CAM-ICU - IS MU [PDF]

Poststroke delirium incidence and outcomes: Validation of the Confusion Assessment Method for the Intensive Care Unit (CAM-ICU)* Adela Mitasova, MD; Milena Kostalova, PhD; Josef Bednarik, MD, PhD; Radka Michalcakova, PhD; Tomas Kasparek, MD, PhD; Petra Balabanova; Ladislav Dusek, PhD; Stanislav Vohanka, MD, PhD; E. Wesley Ely, MD, MPH Objective: To describe the epidemiology and time spectrum of delirium using Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition criteria and to validate a tool for delirium assessment in patients in the acute poststroke period. Design: A prospective observational cohort study. Setting: The stroke unit of a university hospital. Patients: A consecutive series of 129 patients with stroke (with infarction or intracerebral hemorrhage, 57 women and 72 men; mean age, 72.5 yrs; age range, 35–93 yrs) admitted to the stroke unit of a university hospital were evaluated for delirium incidence. Interventions: None. Measurements and Main Results: Criterion validity and overall accuracy of the Czech version of the Confusion Assessment Method for the Intensive Care Unit (CAM-ICU) were determined using serial daily delirium assessments with CAM-ICU by a junior physician compared with delirium diagnosis by delirium experts using the Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition criteria that began the first day after stroke onset and continued for at least 7 days. Cox regression models using time-dependent covariate analysis adjusting for age, gender, prestroke dementia, National Institutes of Stroke Health Care at admission, first-day Sequential Organ Failure Assessment, and asphasia were used to understand

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the relationships between delirium and clinical outcomes. An episode of delirium based on reference Diagnostic and Statistical Manual assessment was detected in 55 patients with stroke (42.6%). In 37 of these (67.3%), delirium began within the first day and in all of them within 5 days of stroke onset. A total of 1003 paired CAM-ICU/ Diagnostic and Statistical Manual of Mental Disorders daily assessments were completed. Compared with the reference standard for diagnosing delirium, the CAM-ICU demonstrated a sensitivity of 76% (95% confidence interval [CI] 55% to 91%), a specificity of 98% (95% CI 93% to 100%), an overall accuracy of 94% (95% CI 88% to 97%), and high interrater reliability (␬ ⴝ 0.94; 95% CI 0.83–1.0). The likelihood ratio of the CAM-ICU in the diagnosis of delirium was 47 (95% CI 27–83). Delirium was an independent predictor of increased length of hospital stay (hazard ratio 1.63; 95% CI 1.11–2.38; p ⴝ .013). Conclusions: Poststroke delirium may frequently be detected provided that the testing algorithm is appropriate to the time profile of poststroke delirium. Early (first day after stroke onset) and serial screening for delirium is recommended. CAM-ICU is a valid instrument for the diagnosis of delirium and should be considered an aid in delirium screening and assessment in future epidemiologic and interventional studies in patients with stroke. (Crit Care Med 2012; 40:484–490) KEY WORDS: delirium; diagnosis; intensive care; stroke

here are only a few prospective studies available that have addressed the incidence (1– 8), the type, or the time course of poststroke delirium. The reported inci-

dence of poststroke delirium varies widely, from 10% (8) to 48% (2). Despite being a frequent complication of stroke, the pathophysiology of delirium in the acute stroke setting is poorly understood

*See also p. 676. From the Departments of Neurology (AM, MK, JB, RM, PB, SV) and Psychiatry (TK), University Hospital and Masaryk University, Brno, Czech Republic; CEITEC– Central European Institute of Technology (JB, TK), Masaryk University, Brno, Czech Republic; the Institute of Biostatistics and Analyses (LD), Masaryk University Brno, Brno, Czech Republic; and the Center for Health Services Research (EWE), Vanderbilt University Medical Center, Nashville, TN, and the Veteran’s Affairs Geriatric Research Education Clinical Center (GRECC) of the VA Tennessee Valley Healthcare System (http://www.icudelirium.org). This study was supported by the Internal Grant Agency of the Czech Ministry of Health, Project No. NS10216-3/2009.

The study was performed at Complex Cerebrovascular Centre of the Department of Neurology, University Hospital and Masaryk University, Brno, Czech Republic. Dr. Bednarik received a grant from the Internal Grant Agency of the Czech Ministry of Health. Dr. Ely consulted for Hospira, Cumberland, and Masimo; received honoraria/speaking fees from Hospira; and received a grant from Eli Lilly. The remaining authors have not disclosed any potential conflicts of interest. For information regarding this article, E-mail: [email protected] Copyright © 2012 by the Society of Critical Care Medicine and Lippincott Williams & Wilkins

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DOI: 10.1097/CCM.0b013e318232da12

(9). In addition to common risk factors, the development of delirium poststroke is likely to be dependent on several factors unique to this clinical setting that could also distort detection of delirium episode. Among them, the area of brain affected by the stroke is important both from pathophysiological and diagnostic points of view. Focal forms of “acute confusional syndrome” have been described after strokes in specific locations (10). Although it would be challenging to incontrovertibly distinguish between the clinical states of the macroinjury of stroke and metabolic, septic, hypoxic, or pharmacologic microinjuries, this does not preclude the need for detection of delirium to offer a chance for early intervention of remediable causes. The ideal screening tool for the detection of delirium poststroke thus would be able to Crit Care Med 2012 Vol. 40, No. 2

disclose the fluctuating nature of delirium symptomatology to distinguish between patients with stroke with delirium and those with nonfluctuating disturbances of memory, perception, or attention resulting from lesions of key brain areas, prestroke dementia, depression, or psychosis. Necessity of repetitive and widespread use of such a test requires a tool that would be quick, reliable, evidence-based, accurate, reproducible, easy for various health professionals to use, and applicable to all patients with stroke. It would also rely to a lesser degree on level of consciousness, verbal ability, and motor disturbance, because these may be independently affected by cerebral damage secondary to stroke (9). A prospective observational study on delirium in patients with acute stroke was therefore undertaken both to describe the epidemiology of delirium in a cohort of patients in the acute poststroke period using The Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition (DSM-IV) criteria (11) as well as to determine the sensitivity, specificity, and overall accuracy of a tool for delirium monitoring. We tested the Confusion Assessment Method for the Intensive Care Unit (CAMICU) (12, 13), a well-validated screening instrument for detection of delirium in intensive care settings, to investigate its validity as a routine monitoring instrument for hospitalized patients with stroke by nonpsychiatrically trained clinicians.

MATERIALS AND METHODS Patients. The study population was recruited over an 18-month period (between January 2009 and June 2010) from all patients with stroke consecutively admitted to a specialized stroke center of a university hospital, who were considered eligible for the study. All patients were admitted to a stroke unit that comprises a six-bed intensive care unit providing mechanical ventilation and central hemodynamic monitoring and six semi-intensive care beds. The inclusion criteria were: admission diagnosis of cerebral infarction or intracerebral hemorrhage; that a delirium assessment could be carried out within 24 hrs of stroke onset; and approval of the patient or his or her relatives. A priori exclusion criteria were: duration of stroke symptoms and signs ⬍24 hrs; history of severe head trauma or neurosurgery at any time before stroke; subarachnoid hemorrhage, venous infarction, or brain tumor; history of psychosis; patients who did not speak Czech; and patients who were comatose or stuporous on admission and did not improve during the first week poststroke with a Richmond Agitation and Sedation Scale

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(RASS) score ⱕ⫺4 (14, 15). The institutional ethics committee approved the study. Demographic data, type of stroke, severity of stroke using the National Institutes of Health Stroke Scale (16), location of the infarct lesion using the Oxfordshire classification (17), etiology of ischemic stroke in accordance with the Trial of ORG 10,172 in Acute Stroke Treatment subtype classification (18), and severity of illness expressed as the Sequential Organ Failure Assessment score (19) were scored and recorded. Any presence of suspected prestroke dementia, evaluated by Blessed Dementia Rating Scale, was recorded (20). The presence of aphasia was determined by standard logopedic examination and quantified by the Czech version of the Mississippi Aphasia Screening Test (21, 22). Daily and incidental administration of sedatives, opioids, neuroleptics, and muscleblocking agents was recorded. Duration of confinement in the stroke unit and period of institutionalization were recorded, and the functional status of the patients was evaluated with the Barthel index at the end of the first week and 6 months after stroke (23). In addition to patients who died, nine patients were lost after hospitalization and their data therefore not analyzed at 6 months. Evaluation of Delirium. Enrolled patients underwent paired daily evaluation with the CAM-ICU either before or after reference full diagnostic evaluation for delirium. The CAM-ICU was originally adapted from the most widely used instrument for delirium assessment by nonpsychiatrists and nonneurologically trained healthcare professionals, the Confusion Assessment Method (24), to enable evaluation of delirium in an intensive care setting including mechanically ventilated patients (12, 13). The CAM-ICU was chosen among other available screening tests (e.g., the Intensive Care Delirium Screening Checklist) (25) for delirium as a simple test that enables daily monitoring of patients as a discreet assessment that takes usually ⬍1 min and could be used by nonpsychiatric or neurologic specialists such as nurses over the whole spectrum of patients with stroke, including patients not fully alert, aphasic, or who were being managed with mechanical ventilation. The CAM-ICU consists of two steps: the arousal level is assessed by RASS (14, 15) and only those aroused by verbal stimuli (RASS score ⱖ⫺3, meaning more arousable and thus not comatose) proceed to the second step. Patients with RASS ⫺4 or ⫺5 (aroused only by mechanical/physical stimuli or unarousable) were assessed later, within 24 hrs if possible. The evaluation of delirium using CAM-ICU is based on similar principles to that of the Confusion Assessment Method: 1) acute change or fluctuating course in mental status; and 2) inattention with either 3) disorganized thinking or 4) altered level of consciousness at the

time of the evaluation. (Note: the new CAMICU training manual swapped these features so that Feature 3 is now level of consciousness and Feature 4 is now disorganized thinking.) We used the Czech version of the original test (CAM-ICUcz) translated and adopted under the surveillance of the authors of the original version (26). The first CAM-ICU evaluation was performed by a junior physician (A.M.) on the first day after stroke onset and admission (day 1) and then daily Monday through Saturday on at least 7 consecutive days (except Sunday) on which the patient was accessible to testing (RASS ⱖ⫺3). The CAM-ICUcz assessment was performed once a day at a predefined time, between 10 AM and midday, or if patient was inaccessible or unable to cooperate (RASS ⬍⫺3 or severe agitation), the evaluation was repeated between 3 and 5 PM. In case of ⬍8-hr interval between admission and planned assessment, the first assessment was postponed to the next day. In sedated or mechanically ventilated patients, we used a specific sedation protocol with spontaneous awakening trials: administration of sedatives or nondepolarizing muscle-blocking agents was stopped 2 hrs before delirium testing (if possible) and the doses of opioids were decreased to the minimum possible. The mental status of patients including assessment of a level of consciousness and responsiveness was a part of the clinical evaluation made immediately on admission by an admitting neurologist, a stroke specialist. The mental status determined from that evaluation poststroke was considered as a new baseline after stroke onset and was available both for CAM-ICU scoring junior physician and for specialists who performed reference evaluation. This “new baseline” was used for all subsequent delirium assessments including the first assessment made on day 1. Importantly, if the mental status was altered on admission and normalized subsequently, the baseline was adjusted back to normal “baseline” and used from that point forward for all baseline. This approach maximized the likelihood that we would take into account a “new baseline” mental status resulting from stroke and thus not falsely call the patient delirious as a result of alterations in cognition from their structural disease. If delirium was present on day 6 or 7, we continued with both expert and CAM-ICU follow-up until at least 2 subsequent days without delirium were recorded. Follow-up was stopped in patients who became inaccessible to testing because of deterioration of consciousness (RASS ⫺4 or ⫺5) or death. In addition, the reference standard DSM evaluation of delirium was performed ⬍2 hrs apart daily by a panel of specialists, delirium experts working in the university hospital: two

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neurologists (J.B., S.V.), two neuropsychologists (R.M., P.B.), a psychiatrist (T.K.), and a speech therapist (M.K.), all with ⬎5 yrs of experience with stroke and intensive care patients. The reference evaluation was performed by at least one neurologist and one neuropsychologist. They applied the criteria for delirium presented in DSM-IV (9). The final classification of the evaluated 24-hr period as delirium present or absent was based on agreement of evaluating specialists. The type of delirium was also classified daily as hyperactive (increased motor activity with agitated behavior and increased level of arousal; RASS score ⬎0); hypoactive (reduced motor behavior and lethargy, decreased level of arousal; RASS score ⬍0); or mixed, i.e., an episode of both hypoactive and hyperactive delirium lasting at least several hours was identified within last 24-hr period (27). The CAM-ICUcz evaluation was done independently and blind to the experts’ evaluation. The specialists using the DSM-IV have the most access to patients, families, intensive care unit team, and chart in addition to the patient evaluations. That is important because that is really what makes their evaluation the “reference standard” against which the CAM-ICU is compared. The CAM-ICU raters did, appropriately for completion of feature 1 as accurately as possible, have access to interview family members, information obtained from junior and nursing staff, and chart reviews that were readily available, although they generally spent only a few minutes maximum on their delirium evaluation with the CAM-ICU as compared with the reference rater DSM-IV approach. The research team provided a review of delirium to the stroke unit clinicians and nursing staff. Patient management was the responsibility of the medical team. The delirium experts and a scoring junior physician standardized their approach to DSM-IV criteria and CAM-ICU scoring over a 3-month training phase and a validation study (28). First they met with attending neurologists and intensive care specialists (including a scoring junior physician) through roundtable discussions regarding their approach to standardizing their intensive care unit delirium assessment. A scoring physician (A.M.) was trained in CAM-ICU scoring by the experts (J.B., M.K., the authors of the CAM-ICUcz); this person then performed evaluations of ten pilot patients, which were videotaped, reanalyzed by one of the experts (M.K.), used for the interrater reliability calculations, and discrepancies between investigators were then finally discussed together with the other experts. Validity and Reliability Testing. Criterion validity was determined by the ability of the CAM-ICU to classify patients into normal and delirious categories compared with the reference rater’s evaluation using DSM criteria. We

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Figure 1. Flowchart of patients to stroke unit, screened, enrolled, and analyzed.

assessed overall validity in addition to validity for subgroup with decreased consciousness or sedation based on RASS evaluation (⬍0 points). Independent CAM-ICU ratings of ten pilot patients were used to calculate interrater reliability. Statistical Analysis. Patient characteristics were summarized using proportions for categorical variables with mean and SDS for continuous variables. To compare demographic variables and other baseline characteristics between enrolled and excluded patients, the nonparametric Mann-Whitney U test was used. Proportional hazard Cox regression models with delirium onset as time-dependent covariate were applied to estimate hazard ratio associated with length of stay in the hospital and hazard ratio of mortality up to 6 months since admission (29). The hazard ratio estimates were adjusted for the influence of other potential confounders (age, gender, prestroke dementia, National Institutes of Health Stroke Scale at admission, first-day Sequential Organ Failure Assessment, aphasia). The reliability of the CAM-ICU was assessed through ␬ coefficient. For ␬, confidence intervals (CIs) were constructed using bootstrap estimates (30) to account for dependence among repeatedly measured data. The performance test characteristics for CAM-ICU were calculated from 2 ⫻ 2 frequency tables using standard definitions: sensitivity, specificity, positive and negative predictive value, and overall accuracy as ratio (true-positives ⫹ true-negatives)/)truepositives ⫹ false-positives ⫹ true-negatives ⫹ false-negatives). Because delirium was assessed repeatedly over the stroke unit stay, we used estimates of 95% CIs for binary repeated

data using generalized estimating equation with logit-link function and in conjunction with Huber-White estimator of SE (31). Statistical analyses were performed using SPSS software package (SPSS 19.01; IBM Corporation, Chicago, IL). All statistical tests were twosided, and a value ␣ ⬍ 0.05 was considered as a threshold for statistical significance in all the comparisons made.

RESULTS Patient Recruitment and Characteristics. During the recruitment period, 331 patients with stroke were admitted to the stroke unit, of whom 236 were screened (those admitted on weekdays); 151 patients with stroke were enrolled and 129 patients completed a 7-day evaluation and their data were analyzed (Fig. 1). Data from 22 patients were not analyzed because they died or became comatose or stuporous during the first week poststroke and were thus inaccessible to follow-up. Comparison of the demographic variables of the 151 enrolled patients with the 85 patients excluded based on criteria designated a priori showed no significant differences in age, gender, or other baseline characteristics (all p ⬎ .10) with the exception of severity of illness: excluded patients had significantly higher National Institutes of Health Stroke Scale scores (median admission National Institutes of Health Stroke Scale 12.0 vs. 9.0; p ⬍ .01) Crit Care Med 2012 Vol. 40, No. 2

Table 1. Patient characteristics at enrollment

Characteristics Age, mean (SD), yrs Men Admission Sequential Organ Failure Assessment score, mean (SD) Maximum Sequential Organ Failure Assessment score, mean (SD) Blessed Dementia Rating Scale, mean (SD) Blessed dementia rating scale, ⱖ3 points (%) Blessed dementia rating scale, ⱖ4 points (%) Admission National Institutes of Health Stroke Scale score, mean (SD) Infratentorial stroke Right hemisphere stroke Left hemisphere stroke Cerebral infarction Total anterior circulation infarctiona Partial anterior circulation infarctiona Lacunar anterior circulation infarctiona Posterior circulation infarctiona Large vessel etiologyb Lacunar etiologyb Cardioembolic etiologyb Other etiologyb Undetermined etiologyb Intracerebral hemorrhage Aphasia Hemineglect

Frequency, No. (%) (n ⫽ 129)

Group Total Assessments

71.2 (11.5) 72 (55.8) 1.1 (1.3)

2.3 (1.8)

1.8 (3.1) 31.8 19.4 8.9 (3.9)

13 (10.1) 56 (43.4) 60 (46.5) 107 (82.9) 21 (19.6) 39 (36.5) 33 (30.8) 14 (13.1) 20 (15.5) 35 (27.1) 39 (30.2) 5 (3.9) 30 (23.3) 22 (17.1) 38 (29.5) 25 (19.4)

a Oxfordshire classification of ischemic stroke (22); bTOAST classification of ischemic stroke (23).

and lower Glasgow Coma Scales (median admission Glasgow Coma Scales 13.0 vs. 14.5, p ⬍ .01). After excluding the data from 22 patients who died or became comatose or stuporous during the follow-up, 129 (85.4%) of the 151 patients enrolled made up the final study population. The mean (SD) age of the study population was 71.2 (11.5) yrs (range, 30 –93 yrs), 57 women and 72 men. Twenty-five patients (19.4%) showed abnormal Blessed Dementia Rating Scale score ⱖ4 (classified as suspected dementia); in five of them (3.8%) dementia of slight-tomoderate degree was documented before stroke. Nine patients (7.0%) were intubated and mechanically ventilated during the follow-up period. Forty-nine patients (38.0%) received some sedation and/or analgesia during Crit Care Med 2012 Vol. 40, No. 2

Table 2. Criterion validity of the CAM-ICU reported as sensitivity, specificity, positive predictive value, negative predictive value, and overall accuracya Richmond Agitation and Sedation Scale ⬍0 240

All 1003 CAM-ICU Positive

CAM-ICU Negative

CAM-ICU Positive

CAM-ICU Negative

Diagnostic and Statistical 225 (true-positive) 60 (false-negative) 98 (true-positive) 16 (false-negative) Manual of Mental Disorders positive Diagnostic and Statistical 12 (false-positive) 706 (true-negative) 2 (false-positive) 124 (true-negative) Manual of Mental Disorders negative Sensitivity (95% CI) 76.0 (54.9–90.6) 85.0 (62.1–96.8) Specificity (95% CI) 98.1 (93.2–99.8) 97.1 (85.1–99.9) Positive predictive value 90.5 (69.6–98.8) 94.4 (88.3–97.9) (95% CI) Negative predictive value 94.4 (88.3–97.9) 91.9 (78.1–98.3) (95% CI) Overall accuracy 93.8 (88.2–97.3) 92.7 (82.4–98.0) (95% CI) CAM-ICU, Confusion Assessment Method for the Intensive Care Unit; CI, confidence interval. Comparisons were made between ratings completed with the CAM-ICU by a junior physician vs. reference standard evaluations by delirium experts using Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition criteria. a

the follow-up period. The drugs used for sedation were tiapride (a neuroleptic drug) (n ⫽ 30; median dose, 300 mg; range, 50 – 4800 mg), haloperidol (n ⫽ 10; median dose, 20; range, 1.5–50 mg), and diazepam (n ⫽ 10; median dose, 10 mg; range 5– 80 mg). Mechanically ventilated patients (n ⫽ 7) received sufentanil (median dose, 1.25 mg; range, 0.5– 6 mg) and three of them pipecuronium bromide (median dose, 12 mg; range, 8 –24 mg). Characteristics of these 129 patients at the time of enrollment are presented in Table 1. Epidemiology of Delirium. An episode of delirium was detected using the reference raters DSM-IV criteria in 55 patients with stroke (42.6% delirium-positive cases). In 37 patients (67.3%), delirium was present on the first day after admission; it was detected in 30 (54.5%), 25 (45.5%), 24 (43.6%), 27 (49.1%), 25 (45.5%), and 21 patients (38.2%) in the course of days 2–7, respectively. Delirium developed within 5 days of stroke onset in all delirium-positive patients. The median duration of delirium episode was 4 days (range, 1–28). In 14 patients (25.5%), an episode of delirium lasted ⱕ24 hrs. Altogether, we recorded 295 days of delirium: 111 days of hypoactive, 78 days of hyperactive, and 109 of mixed. Criterion Validity and Reliability of the CAM-ICU. A total of 1003 blinded, paired CAM-ICU/DSM evaluations were

completed. The reference standard DSM assessments diagnosed delirium in 225 of the 1003 (22.4%) patient assessments or in 55 of 129 (42.6%) patients. The sensitivity of the CAM-ICU was 76% (95% CI 55% to 91%) and the specificity was 98% (95% CI 93% to 100%) (Table 2). This resulted in a positive predictive value of 91% (95% CI 70% to 99%) and a negative predictive value of 94% (95% CI 88% to 98%). The accuracy of the CAM-ICU reached 94% (95% CI 88% to 97%) (Table 2). The likelihood ratio of the CAM-ICU in the diagnosis of delirium was 47 (95% CI 27– 83). To evaluate the performance of the CAM-ICU inpatient group that may pose particular challenges in delirium assessments, we performed a subgroup analysis in patients with decreased level of consciousness or sedation (as evaluated by the RASS score). The mean (median; SD) RASS value in all CAM-ICU evaluations (n ⫽ 1003) was ⫺0.30 (0; 0.84), and the mean (median; SD) RASS value in positive CAMICU evaluations (n ⫽ 237) was ⫺0.30 (0; 1.06). In patients with RASS 0, the sensitivity and specificity of the CAM-ICU were 85% (95% CI 62% to 97%) and 97% (95% CI 85% to 100%) (Table 2). CAM-ICUcz generated false-negatives in 60 paired measurements/eight patients. In four false-positive patients, the signs of delirium were transient, present during the night and fading during the 487

daylight hours (when CAM-ICZcz testing was performed); in four patients with signs of delirium on testing, CAM-ICUcz proved negative because their score on the Attention Screening Examination was normal and therefore “feature 2—inattention” of CAM-ICU was not met. In 12 paired measurements/three patients, the CAM-ICUcz criteria of delirium were falsely positive: all three patients had either global or Wernicke’s type of aphasia to a severe degree with prominent involvement of comprehension (Czech version of the Mississippi Aphasia Screening Test total index of 6, 8, and 34). Among 237 CAM-ICU-positive tests, positivity of the CAM-ICU assessment was based on positive feature 3 (disorganized thinking) in 92 tests (38.8% of all positive tests), on positive feature 4 (altered level of consciousness; RASS other than 0) in 34 tests (14.3%) (30 with RASS ⬍0, 4 with RASS ⬎0), and on positivity of both features 3 and 4 in 111 tests (46.8%). Thus, 203 of 237 positive CAM-ICU evaluations (85.7%) had a positive “disorganized thinking” feature as a component of the delirium in this population and the CAM-ICU was not merely positive as a result of an altered level of consciousness poststroke in many patients. (Note: the new CAM-ICU training manual swapped these features so that Feature 3 is now level of consciousness and Feature 4 is now disorganized thinking.) The CAM-ICU in ten pilot patients was completed with very high interrater reliability of ␬ ⫽ 0.94 (95% CI 0.83–1.0). Clinical Outcomes. The mean (SD) duration of stay in the stroke unit was 6.0 (3.8) days (median, 5; range, 2–18 days) and in the hospital 16.6 (9.7) days (median, 14; range, 7–51 days). The mean (SD) Barthel index (indicative of functional outcomes) at the end of the first week poststroke for the population as a whole was 41.9 (40.8) points (median, 25; range, 0 –100 points) and after 6 months was 51.4 (43.1) points (median, 35; range, 0 –100 points). Inhospital mortality reached 10.8% and after 6 months it was 18.6%. The subgroup of patients with stroke with delirium stayed longer in the hospital than patients with stroke without delirium (median, 18.0 vs. 12.0 days). Cox regression model using time-dependent covariate analysis and adjusting for age, gender, prestroke dementia, National Institutes of Health Stroke Scale at admission, first-day Sequential Organ Failure Assessment, and aphasia showed a statistically significant increase in risk for 488

length of stay in the hospital in patients with delirium compared with those without delirium (hazard ratio 1.63; 95% CI 1.11–2.38; p ⫽ .013). The Barthel index of patients with delirium was significantly lower (indicating worse functional status) at the end of the follow-up period (median, 15.0 vs. 37.5 points; p ⫽ .031) and insignificantly lower after 6 months (median, 27.5 vs. 75.0 points; p ⫽ .075) compared with patients without delirium. The mortality after 6 months of follow-up was higher in patients with stroke with delirium as compared with the subgroup without delirium (23.6% vs. 14.9%). Cox regression model revealed that delirium was not significantly associated with an independent increase in the risk of death within 6 months follow-up period (hazard ratio 1.22; 95% CI 0.48 –2.98; p ⫽ .668).

DISCUSSION Our prospective cohort study confirmed the high incidence of poststroke delirium and showed high criterion validity, overall accuracy, and reliability of the CAM-ICU in the detection of poststroke delirium comparable to that reported in subsets of critically ill and intensive care patients without focal brain lesions (12, 13). This is, to the best of our knowledge, the first study to validate the CAM-ICU in a population of patients with stroke. In addition, although preliminary and in need of future larger studies, these data indicated that delirium may be a predictor of relevant outcomes such as length of hospital stay in patients with stroke (considering that we used very robust modeling with time-varying covariate analysis). Approaches to delirium detection may have had important impacts on the differences in delirium incidence in patients with stroke reported by previous studies with incidence estimates ranging from 10% to 48% (1– 8). A study by Gustafson et al reported delirium incidence at 48% and 42% (2, 3) and made two assessments within the first week in contrast to the one-step approach appearing in other studies (1, 4 –7). In our patients with stroke, assessed daily for at least the first 7 days, delirium was detected during the first day after stroke onset in two-thirds of patients with delirium. Furthermore, despite median duration of 4 days, it lasted ⬍24 hrs in 25.5% of deliriumpositive cases. Therefore, if assessment

had been made on the first day poststroke only, delirium would have been missed in 18 cases (32.6% of delirium-positive patients), and assessment on days 2–5 would have missed even more cases (up to 54.6% of delirium-positive cases on day 4). These findings are similar to those by McManus et al who tested patients with stroke for delirium within first 4 days after stroke, mostly within 1 day of admission and then at weekly intervals during 1 month, and detected delirium in 21 of 23 delirium-positive cases on the initial assessment (7). Our results thus showed that any diagnostic algorithm for detection of delirium poststroke should consider the time profile of poststroke delirium; in this study, it began within 24 hrs after the stroke in most cases and lasted ⬍1 day in one-fourth of patients. Despite the fact that usual clinical follow-up often misses, in particular, the hypoactive form of delirium that prevailed in our series (32), validated screening tools are still used by only a minority of healthcare professionals (33, 34). There exist several such diagnostic tools for detection of delirium both in general and intensive care settings (11–14, 35– 40). CAM-ICU was found to have excellent criterion validity and overall accuracy in intensive care settings for adult patients without structural brain injury (12, 13, 41) and its pediatric version has proved to be a valid diagnostic instrument for delirium in the young (42). Recently, CAMICU showed favorable test characteristics alongside the Intensive Care Delirium Screening Checklist and physicians’ views in a mixed intensive care unit population that included patients with structural brain injury (43). The poststroke population is, however, very difficult to assess, because it is quite specific with respect to assessment of delirium diagnosis. It comprises patients with high prevalence of prestroke cognitive deficit (30.6% in a study by Henon et al [4] and in 19.4% in our study) and communication deficit (21% to 38% in the acute stage of stroke [44] and in 38% in our study). Because dementia is a welldocumented risk factor for poststroke delirium (4, 5), a high prevalence of patients with unrecognized baseline cognitive deficits (i.e., dementia) in our study could have played a role in the high incidence of poststroke delirium reported in this investigation. Future work on the epidemiology of delirium in stroke cohorts should strive more diligently to decipher these relationships. The pathoCrit Care Med 2012 Vol. 40, No. 2

physiology of delirium in structural brain injuries also remains beyond immediate access, because one can never be sure whether the delirium is simple delirium as opposed to being under the influence of specific key brain regions. Furthermore, both the DSM criteria for delirium and those used by screening tests such as CAM-ICU do not address the mechanism of delirium. Serial assessment of delirium is therefore necessary to capture the fluctuating nature of delirium episodes that is crucial for differentiation from both prestroke cognitive deficits and poststroke disturbance of memory, attention, or perception resulting from focal ischemic or hemorrhagic brain lesions. A high incidence of delirium on the first day poststroke in our study is not influenced by the change of mental status caused by stroke itself, because the mental status of patients on admission was considered as a new baseline and in case of alteration of mental status on admission and its early normalization, it was adjusted back to normal as a new baseline for the rest of CAM-ICU ratings (in reference to handling feature 1). Patients with stroke with aphasia deserve special comment. We observed false-positive CAM-ICU assessment in three cases with severe aphasia and disturbance of comprehension that made evaluation of attention and thinking difficult. We thus recommend re-evaluation of CAM-ICU positivity using more comprehensive consult/liaison neuropsychiatric evaluations in patients with severe disturbance of comprehension with a focus on fluctuation of mental status and behavior. Practical importance of delirium evaluation in patients with “macro” brain lesions including those after stroke is based on two main aspects. First, delirium development may provide an early warning signal for the managing team that additional treatable or modifiable complications of the underlying stroke such as nosocomial infections/sepsis, metabolic disturbances, or congestive heart failure because many with stroke have atherosclerotic coronary disease as well, are present, and need addressing. In a sense, diagnosing delirium in these patients may eventually prove as a beneficial management tool serving as a “canary in a coal mine.” Second, delirium was shown to predict worse prognosis in hospitalized patients. Patients who develop delirium have been reported as having high mortality, longer inpatient stays, and higher Crit Care Med 2012 Vol. 40, No. 2

complication rates at the same time as being at increased risk of institutionalization and of dementia (45, 46). Only few studies, however, showed the same impact of delirium on the prognosis of patients with stroke; poststroke patients had longer lengths of stay (7), worse functional outcome in patients with stroke with delirium (5), increased risk of institutionalization (7), and higher longterm mortality (5, 7). We confirmed longer stay in the hospital and higher disability after 1 wk, but only an insignificant trend toward higher mortality and disability at 6 months after stroke onset in patients with delirium compared with those without delirium. Our study, however, was not designed to study the impact of delirium on the long-term outcome of patients with stroke. Future studies comprising larger study samples and using screening tools such as CAM-ICU need to be performed to see if change over time (i.e., delirium compared with stable cognitive deficit) is really helpful in identifying prognostic indicators and introducing modifications in treatment and practical management of patients with stroke and to better study the relationships between delirium and clinical outcomes touched on in this investigation. Our study has several limitations. Only 54.7% of screened patients with stroke completed the follow-up. Most patients excluded were, however, attributable to designated a priori exclusion criteria. The dropout cases—22 patients (14.6% of enrolled patients)—were lost as a result of new developed decreased consciousness or death. These cases, however, would not have been testable for delirium not only by CAM-ICU, but by any other method or test. The CAM-ICU testing was not performed by nurses, and the interrater reliability was estimated in a small sample of cases. High validity and reliability of the CAM-ICU when used by nurses and physicians were, however, have shown by previous studies (12, 13, 42). A recent study by van Eijk et al (47), although performed in a different population of general intensive care unit patients, showed that the sensitivity of the CAM-ICU in routine practice might be lower compared with research study settings. This study is helpful as a reminder that changing culture in the intensive care unit to include daily monitoring should not be assumed to be easy and it will likely require repeated implementation and calibration efforts (the van Eijk

study, for example, conducted their implementation training in some cases briefly and remote in time from the testing). Thus, for the population of poststroke patients, to achieve the same test characteristics as were found in our investigation, a center needs to take into consideration the need for ongoing monitoring and compliance checks. Because this patient population may be more challenging than general medical and general surgical patients, we believe a future line of study should include implementation and quality improvement to hone the methods of enacting delirium screening at the bedside in practice for patients with stroke. Evaluation every 8 –12 hrs, as recommended in the training manual for CAM-ICU (48), appears to be more sensitive to detect fluctuating course of delirium than a 24-hr schedule used in our study. The detectin of post-stroke delirium is decreased if the assessment is made only once or if there is a delay in assessment beyond 24 hours (49).

CONCLUSION Delirium was detected very frequently after stroke using a testing algorithm that we judged a priori to be appropriate to the time profile of poststroke delirium. Early (i.e., within 24 hrs after stroke onset) and serial screening for delirium for at least 5 days may be necessary to see change over time in this high-risk population with the added challenge that they have new baseline neurologic status as a result of the recent stroke. CAM-ICU was a valid screening method and may be suitable for the clinical spectrum of patients with stroke with the caveat that a more in-depth evaluation (e.g., 20- to 30min neuropsychiatric examinations) will be necessary for selected patients to diagnose more subtle or complex neurologic presentations. This tool may enable routine monitoring in stroke units where there is no psychiatric or formal neurologically trained expert immediately available. In concert with selected consultations mentioned, the CAM-ICU will provide a means for delirium recording in future epidemiologic and interventional studies in patients with stroke.

REFERENCES 1. Caeiro L, Ferro JM, Albuquerque R, et al: Delirium in the first days of acute stroke. J Neurol 2004; 251:171–178

489

2. Gustafson Y, Olsson T, Erikkson S, et al: Acute confusional states (delirium) in stroke patients. Cerebrovasc Dis 1991; 1:257–264 3. Gustafson Y, Olsson T, Asplund K, et al: Acute confusional state (delirium) soon after stroke is associated with hypercortisolism. Cerebrovasc Dis 1993; 3:33–38 4. Henon H, Lebert F, Durieu I, et al: Confusional state in stroke: Relation to preexisting dementia, patient characteristics, and outcome. Stroke 1999; 30:773–779 5. Sheng AZ, Shen Q, Cordato D, et al: Delirium within three days of stroke in a cohort of elderly patients. J Am Geriatr Soc 2006; 54: 1192–1198 6. McManus J, Pathansali R, Hassan H, et al: The evaluation of delirium post-stroke. Int J Geriatr Psychiatry 2009; 24:1251–1256 7. McManus J, Pathansali R, Hassan H, et al: The course of delirium in acute stroke. Age Ageing 2009; 38:385–389 8. Dahl MH, Rånning OM, Thommessen B: Delirium in acute stroke—Prevalence and risk factors. Acta Neurol Scand 2010; 190(Suppl): 39 – 43 9. McManus J, Pathansali R, Stewart R, et al: Delirium post-stroke. Age Ageing 2007; 36: 613– 618 10. Ferro JM, Caeiro L, Verdelho A: Delirium in acute stroke. Curr Opin Neurol 2002; 15: 51–55 11. American Psychiatric Association: Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition. Washington, DC, American Psychiatric Association, 1994, pp 123–133 12. Ely EW, Inouye S, Bernard GL, et al: Delirium in mechanically ventilated patients: Validity and reliability of the Confusion Assessment Method for the Intensive Care Unit (CAM-ICU). JAMA 2001; 286:2703–2710 13. Ely EW, Margolin R, Francis J, et al: Evaluation of delirium in critically ill patients: Validation of the Confusion Assessment Method for the Intensive Care Unit (CAMICU). Crit Care Med 2001; 29:1370 –1379 14. Sessler CN, Gosnell M, Grap MJ, et al: The Richmond Agitation-Sedation Scale: Validity and reliability in adult intensive care patients. Am J Respir Crit Care Med 2002; 166: 1338 –1344 15. Ely EW, Truman B, Shintani A, et al: Monitoring sedation status over time in ICU patients: The reliability and validity of the Richmond Agitation Sedation Scale (RASS). JAMA 2003; 289:2983–2991 16. Brott T, Adams HP Jr, Olinger CP, et al: Measurements of acute cerebral infarction: A clinical examination scale. Stroke 1989; 20: 964 –970 17. Bamford J, Sandercock P, Dennis M, et al: Classification and natural history of clinically identifiable subtypes of cerebral infarction. Lancet 1991; 337:1521–1526 18. Adams HP Jr, Bendixen BH, Kappelle LJ, et al: Classification of subtype of acute ischemic stroke. Definition for use in a multicenter clinical trial. TOAST Trial of Org 10172 in

490

19.

20.

21.

22.

23.

24.

25.

26.

27.

28.

29.

30.

31.

32.

33.

Acute Stroke Treatment. Stroke 1993; 24: 35– 41 Moreno R, Vincent JL, Matos R, et al: The use of maximum SOFA score to quantify organ dysfunction/failure in intensive care. Results of a prospective, multicentre study Working Group on Sepsis related Problems of the ESICM, Intensive Care Med 1999; 25:686 – 696 Blessed G, Tomlinson BE, Roth M: The association between quantitative measures of dementia and of senile change in the cerebral grey matter of elderly subjects. Br J Psychiatry 1968; 114:797– 811 Nakase-Thompson R, Manning E, Sherer M, et al: Brief assessment of severe language impairments: Initial validation of the Mississippi aphasia screening test. Brain Inj 2005; 19:685– 691 Kosˇta´lova´ M, Ba´rtkova´ E, Sˇajgalíkova´ K, et al: A Standardization study of the Czech version of the Mississippi Aphasia Screening Test (MASTcz) in stroke patients and control subjects. Brain Inj 2008; 22:793– 801 Mahoney FI, Barthel D: Functional evaluation: The Barthel Index. Md State Med J 1965; 14:56 – 61 Inouye SK, van Dyck CH, Alessi CA, et al: Clarifying confusion: The Confusion Assessment Method. A new method for detection of delirium. Ann Intern Med 1990; 113:941–948 Bergeron N, Dubois MJ, Dumont M, et al: Intensive Care Delirium Screening Checklist: Evaluation of a new screening tool. Intensive Care Med 2001; 27:859 – 864 CAM-ICU. Czech version. Available at: http://www.icudelirium.org/docs/CAM_ICU_ worksheet_Czech.pdfweb. Accessed July 30, 2010 Stagno D, Gibson C, Breitbart W: The delirium subtypes: A review of prevalence, phenomenology, pathophysiology, and treatment response. Palliat Support Care 2004; 2:171–179 Mita´sˇova´ A, Bednaøı´k J, Kosˇta´lova´ M, et al: Standardization of the Czech version of The Confusion Assessment Method for the Intensive Care Unit (CAM-ICUcz)—A screening test for delirium in the intensive care settings [in Czech]. Cesk Slov Neurol N 2010; 73/106:258 –266 Shintani AK, Girard TD, Eden SK, et al: Immortal time bias in critical care research: Application of time-varying Cox regression for observational cohort studies. Crit Care Med 2009; 37:2939 –2945 Davison AC, Hinkley DV: Bootstrap Methods and Their Application. Cambridge, Cambridge University Press, 1997 Hardin J, Hilbe J (Eds): Generalized Estimating Equations. First Edition. London, Chapman and Hall/CRC, 2003 Spronk PE, Riekerk B, Hofhuis J, et al: Occurrence of delirium is severely underestimated in the ICU during daily care. Intensive Care Med 2009; 35:1276 –1280 Ely EW, Stephens RK, Jackson JC, et al: Current opinions regarding the importance, diagnosis, and management of delirium in

34.

35.

36.

37.

38.

39.

40.

41.

42.

43.

44.

45.

46. 47.

48.

49.

the intensive care unit: A survey of 912 healthcare professionals. Crit Care Med 2004; 32:106 –112 Patel RP, Gambrell M, Speroff T, et al: Delirium and sedation in the intensive care unit: Survey of behaviors and attitudes of 1384 healthcare professionals. Crit Care Med 2009; 37:825– 832 Trzepacz PT, Baker RW, Greenhouse J: A symptom rating scale for delirium. J Psychiatry Res 1988; 23:89 –97 Trzepacz PT, Mittal D, Torres R, et al: Validation of the Delirium Rating Scale–revised-98: Comparison with the delirium rating scale and the cognitive test for delirium. J Neuropsychiatry Clin Neurosci 2001; 13:229 –242 Breitbart W, Rosenfeld B, Roth A, et al: The Memorial Delirium Assessment Scale. J Pain Symptom Manage 1997; 13:128 –137 Gaudreau J-D, Gagnon P, Harel F, et al: Fast, systematic, and continuous delirium assessment in hospitalized patients: The Nursing Delirium Screening Scale. J Pain Symptom Manage 2005; 29:368 –375 Neelon VJ, Champagne MT, Carlson J, et al: The NEECHAM Confusion Scale: Construction, validation and clinical testing. Nurs Res 1996; 45:324 –330 Schuurmans MJ, Shortridge-Baggett LM, Duursma SA: The Delirium Observation Screening Scale: A screening instrument for delirium. Res Theory Nurs Pract 2003; 17: 31–50 Guenther U, Popp J, Koecher L, et al: Validity and reliability of the CAM-ICU Flowsheet to diagnose delirium in surgical ICU patients. J Crit Care 2010; 25:144 –151 Smith HAB, Boyd J, Fuchs C, et al: Diagnosing 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 Van Eijk MM, van Marum RJ, Klijn IA, et al: Comparison of delirium assessment tools in a mixed intensive care unit. Crit Care Med 2009; 37:1881–1885 Berthier ML: Poststroke aphasia: Epidemiology, pathophysiology and treatment. Drugs Aging 2005; 22:163–182 Siddiqi N, House AO, Holmes JD: Occurrence and outcome of delirium in medical inpatients: A systemic literature review. Age Ageing 2006; 35:350 –364 Young J, Inouye S: Delirium in older people. BMJ 2007; 334:842– 846 Van Eijk MM, van den Boogaard M, van Marum RJ, et al: Routine use of the Confusion Assessment Method for the Intensive Care Unit: A multicenter study. Am J Respir Crit Care Med 2011 May 11 [Epub ahead of print] The Confusion Assessment Method for the ICU (CAM-ICU).Trainingmanual.Availableat:http:// www.icudelirium.org/docs/CAM_ICU_training. pdf. Accessed January 3, 2011 Oldenbeuving AW, de Kort PL, Jansen BP, et al: Delirium in the acute phase after stroke: Incidence, risk factors, and outcome. Neurology 2011; 76:993–999

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