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Record W3035630663 · doi:10.1101/2020.06.11.20128280

Diagnostic accuracy of the 4AT for delirium detection: systematic review and meta-analysis

2020· preprint· en· W3035630663 on OpenAlexaff
Zoë Tieges, Alasdair M. J. MacLullich, Atul Anand, Claire Brookes, Marica Cassarino, Margaret O’Connor, Damien Ryan, Thomas Saller, Rakesh C. Arora, Yue Chang, Kathryn Agarwal, George E. Taffet, Terence J. Quinn, Susan D. Shenkin, Rose Galvin

Bibliographic record

VenuemedRxiv · 2020
Typepreprint
Languageen
FieldMedicine
TopicIntensive Care Unit Cognitive Disorders
Canadian institutionsUniversity of ManitobaSt. Boniface Hospital
FundersMedical Research CouncilWellcome Trust
KeywordsDeliriumMedicineMeta-analysisMEDLINECINAHLPsycINFODiagnostic odds ratioGold standard (test)Cochrane LibraryStroke (engine)Internal medicineEmergency medicineIntensive care medicinePsychiatryPsychological intervention

Abstract

fetched live from OpenAlex

ABSTRACT Objective Detection of delirium in hospitalised older adults is recommended in national and international guidelines. The 4 ‘A’s Test (4AT) is a short (<2 min) instrument for delirium detection that is used internationally as a standard tool in clinical practice. We performed a systematic review and meta-analysis of diagnostic test accuracy of the 4AT for delirium detection. Methods We searched MEDLINE, EMBASE, PsycINFO, CINAHL, clinicaltrials.gov and the Cochrane Central Register of Controlled Trials, from 2011 (year of 4AT release on the website www.the4AT.com ) until 21 December 2019. Inclusion criteria were: older adults (≥ 65y); diagnostic accuracy study of the 4AT index test when compared to delirium reference standard (standard diagnostic criteria or validated tool). Methodological quality was assessed using the Quality Assessment of Diagnostic Accuracy Studies-2 tool. Pooled estimates of sensitivity and specificity were generated from a bivariate random effects model. Results 17 studies (3702 observations) were included. Settings were acute medicine, surgery, a care home, and the emergency department. Three studies assessed performance of the 4AT in stroke. The overall prevalence of delirium was 24.2% (95% CI 17.8-32.1%; range 10.5-61.9%). The pooled sensitivity was 0.88 (95% CI 0.80-0.93) and the pooled specificity was 0.88 (95% CI 0.82-0.92). Excluding the stroke studies, the pooled sensitivity was 0.86 (95% CI 0.77-0.92) and the pooled specificity was 0.89 (95% CI 0.83-0.93). The methodological quality of studies varied but was moderate to good overall. Conclusions The 4AT shows good diagnostic test accuracy for delirium in the 17 available studies. These findings support its use in routine clinical practice in delirium detection. PROSPERO Registration number CRD42019133702. Key points The 4AT is a short delirium assessment tool that is widely used internationally in clinical practice. This systematic review and meta-analysis of diagnostic accuracy studies of the 4AT included 3702 observations in 17 studies from nine countries. Studies recruited from a range of settings including the Emergency Department, and medical, stroke, and surgical wards. The 4AT had a pooled sensitivity of 0.88 and pooled specificity of 0.88. The methodological quality of studies varied but was moderate to good overall.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.178
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.916
Threshold uncertainty score0.829

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.178
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0030.003
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.070
GPT teacher head0.330
Teacher spread0.260 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designMeta-analysis
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations14
Published2020
Admission routes1
Has abstractyes

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