Confusion Assessment Method For Intensive Care Unit Research Articles

Delirium as a Risk Factor for Mortality in Critically Ill Patients With Cancer.

Although delirium is known to negatively affect critically ill patients, little data exist on delirium in critically ill patients with cancer. We analyzed 915 critically ill patients with cancer between January and December 2018. Delirium screening was performed using the Confusion Assessment Method for the intensive care unit (ICU), performed twice daily. Confusion Assessment Method-ICU incorporates four features of delirium: acute fluctuations in mental status, inattention, disorganized thinking, and altered levels of consciousness. Multivariable analysis controlling for admitting service, pre-ICU hospital length of stay (LOS), metastatic disease, CNS involvement, Mortality Probability Model II score on ICU admission, mechanical ventilation, and others was performed to determine precipitating factors for delirium, ICU, and hospital mortality and LOS. Delirium occurred in 40.5% (n = 317) of patients; 43.8% (n = 401) were female; the median age was 64.9 (interquartile range, 54.6-73.2) years; 70.8% (n = 647) were White, 9.3% (n = 85) were Black, and 8.9% (n = 81) were Asian. The most common cancer types were hematologic (25.7%, n = 244) and gastrointestinal (20.9%, n = 191). Delirium was independently associated with age (OR, 1.01; 95% CI, 1.00 to 1.02; P = .038), longer pre-ICU hospital LOS (OR, 1.04; 95% CI, 1.02 to 1.06; P < .001), not resuscitating on admission (OR, 2.18; 95% CI, 1.07 to 4.44; P = .032), CNS involvement (OR, 2.25; 95% CI, 1.20 to 4.20; P = .011), higher Mortality Probability Model II score (OR, 1.02; 95% CI, 1.01 to 1.02; P < .001), mechanical ventilation (OR, 2.67; 95% CI, 1.84 to 3.87; P < .001), and sepsis diagnosis (OR, 0.65; 95% CI, 0.43 to 0.99; P = .046). Delirium was also independently associated with higher ICU mortality (OR, 10.75; 95% CI, 5.91 to 19.55; P < .001), hospital mortality (OR, 5.84; 95% CI, 4.03 to 8.46; P < .001), and ICU LOS (estimate, 1.67; 95% CI, 1.54 to 1.81; P < .001). Delirium significantly worsens outcome in critically ill patients with cancer. Delirium screening and management should be integrated into the care of this patient subgroup.

Prevalence and Risk Factors for Intensive Care Unit Delirium After Traumatic Brain Injury: A Retrospective Cohort Study.

Delirium remains understudied after traumatic brain injury (TBI). We sought to identify independent predictors of delirium among intensive care unit (ICU) patients with TBI. This single-center retrospective cohort study evaluated adult patients with TBI requiring ICU admission. Outcomes included delirium days within the first 14days, as assessed by the Confusion Assessment Method-ICU (CAM-ICU). Models were adjusted for age, sex, insurance, Marshall head computed tomography classification, presence of subarachnoid hemorrhage (SAH), Injury Severity Score (ISS), need for cardiopulmonary resuscitation, maximum admission Glasgow Coma motor score, glucose level, hemoglobin level, and pupil reactivity. Delirium prevalence was 60%, with a median duration of 4days (interquartile range: 2-8) among ICU patients with TBI (n = 2,664). Older age, higher ISS, maximum motor score < 6, Marshall class II-IV, and SAH were associated with risk of increased delirium duration (all p < 0.001). In this large cohort, ICU delirium after TBI affected three of five patients for a median duration of 4days. Age, general injury severity, motor score, and features of intracranial hemorrhage were predictive of more TBI-associated delirium days. Given the high prevalence of ICU delirium after TBIand itsimpact on hospitalization, further work is needed to understand the impact of delirium and TBI on outcomes and to determine whether delirium risk can be minimized.

Occurrence of Postoperative Delirium and the Use of Different Assessment Tools.

(1) Background: Postoperative delirium (POD) poses a high risk of worsening outcomes for patients and is also a burden for hospitals. The leading guidelines recommend standardized POD assessment and prevention. The aim of this subgroup analysis of the PRe-Operative Prediction of Postoperative DElirium by Appropriate SCreening (PROPDESC) trial was to compare different delirium assessments and to analyse the frequency of POD on five postoperative days. (2) Methods: This prospective observational trial enrolled 1097 patients in a university hospital from 2018 until 2019. The following POD assessment tools were used for five consecutive days: Confusion Assessment Method for ICU (CAM-ICU) or Confusion Assessment Method for normal ward (CAM), 4 A's Test (4AT) and Delirium Observation Screening (DOS) scale. (3) Results: In a 5-day visit interval, most new POD developments occurred on the first and second postoperative day. A clear recommendation for a specific POD assessment tool based on our results cannot be given. (4) Conclusions: According to guidelines, a POD assessment should take place on the first five postoperative days, but of these, the first two are those of highest POD occurrence. The POD assessment tool used should at best include direct patient questioning and aspects of patient observation.

Intraoperative infusion of dexmedetomidine for prevention of postoperative delirium in elderly patients undergoing craniotomy: a protocol of randomised clinical trial

IntroductionPostoperative delirium (POD) is a common surgical complication. The incidence is 19% in neurological procedures, and advanced age is a risk factor for neurological procedures. Many studies have shown that...

Effects of Coronavirus Disease 2019 and Frailty on Delirium in the Intensive Care Unit: A Propensity Score Analysis

Purpose: The association between frailty and delirium has emerged as a research topic. Neurological symptoms have been reported among patients with coronavirus disease 2019 (COVID-19), but its effects on delirium remain unclear. This study aimed to compare the incidence of delirium between patients with COVID-19 and those without COVID-19, and to evaluate the impact of COVID-19 and frailty on delirium. Methods: This retrospective study included patients aged ≥ 20 years who were admitted to our intensive care unit (ICU) between January 2020 and February 2022. An inverse probability of treatment weighting using stabilized inverse propensity scores was adopted to minimize bias. After patient demographics were adjusted, the incidence of delirium, assessed using the Confusion Assessment Method for ICU, was compared between patients with COVID-19 and those without COVID-19. The effects of COVID-19 and the Clinical Frailty Scale score on delirium were analyzed by adjusting some covariates, including the sequential organ failure assessment (SOFA) score, using a generalized estimating equation. Results: Among 260 eligible patients, 226 patients were included. The weighted incidence of delirium was 56.9% and 61.9% in patients with and without COVID-19, respectively (p = 0.67). The generalized estimating equation revealed that the odds ratios (95% confidence interval) for COVID-19, the CFS score, and the SOFA score were 1.49 (0.62 - 3.57), 1.46 (1.11 - 1.91), and 1.22 (1.10 - 1.36), respectively. Conclusion: CFS and SOFA scores on ICU admission may be associated with delirium, with no significant difference between patients with COVID-19 and those without COVID-19.

Delirium severity and outcomes of critically ill COVID-19 patients.

To investigate the impact of delirium severity in critically ill COVID-19 patients and its association with outcomes. This prospective cohort study was performed in two tertiary intensive care units in Rio de Janeiro, Brazil. COVID-19 patients were evaluated daily during the first 7 days of intensive care unit stay using the Richmond Agitation Sedation Scale, Confusion Assessment Method for Intensive Care Unit (CAM-ICU) and Confusion Method Assessment for Intensive Care Unit-7 (CAM-ICU-7). Delirium severity was correlated with outcomes and one-year mortality. Among the 277 COVID-19 patients included, delirium occurred in 101 (36.5%) during the first 7 days of intensive care unit stay, and it was associated with a higher length of intensive care unit stay in days (IQR 13 [7 - 25] versus 6 [4 - 12]; p < 0.001), higher hospital mortality (25.74% versus 5.11%; p < 0.001) and additional higher one-year mortality (5.3% versus 0.6%, p < 0.001). Delirium was classified by CAM-ICU-7 in terms of severity, and higher scores were associated with higher in-hospital mortality (17.86% versus 34.38% versus 38.46%, 95%CI, p value < 0.001). Severe delirium was associated with a higher risk of progression to coma (OR 7.1; 95%CI 1.9 - 31.0; p = 0.005) and to mechanical ventilation (OR 11.09; 95%CI 2.8 - 58.5; p = 0.002) in the multivariate analysis, adjusted by severity and frailty. In patients admitted with COVID-19 in the intensive care unit, delirium was an independent risk factor for the worst prognosis, including mortality. The delirium severity assessed by the CAM-ICU-7 during the first week in the intensive care unit was associated with poor outcomes, including progression to coma and to mechanical ventilation.

A Descriptive Cross-Sectional Study on Clinical Profile and Outcome of Delirium in Trauma Patients in the Semi-Closed Intensive Care Unit of a Medical College

Introduction: Delirium in trauma patients is common and underdiagnosed.&#x0D; Objectives: This study aimed to identify the risk factors and outcome of delirium in trauma patients in a mixed semi-closed intensive care unit.&#x0D; Methodology: This descriptive cross-sectional study was done on 77 patients of age 18 years or more admitted for more than 24 hours with the history of road traffic accidents, falls, drowning, physical assaults, and self- inflicted violence in a level three intensive care unit of the National Medical College for six months. The whole sampling method was used in our study and all cases during a given time were included in the study. The Confusion Assessment Method-ICU and Richmond Agitation Sedation Scale were used to diagnose delirium and level of arousal respectively. All data was transferred to the excel sheet and transferred to a statistical package for the social sciences-16. The Chi-square test and Fisher’s exact probability test were used to detect the difference between groups in the univariate analysis, as appropriate. The variables were analyzed using binary logistic regression. Any variables which had P&lt;0.2 after the univariable risk regression and all other potential variables associated with the delirium were included for the multivariable risk regression. The level of significance was P&lt;0.05.&#x0D; Result: Of the 77 ICU admissions 17(22.1%) developed delirium. Hyperactive delirium was the most common motor subtype 9(52.9%). The mean duration of delirium was 3.69±4.06 days. Age, hypertension, blood transfusion, and orthopedic trauma were identified as risk factors for delirium. Delirious patients had a longer length of stay in the ICU (7.0 ±4.6 vs 4.5±4.1 days) with no impact on the duration of mechanical ventilation, mortality, reintubation, and unplanned extubation.&#x0D; Conclusion: Age, hypertension, blood transfusion and orthopaedic trauma were identified as the risk factor for delirium in trauma patients that should be identified early to prevent complications such as longer length of stay in the ICU, longer duration of mechanical ventilation, mortality, reintubation and unplanned extubation.

Prognostic significance of delirium subtypes in critically ill medical and surgical patients: a secondary analysis of a prospective multicenter study

BackgroundThe prognostic implication of delirium subtypes in critically ill medical and surgical patients is scarcely investigated. The objective was to determine how delirium subtypes are associated with hospital mortality and other clinical outcomes.MethodsWe performed a secondary analysis on data from a prospective multicenter study aimed at implementation of delirium-oriented measures, conducted between 2012 and 2015 in The Netherlands. We included adults (≥ 18 years) admitted to the medical or surgical intensive care unit (ICU). Exclusion criteria were neurological admission diagnosis, persistent coma or ICU readmissions. Delirium was assessed using the Confusion Assessment Method-ICU or Intensive Care Delirium Screening Checklist, and delirium subtypes (hypoactive, hyperactive, or mixed) were classified using the Richmond Agitation–Sedation Scale. The main outcome was hospital mortality. Secondary outcomes were ICU mortality, ICU length of stay, coma, mechanical ventilation, and use of antipsychotics, sedatives, benzodiazepines and opioids.ResultsDelirium occurred in 381 (24.4%) of 1564 patients (52.5% hypoactive, 39.1% mixed, 7.3% hyperactive). After case-mix adjustment, patients with mixed delirium had higher hospital mortality than non-delirious patients (OR 3.09, 95%CI 1.79–5.33, p = 0.001), whereas hypoactive patients did not (OR 1.34, 95%CI 0.71–2.55, p = 0.37). Similar results were found for ICU mortality. Compared to non-delirious patients, both subtypes had longer ICU stay, more coma, increased mechanical ventilation frequency and duration, and received more antipsychotics, sedatives, benzodiazepines and opioids. Except for coma and benzodiazepine use, the most unfavourable outcomes were observed in patients with mixed delirium.ConclusionsPatients with mixed delirium had the most unfavourable outcomes, including higher mortality, compared with no delirium. These differences argue for distinguishing delirium subtypes in clinical practice and future research.Trial registration ClinicalTrials.gov NCT01952899.

Excessive Sedation as a Risk Factor for Delirium: A Comparison between Two Cohorts of ARDS Critically Ill Patients with and without COVID-19.

Excessive sedation is associated with poor outcome in critically ill acute respiratory distress syndrome (ARDS) patients. Whether this prognostic effect varies among ARDS patients with and without COVID-19 has yet to be determined. We compared the prognostic value of excessive sedation-in terms of delirium, length of stay in intensive care unit (ICU-LOS) and ICU mortality-between COVID-19 and non-COVID-19 critically ill ARDS patients. This was a second analysis of prospectively collected data in four European academic centers pertaining to 101 adult critically ill ARDS patients with and without COVID-19 disease. Depth of sedation (DOS) and delirium were monitored through processed electroencephalogram (EEG) and the Confusion Assessment Method for ICU (CAM-ICU). Our main exposure was excessive sedation and how it relates to the presence of delirium, ICU-LOS and ICU mortality. The criterion for excessive sedation was met in 73 (72.3%) patients; of these, 15 (82.2%) and 58 (69.1%) were in non-COVID-19 and COVID-19 ARDS groups, respectively. The criteria of delirium were met in 44 patients (60.3%). Moreover, excessive sedation was present in 38 (86.4%) patients with delirium (p &lt; 0.001). ICU death was ascertained in 41 out of 101 (41.0%) patients; of these, 37 (90.2%) had excessive sedation (p &lt; 0.001). The distribution of ICU-LOS among excessive-sedated and non-sedated patients was 22 (16-27) vs. 14 (10.5-19.5) days (p &lt; 0.001), respectively. In a multivariable framework, excessive sedation was independently associated with the development of delirium (p = 0.001), increased ICU mortality (p = 0.009) and longer ICU-LOS (p = 0.000), but only in COVID-19 ARDS patients. Independent of age and gender, excessive sedation might represent a risk factor for delirium in COVID-19 ARDS patients. Similarly, excessive sedation shows to be an independent predictor of ICU-LOS and ICU mortality. The use of continuous EEG-based depth of sedation (DOS) monitoring and delirium assessment in critically ill COVID-19 patients is warranted.

The effect of intravenous remifentanil and fentanyl postoperative delirium incidence in patients receiving elective orthopedic surgeries

Background: The use of certain opioids associated differently with the incidence of postoperative delirium (POD). Remifentanil and fentanyl are short-acting opioids widely used in surgery; however, studies assessing their relationship with POD incidence are still limited. This study aimed to determine the association of remifentanil and fentanyl uses with the incidence of POD in elective orthopedic surgery patients. Methods: A cross-sectional study was conducted in Surgical Unit at Dr Soetomo General Academic Hospital in Surabaya, Indonesia from August to September 2022. Patients who underwent elective orthopedic surgery and used remifentanil (n=16) and fentanyl (n=14) as postoperative analgesia were enrolled in the study. Delirium was assessed using Confusion Assessment Method-ICU tool (CAM-ICU). The associations of remifentanil and fentanyl use as well as patients’ characteristics with POD incidence were assessed statistically. Results: Our data found that there was no significant difference between the incidence of POD with the use of remifentanil (p=0.125) in orthopedic surgery patients. The total doses of fentanyl and morphine equivalent (of remifentanil or fentanyl) were associated significantly with the POD incidence (p=0.010 and p=0.002, respectively). Other factors associated with POD incidence were the use of bone cement during the surgery (p=0.034), duration of surgery (p&lt;0.001), and bleeding volume during the surgery (p=0.024). Conclusions: Our study showed high dose of fentanyl, use of bone cement, longer duration of surgery, and high bleeding volume have greater risk of developing POD in orthopedic surgery patients.

Relation between postoperative delirium and preoperative routine serum biomarkers

Background: Delirium is an acute and fluctuating change in the mental state characterised by diminished awareness and attention disturbance. Postoperative delirium (POD) is one of the most prevalent complications after surgery, especially in older indiviuals, and is related to a longer hospital stay and increased mortality.1 Although the cause of POD is less clear, several hypothesised causes include neuroinflammation, neurotransmitter imbalance, and oxidative stress, all of which may contribute to the pathophysiology of POD.2 This study aimed to investigate the relationship between routine preoperative blood inflammatory markers and POD, and the incidence and outcomes of POD. Methods: We included patients from the National Emergency Laparotomy Audit (NELA) database aged ≥65 yr at the time of operation at Queen Elizabeth Hospital, Birmingham, UK. The study was conducted prospectively and retrospectively. In the prospective part, we screened the patients for delirium 5 days postoperatively using the modified Richmond Agitation Sedation Scale (mRASS), Confusion Assessment Method for ICU (CAM-ICU),3 and patient notes. Retrospectively, the clinical notes were scanned for keywords according to a validated chart abstraction method.4 We applied the Diagnostic and Statistical Manual of Mental Disorders V (DSM-V) criteria to diagnose POD in those who screened positive. We documented the preoperative blood results, including haemoglobin, white blood cells (WBCs), neutrophils, lymphocytes, platelets, neutrophil/lymphocyte ratio (NLR), urea, creatinine, and lactate. Multivariate logistic regression analyses were performed. Results: POD was diagnosed in 49 of 164 patients (29.9%). Sepsis, renal disease, and higher ASA grade and NELA mortality scores were significantly related to POD incidence. Statistical analysis showed a significant relation between POD and higher levels of preoperative urea, C-reactive protein (CRP), CRP/albumin ratio (CAR), NLR, and platelet/lymphocyte ratio (PLR). Furthermore, low levels of haemoglobin and albumin were significantly associated with POD. POD patients required significantly longer hospital stays with higher mortality. Multivariate logistic regression analysis demonstrated that age >75 yr, sepsis, and high preoperative PLR are independent risk factors for POD. Conclusions: Higher preoperative CAR, PLR, and NLR were associated with a higher incidence of POD in patients aged ≥65 yr undergoing emergency laparotomy. Our study supports that preoperative inflammatory status can be linked to POD. Knowing the mechanisms and risk factors can help clinicians to decrease POD incidence. 1.Aldecoa C, Bettelli G, Bilotta F, et al. Eur J Anaesth 2017; 34: 192–2142.Moppett I, Noah A. Br J Anaesth 2021; 127: 424–343.Oh ES, Fong TG, Hsieh TT, Inouye SK. JAMA 2017; 318: 1161–744.Kuhn E, Lorenz R, Banaschewski T, et al. PloS One 2014; 9: e91506

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

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

A Descriptive Cross-Sectional Study on the Incidence, Risk Factor and Outcome of Delirium in Surgical Patients in the Semi-Closed Intensive Care Unit

Introduction: There is a variation in risk factors and outcome of delirium in surgical patients in different studies. This study was conducted to determine the incidence, risk factors, and outcome of delirium in the surgical semiclosed intensive care unit in a developing country. Materials and Methods: This descriptive study was done in 82 patients of age≥18 years that underwent non-neurological surgery and admitted for more than 24 hours in a level three intensive care unit of medical college from January 10, 2021 to January 9, 2022. The whole sampling method was used in our study. The Confusion Assessment Method-ICU and Richmond Agitation Sedation Scale were used to diagnose delirium and sedation, respectively, along with a checklist to assess risk factors. All data was transferred to the excel sheet and transferred to a statistical package for the social sciences-16. Chi-square test and Fisher’s exact probability test were used to detect the difference between groups in the univariate analysis, as appropriate. The risk factors were analysed using binary logistic regression. Result: Of the 82 ICU admissions 28(34.1%) developed delirium. Hyperactive delirium was the most common motor subtype 12(42.8%). The mean duration of delirium was 4.69±5.06 days. Hypertension and alcohol were identified as risk factors for delirium. Delirious patients had a longer length of stay in the ICU (10.1 ±12.7 vs 5.1 ±4.2 days) with no impact on the duration of mechanical ventilation, mortality, reintubation, and unplanned extubation. Conclusion: Early recognition of risk factors for delirium in surgical patients can decrease the mortality and morbidity of surgical patients.

The effect of taurine supplementation on delirium post liver transplantation: A randomized controlled trial

Delirium is a prevalent complication of liver transplantation (LT). It may enhance the risk of morbidity and mortality. Taurine is considered to have antioxidant and neuroprotective activities. The aim of this study was to evaluate taurine supplementation effect on post-LT delirium. Patients older than 18 years old who had received LT in Abu-Ali Sina transplantation center in Shiraz, Iran from September 2020 to June 2021, were enrolled in this double-blinded randomized clinical trial. Exclusion criteria was known hypersensitivity to taurine, pregnancy or breast-feeding and death within 72h post-LT. Patients were randomly divided into two groups, each received 2g/day placebo or taurine from the first day post-LT for 30 days. Delirium was assessed using Confusion Assessment Method-Intensive Care Unit (CAM-ICU). Mortality and rejection rates and length of Intensive Transplantation Unit (ITU) and hospital stays were evaluated within one month after transplantation. Two hundred and seven patients were divided into two groups. Twenty-eight and 23 patients were excluded due to their refuse to participate in the study and death within 72h post-LT, respectively. Delirium rate within the first month was 23.08% and was significantly lower in taurine group (9.46%) compared with placebo (35.36%, P=0.012). Length of ITU stay was significantly higher among delirious patients (P=0.015) in this analysis. we reached to the result that taurine can prevent post-LT delirium, dramatically. Placebo receiving and longer stay in ITU were the only independent risk factors in this trial. The study was registered at the Iranian Registry of Clinical Trials (IRCT20200312046755N1; http://www.irct.ir/).

Comparison Between Deltascan Single Channel Electroencephalography (EEG), Confusion Assessment Method-Intensive Care Unit (CAM-ICU) Score and Clinical Assessment in Diagnosing Delirium in Intubated Patients in the Intensive Care Unit.

BackgroundThe aim of this article is to assess the feasibility of using single-channel electroencephalography (EEG) measurement for detecting delirium in intubated Intensive care (ICU) patients and to assess the level of agreement between the EEG measurements, the CAM-ICU score and the clinical diagnosis of delirium.Materials and methodsThis study was an exploratory pilot between May 2021 and September 2021 including intubated patients in the ICU. For this study the Prolira® (Arnhem, The Netherlands) Deltascan single-channel EEG was used and compared with the Confusion Assessment Method (CAM)-ICU and the clinical diagnosis of delirium by ICU physicians.ResultsIn total 23 patients were found eligible for this study, of which 20 were included in the final analysis. The patients mean age was 63.0 ± 8.8 years, and the majority (thirteen) was male (65%). In total 17 of the 20 patients (85%) received the diagnosis delirium by the medical team. There were no statistically significant differences between the Deltascan and CAM-ICU measurements in diagnosing delirium per time point (p values respectively 0.21; 0.90; 0.34; 0.11; 0.056 and 0.091). AUCs for the agreement between the CAM-ICU and the Deltascan measurements were respectively: 0.676 ± 0.205; 0.333 ± 0.224; 0.402 ± 0.146; 0.488 ± 0.202; 0.06 ± 0.077 and 0.06 ± 0.109 (all p>0.05). AUCs for the level of agreement between the clinical diagnosis delirium and Deltascan were: 0.676 ± 0.152; 0.686 ± 0.146; 0.711 ± 0.132; 0.688 ± 0.136; 0.500 ± 0.158 and 0.700 ± 0.211 (all p>0.05).ConclusionIn this exploratory study, we showed that there is no statistical agreement between CAM-ICU and Delta scan measurements. Secondly, there is a higher agreement, although not statistically significant between the clinical diagnoses of a delirium (by a clinician) with the Deltascan measurements. Despite this small study we think that the Deltascan can be of additional value in intubated ICU patients and therefore larger studies are needed to substantiate our findings.

The Impact of Perioperative and Predisposing Risk Factors on the Development of Postoperative Delirium and a Possible Gender Difference.

(1) Background: Postoperative delirium (POD) is an undesirable event especially for older patients after surgery. Perioperative risks for POD development are multiple, but gender differences are still poorly considered. In this observational study, predisposing and precipitating risk factors of POD and the possible gender influence are distinguished. (2) Methods: This observational prospective trial enrolled 1097 patients in a tertiary hospital from September 2018 until October 2019. POD was considered positive, if one of the tests Confusion Assessment Method for ICU (CAM-ICU) or Confusion Assessment Method (CAM), 4 ‘A’s Test (4AT) or Delirium Observation Screening (DOS) scale was positive on one of five assessment days. (3) Results: POD incidence was 23.5% and the mean age of study population was 72.3 ± 7.3 years. The multiple logistic regression model showed a significant impact of age (Odds Ratio (OR) 1.74; 95% Confidence Interval (CI): 1.37–2.22), American Society of Anesthesiologists (ASA) (OR 1.67; 95% CI: 1.25–2.26), surgery risk (OR 2.10; 95% CI: 1.52–2.95) and surgery duration (OR 1.17; 95% CI: 1.07–1.28), ventilation time (OR 1.64; 95% CI: 1.27–2.24), as well as the male sex (OR 1.74; 95% CI: 1.37–2.22) on POD risk. (4) Conclusions: Perioperative and predisposing risk factors had an impact on the development of POD. The influence of male sex should be considered in future research.

Delirium incidence and risk factors in patients undergoing non-invasive ventilation for acute respiratory failure: a multicenter observational trial.

Noninvasive ventilation (NIV) still has high failure rate when used for de novo acute respiratory failure (ARF). Delirium may impact the outcome, however data regarding its incidence, timing of occurrence and clinical predictors in this subset of patients are scarce. Consecutive patients with de novo ARF subjected to NIV were recruited in 10 Italian Respiratory Intensive Care Units (RICUs) and Intensive Care Units (ICUs). Demographics and clinical features, including tolerance to interface and NIV setting were recorded on admission and during stay, whereas delirium onset and type was assessed by the Confusion Assessment Method for ICU (CAM-ICU)-7 scale and Richmond Agitation Sedation Scale (RASS) twice/per day up to a week. The association between clinical variables and the occurrence of delirium and its influence on NIV failure and other clinical outcomes were analyzed. Thirty-two out of 90 enrolled patients (36%) developed delirium over seven days upon admission; median time to onset was 48 hours (24-60). Older age (OR=2.7 [1.9-9], P=0.01), the presence of cancer OR=3.7 [2-5.4], P=0.002), sepsis (OR=1.7 [1.1-3.4], P=0.01), SOFA Score (OR=1.8 [1.1-3.1], P=0.01), low tolerance to interface (OR=3.2 [2.1-5], P=0.002), use of helmet (OR=1.9 [1.2-4.3] P=0.04), and higher PRE-DELIRIC (OR=3.5 [1.3-15], P=0.03) and BORG (OR=1.7 [1.1-4.6], P=0.02] scores were significantly associated with delirium. Delirium had high risk for NIV failure (HR=3.5 95% CI: [1.4-8.6], P=0.0002) and it significantly associated with longer RICU/ICU stay and higher mortality. Delirium onset in acute hypoxic patients undergoing NIV is frequent and negatively affects the outcome. Multiple related clinical factors should be addressed early on admission to prevent the delirium-related risk of NIV failure in these patients.

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

BackgroundFluctuating 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.MethodsData 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.ResultsSeventy-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).ConclusionsResults 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 prediction in the ICU: designing a screening tool for preventive interventions.

IntroductionDelirium occurrence is common and preventive strategies are resource intensive. Screening tools can prioritize patients at risk. Using machine learning, we can capture time and treatment effects that pose a challenge to delirium prediction. We aim to develop a delirium prediction model that can be used as a screening tool.MethodsFrom the eICU Collaborative Research Database (eICU-CRD) and the Medical Information Mart for Intensive Care version III (MIMIC-III) database, patients with one or more Confusion Assessment Method-Intensive Care Unit (CAM-ICU) values and intensive care unit (ICU) length of stay greater than 24 h were included in our study. We validated our model using 21 quantitative clinical parameters and assessed performance across a range of observation and prediction windows, using different thresholds and applied interpretation techniques. We evaluate our models based on stratified repeated cross-validation using 3 algorithms, namely Logistic Regression, Random Forest, and Bidirectional Long Short-Term Memory (BiLSTM). BiLSTM represents an evolution from recurrent neural network-based Long Short-Term Memory, and with a backward input, preserves information from both past and future. Model performance is measured using Area Under Receiver Operating Characteristic, Area Under Precision Recall Curve, Recall, Precision (Positive Predictive Value), and Negative Predictive Value metrics.ResultsWe evaluated our results on 16 546 patients (47% female) and 6294 patients (44% female) from eICU-CRD and MIMIC-III databases, respectively. Performance was best in BiLSTM models where, precision and recall changed from 37.52% (95% confidence interval [CI], 36.00%–39.05%) to 17.45 (95% CI, 15.83%–19.08%) and 86.1% (95% CI, 82.49%–89.71%) to 75.58% (95% CI, 68.33%–82.83%), respectively as prediction window increased from 12 to 96 h. After optimizing for higher recall, precision and recall changed from 26.96% (95% CI, 24.99%–28.94%) to 11.34% (95% CI, 10.71%–11.98%) and 93.73% (95% CI, 93.1%–94.37%) to 92.57% (95% CI, 88.19%–96.95%), respectively. Comparable results were obtained in the MIMIC-III cohort.ConclusionsOur model performed comparably to contemporary models using fewer variables. Using techniques like sliding windows, modification of threshold to augment recall and feature ranking for interpretability, we addressed shortcomings of current models.

Prediction of Postoperative Delirium After Cardiac Surgery with A Quick Test of Cognitive Speed, Mini-Mental State Examination and Hospital Anxiety and Depression Scale.

PurposeTo evaluate if preoperative assessment with A Quick Test of Cognitive Speed (AQT) could increase the accuracy of predicting delirium after cardiac surgery compared to Mini-Mental State Examination (MMSE), and examine if a composite of variables, including cognitive function and depressive symptoms, could be useful to predict delirium.Patients and MethodsCardiac surgery was performed in 218 patients (mean age 72 years). Preoperative evaluation involved AQT, MMSE and Hospital Anxiety And Depression Scale (HADS). Postoperative delirium was assessed using Nursing Delirium Screening Scale (Nu-DESC) and Confusion Assessment Method-ICU (CAM-ICU). Logistic regression was performed to detect predictors of postoperative delirium and receiver operator characteristic curves (ROC) with area under the curve (AUC) to determine the accuracy.ResultsPostoperative delirium occurred in 47 patients (22%) who had lower MMSE scores (median (range), 27 (19–30) vs 28 (20–30), p=0.009) and slower AQT (median (range), 76 (48–181) vs 70 (40–182) seconds, p=0.030) than patients without delirium. Predictive power measured as AUC (95% CI) was 0.605 (0.51–0.70) for AQT and 0.623 (0.53–0.72) for MMSE. Logistic regression (OR, 95% CI) showed MMSE <27 points (2.72, 1.27–5.86), AQT >70 sec (2.26, 1.03–4.95), HADS-D >4 points (2.60, 1.21–5.58) and longer cardiopulmonary bypass-time (1.007, 1.002–1.013) to be associated with postoperative delirium. Combining these parameters yielded an AUC of 0.736 (0.65–0.82).ConclusionThe ability of predicting delirium using AQT was similar to MMSE, and only slightly higher by combining AQT and MMSE. Adding HADS-D and cardiopulmonary bypass-time to MMSE and AQT increased the predictive power to a borderline acceptable discriminatory value. Preoperative cognitive tests and screening for depressive symptoms may help identify patients at risk of postoperative delirium. Yet, there is still a need to establish useful preoperative tests.