Secondary Logo

Share this article on:

Delirium Monitoring in Neurocritically Ill Patients: A Systematic Review*

Patel, Mayur B., MD, MPH, FACS1,2,3,4; Bednarik, Josef, MD, PhD5,6; Lee, Patricia, MLS7; Shehabi, Yahya, PhD, FCICM, EMBA8; Salluh, Jorge I., MD, PhD9; Slooter, Arjen J., MD, PhD10; Klein, Kate E., MS, ACNP-BC, RN, CCRN11; Skrobik, Yoanna, MD, FRCP(c), MSc, FCCM12; Morandi, Alessandro, MD, MPH13,14; Spronk, Peter E., MD, PhD15; Naidech, Andrew M., MD, MSPH16; Pun, Brenda T., RN, DNP1,17; Bozza, Fernando A., MD, PhD18; Marra, Annachiara, MD1,17,19; John, Sayona, MD20; Pandharipande, Pratik P., MD, MSCI, FCCM1,2,21,22; Ely, E. Wesley, MD, MPH, FCCM1,2,17

doi: 10.1097/CCM.0000000000003349
Review Article
Editor's Choice

Objectives: The Society of Critical Care Medicine recommends routine delirium monitoring, based on data in critically ill patients without primary neurologic injury. We sought to answer whether there are valid and reliable tools to monitor delirium in neurocritically ill patients and whether delirium is associated with relevant clinical outcomes (e.g., survival, length of stay, functional independence, cognition) in this population.

Data Sources: We systematically reviewed Cumulative Index to Nursing and Allied Health Literature, Web of Science, and PubMed.

Study Selection and Data Extraction: Inclusion criteria allowed any study design investigating delirium monitoring in neurocritically ill patients (e.g., neurotrauma, ischemic, and/or hemorrhagic stroke) of any age. We extracted data relevant to delirium tool sensitivity, specificity, negative predictive value, positive predictive value, interrater reliability, and associated clinical outcomes.

Data Synthesis: Among seven prospective cohort studies and a total of 1,173 patients, delirium was assessed in neurocritically patients using validated delirium tools after considering primary neurologic diagnoses and associated complications, finding a pooled prevalence rate of 12–43%. When able to compare against a common reference standard, Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition, the test characteristics showed a sensitivity of 62–76%, specificity of 74–98%, positive predictive value of 63–91%, negative predictive value of 70–94%, and reliability kappa of 0.64–0.94. Among four studies reporting multivariable analyses, delirium in neurocritically patients was associated with increased hospital length of stay (n = 3) and ICU length of stay (n = 1), as well as worse functional independence (n = 1) and cognition (n = 2), but not survival.

Conclusions: These data from studies of neurocritically ill patients demonstrate that patients with primary neurologic diagnoses can meet diagnostic criteria for delirium and that delirious features may predict relevant untoward clinical outcomes. There is a need for ongoing investigations regarding delirium in these complicated neurocritically ill patients.

1Critical Illness, Brain dysfunction, and ICU Survivorship (CIBS) Center, Center for Health Services Research, Vanderbilt University Medical Center, Nashville, TN.

2Geriatric Research Education and Clinical Center (GRECC), Department of Veterans Affairs Medical Center, Tennessee Valley Healthcare System, Nashville, TN.

3Section of Surgical Sciences, Departments of Surgery, Neurosurgery, Hearing & Speech Sciences, Division of Trauma, Surgical Critical Care, and Emergency General Surgery, Vanderbilt Brain Institute, Vanderbilt University Medical Center, Nashville, TN.

4Surgical Service, Department of Veterans Affairs Medical Center, Tennessee Valley Healthcare System, Nashville, TN.

5Department of Neurology, University Hospital Brno, Brno, Czech Republic.

6Applied Neuroscience Research Group, Central European Institute of Technology, Masaryk University, Brno, Czech Republic.

7Center for Knowledge Management, Vanderbilt University Medical Center, Nashville, TN.

8University New South Wales, Clinical School of Medicine, Prince of Wales Hospital, Randwick, NSW, Australia.

9D’Or Institute for Research and Education, Rio De Janeiro, Brazil.

10Department of Intensive Care Medicine, Brain Center Rudolf Magnus, University Medical Center Utrecht, the Netherlands.

11Novant Health Presbyterian Medical Center, Charlotte, NC.

12Department of Medicine, McGill University, Montreal, QC, Canada.

13Department of Rehabilitation and Aged Care of the Fondazione Camplani, Ancelle Hospital, Cremona, Italy.

14Geriatric Research Group, Brescia, Italy.

15Department of Intensive Care, Gelre Ziekenhuizen (Lukas), the Netherlands.

16Departments of Neurology (Stroke and Neurocritical Care), Neurological Surgery, Anesthesiology, Medical Social Sciences, and Preventive Medicine (Health and Biomedical Informatics), Northwestern University, Feinberg School of Medicine, Chicago, IL.

17Department of Medicine, Division of Allergy, Pulmonary and Critical Care Medicine, Vanderbilt University Medical Center, Nashville, TN.

18Intensive Care Lab, Instituto Nacioinal de Infectologia Evandro, Chagas (INI), Fundacao Oswaldo Cruz, (FIOCRUZ), Rio De Janeiro, Brazil.

19Department of Neurosciences and Department of Public Health, University of Naples, Naples, Italy.

20Section of Neurocritical Care, Department of Neurological Sciences, Rush University Medical Center, Chicago, IL.

21Department of Anesthesiology, Division of Critical Care Medicine, Vanderbilt University Medical Center, Nashville, TN

22Anesthesiology Service, Department of Veterans Affairs Medical Center, Tennessee Valley Healthcare System, Nashville, TN.

*See also p. 1881.

Drs. Patel, Lee, Marra, Pandharipande, and Ely contributed to review structure; Drs. Patel and Lee contributed to literature search; Drs. Patel, Lee, Pandharipande, and Ely contributed data sheets; Drs. Patel, Pandharipande, and Ely contributed to title and abstract screening; Drs. Patel, Pandharipande, and Ely contributed to full text screening; Drs. Patel, Pandharipande, and Ely contributed to data extraction; Drs. Patel, Pandharipande, and Ely contributed to bias assessments; Drs. Patel, Lee, and Ely contributed to systematic review coordination; and all contributed to critical revisions to article.

Supplemental digital content is available for this article. Direct URL citations appear in the printed text and are provided in the HTML and PDF versions of this article on the journal’s website (

Supported, in part, by Veterans Affairs Tennessee Valley Geriatric Research, Education and Clinical Center (Nashville, TN) and the National Institutes of Health AG027472, AG035117, HL111111, GM120484 (Bethesda, MD).

Dr. Patel’s institution received funding from National Institutes of Health (NIH) HL111111 and NIH GM120484; he received funding from Pfizer/Hospira (education presentation); and he disclosed that funding was provided by federal sources including the Veterans Affairs (VA) Tennessee Valley Geriatric Research, Education and Clinical Center (Nashville, TN) and the NIH AG027472, AG035117, HL111111, GM120484 (Bethesda, MD). Drs. Patel and Ely received support for article research from the NIH. Ms. Klein’s institution received funding from Hill Rom Co. Dr. Naidech received support for article research from the Agency for Healthcare Research and Quality (K18 HS023437). Dr. Pun received funding from the Society of Critical Care Medicine, the American Association of Critical Care Medicine, and the France Foundation to provide continuing education. Dr. John disclosed other support from CSL Behring (speaker). Dr. Pandharipande’s institution received funding from Hospira. Dr. Ely’s institution received funding from NIH and VA funding, and he received funding from Orion Laboratories, Abbott Laboratories, and Pfizer. Dr. Pandharipande has received a research grant from Hospira Inc, in collaboration with the NIH. Dr. Ely has conducted Continuing Medical Education activities sponsored by Abbott, Hospira, and Orion. The remaining authors have disclosed that they do not have any potential conflicts of interest.

For information regarding this article, E-mail:

Delirium is a phenotypic syndrome manifested by the cardinal clinical features of fluctuations in mental status from baseline, inattention, altered level of consciousness, and disorganized thinking that represents acute cerebral dysfunction. Obviously in patients who have primary neurologic pathology (e.g., stroke, traumatic brain injury [TBI]), wholesale attribution of such clinical findings to delirium would be inappropriate without first considering the admission diagnostic injury or an extension of this injury. Indeed, it would be clinically dangerous to misattribute a patient’s clinical deterioration to delirium when it was actually due to edema, vasospasm, rebleeding, seizures, and/or ischemia. That is precisely why the study of delirium, an extremely common malady possible in any hospitalized patient, is so difficult. Yet, we must acknowledge the medical-surgical ICU literature, which has shown how predictive delirium is for clinical outcomes like mortality and long-term dementia (1–4). These associations may also be applicable to the most neurologically vulnerable patients.

Instruments that are used to screen or diagnose delirium (5–8) in settings such as general medical or surgical ICUs could be adapted to a population of patients who have primary neurologic injury. For reference, in medical-surgical critical care, the clinician (e.g., nurse and physician) must consider new onset of delirium (e.g., fluctuations in mental status and inattention) as a potential indicator of an untreated primary illness. If this is unlikely after thorough evaluation, then delirium could indicate an untreated secondary ICU complication. Due to a plethora of data in nonneuro ICU patients, delirium has been considered a “canary in the coal mine” and has triggered clinical teams to consider other dangerous secondary events such as nosocomial sepsis, metabolic derangements, pharmacologic causes, and/or immobilization (9–12). Delirium during critical illness has had associations with survival, length of stay, cost, and long-term cognition (1–4 , 13–16), although causation remains unproven, early recognition of delirium remains important.

The Society of Critical Care Medicine’s guidelines for Pain Agitation and Delirium (17) recommend routinely monitoring delirium with the Confusion Assessment Method for the ICU (CAM-ICU) (5) or Intensive Care Delirium Screening Checklist (ICDSC) (6) in adult critically ill patients (grade 1B). However, the data were mostly derived from patients in medical, surgical, and cardiovascular ICUs rather than those with primary brain injury (e.g., stroke, neurosurgical resection, TBI). For example, it is known that severe disorders of consciousness (e.g., coma) currently preclude delirium assessment, yet clinicians might extend this logic to patients with diseases such as stroke and TBI and not bother to perform delirium monitoring in these ICU patients, even if they are noncomatose.

Thus, we hypothesized that delirium measured by known tools is often (but not always) assessable in those with neurocritical illness (i.e., ICU patients with acute pathoanatomic abnormalities on CT or MRI) and a marker for future adverse outcomes. To paraphrase for clarity, the primary objective of this article is to discuss the hypothesis that delirium is part of the larger risk profile of ongoing brain injury for many patients with primary diagnoses such as stroke or TBI and should be considered in the landscape of their clinical course. In order to demonstrate that formal scientific inquiry in this area is nascent and to stimulate more work in this field, we conducted a systematic review of the literature in neurocritically ill patients related to 1) delirium monitoring and 2) clinical outcomes associated with duration of delirium.

Back to Top | Article Outline



In neurocritically ill patients with delirium versus without delirium (target condition), are there valid and reliable means by which to monitor for delirium (index test), as compared to a psychiatric reference standard when available (reference test)? And, in neurocritically ill patients with delirium versus without delirium, are there altered outcomes (e.g., survival, length of stay, functional independence, cognition)?

Back to Top | Article Outline

Study Eligibility

This review and associated protocol were registered with the PROSPERO international prospective register of systematic reviews (Registration Number: CRD42017074611). Inclusion criteria allowed any type of study design investigating delirium monitoring in neurocritically ill patients of any age. Our definition of neurocritically ill was restricted to and referred to ICU patients with acute intracranial injury (e.g., TBI, hemorrhagic stroke) or ischemic stroke. Reference lists of potentially included studies and review articles were also reviewed for additional citations pertinent to this search. Delirium assessments should have occurred at least daily using a delirium screening assessment tool with reporting of rate. When available, the criterion validity data (i.e., sensitivity, specificity, positive predictive value [PPV], negative predictive value [NPV]) were captured comparing delirium screening tools against psychiatric standard assessment using the Diagnostic and Statistical Manual (any edition) (18). If validation studies were done, then we also sought associated interrater reliability data (i.e., test-retest stability or kappa), but not those performed in isolation. Only English language studies and studies published in the peer-reviewed literature were eligible for inclusion. No date restriction was imposed on the search strategy. Exclusion criteria removed editorials, case reports, case-series, lay press articles, abstracts, and reviews.

Back to Top | Article Outline

Search Methods and Data Extraction

With the assistance of an experienced medical librarian (P.L.), we systematically searched Cumulative Index to Nursing and Allied Health Literature (CINAHL), Web of Science, and PubMed from the National Center for Biotechnology Information (Supplementary Table 1, Supplemental Digital Content 1, The search was not restricted by date. Reference lists of potentially included studies and review articles were reviewed for additional citations pertinent to this search. All of the abstracts of the studies identified by our search were independently examined by two authors who determined the eligibility of each study. A third author resolved any disagreements by consensus at each step as needed in the review process. Then, two authors reviewed the titles and abstracts of all remaining eligible studies to determine which required further inclusion. Two authors then retrieved and reviewed the manuscripts of the remaining articles and used data abstraction forms to collect the relevant study information. Captured data included study time period, sample size, subject sex characteristic, eligibility criteria, severity of illness markers, as well as delirium tool used, delirium prevalence, reference standard for delirium assessment with test characteristics (if present) (18). Note, the term “prevalence” was conservatively chosen as a more inclusive epidemiologic term encompassing old and new cases of delirium, although some articles reported incidence without clarifying how new cases were distinguished. We did not plan for a quantitative synthesis or meta-analysis given the anticipated heterogeneity of this emerging literature, delirium tools, and reference standards. For cohort studies, selection of the exposed and nonexposed groups, the comparability of the groups, the assessment of the outcomes, and the adequacy of follow-up were addressed using the Newcastle-Ottawa Scale.

Back to Top | Article Outline


A total of 1,460 relevant citations were screened from our search strategies (CINAHL, n = 128; Web of Science, n = 888; PubMed, n = 441; reference lists, n = 3), whereas 166 duplicates were excluded. Twelve-hundred sixty-one were excluded after title and abstract review because they did not meet inclusion criteria (Fig. 1). A total of 33 citations were reviewed at the article level, and we excluded 20 of those. Of these excluded articles, 19 were unrelated to our review (4 , 15 , 19–35), one was written in a non-English language (36), one was an editorial, and one was a review (19 , 30). During data extraction, two articles were further excluded as they failed to provide outcome data relevant to delirium test characteristics or complications of delirium (37 , 38). Of the remaining were 11 articles (39–49) without overlapping data, four final articles were excluded due to the ICU cohorts not exclusively composed of neurocritically ill patients (39–41 , 49), thus leaving seven articles for qualitative synthesis.

Figure 1

Figure 1

Descriptive statistics were extracted from the seven prospective cohort designs, representing five single-center studies, and two dual-center studies (Table 1; and Supplementary Table 2, Supplemental Digital Content 2, In total, 1,173 subjects were represented across studies with a range from 61 to 527 (median 108) subjects per study. Sex characteristics were unclear or not stated for three of the cohorts. One study involved trauma and TBI patients, and six studies involved stroke patients and no trauma patients. Five studies did not state whether mechanical ventilation was affecting the study population, with the remaining two studies having mechanical ventilation rates from 7% to 66% (median 36%). Severity of illness was broadly defined and either used the Injury Severity Scale (score of 23.3 among one study), Glasgow Coma Scale (score range 13.9–14.5 with median 14 among three studies), National Institutes of Health Stroke Scale (score range 3–9 with median 8 among five studies), and/or the Acute Physiology and Chronic Health Evaluation II (score of 11.5 among one study); severity of illness was unclassified in one study.



Delirium was assessed most commonly by the CAM-ICU (five studies) with a prevalence rate of 24–43% (median 29%) when reported (Table 2). Other tools used were the ICDSC (prevalence not reported), 4-A Test (4-AT, prevalence 27%), and Confusion Assessment Method (CAM) (prevalence 12%). Four studies used a reference standard (n = 61–129; median, 104), mostly commonly the Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition (DSM-IV, three of four studies with a 28–46% prevalence with median 37% when reported), and the CAM (one study, 11% prevalence). Two studies used the CAM-ICU tool against a DSM-IV reference standard with sensitivities ranging 62–76% (median 69%), specificities ranging 74–98% (median 86%), PPVs ranging 63–91% (median 77%), and NPVs ranging 70–94% (median 82%). The ICDSC against a DSM-IV reference standard reported 64% sensitivity, 79% specificity, 74% PPV, and 69% NPV, whereas the 4-AT against a CAM reference standard reported 100% sensitivity, 82% specificity, 43% PPV, and 100% NPV. Reliability was assessed in two studies using the CAM-ICU with kappa range from 0.64 to 0.94 (median 0.79). The risk of bias was predominantly low (Table 3).





Across four studies (Table 4), the occurrence of delirium was studied with different outcomes including mortality, ICU length of stay, hospital length of stay, disposition, and neuropsychologic outcomes (e.g., disability, cognition, health-related quality of life). None of these studies reported delirium completely with test characteristics with a reference standard (above), and none reported all of these outcome domains. Four studies used multivariable analysis to associate delirium with selected outcome measures. For example, delirium independently prolonged ICU length of stay by a median 2.1 days (95% CI, 1.1–4.5; p = 0.03) after adjusting for age, admission National Institutes of Health Stroke Scale, and any benzodiazepine exposure (46). Similarly, delirium independently prolonged hospital length of stay in three studies (hazard ratio, 1.63; 95% CI, 1.11–2.38; p = 0.013 [45] and median 3.5 d longer; 95% CI, 1.5–8.3; p = 0.004 [46] and median 5.4 d longer; 95% CI, 2.1–8.6; p < 0.001 [47]). Also, delirium independently was associated with worse functional independence (by Barthel Index [49]) and cognition in two studies (by quality of life in neurologic disorders metric [46]).



Back to Top | Article Outline


These data from the first systematic review of delirium monitoring in the neurocritically ill patient show that, in these subsets of patients, it is possible to measure delirium in adult ICU patients with mild-moderate stroke (ischemic and/or hemorrhagic) or neurotrauma with existing delirium instruments. Important caveats include of course that the delirium prevalence rates and test characteristics were variable, as expected, likely due to diversity of patient populations and severity of illness, and also due to performance variations that exist depending on tool application (e.g., approach to determination of baseline mental status and attention testing) in this challenging and understudied population. In this nascent field, it is important that in four studies, the identification of delirium in neurocritically ill patients independently predicted poor clinical outcomes including longer length of stay and worse functional recovery and cognition. Among seven prospective cohort studies and a total of 1,173 neurocritically ill subjects, delirium was assessable using a myriad of tools (e.g., CAM-ICU, ICDSC, 4-AT) with a pooled prevalence rate of 12–43% and often validated against the DSM-IV. This work shows monitoring delirium in the neurocritically ill is relevant, has potential to improve ICU prognostics for this population, needs integration into ICU delirium guidelines, and requires further research.

We warn the readership that it is important to use the delirium monitoring information as a complement to the neurologic examination and to expand the differential diagnosis when there is a change in the neurologic examination. In this complicated patient population, it is critical to acknowledge that a positive screen for delirium may be due to the underlying neurologic disease or its sequelae (e.g., edema, vasospasm, seizures, rebleeding, ischemia) requiring very different treatments than delirium and often with urgent or emergent time pressure to avoid further brain damage. Only once these have been evaluated as a primary cause for the neurologic decline, should delirium rise on the differential diagnosis.

These encouraging data are limited regarding the reliability of delirium tools (two studies; 0.64–0.94; median 0.79) in a neurocritical care population. However, another two studies have corroborating reliability data on delirium monitoring in the neurologically injured patient, which were excluded from our review’s eligibility criteria (i.e., studies that did not measure delirium incidence or prevalence). Soja et al (38) implemented delirium monitoring in a trauma ICU with a subset of patients with TBI, representing over one third of observations. An expert evaluator performed 1,011 random CAM-ICU assessments within 1 hour of the bedside nurse’s assessments. Overall agreement (kappa) between nurses and expert evaluator was 0.75 (0.667–0.829; p < 0.0001) in TBI patients, attesting to the ease of delirium monitoring in patients with polytrauma. Also, Yu et al (37) evaluated 151 patients from neurologic, neurosurgical, and trauma ICUs. In the 439 assessments performed by bedside staff and researchers, pain and sedation were always assessable with excellent interrater reliability (intraclass correlation, 0.86). Patients were sufficiently alert for delirium screening 75% of the time, and delirium screening items had good concordance. Importantly, each additional ICDSC item present, in proportion to the total ICDSC score, was associated with a 10% increase in ICU length of stay. Ultimately, clinicians should feel confident that delirium tools have solid reliability in the neurocritical care setting.

Past ICU data show that delirium is independently associated with increased mortality, length of stay, cost of care, accelerated or acquired dementia-like cognitive impairment, and the inability to return to independent living (2 , 3 , 16 , 50–57). Now, the literature is showing a similar pattern in the neurocritically ill population, except the lack of association of delirium with mortality, which may be unique to this population and/or due to better statistical risk-adjustment methods compared with past work. This work may shed light and provide structure to the care of the complex neurocritically ill patient given the utility and prognostics associated with delirium monitoring.

Back to Top | Article Outline

Unaddressed Challenges for Delirium Monitoring in the Neurocritically Ill

The neurocritically ill patient population is obviously more challenging than general medical and general surgical patients with respect to delirium assessment (58). Some are not testable for delirium due to decreased level of consciousness (i.e., coma) because of the primary neurologic injury or due to deep sedation (Richmond Agitation-Sedation Scale < –3) for high intracranial pressures. Stroke patients, for example, present with a high prevalence of cognitive and communication deficits such as aphasia that can make delirium assessments especially challenging (45). For example, it is not possible to do delirium assessments on receptive aphasic patients, but expressive aphasic patients can follow commands and indicate answers to questions with head nods or hand movements, thus can complete tests of attentiveness. Purely aphasic (expressive or receptive) patients do not have impaired arousal; however, aphasia often times is not an isolated finding. Level of arousal will depend on the degree of comorbid brain injury along with other covariates such as psychoactive medications, sleep deficits, degree of agitation. Psychiatric disorders, such as depression or catatonia, are other confounders that may mimic some hypoactive delirium symptoms in their most severe forms (59). Overall, it remains unclear which proportions of hypoactive or hyperactive delirium exist in neurocritical populations or subpopulations.

Similarly, nonconvulsive status epilepticus may also mimic some features of delirium and can only be diagnosed with an electroencephalogram. An unproven approach is that seizures should remain on the differential diagnosis when underlying neurologic abnormalities or common risk factors of delirium do not explain a patient’s neurologic examination. Furthermore, patients afflicted by both blindness and deafness often pose challenges for delirium assessments, neurologic examination, and ICU care. Despite these difficulties, there is growing evidence that it is possible to assess delirium using tools such as the CAM-ICU or ICDSC in many (37) neurologically injured patients. This is done using serial assessments conducted to detect fluctuations in relationship to the postinjury "new" baseline mental status determined (i.e. feature 1 of the CAM-ICU).

Back to Top | Article Outline

Future Areas for Delirium Research in Neurocritically Ill Patients

There have been broader and well-done reviews relevant to delirium in stroke (58, 60), and our work is uniquely limited by our focus on the critically ill patient affected by primary neurologic conditions. Additionally, we acknowledge our review excluded four studies that were not confined to neurocritically populations (39–41, 49). We note that there is no study validating any delirium tool in the neurocritically ill against the newer Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition, DSM-5 (61), which formally excludes coma from inattention (i.e. delirium) assessments but broadly classifies anything else as inattention. Also, the DSM-5 does not specify whether to include those with preexisting impaired cognition (i.e., delirium superimposed on dementia) (62), further complicating delirium assessments in neurocritically ill populations. Within any delirium tool, it is unclear which subfeatures (e.g., fluctuating mental status, inattention) are more prevalent in stroke and/or neurotrauma. The stroke and neurotrauma delirium data are not entirely comparable, as neither population has been studied under a single delirium protocol or framework. We also designed our review to be broad, inclusive of any age, yet we found no children have been studied in either stroke or neurotrauma population. Although assessment tools for the child have been created, such as the pediatric or preschool delirium assessment or Cornell Assessment for Pediatric Delirium (63–65), none of these have specifically been assessed for reliability and validity for the neurocritically ill child. Another significant knowledge gap appears to be that delirium prognostics are being inconsistently reported across studies, and no study provides comprehensive associations with clinical outcomes. We also acknowledge that there are no data available to the guide-specific treatment of delirium among neurologic ICU patients.

Stroke or neurotrauma studies consist of heterogeneous groups of neurocritically ill patients, use varying research and clinical environments, employ different diagnostic tools, and claim wide ranges about the assessable proportion of subjects. Also, the characteristics of any tool can be influenced by factors such as education and training of the rater (49 , 66 , 67). Further research is needed and has started on well-defined and homogenous subgroups of neurologically injured patients (68), like the PRospective Observational POLIsh Study on post-stroke delirium. Given the heterogeneity among patients, future studies should expand our nascent understanding of the prevalence and long-term neuropsychiatric implications (e.g., cognitive impairment, mood disorders) of both duration and pattern of time spent in a delirious state in populations like stroke and trauma. The methodological rigor of such investigations must be high (e.g., biostatistical design must include time-varying covariates).

Although there are no acute imaging correlates for delirium seen acutely or in-hospital, MRI and other techniques offer promise to uncover the hidden consequences of this secondary acute brain dysfunction. Neuroimaging of ICU cohorts with delirium is being pursued but is still in its infancy. The VISualizing Icu SurvivOrs Neuroradiological Sequelae (VISIONS) MRI studies (14 , 69) showed that medical and surgical ICU survivors with delirium were more likely to have brain atrophy in the prefrontal cortex and hippocampus as well as white matter abnormalities demonstrated via fractional anisotropy and diffusion tensor imaging. This suggests that there is indeed microstructural damage, and this cohort did prove to have subsequent cognitive impairment manifested by executive dysfunction and memory deficits. In patients with intracerebral hemorrhage, hematomas in specific locations are more likely to manifest delirium symptoms (70). Moving forward, it will be important to study the hypothesis that quantifiable delirium variables predict some portion of the long-term neuroimaging and clinical deficits seen in survivors of neurocritical illness.

Back to Top | Article Outline


Data from adult neurocritical care investigations indicate that tools are available for delirium monitoring in stroke patients, as well as neurotrauma patients. In such patients, the clinical information is a complement to the neurologic examination. In this case, delirium tools serve to expand the differential diagnosis. Delirium tools are to be used only after first considering the underlying admitting neurologic diagnosis. The value of the delirium tool, therefore, rests both in earlier detection of expected causes of an abnormal neurologic examination in this population (e.g., edema, vasospasm, seizures, rebleeding, ischemia), as well as adding common causes of delirium that might not be considered early enough (e.g., sepsis or sedatives) into the daily diagnostic and therapeutic conversations for these high-risk patients. We hope this work provides the reader with a clinically applicable framework for neurologically critically ill patients that considers delirium as a manifestation of secondary brain injury potentially superimposed on major neurologic deficits seen after primary brain injury. It is incumbent on the medical field to generate more data and advance our understanding, so that we may develop specific preventative and treatment strategies that will allow us to serve our neurologically injured patients better tomorrow than we do today.

Back to Top | Article Outline


1. Salluh JI, Wang H, Schneider EB, et alOutcome of delirium in critically ill patients: Systematic review and meta-analysis. BMJ 2015; 350:h2538
2. Pandharipande PP, Girard TD, Jackson JC, et alBRAIN-ICU Study Investigators: Long-term cognitive impairment after critical illness. N Engl J Med 2013; 369:1306–1316
3. Girard TD, Jackson JC, Pandharipande PP, et alDelirium as a predictor of long-term cognitive impairment in survivors of critical illness. Crit Care Med 2010; 38:1513–1520
4. Mehta S, Cook D, Devlin JW, et alSLEAP Investigators; Canadian Critical Care Trials Group: Prevalence, risk factors, and outcomes of delirium in mechanically ventilated adults. Crit Care Med 2015; 43:557–566
5. Ely EW, Inouye SK, Bernard GR, et alDelirium in mechanically ventilated patients: Validity and reliability of the confusion assessment method for the intensive care unit (CAM-ICU). JAMA 2001; 286:2703–2710
6. Bergeron N, Dubois MJ, Dumont M, et alIntensive care delirium screening checklist: Evaluation of a new screening tool. Intensive Care Med 2001; 27:859–864
7. Brummel NE, Vasilevskis EE, Han JH, et alImplementing delirium screening in the ICU: Secrets to success. Crit Care Med 2013; 41:2196–2208
8. Ely EW, Margolin R, Francis J, et alEvaluation of delirium in critically ill patients: Validation of the Confusion Assessment Method for the Intensive Care Unit (CAM-ICU). Crit Care Med 2001; 29:1370–1379
9. Bleck TP, Smith MC, Pierre-Louis SJ, et alNeurologic complications of critical medical illnesses. Crit Care Med 1993; 21:98–103
10. Young GB, Wijdicks EFMDisorders of Consciousness. 2008Edinburgh, New York, Elsevier,
11. Eidelman LA, Putterman D, Putterman C, et alThe spectrum of septic encephalopathy. Definitions, etiologies, and mortalities. JAMA 1996; 275:470–473
12. Bleck TPSepsis on the brain. Crit Care Med 2002; 30:1176–1177
13. van den Boogaard M, Schoonhoven L, Evers AW, et alDelirium in critically ill patients: Impact on long-term health-related quality of life and cognitive functioning. Crit Care Med 2012; 40:112–118
14. Gunther ML, Morandi A, Krauskopf E, et alVISIONS Investigation, VISualizing Icu SurvivOrs Neuroradiological Sequelae: The association between brain volumes, delirium duration, and cognitive outcomes in intensive care unit survivors: The VISIONS cohort magnetic resonance imaging study*. Crit Care Med 2012; 40:2022–2032
15. Lat I, McMillian W, Taylor S, et alThe impact of delirium on clinical outcomes in mechanically ventilated surgical and trauma patients. Crit Care Med 2009; 37:1898–1905
16. Milbrandt EB, Deppen S, Harrison PL, et alCosts associated with delirium in mechanically ventilated patients. Crit Care Med 2004; 32:955–962
17. Barr J, Fraser GL, Puntillo K, et alAmerican College of Critical Care Medicine: Clinical practice guidelines for the management of pain, agitation, and delirium in adult patients in the intensive care unit. Crit Care Med 2013; 41:263–306
18. American Psychiatric Association, American Psychiatric Association, Task Force on DSM-IV: Diagnostic and Statistical Manual of Mental Disorders: DSM-IV-TR. 20004th Edition Washington, DC, American Psychiatric Association,
19. Agarwal SEditorial Critique: Risk factors for delirium in older trauma patients admitted to the surgical intensive care unit (Vol 77, Pg 944, 2014). J Trauma Acute Care Surg 2015; 78:211
20. Anderson BJ, Reilly JP, Shashaty MGS, et alAdmission plasma levels of the neuronal injury marker neuron-specific enolase are associated with mortality and delirium in sepsis. J Crit Care 2016; 36:18–23
21. Bigatello LM, Amirfarzan H, Haghighi AK, et alEffects of routine monitoring of delirium in a surgical/trauma intensive care unit. J Trauma Acute Care Surg 2013; 74:876–883
22. Blondell RD, Powell GE, Dodds HN, et alAdmission characteristics of trauma patients in whom delirium develops. Am J Surg 2004; 187:332–337
23. Branco BC, Inaba K, Bukur M, et alRisk factors for delirium in trauma patients: The impact of ethanol use and lack of insurance. Am Surg 2011; 77:621–626
24. Ceriana P, Fanfulla F, Mazzacane F, et alDelirium in patients admitted to a step-down unit: Analysis of incidence and risk factors. J Crit Care 2010; 25:136–143
25. Colombo R, Corona A, Praga F, et alA reorientation strategy for reducing delirium in the critically ill. Results of an interventional study. Minerva Anestesiol 2012; 78:1026–1033
26. Guenther U, Popp J, Koecher L, et alValidity and reliability of the CAM-ICU flowsheet to diagnose delirium in surgical ICU patients. J Crit Care 2010; 25:144–151
27. Ingalls NK, Armstrong B, Hester M, et alThe fog of war: Delirium prevalence in a combat intensive care unit. Mil Med 2016; 181:209–212
28. Kozak HH, Uğuz F, Kilinç İ, et alDelirium in patients with acute ischemic stroke admitted to the non-intensive stroke unit: Incidence and association between clinical features and inflammatory markers. Neurol Neurochir Pol 2017; 51:38–44
29. Otter H, Martin J, Bäsell K, et alValidity and reliability of the DDS for severity of delirium in the ICU. Neurocrit Care 2005; 2:150–158
30. Rahme RJ, Pines AR, Welz M, et alImproving neurosurgical outcomes in the intensive care unit: Could dexmedetomidine make a difference in ventilator free days, neurological monitoring, and outcomes? World Neurosurg 2016; 94:556–558
31. Reddy DR, Singh TD, Guru PK, et alIdentification of acute brain failure using electronic medical records. J Crit Care 2016; 34:12–16
32. Robinson BR, Mueller EW, Henson K, et alAn analgesia-delirium-sedation protocol for critically ill trauma patients reduces ventilator days and hospital length of stay. J Trauma 2008; 65:517–526
33. Ryosuke T, Yasutaka O, Ayumi S, et alDelirium and coma evaluated in mechanically ventilated patients in the intensive care unit in japan: A multi-institutional prospective observational study. Journal of Critical Care 2014; 29:472.e471–475
34. Serpa Neto A, Slooter AJDelirium detection in stroke patients. Crit Care Med 2012; 40:2266–2267; author reply 2267
35. van Rijsbergen MW, Oldenbeuving AW, Nieuwenhuis-Mark RE, et alDelirium in acute stroke: A predictor of subsequent cognitive impairment? A two-year follow-up study. J Neurol Sci 2011; 306:138–142
36. Bajo BR, Bueno JCR, Moral MS, et alIncidence and predictive factors of delirium in hospitalised neurological patients. Neurologia 2013; 28:356–360
37. Yu A, Teitelbaum J, Scott J, et alEvaluating pain, sedation, and delirium in the neurologically critically ill-feasibility and reliability of standardized tools: A multi-institutional study. Crit Care Med 2013; 41:2002–2007
38. Soja SL, Pandharipande PP, Fleming SB, et alImplementation, reliability testing, and compliance monitoring of the Confusion Assessment Method for the Intensive Care Unit in trauma patients. Intensive Care Med 2008; 34:1263–1268
39. Angles EM, Robinson TN, Biffl WL, et alRisk factors for delirium after major trauma. Am J Surg 2008; 196:864–869; discussion 869870
40. Bryczkowski SB, Lopreiato MC, Yonclas PP, et alRisk factors for delirium in older trauma patients admitted to the surgical intensive care unit. J Trauma Acute Care Surg 2014; 77:944–951
41. Duceppe MA, Williamson DR, Elliott A, et alModifiable risk factors for delirium in critically ill trauma patients. J Intensive Care Med 2017 Jan 1:885066617698646. [Epub ahead of print]
42. Frenette AJ, Bebawi ER, Deslauriers LC, et alValidation and comparison of CAM-ICU and ICDSC in mild and moderate traumatic brain injury patients. Intensive Care Med 2016; 42:122–123
43. Kostalova M, Bednarik J, Mitasova A, et alTowards a predictive model for post-stroke delirium. Brain Inj 2012; 26:962–971
44. Lees R, Corbet S, Johnston C, et alTest accuracy of short screening tests for diagnosis of delirium or cognitive impairment in an acute stroke unit setting. Stroke 2013; 44:3078–3083
45. Mitasova A, Kostalova M, Bednarik J, et alPoststroke delirium incidence and outcomes: Validation of the Confusion Assessment Method for the Intensive Care Unit (CAM-ICU). Crit Care Med 2012; 40:484–490
46. Naidech AM, Beaumont JL, Rosenberg NF, et alIntracerebral hemorrhage and delirium symptoms. Length of stay, function, and quality of life in a 114-patient cohort. Am J Respir Crit Care Med 2013; 188:1331–1337
47. Oldenbeuving AW, de Kort PL, Jansen BP, et alDelirium in the acute phase after stroke: incidence, risk factors, and outcome. Neurology 2011; 76:993–999
48. Rosenthal LJ, Francis BA, Beaumont JL, et alAgitation, delirium, and cognitive outcomes in intracerebral hemorrhage. Psychosomatics 2017; 58:19–27
49. van Eijk MM, van den Boogaard M, van Marum RJ, et alRoutine use of the confusion assessment method for the intensive care unit: A multicenter study. Am J Respir Crit Care Med 2011; 184:340–344
50. Ouimet S, Kavanagh BP, Gottfried SB, et alIncidence, risk factors and consequences of ICU delirium. Intensive Care Med 2007; 33:66–73
51. Ouimet S, Riker R, Bergeron N, et alSubsyndromal delirium in the ICU: Evidence for a disease spectrum. Intensive Care Med 2007; 33:1007–1013
52. Ely EW, Shintani A, Truman B, et alDelirium as a predictor of mortality in mechanically ventilated patients in the intensive care unit. JAMA 2004; 291:1753–1762
53. Pisani MA, Kong SY, Kasl SV, et alDays of delirium are associated with 1-year mortality in an older intensive care unit population. Am J Respir Crit Care Med 2009; 180:1092–1097
54. Shehabi Y, Riker RR, Bokesch PM, et alSEDCOM (Safety and Efficacy of Dexmedetomidine Compared With Midazolam) Study Group: Delirium duration and mortality in lightly sedated, mechanically ventilated intensive care patients. Crit Care Med 2010; 38:2311–2318
55. Ely EW, Gautam S, Margolin R, et alThe impact of delirium in the intensive care unit on hospital length of stay. Intensive Care Med 2001; 27:1892–1900
56. Wolters AE, van Dijk D, Pasma W, et alLong-term outcome of delirium during intensive care unit stay in survivors of critical illness: A prospective cohort study. Crit Care 2014; 18:R125
57. Klein Klouwenberg PM, Zaal IJ, Spitoni C, et alThe attributable mortality of delirium in critically ill patients: Prospective cohort study. BMJ 2014; 349:g6652
58. Klimiec E, Dziedzic T, Kowalska K, et alKnowns and unknowns about delirium in stroke: A review. Cogn Behav Neurol 2016; 29:174–189
59. Skrobik YDelirium in patients with stroke: The dark side of the moon? Crit Care Med 2012; 40:676–677
60. Carin-Levy G, Mead GE, Nicol K, et alDelirium in acute stroke: screening tools, incidence rates and predictors: A systematic review. J Neurol 2012; 259:1590–1599
61. American Psychiatric Association: Diagnostic and Statistical Manual of Mental Disorders: DSM-5. 2013Washington, DC, American Psychiatric Association,
    62. Morandi A, Davis D, Bellelli G, et alThe diagnosis of delirium superimposed on dementia: An emerging challenge. J Am Med Dir Assoc 2017; 18:12–18
    63. Smith HA, Boyd J, Fuchs DC, et alDiagnosing delirium in critically ill children: Validity and reliability of the Pediatric Confusion Assessment Method for the Intensive Care Unit. Crit Care Med 2011; 39:150–157
    64. Traube C, Silver G, Kearney J, et alCornell assessment of pediatric delirium: A valid, rapid, observational tool for screening delirium in the PICU*. Crit Care Med 2014; 42:656–663
    65. Smith HA, Gangopadhyay M, Goben CM, et alThe preschool confusion assessment method for the ICU: Valid and reliable delirium monitoring for critically ill infants and children. Crit Care Med 2016; 44:592–600
    66. Neto AS, Nassar AP Jr, Cardoso SO, et alDelirium screening in critically ill patients: A systematic review and meta-analysis. Crit Care Med 2012; 40:1946–1951
    67. Devlin JW, Marquis F, Riker RR, et alCombined didactic and scenario-based education improves the ability of intensive care unit staff to recognize delirium at the bedside. Crit Care 2008; 12:R19
    68. Klimiec E, Dziedzic T, Kowalska K, et alPRospective Observational POLIsh Study on post-stroke delirium (PROPOLIS): Methodology of hospital-based cohort study on delirium prevalence, predictors and diagnostic tools. BMC Neurol 2015; 15:94
    69. Morandi A, Rogers BP, Gunther ML, et alVISIONS Investigation, VISualizing Icu SurvivOrs Neuroradiological Sequelae: The relationship between delirium duration, white matter integrity, and cognitive impairment in intensive care unit survivors as determined by diffusion tensor imaging: the VISIONS prospective cohort magnetic resonance imaging study*. Crit Care Med 2012; 40:2182–2189
    70. Naidech AM, Polnaszek KL, Berman MD, et alHematoma locations predicting delirium symptoms after intracerebral hemorrhage. Neurocrit Care 2016; 24:397–403

    delirium; intensive care unit; neurocritical care; neurotrauma; stroke; traumatic brain injury

    Supplemental Digital Content

    Back to Top | Article Outline
    Copyright © by 2018 by the Society of Critical Care Medicine and Wolters Kluwer Health, Inc. All Rights Reserved.