Head computed tomography findings in geriatric emergency department patients with delirium, altered mental status, and confusion: A systematic review
Bibliographic record
Abstract
BACKGROUND: Delirium, altered mental status (AMS), or confusion among older adults are common presentations to the emergency department (ED). We aimed to report the proportion of older ED patients presenting with delirium who have acute abnormal findings on head imaging. We also assessed whether anticoagulation, neurological deficits, trauma, or headache were associated with head imaging abnormalities in these patients. METHODS: A systematic review was performed using Ovid Medline, Embase, Clinicaltrials.gov, Web of Science, and Cochrane Central from conception to April 8, 2021. Citations were included if they described patients aged 65 years or older who received neuroimaging at the time of ED assessment for delirium, confusion, or AMS. Screening, data extraction, and bias assessment were performed in duplicate. The estimated proportion of patients with abnormal neuroimaging and odds ratios (ORs) for each predictor were calculated. RESULTS: The search strategy identified 3014 unique citations, of which six studies reporting on 909 patients with confusion or AMS were included. None of the studies formally diagnosed delirium. Overall, the proportions of older ED patients with AMS or confusion were found to have an abnormal head computed tomography (CT) was 15.6% (95% confidence interval [CI] 7.3%-26.2%). The prevalence of focal neurologic findings was 13.0% (66/506) and for anticoagulation was 9.8% (33/337) among the studies who reported them. The presence of a focal neurological deficit was associated with abnormal head CT (OR 101.8, 95% CI 30.5-340.1). Anticoagulation was not associated with abnormal head CT (OR 1.2, 95% CI 0.4-3.3). No studies reported on the association between headache or trauma and abnormal neuroimaging. CONCLUSIONS: The proportion of abnormal findings on CT neuroimaging in older ED patients with AMS or confusion was 15.6%. The presence of a focal neurological deficit was a strong predictor for the presence of acute abnormality, whereas anticoagulation was not.
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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 | 0.005 | 0.036 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.006 |
| Bibliometrics | 0.010 | 0.011 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| 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".