The consistent burden in published estimates of delirium occurrence in medical inpatients over four decades: a systematic review and meta-analysis study
Bibliographic record
Abstract
Abstract Introduction Delirium is associated with a wide range of adverse patient safety outcomes. We sought to identify if trends in healthcare complexity were associated with changes in reported delirium in adult medical patients in the general hospital over the last four decades. Methods We used identical criteria to a previous systematic review, including studies using DSM and ICD-10 criteria for delirium diagnosis. Random effects meta-analysis pooled estimates across studies, meta-regression estimated temporal changes, funnel plots assessed publication bias. Results Overall delirium occurrence was 23% (95% CI 19%-26%) (33 studies). There was no change between 1980-2019, nor was case-mix (average age of sample, proportion with dementia) different. There was evidence of increasing publication bias over time. Discussion The incidence and prevalence of delirium in hospitals appears to be stable, though publication bias may mask true changes. Nonetheless, delirium remains a challenging and urgent priority for clinical diagnosis and care pathways.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.093 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.011 | 0.002 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".