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. 2023 Nov 21;11(11):CD013126.
doi: 10.1002/14651858.CD013126.pub2.

Confusion Assessment Method for the Intensive Care Unit (CAM-ICU) for the diagnosis of delirium in adults in critical care settings

Fabian Miranda  1 , Francisco Gonzalez  1 , Maria Nieves Plana  2 , Javier Zamora  3   4 , Terry J Quinn  5 , Pamela Seron  6
Affiliations

Confusion Assessment Method for the Intensive Care Unit (CAM-ICU) for the diagnosis of delirium in adults in critical care settings

Fabian Miranda et al. Cochrane Database Syst Rev. .

Abstract

Background: Delirium is an underdiagnosed clinical syndrome typified by an acute alteration of mental state. It is an important problem in critical care and intensive care units (ICU) due to its high prevalence and its association with adverse outcomes. Delirium is a very distressing condition for patients, with a huge impact on their well-being. Diagnosis of delirium in the critical care setting is challenging. This is especially true for patients who are mechanically ventilated and are therefore unable to engage in a verbal interview. The Confusion Assessment Method for the Intensive Care Unit (CAM-ICU) is a tool specifically designed to assess for delirium in the context of ICU patients, including those on mechanical ventilation. CAM-ICU can be administered by non-specialists to give a dichotomous delirium present/absent result.

Objectives: To determine the diagnostic accuracy of the CAM-ICU for the diagnosis of delirium in adult patients in critical care units.

Search methods: We searched MEDLINE (Ovid SP, 1946 to 8 July 2022), Embase (Ovid SP, 1982 to 8 July 2022), Web of Science Core Collection (ISI Web of Knowledge, 1945 to 8 July 2022), PsycINFO (Ovid SP, 1806 to 8 July 2022), and LILACS (BIREME, 1982 to 8 July 2022). We checked the reference lists of included studies and other resources for additional potentially relevant studies. We also searched the Health Technology Assessment database, the Cochrane Library, Aggressive Research Intelligence Facility database, WHO ICTRP, ClinicalTrials.gov, and websites of scientific associations to access any annual meetings and abstracts of conference proceedings in the field.

Selection criteria: We included diagnostic studies enrolling adult ICU patients assessed using the CAM-ICU tool, regardless of language or publication status and reporting sufficient data on delirium diagnosis for the construction of 2 x 2 tables. Eligible studies evaluated the diagnostic performance of the CAM-ICU versus a clinical reference standard based on any iteration of the Diagnostic and Statistical Manual of Mental Disorders (DSM) criteria applied by a clinical expert.

Data collection and analysis: Two review authors independently selected and collated study data. We assessed the methodological quality of studies using the QUADAS-2 tool. We used two univariate fixed-effect or random-effects models to determine summary estimates of sensitivity and specificity. We performed sensitivity analyses that excluded studies considered to be at high risk of bias and high concerns in applicability, due mainly to the target population included (e.g. patients with traumatic brain injury). We also investigated potential sources of heterogeneity, assessing the effect of reference standard diagnosis and proportion of patients ventilated.

Main results: We included 25 studies (2817 participants). The mean age of participants ranged from 48 to 69 years; 15 of the studies included critical care units admitting mixed populations (e.g. medical, trauma, surgery patients). The percentage of patients receiving mechanical ventilation ranged from 11.8% to 100%. The prevalence of delirium in the studies included ranged from 12.5% to 83.9%. Presence of delirium was determined by the application of DSM-IV criteria in 13 out of 25 included studies. We assessed 13 studies as at low risk of bias and low applicability concerns for all QUADAS-2 domains. The most common issue of concern was flow and timing of the tests, followed by patient selection. Overall, we estimated a pooled sensitivity of 0.78 (95% confidence interval (CI) 0.72 to 0.83) and a pooled specificity of 0.95 (95% CI 0.92 to 0.97). Sensitivity analysis restricted to studies at low risk of bias and without any applicability concerns (n = 13 studies) gave similar summary accuracy indices (sensitivity 0.80 (95% CI 0.72 to 0.86), specificity 0.95 (95% CI 0.93 to 0.97)). Subgroup analyses based on diagnostic assessment found summary estimates of sensitivity and specificity for studies using DSM-IV of 0.79 (95% CI 0.72 to 0.85) and 0.94 (95% CI 0.90 to 0.96). For studies that used DSM-5 criteria, summary estimates of sensitivity and specificity were 0.75 (95% CI 0.67 to 0.82) and 0.98 (95% CI 0.95 to 0.99). DSM criteria had no significant effect on sensitivity (P = 0.421), but the specificity for detection of delirium was higher when DSM-5 criteria were used (P = 0.024). The relative specificity comparing DSM-5 versus DSM-IV criteria was 1.05 (95% CI 1.02 to 1.08). Summary estimates of sensitivity and specificity for studies recruiting < 100% of patients with mechanical ventilation were 0.81 (95% CI 0.75 to 0.85) and 0.95 (95% CI 0.91 to 0.98). For studies that exclusively recruited patients with mechanical ventilation, summary estimates of sensitivity and specificity were 0.91 (95% CI 0.76 to 0.97) and 0.98 (95% CI 0.92 to 0.99). Although there was a suggestion of differential performance of CAM-ICU in ventilated patients, the differences were not significant in sensitivity (P = 0.316) or in specificity (P = 0.493).

Authors' conclusions: The CAM-ICU tool may have a role in the early identification of delirium, in adult patients hospitalized in intensive care units, including those on mechanical ventilation, when non-specialized, properly trained clinical personnel apply the CAM-ICU. The test is most useful for exclusion of delirium. The test may miss a proportion of patients with incident delirium, therefore in situations where detection of all delirium cases is desirable, it may be best to repeat the test or combine CAM-ICU with another assessment. Future studies should compare different screening tests proposed for bedside assessment of delirium, as this approach will reveal which tool yields superior accuracy. In addition, future studies should consider and report the flow and timing of the tests and clearly report key characteristics related to patient selection. Finally, future research should focus on the impact of CAM-ICU screening on patient outcomes.

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Conflict of interest statement

Fabián Miranda has no conflicts of interest to declare.

Francisco González has no conflicts of interest to declare.

Maria N Plana has no conflicts of interest to declare.

Javier Zamora has no conflicts of interest to declare.

Terry Quinn has no conflicts of interest to declare.

Pamela Seron has no conflicts of interest to declare.

Figures

1
1
Confusion Assessment Method for the Intensive Care Unit (CAM‐ICU) Flowsheet (Ely 2016).
2
2
Study flow diagram.
3
3
Risk of bias and applicability concerns graph: review authors' judgments about each domain presented as percentages across included studies.
4
4
Risk of bias and applicability concerns graph.
5
5
Forest plot of CAM‐ICU primary analysis.
6
6
Summary ROC plot of CAM‐ICU for diagnosis of delirium.
1
1. Test
CAM‐ICU‐primary analysis
See this image and copyright information in PMC

Update of

References

References to studies included in this review

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