEG can detect POD, and EEG changes based therapeutic interventions can mitigate POD.

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

BACKGROUND

Subsyndromal delirium is a dynamic, recognizable condition commonly observed in intensive care unit (ICU) patients that can lead to poor patient prognosis, and its prompt recognition and management can prevent disease progression. However, no evidence-based predictive tool has been developed specifically to assess the occurrence of subsyndromal delirium in the ICU.

OBJECTIVE

To develop and validate a novel, simple and effective tool for estimating the risk of subsyndromal delirium among ICU patients.

DESIGN

A prospective, nested case-controlled study.

DATA SOURCES

A total of 731 patients were recruited from the central ICU of a tertiary hospital in southwestern China from August 2021 to November 2022.

METHODS

The least absolute shrinkage and selection operator was applied to screen potential features for univariate and multivariate logistic regression. A nomogram was constructed using the selected variables. The performance of the nomogram was evaluated by combining the area under the receiver operating characteristic curve (AUC), calibration curves and decision curve analysis (DCA).

RESULTS

The prevalence of subsyndromal delirium among ICU patients was 23.06 %. Multiple logistic regression analysis revealed that the independent predictive factors for subsyndromal delirium among ICU patients were vision impairment, a history of falls, the use of restraint, blood transfusion, the use of antibiotics, surgery, the Caprini score, and the Braden score, all of which were used to construct the nomogram. The AUCs for the model were 0.710 (95 % CI, 0.654-0.766, P < 0.001) and 0.825 (95 % CI, 0.732-0.917, P < 0.001) in the training and validation cohorts, respectively, indicating that the model had high accuracy in distinguishing patients with and without subsyndromal delirium. The calibration curve of the nomogram showed good consistency between the predicted and actual probabilities. The DCA indicated that the nomogram has clinical application for patients in the ICU.

CONCLUSIONS

We developed an easy-to-use nomogram for identifying subsyndromal delirium in ICU patients with satisfactory predictive ability based on simple and easily accessible clinical features. The nomogram can identify ICU patients at high-risk for subsyndromal delirium and may be a useful subsyndromal delirium tool for current ICU physicians.

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.

Delirium and delirium severity screening in the intensive care-correspondence of screenings tools

BACKGROUND

Delirium severity scores are gaining acceptance for measuring delirium in the intensive care unit (ICU).

OBJECTIVE

The aim of this study was to evaluate the concordance between the Confusion Assessment Method for the intensive care unit (CAM-ICU)-7 and the Intensive Care Delirium Screening Checklist (ICDSC) as delirium severity measurement tools.

METHODS

This was a prospective, comparative, observational multicentre study. This study was conducted in 18 Danish ICUs. Delirium was assessed in adult critically ill patients admitted to an ICU with a Richmond Agitation and Sedation Score (RASS) of -2 or above. ICU nurses assessed delirium with randomised paired delirium screening instruments, using the CAM-ICU, the ICDSC, and the CAM-ICU-7. The correlation between the CAM-ICU-7 and the ICDSC severity scores was evaluated for all predefined patient subgroups.

RESULTS

A total of 1126 paired screenings were conducted by 127 ICU nurses in 850 patients. The patients' median age was 70 years (interquartile range: 61-77), 40% (339/850) were female, and 54% (457/850) had at least one positive delirium score. Delirium severity ranges (CAM-ICU-7: 0-7; and ICDSC: 0-8) were positively correlated (Pearson's correlation coefficient, r = 0.83; p < 0.0001). The overall agreement between the CAM-ICU-7 and the ICDSC for delirium measurement (CAM-ICU-7: >2, and ICDSC: >3) was substantial (kappa = 0.74), but the agreement decreased to fair (kappa = 0.38) if a patient had a RASS less than 0.

CONCLUSIONS

The agreement between the CAM-ICU-7 and the ICDSC for delirium severity measurement was substantial but might be affected by the patient's sedation and agitation level at the time of assessment.

IMPLICATIONS FOR PRACTICE

Both CAM-ICU-7 and ICDSC can be implemented for delirium severity measurement. Attention is warranted in both scores if a patient has a RASS of -2.

Risk stratification and predictive modeling of postoperative delirium in chronic subdural hematoma

Background- Postoperative delirium is a common complication associated with the elderly, causing increased morbidity and prolonged hospital stay. However, its risk factors in chronic subdural hematoma patients have not been well studied. Methods- A total of 202 consecutive patients with chronic subdural hematoma at Peking University Third Hospital between January 2018 and January 2023 were enrolled. Various clinical indicators were analyzed to identify independent risk factors for postoperative delirium using univariate and multivariate regression analyses. Delirium risk prediction models were developed as a nomogram and a Markov chain. Results- Out of the 202 patients (age, 71 (IQR, 18); female-to-male ratio, 1:2.7) studied, 63 (31.2%) experienced postoperative delirium. Univariate analysis identified age (p < 0.001), gender (p = 0.014), restraint belt use (p < 0.001), electrolyte imbalance (p < 0.001), visual analog scale score (p < 0.001), hematoma thickness (p < 0.001), midline shift (p < 0.001), hematoma side (p = 0.013), hematoma location (p = 0.018), and urinal catheterization (p = 0.028) as significant factors. Multivariate regression analysis confirmed the significance of restraint belt use (B = 7.657, p < 0.001), electrolyte imbalance (B = -3.993, p = 0.001), visual analog scale score (B = 2.331, p = 0.016), and midline shift (B = 0.335, p = 0.007). Hematoma thickness and age had no significant impact. Conclusion- Increased midline shift and visual analog scale scores, alongside restraint belt use and electrolyte imbalance elevate delirium risk in chronic subdural hematoma surgery. Our prediction models may offer reference value in this context.

Decreasing the incidence of delirium via multi-sensory stimulation in patients receiving mechanical ventilation in the intensive care unit: A protocol for a randomized feasibility study

Introduction

Delirium is a common acute brain dysfunction syndrome in patients admitted to intensive care units (ICUs). Family engagement strategies, based on the theory of multi-sensory stimulation to ameliorate sensory deprivation in patients, may be an effective and scalable method to reduce the burden of delirium.

Methods

/design: This is a assessor-blinded, randomised controlled trial of the feasibility of multi-sensory stimulation (MS) in patients with delirium. A total of 72 mechanically ventilated patients (n = 24 in each group) admitted to the ICU will be randomised to routine non-pharmacological delirium care (control), family multi-sensory stimulation and nurse multi-sensory stimulation groups. All participants except the control group will receive multi-sensory stimulation, including visual, auditory, tactile and kinesthetic stimulation, for 5 days. Our primary aim is to determine the feasibility of the study procedure (recruitment, eligibility, retention and attrition rates, appropriateness of clinical outcome measures), feasibility, acceptability and safety of the intervention (adverse events, satisfaction and other). Our secondary objective is to assess the preliminary efficacy of the MS protocol in reducing the incidence, duration and severity of delirium. Sedation levels and delirium severity will be assessed twice daily. Enrolled participants will be followed in hospital until death, discharge or up to 28 days after treatment.

Ethics and dissemination

The current study was approved by the Ethics Review Board of Huazhong University of Science and Technology Union Shenzhen Hospital, China (KY-2023-031-01). The results of this study will be presented at scientific conferences and submitted for publication in peer-reviewed journals.

Trial registration number

ChiCTR2300071457.

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.

Does pain optimisation impact delirium outcomes in critically ill patients? A systematic review and meta-analysis protocol

BACKGROUND

Untreated pain is associated with short-term and long-term consequences, including post-traumatic stress disorder and insomnia. Side effects of some analgesic medications include dysphoria, hallucinations and delirium. Therefore, both untreated pain and analgesic medications may be risk factors for delirium. Delirium is associated with longer length of stay or cognitive impairment. Our systematic review and meta-analysis will examine the relationship between pain or analgesic medications with delirium occurrence, duration and severity among critically ill adults.

METHODS AND ANALYSIS

MEDLINE, EMBASE, CINAHL, the Cochrane Central Register of controlled trials and a review of recent conference abstracts will be searched without restriction from inception to 15 May 2023. Study inclusion criteria are: (1) age≥18 years admitted to intensive care; (2) report a measure of pain, analgesic medications and delirium; (3) study design-randomised controlled trial, quasiexperimental designs and observational cohort and case-control studies excluding case reports. Study exclusion criteria are: (1) alcohol withdrawal delirium or delirium tremens; or (2) general anaesthetic emergence delirium; or (3) lab or animal studies. Risk of bias will be assessed with the Risk of Bias V.2 and risk of bias in non-randomised studies tools. There is no language restriction. Occurrence estimates will be transformed using the Freeman-Tukey double arcsine. Point estimates will be pooled using Hartung-Knapp Sidik-Jonkman random effects meta-analysis to estimate a pooled risk ratio. Statistical heterogeneity will be estimated with the I2 statistic. Risk of small study effects will be assessed using funnel plots and Egger test. Studies will be analysed for time-varying and unmeasured confounding using E values.

ETHICS AND DISSEMINATION

Ethical approval is not required as this is an analysis of published aggregated data. We will share our findings at conferences and in peer-reviewed journals.

PROSPERO REGISTRATION NUMBER

The finalised protocol was submitted to the International Prospective Register of Systematic Reviews (PROSPERO ID: CRD42022367715).

Intensive care unit nurses' perception of three different methods for delirium screening: A survey (DELIS-3)

BACKGROUND

Delirium is common in critically ill patients with detrimental effects in terms of increased morbidity, mortality, costs, and human suffering. Delirium detection and management depends on systematic screening for delirium, which can be challenging to implement in clinical practice.

OBJECTIVES

The aim of this study was to explore how nurses in the intensive care unit perceived the use of Confusion Assessment Method for the Intensive Care Unit (CAM-ICU), the Confusion Assessment Method for the Intensive Care Unit-7 (CAM-ICU-7), and Intensive Care Delirium Screening Checklist (ICDSC) for delirium screening of patients in the intensive care unit.

METHODS

This was a cross-sectional, electronic-based survey of nurses' perceptions of delirium screening with the three different instruments for delirium screening. Nurses were asked to grade their perception of the usability of the three instruments and how well they were perceived to detect delirium and delirium symptom changes on a 1- to 6-point Likert scale. Open questions about perceived advantages and disadvantages of each instrument were analysed using the framework method.

RESULTS

One hundred twenty-seven of 167 invited nurses completed the survey and rated the CAM-ICU-7 as faster and easier than the ICDSC, which was more nuanced and reflected changes in the patient's delirium better. Despite being rated as the fastest, easiest, and most used, the CAM-ICU provided less information and was considered inferior to the CAM-ICU-7 and ICDSC. Using familiar instruments made delirium screening easier, but being able to grade and nuance the delirium assessment was experienced as important for clinical practice.

CONCLUSIONS

Both the ICDSC and the CAM-ICU-7 were perceived well suited for detection of delirium and reflected changes in delirium intensity. The CAM-ICU was rated as fast and easy but inferior in its ability to grade and nuance the assessment of delirium. Emphasis on clinical meaningfulness and continued education in delirium screening are necessary for adherence to delirium management guidelines.

Current Trends for Delirium Screening within the Emergency Department

Delirium is an acute neurological disorder that involves attention and cognition. It is associated with a high risk of morbidity and mortality among older people (>65 years old). In the context of the Emergency Department (ED), it is frequently experienced by patients but often not recognized. Literature studies have identified some screening instruments for an initial evaluation of delirium. Most of these tools have not been validated yet in the context of emergencies, but, in other settings, they were very useful for assessing and maximizing the recognition of this condition among older patients. We conducted a review of the literature, including randomized control trials, clinical and observational studies, and research studies published in recent years, confirming that most of the screening tools for delirium used in the intensive care unit (ICU) or the geriatric department have not been tested in the ED, and the ideal timing and form of the delirium assessment process for older adults have not been defined yet. The aim of our review is to summarize the updated evidence about the screening tools for delirium in the context of the ED, due to the fact that overcrowding of the ED and the stressful condition of emergency situations (that contribute to the onset of delirium) could expose older patients to a high risk of complications and mortality if delirium is not promptly recognized. In conclusion, we support the evidence that delirium is a current and real condition that emergency physicians have to face daily, and we are aware that more research is needed to explore this field in order to improve the overall outcomes of older patients admitted to the ED.

Incidence of Delirium in Critically Ill Patients With and Without COVID-19

BACKGROUND

It is known that patients with COVID-19 are at high risk of developing delirium. The aim of the study was to compare the incidence of delirium between critically ill patients with and without a diagnosis of COVID-19.

METHODS

This is a retrospective study conducted in a southern Brazilian hospital from March 2020 to January 2021. Patients were divided into two groups: the COVID-19 group consisted of patients with a diagnosis of COVID-19 confirmed by reverse transcription-polymerase chain reaction (RT-PCR) or serological tests who were admitted to specific ICUs. The non-COVID-19 group consisted of patients with other surgical and medical diagnoses who were admitted to non-COVID ICUs. All patients were evaluated daily using the Intensive Care Delirium Screening Checklist (ICDSC). The two cohorts were compared in terms of the diagnosis of delirium.

RESULTS

Of the 649 patients who remained more than 48 h in the ICU, 523 were eligible for the study (COVID-19 group: 292, non-COVID-19 group: 231). There were 119 (22.7%) patients who had at least one episode of delirium, including 96 (32.9%) in the COVID-19 group and 23 (10.0%) in the non-COVID-19 group (odds ratio [OR] 4.42; 95% confidence interval [CI], 2.69 to 7.26; p < 0.001). Among patients mechanically ventilated for two days or more, the incidence of delirium did not differ between groups (COVID-19: 89/211, 42.1% vs non-COVID-19: 19/47, 40.4%; p  =  0.82). Logistic regression showed that the duration of mechanical ventilation was the only independent factor associated with delirium (p  =  0.001).

CONCLUSION

COVID-19 can be associated with a higher incidence of delirium among critically ill patients, but there was no difference in this incidence between groups when mechanical ventilation lasted two days or more.

Deep Learning-Based Recurrent Delirium Prediction in Critically Ill Patients

OBJECTIVES

To predict impending delirium in ICU patients using recurrent deep learning.

DESIGN

Retrospective cohort study.

SETTING

Fifteen medical-surgical ICUs across Alberta, Canada, between January 1, 2014, and January 24, 2020.

PATIENTS

Forty-three thousand five hundred ten ICU admissions from 38,426 patients.

INTERVENTIONS

None.

MEASUREMENTS AND MAIN RESULTS

We used ICU and administrative health data to train deep learning models to predict delirium episodes in the next two 12-hour periods (0-12 and 12-24 hr), starting at 24 hours after ICU admission, and to generate new predictions every 12 hours. We used a comprehensive set of 3,643 features, capturing patient history, early ICU admission information (first 24 hr), and the temporal dynamics of various clinical variables throughout the ICU admission. Our deep learning architecture consisted of a feature embedding, a recurrent, and a prediction module. Our best model based on gated recurrent units yielded a sensitivity of 0.810, a specificity of 0.848, a precision (positive predictive value) of 0.704, and an area under the receiver operating characteristic curve (AUROC) of 0.909 in the hold-out test set for the 0-12-hour prediction horizon. For the 12-24-hour prediction horizon, the same model achieved a sensitivity of 0.791, a specificity of 0.807, a precision of 0.637, and an AUROC of 0.895 in the test set.

CONCLUSIONS

Our delirium prediction model achieved strong performance by applying deep learning to a dataset that is at least one order of magnitude larger than those used in previous studies. Another novel aspect of our study is the temporal nature of our features and predictions. Our model enables accurate prediction of impending delirium in the ICU, which can potentially lead to early intervention, more efficient allocation of ICU resources, and improved patient outcomes.

Perioperative Hemodynamic Optimization in Patients at Risk for Delirium – A Randomized-Controlled Trial

Background

Post-operative delirium is common in elderly patients and associated with increased morbidity and mortality. We evaluated in this pilot study whether a perioperative goal-directed hemodynamic optimization algorithm improves cerebral oxygenation and can reduce the incidence of delirium.

Materials and Methods

Patients older than 70 years with high risk for post-operative delirium undergoing elective non-cardiac surgery were randomized to an intervention or control group. Patients in the intervention group received a perioperative hemodynamic optimization protocol based on uncalibrated pulse-contour analysis. Patients in the control group were managed according to usual standard of care. Incidence of delirium until day seven was assessed with confusion assessment method (CAM) and chart review. Cerebral oxygenation was measured with near-infrared spectroscopy.

Results

Delirium was present in 13 of 85 (15%) patients in the intervention group and 18 of 87 (21%) in the control group [risk difference −5.4%; 95% confidence interval, −16.8 to 6.1%; P = 0.47]. Intervention did not influence length of stay in hospital or in-hospital mortality. Amounts of fluids and vasopressors applied, mean arterial pressure, cardiac index, and near-infrared spectroscopy values were comparable between groups.

Conclusion

The hemodynamic algorithm applied in high-risk non-cardiac surgery patients did not change hemodynamic interventions, did not improve patient hemodynamics, and failed to increase cerebral oxygenation. An effect on the incidence of post-operative delirium could not be observed.

Clinical Trial Registration

[Clinicaltrials.gov], identifier [NCT01827501].

Delirium diagnosis without a gold standard: Evaluating diagnostic accuracy of combined delirium assessment tools

Background

Fluctuating course of delirium and complexities of ICU care mean delirium symptoms are hard to identify or commonly confused with other disorders. Delirium is difficult to diagnose, and clinicians and researchers may combine assessments from multiple tools. We evaluated diagnostic accuracy of different combinations of delirium assessments performed in each enrolled patient.

Methods

Data were obtained from a previously conducted cross-sectional study. Eligible adult patients who remained admitted to ICU for >24 hours with at least one family member present were consecutively enrolled as patient-family dyads. Clinical delirium assessments (Intensive Care Delirium Screening Checklist [ICSDC] and Confusion Assessment Method-ICU [CAM-ICU]) were completed twice daily by bedside nurse or trained research assistant, respectively. Family delirium assessments (Family Confusion Assessment Method and Sour Seven) were completed once daily by family members. We pooled all delirium assessment tools in a single two-class latent model and pairwise (i.e., combined, clinical or family assessments) Bayesian analyses.

Results

Seventy-three patient-family dyads were included. Among clinical delirium assessments, the ICDSC had lower sensitivity (0.72; 95% Bayesian Credible [BC] interval 0.54–0.92) and higher specificity (0.90; 95%BC, 0.82–0.97) using Bayesian analyses compared to pooled latent class analysis and CAM-ICU had higher sensitivity (0.90; 95%BC, 0.70–1.00) and higher specificity (0.94; 95%BC, 0.80–1.00). Among family delirium assessments, the Family Confusion Assessment Method had higher sensitivity (0.83; 95%BC, 0.71–0.92) and higher specificity (0.93; 95%BC, 0.84–0.98) using Bayesian analyses compared to pooled latent class analysis and the Sour Seven had higher specificity (0.85; 95%BC, 0.67–0.99) but lower sensitivity (0.64; 95%BC 0.47–0.82).

Conclusions

Results from delirium assessment tools are often combined owing to imperfect reference standards for delirium measurement. Pairwise Bayesian analyses that explicitly accounted for each tool’s (performed within same patient) prior sensitivity and specificity indicate that two combined clinical or two combined family delirium assessment tools have fair diagnostic accuracy.

Delirium in Older Adults: What a Surgeon Needs to Know

Delirium remains a challenging clinical problem in hospitalized older adults, especially for postoperative patients. This complication, with a high risk of postoperative mortality and an increased length of stay, frequently occurs in older adult patients. This brief narrative paper aims to review the recent literature regarding delirium and its most recent update. We also offer physicians a brief and essential clinical practice guide to managing this acute and common disease.

Animal-Assisted Interventions in Intensive Care Delirium: A Literature Review

Critical illness has lasting consequences on the mind and the body. Acute sequelae include a decline in cognitive function known as delirium. Increased interest in improving outcomes for intensive care unit survivors without a high incidence of delirium has initiated a focus on an array of nonpharmacologic interventions in many countries. One such intervention is animalassisted intervention. As the role of animals in human healing is being recognized by clinicians, need is increasing for formal and professionally directed therapies. This review ascertains the effect of interaction with animals on critically ill patients. Emerging evidence indicates that animal-assisted intervention improves the efficacy of critical care regarding primary symptoms and secondary factors of delirium.