An 85-year-old man with non–small cell lung cancer was admitted yesterday to the oncology ward for treatment of pneumonia. He started antibiotics and supplemental oxygen. Prior to hospitalization, he lived independently in the community. An overnight nursing report indicates that he did not sleep and was pacing up and down the ward. During morning rounds, he was easily startled and noted to be picking at the bed sheets. The patient's daughter says, “This is not my father. Right now, he's in his own little world. He never behaves this way!” What instruments could the nurse and physician use to determine if these changes and observations are indicative of a delirium?
Patients with delirium have a reduced ability to focus, to sustain or shift attention with an associated change in cognition, or they develop a perceptual disturbance that occurs over a short period of time and tends to fluctuate over the course of the day. There is usually evidence of a medical cause from history, physical examination, or investigations.1 Many hospitalized older patients become delirious and delirium is an independent marker for increased mortality during the 12 months after hospital admission.2 In addition to death, developing delirium has been associated with longer length of hospital stay, increased hospital-acquired complications, persistent cognitive deficits, and increased discharge rates to long-term care.3-6
The symptoms of delirium may become apparent when a patient has difficulty in carrying on a normal conversation. Because visiting family members or nurses often spend more time with the patient than physicians do, they may be the first to detect delirium. Health care workers fail to recognize more than half of delirium cases.7-9 The Diagnostic and Statistical Manual of Mental Disorders (Third Edition) (DSM-III) criteria for delirium, when applied systematically to 133 consecutively admitted patients to an acute medical ward, led to a diagnosis of delirium in 20 patients, only 1 of whom was reported as delirious by the primary clinician.9
Delirium is often iatrogenic, resulting from a diversity of problems such as adverse drug reactions, the multiple stresses of surgery, complications of procedures, or immobilization.10 Given that multiple factors usually contribute to the development of delirium, randomized trials have shown multicomponent preventive strategies to be effective in preventing delirium.11-14
The diagnosis is primarily clinical and based on careful observation of key features. Consensus from an expert panel identified several clinical features of delirium: acute onset and fluctuating course, inattention, disorganized thinking, altered level of consciousness, disorientation, memory impairment, perceptual disturbances, increased or decreased psychomotor activity, and disturbance of the sleep-wake cycle.15 The key diagnostic feature that helps to distinguish delirium from dementia is that delirium has an acute and rapid onset, whereas dementia is much more gradual in progression. Alternations in attention and changes in level of consciousness also favor a diagnosis of delirium. Delirium typically presents in 1 of 2 major forms—hypoactive or hyperactive. The hypoactive form is characterized by lethargy and reduced psychomotor functioning; this form often goes unrecognized by clinicians and caregivers. The hyperactive form is characterized by agitation, increased vigilance, and often hallucinations; this form rarely goes unnoticed by clinicians or caregivers. There is also a mixed form of delirium in which patients fluctuate between the hypoactive and hyperactive forms.16
The criterion standard for the diagnosis of delirium as defined by the DSM continues to evolve.1, 17, 18 A formal assessment using this reference standard, however, may involve an in-depth interview and series of cognitive tests by a clinician familiar with DSM-IV criteria. Even in the hands of experts, the reference standard for delirium is a clinical diagnosis based on the DSM-IV criteria and may be prone to some subjectivity. For example, one study noted the agreement κ for reliability between 2 geriatricians with each classification of delirium to be 0.74 (DSM-III), 0.74 (DSM-III-R), and 0.72 (DSM-IV).19 Simpler bedside instruments may better guide which patients should receive formal consultation and intervention. The objective of this review was to determine the diagnostic accuracy of bedside delirium instruments.
Literature Search Strategy
Searches of MEDLINE (from 1950 to May 2010) and EMBASE (from 1980 to May 2010) using Ovid were completed to identify studies performed in a clinical setting. The search strategy used terms including confusion and delirium combined with validated search filters for retrieving articles20, 21 on the diagnosis of health disorders (Supplemental Box 1). Additional articles were identified from searching the bibliographies of retrieved articles.
Study Selection and Data Extraction
Inclusion criteria were published prospective studies that were conducted in hospitalized patients not in the intensive care unit, described the use of an appropriate reference standard (DSM-III, DSM-III-R, or DSM-IV),1, 17, 18 had the reference standard performed by a specialist physician (geriatrician, neurologist, or psychiatrist), applied the same index test to most patients (>80%), applied the same reference tests to all patients and all reference test results were available, and included participants with and without delirium. Exclusion criteria were studies involving mostly alcohol-related delirium or a pediatric population, studies in which the index and reference tests were performed by the same individual, and duplicate or non–English-language publication. The bedside index instrument must be feasible in a clinical setting, without requiring special equipment, and may be performed by a nonexpert. Furthermore, primary data or appropriate summary statistics had to be available. When necessary, additional data were obtained by contacting study authors.
Each abstract was reviewed independently by 2 reviewers to select relevant publications that met the inclusion criteria for data extraction. In cases of doubt, full-text articles were retrieved for review and discussion. Two investigators independently reviewed each full-text article to confirm that inclusion and exclusion criteria were met. Disagreements were resolved by discussion, and when necessary, with a third reviewer.
Data were extracted from the included studies independently by 2 reviewers. Disagreements were resolved by consensus with the third reviewer. Information was extracted using a specially designed form based on the principles outlined by the Standards for Reporting of Diagnostic Accuracy (STARD).22 Details pertaining to study quality included study size, participant recruitment method, demographic characteristics of participants, application of reference standard, application of diagnostic test(s), presence of blinding, independence of tests, and attrition rates. Study quality was summarized using a quality checklist designed for the Rational Clinical Examination series in which a threshold of 100 patients was used to distinguish level 1 from level 2 studies.23
For studies of test accuracy, sensitivity, specificity, and likelihood ratios (LRs) were calculated from the raw data and then rounded for display in the data tables.24 If a study contained any zeros in the 2×2 table, resulting in likelihood estimates of zero or infinity, 0.5 was added to all the counts for that study for calculating the LR and respective confidence intervals (CIs). For studies that evaluated the same instrument at different threshold levels, the data were abstracted at each level and then the optimum threshold was selected based on a balance between the diagnostic odds ratio (OR) and our confidence in the findings because the threshold was studied by multiple investigators. The diagnostic OR (positive LR divided by negative LR) is a single indicator of test performance in which higher values indicate better discriminatory test performance. Summary LRs for instruments were derived using a univariate random-effects model (Comprehensive MetaAnalysis, version 2.2046, Biostat Inc, Englewood, New Jersey) since bivariate measures were similar or failed to converge on a solution.25
Heterogeneity was explored using I2, which describes the percentage of total variation across studies that is due to heterogeneity rather than chance. Heterogeneity was categorized as low, moderate, and high to I2 values of 25%, 50%, and 75%.26 If there was at least moderate heterogeneity, summary statistics were recalculated by eliminating the individual studies that contributed most to heterogeneity or by selecting only certain subgroups in a sensitivity analysis. Heterogeneity was assessed using Meta-Disc, version 1.4 (Unit of Clinical Biostatistics, Ramón y Cajal Hospital, Madrid, Spain).27
We identified 6570 potential citations of which 79 unique studies were retrieved for full-text review. Fifty-four studies were later excluded for a variety of reasons, leaving 25 studies15, 28-51 suitable for data extraction and synthesis (Supplemental Figure 1).
The included studies ranged in size from 26 to 791 participants (N=3027; Supplemental Table 1). Eleven bedside delirium instruments, with data on diagnostic accuracy, met our inclusion and exclusion criteria (Box 80-2).15, 29, 31, 38, 39, 47, 48, 52-55
Box 80-2Bedside Delirium Instruments |Favorite Table|Download (.pdf) Box 80-2 Bedside Delirium Instruments
|Clinical Assessment of Confusion (CAC)52 |
|A nursing checklist of 25 psychomotor behaviors associated with varying degrees of confusion (range, 0-77). The presence of more behaviors is associated with more severe confusion. |
|Confusion Assessment Method (CAM)15 |
|The CAM includes an instrument and diagnostic algorithm for identification of delirium. The instrument assesses the presence, severity, and fluctuation of 9 delirium features: acute onset, inattention, disorganized thinking, altered level of consciousness, disorientation, memory impairment, perceptual disturbances, psychomotor agitation or retardation, and altered sleep-wake cycle. The questionnaire can be administered in 5 min. The algorithm is based on the cardinal elements of the Diagnostic and Statistical Manual of Mental Disorders (DSM) (Third Edition, Revised) criteria for delirium: features 1 (acute onset and fluctuating course) and 2 (inattention) are essential features, and feature 3 (disorganized thinking) or 4 (altered level of consciousness) is supported by expert judgment and clinical practice, in which the first 2 and either of the latter 2 are required for diagnosis. |
|Delirium Observation Screening Scale (DOSS)48, 53 |
|The original version consisted of a 25-item scale based on the DSM-IV criteria for delirium. The scale was designed to capture early symptoms of delirium that nurses could observe during regular care. The scale was subsequently reduced to 13 observations that could each be rated as normal (score, 0) or abnormal (score, 1). A total score of 3 or more points indicates delirium. Completion of the instrument requires less than 5 min. |
|Delirium Rating Scale (DRS)47 |
|A 10-item observational scale (range, 0-32) that rates patients on the characteristic symptoms of delirium including temporal onset, perceptual disturbance, hallucinations, delusions, psychomotor behavior, cognitive status, physical disorder, sleep-wake cycle disturbance, lability of mood, and variability of symptoms. It is intended to be used by clinicians with psychiatric training. |
|Delirium Rating Scale-Revised-98 (DRS-R-98)54 |
|This is a revised version of the DRS. It is more comprehensive and separates the scale into 2 sections: 3 diagnostic items for initial ratings and a 13-item scale for repeated measures (range, 0-46). |
|Digit Span Test39 |
|A series of random numbers are presented at a rate of 1 per second. The patient is asked to repeat the sequence. Starting with a 2-number sequence, each correctly repeated series is followed by a sequence with 1 additional digit. The test result is abnormal if the patient cannot repeat at least 5 digits. |
|Global Attentiveness Rating (GAR)38 |
|A physician-rated 10-cm visual analog scale in which a high rating indicates the patient can be easily engaged and a low rating indicates the patient cannot be aroused or is so agitated that a conversation is not possible. The assessment is based on a minimum of 2 min of general conversation with the patient, without any formal cognitive testing or collateral information. |
|Memorial Delirium Assessment Scale (MDAS)29 |
|A 10-item, 4-point clinician-rated scale (range, 0-30) designed to quantify the severity of delirium. Scale items reflect the DSM criteria for delirium, such as assessing for disturbances in arousal and level of consciousness, as well as several areas of cognitive functioning. It is intended for repeated administration for measurement of change. Completion of the instrument takes approximately 10 min. |
|Mini-Mental State Examination (MMSE)55 |
|A widely used brief objective measure of cognitive function in older adults. It is a 30-item instrument that includes tests of orientation, memory, and concentration. |
|Nursing Delirium Screening Scale (Nu-DESC)31 |
|A screening scale (range, 0-10) designed to be administered by a nurse based on clinical observation in routine practice. Five symptoms are rated: disorientation, inappropriate behavior, inappropriate communication, hallucination, and psychomotor retardation. The threshold for delirium is a score of 2 or more. On average, the instrument can be completed in 1 min. |
|Vigilance “A” Test39 |
|A list of 60 letters in which 18 of them are the letter A is read to the patient at a rate of 1 letter per second. The patient is asked to indicate to the examiner each time the letter A is heard. More than 2 errors is considered abnormal. |
All studies provided details on participant recruitment, and 9 enrolled consecutive patients.30, 33-36, 38, 41-43 Eighteen studies described the use of independent, blinded assessment of reference and diagnostic tests in a clinical setting.15, 29-34, 36-41, 45, 47, 48, 50, 51 Application of the diagnostic tests was consistent and complete in all but 2 studies.39, 45 Application of the reference test, a DSM -based diagnosis by a specialist physician, was identical within each study. Overall, 1, 7, 9, and 8 studies were rated levels 1, 2, 3, and 4, respectively, in terms of quality level of evidence using the Rational Clinical Examination quality scale (Supplemental Table 1).23
From the 9 studies30, 33-36, 38, 41-43 that enrolled patients consecutively, the study prevalence of delirium ranged from 9% to 63% depending on the clinical setting (Supplemental Table 1). The prevalent cases in some of these studies likely included patients admitted with delirium, but also patients who developed delirium (incident cases). The highest prevalence, 63%, was in a study of hospitalized patients in an oncology or palliative care ward presenting with mental status change.33 The prevalence of delirium among patients admitted to a geriatric unit ranged from 9% to 43%36, 38, 42, 46 and from 12% to 27% among patients in a postcardiac surgery unit.35, 41
Accuracy of Clinical Examination Findings in the Diagnosis of Delirium
Of the 11 bedside instruments, positive findings on the Global Attentiveness Rating (GAR), Memorial Delirium Assessment Scale (MDAS), Confusion Assessment Method (CAM), Delirium Rating Scale Revised-98 (DRS-R-98), Clinical Assessment of Confusion (CAC), and Delirium Observation Screening Scale (DOSS) all had an LR of greater than 5.0 for diagnosing delirium (Table 80-2). A commonly used test for dementia, the Mini-Mental State Examination (MMSE) was the least useful for identifying patients with delirium (LR, 1.6 for a score <24). Negative findings on the GAR, MDAS, CAM, DRS-R-98, DRS, DOSS, Nursing Delirium Screening Scale (Nu-DESC), and MMSE made delirium less likely with LRs of 0.2 or less (Table 80-2). Circumstances may only allow a clinician to use a time-efficient bedside instrument that can be completed in 5 minutes or less, such as the CAM, DOSS, GAR, or Nu-DESC.15, 31, 38, 48 Also, the choice of instrument may be guided by the background of the examiner. For example, when only considering studies in which a time-efficient instrument was performed by nurses, the CAM had the best diagnostic OR (summary-positive LR, 7.3; 95% CI, 1.9-27; and summary-negative LR, 0.08; 95% CI, 0.03-0.21).31, 43 A physician may also choose to use the CAM (summary-positive LR, 19; 95% CI, 6.7-51; and summary-negative LR, 0.19; 95% CI, 0.13-0.27)15, 32, 36, 37, 50, 51 rather than the MDAS, DRS, or DRS-R-98 because it can be performed in less than 5 minutes. Lastly, the accuracy of the GAR (positive LR, 65; 95% CI, 9.3-458; and negative LR, 0.06; 95% CI, 0.01-0.38) may not apply to nongeriatricians and has only been assessed in 1 study.38
Table 80-2Summary Data for Diagnostic Accuracy of Bedside Instruments for Diagnosing Deliriuma |Favorite Table|Download (.pdf) Table 80-2 Summary Data for Diagnostic Accuracy of Bedside Instruments for Diagnosing Deliriuma
| || || || ||% (95% Confidence Interval) ||Likelihood Ratio (95% Confidence Interval) |
|Source ||Sample Size ||Delirium Prevalence, % ||Examiner Specialty ||Sensitivity ||Specificity ||Positive ||Negative |
|CAC || || || || || || || |
|Pompei et al,39 1995 ||428 ||15 ||Research assistant ||36 (24-49) ||95 (92-97) ||7.4 (4.2-13) ||0.67 (0.56-0.81) |
|CAMb || || || || || || || |
|Farrell and Ganzini,34 1995 ||72 ||45 ||Osteopathic physician ||93 (77-98) ||93 (80-98) ||13 (4.4-39) ||0.07 (0.02-0.28) |
|Gaudreau et al,31 2005 ||59 ||32 ||Nurse ||98 (70-100) ||95 (82-99) ||16 (4.8-53) ||0.03 (0.00-0.42) |
|Gonzalez et al,32 2004 ||123 ||24 ||General physician or psychiatrist ||90 (73-97) ||99 (92-100) ||167 (10-2654) ||0.11 (0.04-0.31) |
|Hestermann et al,50 2009c ||39 ||33 ||Gerontologist or resident physician in geriatric medicine ||77 (48-92) ||96 (77-99) ||20 (2.9-140) ||0.24 (0.09-0.65) |
|Inouye et al,15 1990 (site 1) ||30 ||33 ||Geriatrician ||95 (55-100) ||95 (72-99) ||13 (2.8-63) ||0.05 (0.00-0.74) |
|Inouye et al,15 1990 (site 2) ||26 ||62 ||Geriatrician ||94 (66-99) ||90 (53-99) ||9.4 (1.5-60) ||0.07 (0.01-0.47) |
|Laurila et al,36 2002d ||81 ||40 ||Geriatrician ||81 (64-91) ||84 (71-92) ||5.0 (2.6-9.6) ||0.22 (0.11-0.47) |
|Leung et al,37 2008 ||100 ||25 ||Family physician ||76 (56-89) ||99 (90-100) ||114 (7.1-1822) ||0.25 (0.13-0.49) |
|Pompei et al,39 1995 ||428 ||15 ||Research assistant ||46 (34-58) ||92 (89-94) ||5.8 (3.7-9.0) ||0.59 (0.47-0.74) |
|Rolfson et al,41 1999e ||30 ||27 ||Nurse ||13 (0-53) ||100 (85-100) ||7.7 (0.34-171) ||0.85 (0.63-1.1) |
|Ryan et al,51 2009f ||52 ||33 ||Hospitalist ||88 (63-97) ||99 (82-100) ||65 (4.1-1034) ||0.14 (0.04-0.45) |
|Zou et al,43 1998 ||87 ||49 ||Nurse ||93 (80-98) ||77 (63-87) ||4.1 (2.4-7.1) ||0.09 (0.03-0.27) |
|Pooledg ||1036 || || ||86 (74-93) ||93 (87-96) ||9.6 (5.8-16) ||0.16 (0.09-0.29) |
|DOSS (13-Item)b || || || || || || || |
|van Gemert and Schuurmans,452007 ||87 ||10 ||Nurse ||89 (50-98) ||88 (79-94) ||7.6 (4.0-15) ||0.13 (0.02-0.80) |
|Schuurmans et al,48 2003 ||92 ||20 ||Nurse ||94 (69-99) ||76 (65-84) ||3.9 (2.6-5.9) ||0.07 (0.01-0.50) |
|Pooledg ||178 || || ||92 (74-98) ||82 (66-92) ||5.2 (2.7-9.9) ||0.10 (0.03-0.37) |
|DRS≥10b,h || || || || || || || |
|Grassi et al,33 2001 ||105 ||63 ||Research psychologist ||95 (87-99) ||62 (46-75) ||2.5 (1.7-3.7) ||0.07 (0.02-0.23) |
|Rockwood et al,40 1996i ||67 ||37 ||Resident physician in geriatric medicine or psychiatry ||82 ||94 ||14 ||0.19 |
|Rosen et al,42 1994 ||791 ||9 ||Research clinician ||94 (86-98) ||82 (79-84) ||5.1 (4.3-6.0) ||0.07 (0.03-0.18) |
|Trzepacz et al,47 1988 ||47 ||43 ||Psychiatrist ||98 (71-100) ||98 (77-100) ||55 (3.5-853) ||0.02 (0.00-0.38) |
|Pooledg ||943 || || ||95 (90-98) ||79 (58-91) ||4.3 (2.1-9.1) ||0.07 (0.03-0.13) |
|DRS-R-98>20b,h || || || || || || || |
|de Negreiros et al,44 2008 ||64 ||40 ||Researcher ||93 (75-98) ||95 (81-99) ||17 (4.4-66) ||0.08 (0.02-0.30) |
|de Rooij et al,30 2006 ||65 ||35 ||Geriatrician or psychiatrist ||93 (65-99) ||82 (69-90) ||5.2 (2.8-9.5) ||0.08 (0.01-0.54) |
|Pooledg ||129 || || ||93 (80-98) ||89 (68-97) ||8.0 (2.6-25) ||0.08 (0.03-0.24) |
|Digit Span Test || || || || || || || |
|Pompei et al,39 1995 ||419 ||15 ||Research assistant ||34 (22-48) ||90 (87-93) ||3.4 (2.1-5.5) ||0.73 (0.61-0.89) |
|GAR<7 || || || || || || || |
|O'Keeffe and Gosney,38 1997 ||87 ||21 ||Geriatrician ||94 (73-100) ||99 (92-100) ||65 (9.3-458) ||0.06 (0.01-0.38) |
|MDAS≥10b,h || || || || || || || |
|Breitbart et al,29 1997 ||33 ||52 ||Psychiatrist ||82 (57-94) ||75 (49-90) ||3.3 (1.4-7.9) ||0.24 (0.08-0.68) |
|Kazmierski et al,35 2008 ||260 ||12 ||Psychiatrist ||97 (80-100) ||96 (92-98) ||22 (12-41) ||0.04 (0.01-0.24) |
|Matsuoka et al,46 2001 ||37 ||43 ||Psychiatrist ||97 (66-100) ||98 (72-100) ||43 (2.8-662) ||0.03 (0.00-0.46) |
|Pooledg ||330 || || ||92 (75-98) ||92 (70-98) ||12 (2.4-58) ||0.09 (0.02-0.38) |
|MMSE <24 || || || || || || || |
|Grassi et al,33 2001 ||105 ||63 ||Trained research psychologist ||96 (87-99) ||38 (23-55) ||1.6 (1.2-2.0) ||0.12 (0.04-0.38) |
|Nu-DESC>0 || || || || || || || |
|Leung et al,37 2008 ||100 ||25 ||Nurse ||96 (80-100) ||69 (59-79) ||3.1 (2.3-4.4) ||0.06 (0.01-0.40) |
|Vigilance “A” Test || || || || || || || |
|Pompei et al,39 1995 ||421 ||15 ||Research assistant ||61 (47-74) ||77 (73-81) ||2.7 (2.0-3.5) ||0.50 (0.36-0.71) |
There was significant heterogeneity among the studies likely owing to differences in the study quality, experience level of the individual performing the index test, and the version of the DSM criteria used for the reference standard. For the CAM, the problem of heterogeneity for the negative LR was resolved (I2=0%) when only studies in which the index test was performed by a physician were included, but the negative LR was not substantially different (summary-negative LR, 0.19; 95% CI, 0.13-0.27).15, 32, 36, 37, 50, 51 When a similar sensitivity analysis was performed for the positive LR, the positive LR increased (summary-positive LR, 19; 95% CI, 6.7-51), but the heterogeneity persisted (I2=67%).15, 32, 36, 37, 50, 51 When only levels 1 and 2 evidence studies were included, heterogeneity disappeared for the negative LR (I2=0%), but without any substantial change in the negative LR (summary-negative LR, 0.20; 95% CI, 0.14-0.30).34, 36, 37, 50, 51 Subanalysis by language or DSM version did resolve heterogeneity. Interrater reliability data were available for some of the studies for the CAM, DRS, DRS-R-98, and MDAS. All had a substantial degree of agreement (Supplemental Table 2).
The results of this review should be interpreted within the context of the included studies. The reference standard for delirium is a clinical diagnosis based on the DSM criteria and may be prone to some subjectivity. For example, one study noted the agreement κ for reliability between 2 geriatricians with each classification of delirium to be 0.74 (DSM-III), 0.74 (DSM-III-R), and 0.72 (DSM-IV).19 Although this level of agreement would be considered substantial, less trained clinicians may have lower levels of agreement when evaluating patients for delirium.
Most studies occurred in university hospitals and the data represented heterogeneous patient populations with different prevalence rates ranging from patients in postcardiac surgery wards to those in palliative care wards. Thus, the data likely include both prevalent cases (patients admitted with delirium) and incident cases (delirium developed during the hospital admission) with a wide spectrum of pretest probabilities. The pretest probability depends on the clinical setting (eg, whether the patient is postoperative) and underlying diagnoses. This broad spectrum of probabilities can lead to varying estimates of the probability of delirium after using the screening tests.
For most of the LRs with heterogeneity, the clinical impact can still be inferred from the CIs. While heterogeneity was still present for instruments with many studies such as the CAM, these studies also allow the instrument to be tested across multiple populations to ensure its adequate performance and generalizability across different settings. Clinicians should be less certain when interpreting LRs based on single, small studies. For instance, the extremely high, positive LR and extremely low, negative LR for certain thresholds on the MDAS and DRS have not been validated with further studies. Some studies may have been missed given we limited the search terms to confusion and delirium. Like other types of systematic reviews, systematic reviews of diagnostic tests are subject to publication bias and may exaggerate the summary estimate of test accuracy if publication is related to the positivity of results. There were insufficient studies to look for funnel plot asymmetry.
How to Learn the Method for Diagnosing Delirium
Some training is recommended for optimal use and an instruction manual is available online (http://hospitalelderlifeprogram.org/pdf/). The validity of the CAM for unstandardized observations is poor and performance is linked to the quality of training.8, 51 Thus, the CAM was designed to be scored based on observations made during formal cognitive assessment with brief instruments like the MMSE and the Digit Span test, which were used in the original validation study.55 Although there are several clinical features of delirium, the CAM diagnostic algorithm is based on only 4 cardinal elements of the DSM-III-R criteria for delirium: acute onset and fluctuating course, inattention, disorganized thinking, and altered level of consciousness (Box 80-1; Supplemental Figure 2). The algorithm should be based on observations during any contact with the patient and need not be limited to the interview period alone, but the algorithm should be applied immediately following the interview to ensure accuracy. Although not included in this review, the CAM has also been adapted for other clinical settings such as the intensive care unit,56 emergency department,57 and nursing home.58
The global assessment is based on a minimum of 2 minutes of general conversation with the patient, without necessarily any formal cognitive testing or corroborative information. The question to be answered by the clinician is, “How well did the patient keep his mind on interacting with you during the interview?” The answer is rated on an uninterrupted 10-cm visual analog scale.
We systematically determined the accuracy of bedside delirium instruments in diagnosing the presence of delirium and found several sensitive, specific, rapid, and simple instruments which may be useful for assessment of delirium. Although there have been other systematic reviews of bedside delirium instruments,59, 60 to our knowledge, this is the first study to include such a breadth of instruments and which also quantifies diagnostic accuracy with summary LRs.
The prevalence of delirium is high enough that a bedside delirium instrument should be used in patients 65 years old or older, particularly if there is an impression of a change in mental status. Because of its accuracy, brevity, and ease of use by clinical and lay interviewers, the CAM has become the most widely used standardized delirium instrument for clinical and research purposes over the past 2 decades.60 It has been translated into 10 languages for which published articles are available.60
Since a busy physician may not have 5 minutes to spend assessing a patient's mental status, the most time-efficient screening approach may be to simply have a 2-minute general conversation with the patient. Although the overall impression of the quality and ease with which the physician can easily keep the patient engaged throughout a minimum of 2 minutes of general conversation may be a very valuable guide to delirium (GAR), this is supported by only 1 study with geriatricians. Thus, generalizability may be limited to physicians with expertise in this patient population.
This review highlights some gaps in the literature pertaining to bedside delirium instruments. Future areas of study include testing educational interventions to improve the ability of health care professionals to identify delirium with the available instruments, correlating results of the instruments with clinical outcomes, and validating these instruments outside of the hospital setting.
The older hospitalized patient should be evaluated for delirium, especially if there is an impression of mental status change. The pretest probability of delirium in this patient was 63% based on the clinical setting (oncology ward patient with pneumonia).33 After conducting a formal cognitive assessment with the MMSE, both the physician and nurse used the CAM and agreed the change in mental status was acute and fluctuating in course, the patient was inattentive, and there was an altered level of consciousness. The posttest probability of a delirium was 93% and 97% (pretest oddsÃ—positive LR=posttest odds) for the nurse and physician, respectively. The causes for his delirium require prompt assessment.
The following disclosures were reported at the time this original article was first published in JAMA.
Financial Disclosures: None reported.
Funding/Support: Dr Straus was supported by a Tier 2 Canada Research Chair and a Health Scholar Award from the Alberta Heritage Foundation for Medical Research.
Role of the Sponsor: Supporters for the Tier 2 Canada Research Chair and the Health Scholar Award, and the Alberta Heritage Foundation had no role in the design and conduct of the study, the collection, management, analysis, or for the interpretation of the data; or for the preparation, review, or approval of the manuscript.
et al.. Acute confusional states in elderly patients treated for femoral neck fracture. J Am Geriatr Soc
P. Does delirium
contribute to poor hospital outcomes? J Gen Intern Med
J. The prognostic significance of delirium
in older hospital patients. J Am Geriatr Soc
B. Underdiagnosis and poor documentation of acute confusional states in elderly hip fracture patients. J Am Geriatr Soc
: a test of the Diagnostic and Statistical Manual III criteria on medical inpatients. J Am Geriatr Soc
: a symptom
of how hospital care is failing older persons and a window to improve quality of hospital care. Am J Med
et al.. Postoperative delirium
in old patients with femoral neck fracture: a randomized intervention study. Aging Clin Exp Res
et al.. A multicomponent intervention to prevent delirium
in hospitalized older patients. N Engl J Med
NM. Reducing delirium
after hip fracture: a randomized trial. J Am Geriatr Soc
J. Efficacy of a comprehensive geriatric intervention in older patients hospitalized for hip fracture. J Am Geriatr Soc
SK, van Dyck
RI. Clarifying confusion. Ann Intern Med
among patients with and without dementia
: does the diagnosis according to the DSM-IV differ from the previous classifications? Int J Geriatr Psychiatry
NL. Optimal search strategies for retrieving scientifically strong studies of diagnosis from Medline: analytical survey
RB. Hedges Team. EMBASE search strategies for identifying methodologically sound diagnostic studies for use by clinicians and researchers. BMC Med
et al.. Standards for Reporting of Diagnostic Accuracy. Towards complete and accurate reporting of studies of diagnostic accuracy: the STARD Initiative. Ann Intern Med
D. Update: primer on precision and accuracy. In: The Rational Clinical Examination: Evidence-Based Clinical Diagnosis. New York, NY: McGraw-Hill; 2008:9–16.
DB. Likelihood ratios with confidence: sample size estimation for diagnostic test studies. J Clin Epidemiol
PM. Differences between univariate and bivariate models for summarizing diagnostic accuracy may not be large. J Clin Epidemiol
A. Meta-DiSc: a software for meta-analysis
of test accuracy data. BMC Med Res Methodol
MA. Fast, systematic, and continuous delirium
assessment in hospitalized patients. J Pain Symptom Manage
M, de Pablo
et al.. Instrument for detection of delirium
in general hospitals. Psychosomatics
MA. Assessing attentiveness in older hospital patients. J Am Geriatr Soc
GS. The Delirium Rating Scale
in a psychogeriatric inpatient setting. J Neuropsychiatry Clin Neurosci
J. Detection and diagnosis of delirium
in the elderly. Int Psychogeriatr
PE. The clinical assessment of confusion-A. Appl Nurs Res
case finding: pilot testing of a new screening
scale for nurses. J Am Geriatr Soc
PR. Mini-mental state. J Psychiatr Res
LC. Unrecognized delirium
in ED geriatric patients. Am J Emerg Med
SA. The measurement of delirium
. Res Theory Nurs Pract