Evidence map›Paper›PMID 35436316›Full record

ArticlePloS one2022

Delirium diagnosis without a gold standard: Evaluating diagnostic accuracy of combined delirium assessment tools.

Stephana J Moss, Chel Hee Lee, Christopher J Doig, Liam Whalen-Browne, Henry T Stelfox, Kirsten M Fiest

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed, 1 pooled it
2.9field-weighted citation impact, top 8% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

13 citing papers in PubMed, 1 synthesis or guideline pooled it, 22 citations in OpenAlex.

  1. Pooled it
  2. Diagnose Pediatric Delirium Preferentially by Psychiatric Examination, as CAPD Has Low Specificity.Indian journal of critical care medicine : peer-reviewed, official publication of Indian Society of Critical Care Medicine · 2025
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  9. Identifying Symptoms of Delirium from Clinical Narratives Using Natural Language Processing.Proceedings. IEEE International Conference on Healthcare Informatics · 2024
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors at 1 institution in 1 country.

Stephana J MossDepartment of Community Health Sciences, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada.ORCID 0000-0002-1157-884X
Chel Hee LeeDepartment of Critical Care Medicine, University of Calgary and Alberta Health Services, Calgary, Alberta, Canada.ORCID 0000-0001-8209-8176
Christopher J DoigDepartment of Community Health Sciences, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada.ORCID 0000-0002-8576-9139
Liam Whalen-BrowneDepartment of Critical Care Medicine, University of Calgary and Alberta Health Services, Calgary, Alberta, Canada.ORCID 0000-0002-1335-9413
Henry T StelfoxDepartment of Community Health Sciences, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada.
Kirsten M FiestDepartment of Community Health Sciences, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada.
Alberta Health Services · CA

Funding

CIHR
6 · The paper itself

Abstract

backgroundFluctuating course of delirium and complexities of ICU care mean delirium symptoms are hard to identify or commonly confused with other disorders. Delirium is difficult to diagnose, and clinicians and researchers may combine assessments from multiple tools. We evaluated diagnostic accuracy of different combinations of delirium assessments performed in each enrolled patient.

methodsData were obtained from a previously conducted cross-sectional study. Eligible adult patients who remained admitted to ICU for >24 hours with at least one family member present were consecutively enrolled as patient-family dyads. Clinical delirium assessments (Intensive Care Delirium Screening Checklist [ICSDC] and Confusion Assessment Method-ICU [CAM-ICU]) were completed twice daily by bedside nurse or trained research assistant, respectively. Family delirium assessments (Family Confusion Assessment Method and Sour Seven) were completed once daily by family members. We pooled all delirium assessment tools in a single two-class latent model and pairwise (i.e., combined, clinical or family assessments) Bayesian analyses.

resultsSeventy-three patient-family dyads were included. Among clinical delirium assessments, the ICDSC had lower sensitivity (0.72; 95% Bayesian Credible [BC] interval 0.54-0.92) and higher specificity (0.90; 95%BC, 0.82-0.97) using Bayesian analyses compared to pooled latent class analysis and CAM-ICU had higher sensitivity (0.90; 95%BC, 0.70-1.00) and higher specificity (0.94; 95%BC, 0.80-1.00). Among family delirium assessments, the Family Confusion Assessment Method had higher sensitivity (0.83; 95%BC, 0.71-0.92) and higher specificity (0.93; 95%BC, 0.84-0.98) using Bayesian analyses compared to pooled latent class analysis and the Sour Seven had higher specificity (0.85; 95%BC, 0.67-0.99) but lower sensitivity (0.64; 95%BC 0.47-0.82).

conclusionsResults from delirium assessment tools are often combined owing to imperfect reference standards for delirium measurement. Pairwise Bayesian analyses that explicitly accounted for each tool's (performed within same patient) prior sensitivity and specificity indicate that two combined clinical or two combined family delirium assessment tools have fair diagnostic accuracy.

Indexed as

DeliriumAdultBayes TheoremCritical CareCross-Sectional StudiesHumansIntensive Care UnitsReproducibility of ResultsSensitivity and Specificity

Identifiers

PMID35436316
PMCPMC9015135
OpenAlexW4224236060

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.