Screening instruments for cognitive impairment in older patients in the Emergency Department: a systematic review and meta-analysis
Bibliographic record
Abstract
BACKGROUND: cognitive impairment is highly prevalent among older patients attending the Emergency Department (ED) and is associated with adverse outcomes. METHODS: we conducted a systematic review and meta-analysis to evaluate the diagnostic accuracy of cognitive screening instruments to rule out cognitive impairment in older patients in the ED. A comprehensive literature search was performed in MEDLINE, EMBASE, CINAHL and CENTRAL. A risk of bias assessment using QUADAS-2 was performed. RESULTS: 23 articles, examining 18 different index tests were included. Only seven index tests could be included in the meta-analysis. For ruling out cognitive impairment irrespective of aetiology, Ottawa 3 Day Year (O3DY) (pooled sensitivity 0.90; (95% CI) 0.71-0.97) had the highest sensitivity. Fourteen articles focused on screening for cognitive impairment specifically caused by delirium. For ruling out delirium, the 4 A's Test (4AT) showed highest sensitivity (pooled sensitivity 0.87, 95% confidence interval (95% CI) 0.74-0.94). CONCLUSIONS: high clinical and methodological heterogeneity was found between included studies. Therefore, it is a challenge to recommend one diagnostic test for use as a screening instrument for cognitive impairment in the ED. The 4AT and O3DY seem most promising for ruling out cognitive impairment in older patients attending the ED.The review protocol was registered in PROSPERO (CRD42018082509).
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.019 | 0.049 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.020 | 0.034 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".