P3‐163: Anesthesia and Alzheimer's disease neuropathogenic pathways
Bibliographic record
Abstract
Cognitive disorders such as post-operative cognitive dysfunction (POCD), confusion, and delirium, are common following anesthesia in the elderly. Despite advances in perioperative care, POCD remains a major concern in Alzheimer's disease (AD) patients. Interestingly, it has been suggested that the pathological mechanism(s) underlying POCD mimic AD. Indeed, anesthesia might be a risk factor for the development of neurodegenerative disorders such as Alzheimer's and Parkinson's disease. Patients with AD are considered to be particularly at risk for some of the cognitive side effects of anesthesia, and there is also concern that general anesthesia is a risk factor for AD, with in vitro and in vivo studies suggesting that anesthetics may promote and intensify the neuropathogenesis of AD. After a short review of the clinical literature on anesthesia and AD, we will focus on describing the impact of anesthesia on the two pathological hallmarks of AD: beta-amyloid (Abeta) accumulation and aberrant tau phosphorylation and aggregation, with an emphasis on our most recent data. Evidence from in vitro and animal models demonstrate that exposure to inhaled anesthetics, such as isoflurane and halothane, can increase Abeta production, enhance Abeta oligomerization, and promote plaque formation, while exposure to intravenous anesthetics, such as propofol, thiopental or chloral hydrate, has no effect. We have also demonstrated that exposure to isoflurane could lead to tau hyperphosphorylation, detachment from microtubules and enhanced aggregation in vivo, albeit indirectly, by inducing hypothermia in mouse models of tauopathies. On the other hand, some anesthetics such as propofol also have a direct effect on tau phosphorylation, as demonstrated by maintaining the animals normothermic. While there has been clinical interest on the relation between anesthesia and AD for at least a quarter of a century, the biochemical consequences of anesthesia on AD neuropathogenic pathways have only begun to be studied very recently. Overall, epidemiological evidence establishing a link between anesthetic exposure and the risk of AD remains controversial. On the other hand, clinical studies examining AD biomarkers, and studies exploring the impact of anesthetics on Abeta and tau, converge to indicate that anesthetics could affect AD pathogenesis, either directly or indirectly.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".