Dataset Information

Delirium detection in older acute medical inpatients: a multicentre prospective comparative diagnostic test accuracy study of the 4AT and the confusion assessment method.

ABSTRACT:

Background

Delirium affects > 15% of hospitalised patients but is grossly underdetected, contributing to poor care. The 4 'A's Test (4AT, www.the4AT.com ) is a short delirium assessment tool designed for routine use without special training. The primary objective was to assess the accuracy of the 4AT for delirium detection. The secondary objective was to compare the 4AT with another commonly used delirium assessment tool, the Confusion Assessment Method (CAM).

Methods

This was a prospective diagnostic test accuracy study set in emergency departments or acute medical wards involving acute medical patients aged ≥ 70. All those without acutely life-threatening illness or coma were eligible. Patients underwent (1) reference standard delirium assessment based on DSM-IV criteria and (2) were randomised to either the index test (4AT, scores 0-12; prespecified score of > 3 considered positive) or the comparator (CAM; scored positive or negative), in a random order, using computer-generated pseudo-random numbers, stratified by study site, with block allocation. Reference standard and 4AT or CAM assessments were performed by pairs of independent raters blinded to the results of the other assessment.

Results

Eight hundred forty-three individuals were randomised: 21 withdrew, 3 lost contact, 32 indeterminate diagnosis, 2 missing outcome, and 785 were included in the analysis. Mean age was 81.4 (SD 6.4) years. 12.1% (95/785) had delirium by reference standard assessment, 14.3% (56/392) by 4AT, and 4.7% (18/384) by CAM. The 4AT had an area under the receiver operating characteristic curve of 0.90 (95% CI 0.84-0.96). The 4AT had a sensitivity of 76% (95% CI 61-87%) and a specificity of 94% (95% CI 92-97%). The CAM had a sensitivity of 40% (95% CI 26-57%) and a specificity of 100% (95% CI 98-100%).

Conclusions

The 4AT is a short, pragmatic tool which can help improving detection rates of delirium in routine clinical care.

Trial registration

International standard randomised controlled trial number (ISRCTN) 53388093 . Date applied 30/05/2014; date assigned 02/06/2014.

SUBMITTER: Shenkin SD

PROVIDER: S-EPMC6651960 | biostudies-literature | 2019 Jul

REPOSITORIES: biostudies-literature

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Publications

Delirium detection in older acute medical inpatients: a multicentre prospective comparative diagnostic test accuracy study of the 4AT and the confusion assessment method.

Shenkin Susan D SD Fox Christopher C Godfrey Mary M Siddiqi Najma N Goodacre Steve S Young John J Anand Atul A Gray Alasdair A Hanley Janet J MacRaild Allan A Steven Jill J Black Polly L PL Tieges Zoë Z Boyd Julia J Stephen Jacqueline J Weir Christopher J CJ MacLullich Alasdair M J AMJ

BMC medicine 20190724 1

<h4>Background</h4>Delirium affects > 15% of hospitalised patients but is grossly underdetected, contributing to poor care. The 4 'A's Test (4AT, www.the4AT.com ) is a short delirium assessment tool designed for routine use without special training. The primary objective was to assess the accuracy of the 4AT for delirium detection. The secondary objective was to compare the 4AT with another commonly used delirium assessment tool, the Confusion Assessment Method (CAM).<h4>Methods</h4>This was a p ...[more]

PMID: 31337404

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Project description:ObjectivesTo compare performance characteristics of the Confusion Assessment Method (CAM) algorithm for screening and delirium diagnosis with criteria for delirium from the International Classification of Diseases, Tenth Revision (ICD-10) and Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition (DSM-IV) in high-risk individuals.DesignProspective cohort study.SettingAcademic geriatric hospital.ParticipantsOne hundred two individuals aged 80 to 100 hospitalized for acute medical illness.MeasurementsComplete CAM instrument (nine items), scored using the four-item CAM diagnostic algorithm. Criterion standard classification of delirium was rated independently according to expert consensus based on DSM-IV and ICD-10 criteria for delirium.ResultsIn 79 hospitalized participants, the CAM performed well for delirium screening (delirium prevalence of 24% according to DSM-IV and 14% according to ICD-10). Of all CAM features, acute onset and fluctuating course are most important for diagnosis (area under the receiver operating characteristic curve (AUC) = 0.92 in DSM-IV and 0.83 in ICD-10). The CAM diagnostic algorithm had a sensitivity of 0.74, a specificity of 1.0, and an AUC of 0.88 compared with the DSM-IV reference standard and a sensitivity of 0.82, a specificity of 0.91, and an AUC of 0.85 compared with the ICD-10. Compared with the ICD-10, adding psychomotor change to the CAM algorithm improved specificity to 97%, but sensitivity fell to 55% (AUC = 0.96). Applying psychomotor change sequentially only to the group that the CAM algorithm identified as having no delirium improved sensitivity to 91% with specificity of 85% (AUC = 0.95).ConclusionAlthough the CAM diagnostic algorithm performed well against a DSM-IV reference standard, adding psychomotor change to the CAM algorithm improved specificity and diagnostic value against ICD-10 criteria overall in older adults with dementia and improved sensitivity and screening performance when applied sequentially in CAM-negative individuals.

Project description:ImportanceSystematic reviews of medical imaging diagnostic test accuracy (DTA) studies are affected by between-study heterogeneity due to a range of factors. Failure to appropriately assess the extent and causes of heterogeneity compromises the interpretability of systematic review findings.ObjectiveTo assess how heterogeneity has been examined in medical imaging DTA studies.Evidence reviewThe PubMed database was searched for systematic reviews of medical imaging DTA studies that performed a meta-analysis. The search was limited to the 40 journals with highest impact factor in the radiology, nuclear medicine, and medical imaging category in the InCites Journal Citation Reports of 2021 to reach a sample size of 200 to 300 included studies. Descriptive analysis was performed to characterize the imaging modality, target condition, type of meta-analysis model used, strategies for evaluating heterogeneity, and sources of heterogeneity identified. Multivariable logistic regression was performed to assess whether any factors were associated with at least 1 source of heterogeneity being identified in the included meta-analyses. Methodological quality evaluation was not performed. Data analysis occurred from October to December 2022.FindingsA total of 242 meta-analyses involving a median (range) of 987 (119-441 510) patients across a diverse range of disease categories and imaging modalities were included. The extent of heterogeneity was adequately described (ie, whether it was absent, low, moderate, or high) in 220 studies (91%) and was most commonly assessed using the I2 statistic (185 studies [76%]) and forest plots (181 studies [75%]). Heterogeneity was rated as moderate to high in 191 studies (79%). Of all included meta-analyses, 122 (50%) performed subgroup analysis and 87 (36%) performed meta-regression. Of the 242 studies assessed, 189 (78%) included 10 or more primary studies. Of these 189 studies, 60 (32%) did not perform meta-regression or subgroup analysis. Reasons for being unable to investigate sources of heterogeneity included inadequate reporting of primary study characteristics and a low number of included primary studies. Use of meta-regression was associated with identification of at least 1 source of variability (odds ratio, 1.90; 95% CI, 1.11-3.23; P = .02).Conclusions and relevanceIn this systematic review of assessment of heterogeneity in medical imaging DTA meta-analyses, most meta-analyses were impacted by a moderate to high level of heterogeneity, presenting interpretive challenges. These findings suggest that, despite the development and availability of more rigorous statistical models, heterogeneity appeared to be incomplete, inconsistently evaluated, or methodologically questionable in many cases, which lessened the interpretability of the analyses performed; comprehensive heterogeneity assessment should be addressed at the author level by improving personal familiarity with appropriate statistical methodology for assessing heterogeneity and involving biostatisticians and epidemiologists in study design, as well as at the editorial level, by mandating adherence to methodologic standards in primary DTA studies and DTA meta-analyses.

Project description:ObjectivesDelirium is a common and frequently underdiagnosed complication in acutely hospitalized patients, and its severity is associated with worse clinical outcomes. We propose a physiologically based method to quantify delirium severity as a tool that can help close this diagnostic gap: the Electroencephalographic Confusion Assessment Method Severity Score (E-CAM-S).DesignRetrospective cohort study.SettingSingle-center tertiary academic medical center.PatientsThree-hundred seventy-three adult patients undergoing electroencephalography to evaluate altered mental status between August 2015 and December 2019.InterventionsNone.Measurements and main resultsWe developed the E-CAM-S based on a learning-to-rank machine learning model of forehead electroencephalography signals. Clinical delirium severity was assessed using the Confusion Assessment Method Severity (CAM-S). We compared associations of E-CAM-S and CAM-S with hospital length of stay and inhospital mortality. E-CAM-S correlated with clinical CAM-S (R = 0.67; p < 0.0001). For the overall cohort, E-CAM-S and CAM-S were similar in their strength of association with hospital length of stay (correlation = 0.31 vs 0.41, respectively; p = 0.082) and inhospital mortality (area under the curve = 0.77 vs 0.81; p = 0.310). Even when restricted to noncomatose patients, E-CAM-S remained statistically similar to CAM-S in its association with length of stay (correlation = 0.37 vs 0.42, respectively; p = 0.188) and inhospital mortality (area under the curve = 0.83 vs 0.74; p = 0.112). In addition to previously appreciated spectral features, the machine learning framework identified variability in multiple measures over time as important features in electroencephalography-based prediction of delirium severity.ConclusionsThe E-CAM-S is an automated, physiologic measure of delirium severity that predicts clinical outcomes with a level of performance comparable to conventional interview-based clinical assessment.

Project description:OBJECTIVES:Delirium severity is independently associated with longer hospital stays, nursing home placement, and death in patients outside the ICU. Delirium severity in the ICU is not routinely measured because the available instruments are difficult to complete in critically ill patients. We designed our study to assess the reliability and validity of a new ICU delirium severity tool, the Confusion Assessment Method for the ICU-7 delirium severity scale. DESIGN:Observational cohort study. SETTING:Medical, surgical, and progressive ICUs of three academic hospitals. PATIENTS:Five hundred eighteen adult (? 18 yr) patients. INTERVENTIONS:None. MEASUREMENTS AND MAIN RESULTS:Patients received the Confusion Assessment Method for the ICU, Richmond Agitation-Sedation Scale, and Delirium Rating Scale-Revised-98 assessments. A 7-point scale (0-7) was derived from responses to the Confusion Assessment Method for the ICU and Richmond Agitation-Sedation Scale items. Confusion Assessment Method for the ICU-7 showed high internal consistency (Cronbach's ? = 0.85) and good correlation with Delirium Rating Scale-Revised-98 scores (correlation coefficient = 0.64). Known-groups validity was supported by the separation of mechanically ventilated and nonventilated assessments. Median Confusion Assessment Method for the ICU-7 scores demonstrated good predictive validity with higher odds (odds ratio = 1.47; 95% CI = 1.30-1.66) of in-hospital mortality and lower odds (odds ratio = 0.8; 95% CI = 0.72-0.9) of being discharged home after adjusting for age, race, gender, severity of illness, and chronic comorbidities. Higher Confusion Assessment Method for the ICU-7 scores were also associated with increased length of ICU stay (p = 0.001). CONCLUSIONS:Our results suggest that Confusion Assessment Method for the ICU-7 is a valid and reliable delirium severity measure among ICU patients. Further research comparing it to other delirium severity measures, its use in delirium efficacy trials, and real-life implementation is needed to determine its role in research and clinical practice.

Dataset Information

Delirium detection in older acute medical inpatients: a multicentre prospective comparative diagnostic test accuracy study of the 4AT and the confusion assessment method.

Background

Methods

Results

Conclusions

Trial registration

Publications

Delirium detection in older acute medical inpatients: a multicentre prospective comparative diagnostic test accuracy study of the 4AT and the confusion assessment method.

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