Delirium and frailty in older adults: Clinical overlap and biological underpinnings
Bibliographic record
Abstract
Frailty and delirium are two common geriatric syndromes sharing several clinical characteristics, risk factors, and negative outcomes. Understanding their interdependency is crucial to identify shared mechanisms and implement initiatives to reduce the associated burden. This literature review summarizes scientific evidence on the complex interplay between frailty and delirium; clinical, epidemiological, and pathophysiological commonalities; and current knowledge gaps. We conducted a PubMed systematic search in June 2023, which yielded 118 eligible articles out of 991. The synthesis of the results-carried out by content experts-highlights overlapping risk factors, clinical phenotypes, and outcomes and explores the influence of one syndrome on the onset of the other. Common pathophysiological mechanisms identified include inflammation, neurodegeneration, metabolic insufficiency, and vascular burden. The review suggests that frailty is a risk factor for delirium, with some support for delirium associated with accelerated frailty. The proposed unifying framework supports the integration and measurement of both constructs in research and clinical practice, identifying the geroscience approach as a potential avenue to develop strategies for both conditions. In conclusion, we suggest that frailty and delirium might be alternative-sometimes coexisting-manifestations of accelerated biological aging. Clinically, the concepts addressed in this review can help approach older adults with either frailty or delirium from a different perspective. From a research standpoint, longitudinal studies are needed to explore the hypothesis that specific pathways within the biology of aging may underlie the clinical manifestations of frailty and delirium. Such research will pave the way for future understanding of other geriatric syndromes as well.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.004 |
| 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".