Delirium, Confusion, or Altered mental status as a risk for abnormal head computed tomogram findings in older adults in the emergency department: A systematic review and meta-analysis
Bibliographic record
Abstract
Abstract Background Delirium, confusion, and altered mental status are common presentations among older adults to the emergency department (ED). We aimed to report the association between delirium, confusion or altered mental status in older ED patients and acute abnormal findings on head computed tomogram (CT). Methods A systematic review was conducted using Ovid Medline, Embase, Clinicaltrials.gov , Web of Science, and Cochrane Central from conception to April 8th, 2021. We included citations if they described patients aged 65 years or older who received head imaging at the time of ED assessment, and reported whether or not patients had delirium, confusion, or altered mental status. Screening, data extraction, and bias assessment were performed in duplicate. We estimated the odds ratios (OR) for abnormal neuroimaging in patients with altered mental status. Results The search strategy identified 3,014 unique citations, of which two studies reporting on 909 patients with delirium, confusion or altered mental status were included. No study formally assessed for delirium. The OR for abnormal head CT findings in patients with delirium, confusion or altered mental status was 0.35 (95% CI 0.031 to 3.97) compared to patients without delirium, confusion or altered mental status. Conclusion We did not find a statistically significant association between delirium, confusion or altered mental status and abnormal CT findings in older ED patients.
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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 | 0.011 | 0.037 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.015 | 0.025 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 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".