Risk factors and outcomes of delirium in hospitalized older adults with COVID-19: A systematic review and meta-analysis
Bibliographic record
Abstract
Older adults with COVID-19 are more likely to present with atypical symptoms, notably delirium. The main objective of this meta-analysis is to identify risk factors for delirium and outcomes of delirium in hospitalized older adults (65 years or above) with COVID-19. Comprehensive literature search of Embase, CINAHIL, Medline and Web of Science was performed for published literature until 31st August 2021. Two independent researchers evaluated study eligibility and assessed study quality using the Newcastle Ottawa Scale (NOS) for cohort studies and Joanna Briggs Institute (JBI) critical appraisal tools for case series. The association of various predisposing factors with delirium in this cohort was reported as odds ratio (OR) and its 95% confidence interval (CI). A total of 31 studies from 11 countries were included in this review. Most of the included studies investigated patients from non-ICU settings (n = 24; 77.4%). Frailty (OR 3.52, 95% CI: 1.96–6.31, p<0.0001, I2=71.63%), cognitive impairment including dementia (OR 6.17, 95% CI: 2.92–13.07, p<0.00001, I2=88.63%) and being nursing home residents (OR 1.72, 95% CI: 1.31–2.24, p<0.0001, I2=0) were significantly associated with increased likelihood of developing delirium in older adults with COVID-19. The presence of delirium also significantly increases mortality risk in hospitalized older adults with COVID-19 (OR 2.51, 95% CI: 1.51–4.17, p<0.0001, I2=89.3%). Our review identifies key factors associated with increased risk of developing delirium in hospitalized older adults with COVID-19. Identification of patients at risk of delirium and attention to these factors early during admission may improve outcomes for this vulnerable cohort.
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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 | 0.006 | 0.021 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.009 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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".