Irene J. Zaal

A systematic review of risk factors for delirium in the ICU.

Objective:Although numerous risk factors for delirium in the ICU have been proposed, the strength of evidence supporting each risk factor remains unclear. This study systematically identifies risk factors for delirium in critically ill adults where current evidence is strongest. Data Sources:CINAHL, EMBASE, MEDLINE, the Cochrane Central Register for Controlled Trials, and the Cochrane Database of Systematic Reviews. Study Selection:Studies published from 2000 to February 2013 that evaluated critically ill adults, not undergoing cardiac surgery, for delirium, and used either multivariable analysis or randomization to evaluate variables as potential risk factors for delirium. Data Extraction:Data were abstracted in duplicate, and quality was scored using Scottish Intercollegiate Guidelines Network checklists (i.e., high, acceptable, and low). Using a best-evidence synthesis each variable was evaluated using 3 criteria: the number of studies investigating it, the quality of these studies, and whether the direction of association was consistent across the studies. Strengths of association were not summarized. Strength of evidence was defined as strong (consistent findings in ≥2 high quality studies), moderate (consistent findings in 1 high quality study and ≥1 acceptable quality studies), inconclusive (inconsistent findings or 1 high quality study or consistent findings in only acceptable quality/low quality studies) or no evidence available. Data Synthesis:Among 33 studies included, 70% were high quality. There was strong evidence that age, dementia, hypertension, pre-ICU emergency surgery or trauma, Acute Physiology and Chronic Health Evaluation II score, mechanical ventilation, metabolic acidosis, delirium on the prior day, and coma are risk factors for delirium, that gender is not associated with delirium, and that use of dexmedetomidine is associated with a lower delirium prevalence. There is moderate evidence that multiple organ failure is a risk factor for delirium. Conclusions:Only 11 putative risk factors for delirium are supported by either strong or moderate level of evidence. These factors should be considered when designing delirium prevention strategies or controlling for confounding in future etiologic studies.

The attributable mortality of delirium in critically ill patients: prospective cohort study

Objective To determine the attributable mortality caused by delirium in critically ill patients. Design Prospective cohort study. Setting 32 mixed bed intensive care unit in the Netherlands, January 2011 to July 2013. Participants 1112 consecutive adults admitted to an intensive care unit for a minimum of 24 hours. Exposures Trained observers evaluated delirium daily using a validated protocol. Logistic regression and competing risks survival analyses were used to adjust for baseline variables and a marginal structural model analysis to adjust for confounding by evolution of disease severity before the onset of delirium. Main outcome measure Mortality during admission to an intensive care unit. Results Among 1112 evaluated patients, 558 (50.2%) developed at least one episode of delirium, with a median duration of 3 days (interquartile range 2-7 days). Crude mortality was 94/558 (17%) in patients with delirium compared with 40/554 (7%) in patients without delirium (P<0.001). Delirium was significantly associated with mortality in the multivariable logistic regression analysis (odds ratio 1.77, 95% confidence interval 1.15 to 2.72) and survival analysis (subdistribution hazard ratio 2.08, 95% confidence interval 1.40 to 3.09). However, the association disappeared after adjustment for time varying confounders in the marginal structural model (subdistribution hazard ratio 1.19, 95% confidence interval 0.75 to 1.89). Using this approach, only 7.2% (95% confidence interval −7.5% to 19.5%) of deaths in the intensive care unit were attributable to delirium, with an absolute mortality excess in patients with delirium of 0.9% (95% confidence interval −0.9% to 2.3%) by day 30. In post hoc analyses, however, delirium that persisted for two days or more remained associated with a 2.0% (95% confidence interval 1.2% to 2.8%) absolute mortality increase. Furthermore, competing risk analysis showed that delirium of any duration was associated with a significantly reduced rate of discharge from the intensive care unit (cause specific hazard ratio 0.65, 95% confidence interval 0.55 to 0.76). Conclusions Overall, delirium prolongs admission in the intensive care unit but does not cause death in critically ill patients. Future studies should focus on episodes of persistent delirium and its long term sequelae rather than on acute mortality. Trial registration Clinicaltrials.gov NCT01905033.

Delirium in Critically Ill Patients Epidemiology, Pathophysiology, Diagnosis and Management

Delirium is commonly observed in critically ill patients and is associated with negative outcomes. The pathophysiology of delirium is not completely understood. However, alterations to neurotransmitters, especially acetylcholine and dopamine, inflammatory pathways and an aberrant stress response are proposed mechanisms leading to intensive care unit (ICU) delirium. Detection of delirium using a validated delirium assessment tool makes early treatment possible, which may improve prognosis. Patients at high risk of delirium, especially those with cognitive decline and advanced age, should be identified in the first 24 hours of admission to the ICU. Whether these high-risk patients benefit from haloperidol prophylaxis deserves further study. The effectiveness of a multicomponent, non-pharmacological approach is shown in non-ICU patients, which provides proof of concept for use in the ICU. The few studies on this approach in ICU patients suggest that the burden of ICU delirium may be reduced by early mobility, increased daylight exposure and the use of earplugs. In addition, the combined use of sedation, ventilation, delirium and physical therapy protocols can reduce the frequency and severity of adverse outcomes and should become part of routine practice in the ICU, as should avoidance of deliriogenic medication such as anticholinergic drugs and benzodiazepines. Once delirium develops, symptomatic treatment with antipsychotics is recommended, with haloperidol being the drug of first choice. However, there is limited evidence on the safety and effectiveness of antipsychotics in ICU delirium.

Delirium Detection Using EEG: What and How to Measure

BACKGROUND Despite its frequency and impact, delirium is poorly recognized in postoperative and critically ill patients. EEG is highly sensitive to delirium but, as currently used, it is not diagnostic. To develop an EEG-based tool for delirium detection with a limited number of electrodes, we determined the optimal electrode derivation and EEG characteristic to discriminate delirium from nondelirium. METHODS Standard EEGs were recorded in 28 patients with delirium and 28 age- and sex-matched patients who had undergone cardiothoracic surgery and were not delirious, as classified by experts using Diagnostic and Statistical Manual of Mental Disorders, 4th edition, criteria. The first minute of artifact-free EEG data with eyes closed as well as with eyes open was selected. For each derivation, six EEG parameters were evaluated. Using Mann-Whitney U tests, all combinations of derivations and parameters were compared between patients with delirium and those without. Corresponding P values, corrected for multiple testing, were ranked. RESULTS The largest difference between patients with and without delirium and highest area under the receiver operating curve (0.99; 95% CI, 0.97-1.00) was found during the eyes-closed periods of the EEG, using electrode derivation F8-Pz (frontal-parietal) and relative δ power (median [interquartile range (IQR)] for delirium, 0.59 [IQR, 0.47-0.71] and for nondelirium, 0.20 [IQR, 0.17-0.26]; P = .0000000000018). With a cutoff value of 0.37, it resulted in a sensitivity of 100% (95% CI, 100%-100%) and specificity of 96% (95% CI, 88%-100%). CONCLUSIONS In a homogenous population of nonsedated patients who had undergone cardiothoracic surgery, we observed that relative δ power from an eyes-closed EEG recording with only two electrodes in a frontal-parietal derivation can distinguish among patients who have delirium and those who do not.

Original Research: Critical CareDelirium Detection Using EEG

BACKGROUND Despite its frequency and impact, delirium is poorly recognized in postoperative and critically ill patients. EEG is highly sensitive to delirium but, as currently used, it is not diagnostic. To develop an EEG-based tool for delirium detection with a limited number of electrodes, we determined the optimal electrode derivation and EEG characteristic to discriminate delirium from nondelirium. METHODS Standard EEGs were recorded in 28 patients with delirium and 28 age- and sex-matched patients who had undergone cardiothoracic surgery and were not delirious, as classified by experts using Diagnostic and Statistical Manual of Mental Disorders, 4th edition, criteria. The first minute of artifact-free EEG data with eyes closed as well as with eyes open was selected. For each derivation, six EEG parameters were evaluated. Using Mann-Whitney U tests, all combinations of derivations and parameters were compared between patients with delirium and those without. Corresponding P values, corrected for multiple testing, were ranked. RESULTS The largest difference between patients with and without delirium and highest area under the receiver operating curve (0.99; 95% CI, 0.97-1.00) was found during the eyes-closed periods of the EEG, using electrode derivation F8-Pz (frontal-parietal) and relative δ power (median [interquartile range (IQR)] for delirium, 0.59 [IQR, 0.47-0.71] and for nondelirium, 0.20 [IQR, 0.17-0.26]; P = .0000000000018). With a cutoff value of 0.37, it resulted in a sensitivity of 100% (95% CI, 100%-100%) and specificity of 96% (95% CI, 88%-100%). CONCLUSIONS In a homogenous population of nonsedated patients who had undergone cardiothoracic surgery, we observed that relative δ power from an eyes-closed EEG recording with only two electrodes in a frontal-parietal derivation can distinguish among patients who have delirium and those who do not.

Anticholinergic Medication Use and Transition to Delirium in Critically Ill Patients: A Prospective Cohort Study.

Objective:Although cholinergic deficiency is presumed to increase delirium risk and use of medication with anticholinergic properties in the ICU is frequent, the relationship between anticholinergic medication use and delirium in this setting remains unclear. We investigated whether exposure to medication with anticholinergic properties increases the probability of transitioning to delirium in critically ill adults and whether this relationship is affected by age or the presence of acute systemic inflammation. Design:Prospective cohort study. Setting:A 32-bed medical-surgical ICU at an academic medical center. Patients:Critically ill adults admitted to the ICU for more than 24 hours without an acute neurological disorder or another condition that would hamper delirium assessment. Interventions:None. Measurements and Main Results:Daily anticholinergic burden was calculated for each patient based on the sum of the Anticholinergic Drug Scale score for each medication administered. Daily mental status was classified as “coma,” “delirium,” or an “awake without delirium” state. The primary outcome, the daily transition from an “awake without delirium” state to “delirium,” was analyzed using a first-order Markov model that adjusted for eight covariables. A total of 1,112 patients were evaluated over 9,867 ICU days. The daily median summed Anticholinergic Drug Scale score was 2 (interquartile range, 1–3). The transition from being in an “awake without delirium” state to “delirium” occurred on 562 of ICU days (6%). After correcting for confounding, a one-unit increase in the Anticholinergic Drug Scale score resulted in a nonsignificant increase in the probability of delirium occurring the next day (odds ratio, 1.05; 95% CI, 0.99–1.10). Neither age nor the presence of acute systemic inflammation modified this relationship. Conclusions:Exposure to medication with anticholinergic properties, as defined by the Anticholinergic Drug Scale, does not increase the probability of delirium onset in patients who are awake and not delirious in the ICU.

Systemic Corticosteroids And Transition To Delirium in Critically Ill Patients

Delirium is frequent in the critically ill and is associated with long-term morbidity [1]. Currently, the key approach for delirium in the ICU is avoidance of risk factors. Systemic corticosteroids are often used in the ICU, and regularly administered in high dosages, as increasing evidence suggests potential benefits of these medications in critically ill patients [2, 3]. However, corticosteroids are proposed to be a risk factor delirium in patients with acute lung injury [4].

Light levels of sedation and DSM-5 criteria for delirium.

Dear Editor, In a recent opinion essay, Devlin and colleagues argue that sedation confounds reliable detection of delirium when using current assessment tools [1]. To support this, they state that a low Richmond Agitation and Sedation Score (RASS) or bispectral index (BIS) value increase the likelihood to screen delirium positive [2], and that sedation-induced delirium has a better prognosis than delirium that is unrelated to sedation. The issues raised by Devlin et al. are fundamental, as these refer to the question what delirium ‘really’ means. In the end, this question considers the definition that is used to diagnose delirium, also debated by Brummel and Ely [3]. Recently, the American Psychiatric Association adjusted the criteria for delirium in its fifth Diagnostic and Statistical Manual (DSM) of mental disorders (DSM-5) [4]. Compared to the fourth, revised edition (DSM-IV-R) [5], less emphasis has been put on a disturbance of consciousness, Table 1. Still, a patient at a light level of sedation may fulfil DSM-5 criteria for delirium. Low RASS and BIS values are not characteristic of sedation, and can also be observed in patients with hypoactive delirium who did not receive sedatives. Besides the unpublished study that is cited by the authors, other unpublished material suggests the opposite: the prognosis of sedation-induced delirium was found to be as bad as that of delirium due to other causes (T. Girard, personal communication, Annual Congress European Delirium Association, 20–21 September, 2013). Moreover, because of the complex, multifactorial nature of delirium, it may be questionable whether these two categories can really be distinguished. Delirium in critically ill patients usually results from a multitude of pathogenic factors including inflammation, multi-organ failure, metabolic disturbances, and medication effects. With current assessment tools light levels of sedation may be clinically indistinguishable from hypoactive delirium in which no sedation was used. There is a need for an objective delirium assessment tool that can also identify sedation effects. Electroencephalography with a limited number of electrodes and automatic processing is a promising

Long-Term Self-Reported Cognitive Problems After Delirium in the Intensive Care Unit and the Effect of Systemic Inflammation

To describe the association between intensive care unit (ICU) delirium and self‐reported cognitive problems in 1‐year ICU survivors, and investigate whether this association was altered by exposure to systemic inflammation during ICU stay.

Clarifying the confusion surrounding drug-associated delirium in the ICU.

www.ccmjournal.org 1565 Delirium occurs frequently in the critically ill and may adversely affect both shortand long-term outcomes (1, 2). Treatment options for delirium in the ICU remain limited; therefore, clinicians should focus on delirium prevention and risk reduction strategies (3). Although predisposing (e.g., older age) and many precipitating (e.g., severity of illness) delirium risk factors are not reversible, other precipitating factors such as patient immobility, aspects of the ICU environment (e.g., noise), and administered medications may be modifiable (3). Many of the medications that are administered in an ICU setting have been reported to cause delirium, confusion, or agitation (4). ICU-specific factors that may increase the risk for drug-associated delirium include the large number of medications administered in this setting, the frequent presence of endorgan dysfunction that may influence the pharmacodynamic response observed, the presence of conditions such as sepsis or stroke that may impair blood-brain barrier integrity, and the regular use of medications having psychoactive properties (5, 6). Although the risk for drug-associated delirium appears to correlate with a medication’s serum anticholinergic activity, other mechanistic pathways have been reported, and thus, the pathobiology of drug-induced delirium remains unclear (7). Ascribing delirium at the ICU bedside solely to the use of a particularly medication is potentially fraught with error (5). The causes for delirium in the ICU are usually multifactorial and often not obvious, the temporal relationship between medication initiation and delirium onset remains poorly characterized, and medications (e.g., benzodiazepines) that may be used to treat delirium-associated agitation may also influence both delirium recognition and duration (3, 8, 9). The drug-associated delirium literature consists primarily of case series and uncontrolled cohort studies whose design makes it nearly impossible to determine whether a particular medication is an independent risk factor for delirium. One recent systematic review of ICU delirium risk factors had to exclude 49% of the 138 studies identified given that neither a randomized controlled design nor a multivariable approach was used (8). Furthermore, given the fluctuating nature of critical illness and delirium, it is essential that time-varying analysis techniques (e.g., Markov modeling) are used when investigating drugassociated delirium in the ICU setting (10, 11). Despite the uncertain efficacy of corticosteroids for many critical illnesses and their relatively extensive risk profile, corticosteroids are frequently administered in the ICU (12, 13). Although delirium has long been assumed to be a potential consequence of corticosteroid use, particularly when high doses are administered, there has been a paucity of rigorous data until recently to confirm this association. Although corticosteroids decrease inflammation, and therefore theoretically reduce neuroinflammation and the prevalence of delirium, results of the Dexamethasone for Cardiac Surgery trial suggest that the administration of a corticosteroid prior to cardiac surgery does not influence the prevalence of postoperative delirium (14). However, this study evaluated only a single dose of high-dose dexamethasone (1 mg/ kg), and risk factors for delirium differ substantially between cardiac surgery patients and general ICU patients (8, 15). In this issue of Critical Care Medicine, Schreiber et al (16) analyze a cohort of 520 mechanically ventilated adults with acute lung injury, where delirium status was evaluated once daily. Using multivariable Markov modeling techniques, they found that systemic corticosteroid use was significantly associated with transitioning to delirium from a nondelirious, noncomatose state. Among the nearly 20 potential delirium risk factors incorporated in the model, only age and the administration of a systemic corticosteroid in the preceding 24 hours were independently associated with a transition to delirium. This article has many strengths: sedation and delirium status was evaluated by trained investigators using validated instruments, common baseline and ICU risk factors for delirium were incorporated in a time-dependent fashion, and the corticosteroid dose-response relationship for this association was evaluated. As ICU clinicians use the results of this important analysis to help further inform their corticosteroid prescribing decisions, a few issues are worth highlighting. The authors explored only the transition from a noncomatose, nondelirious state to delirium; therefore, it remains unclear how exposure to corticosteroids influences the risk for transitioning from coma to delirium. Furthermore, the authors may have overestimated the risk for delirium associated with corticosteroid administration given that the competing risks of coma, death, or discharge from the ICU alive were not incorporated in their model (17). Evolving evidence suggests that the presence of a deeper level of sedation may increase the likelihood Copyright