Mild Cognitive Impairment with Associated Inflammatory and Cortisol Alterations as Independent Risk Factor for Postoperative Delirium
Bibliographic record
Abstract
AIMS: The present study aimed to determine the impact of mild cognitive impairment (MCI) on the development of postoperative delirium and, secondly, to assess the association between MCI and raised perioperative cortisol, cytokine, cobalamin and homocysteine levels. METHODS: The study recruited 113 consecutive adult patients scheduled for cardiac surgery with cardiopulmonary bypass. The patients were examined preoperatively with the Montreal Cognitive Assessment and Trail Making Test. A diagnosis of MCI was established based upon the criteria of the National Institute on Aging and Alzheimer's Association. Patients were screened for delirium within the first 5 days postoperatively. RESULTS: MCI was diagnosed in 24.8% of the patients, whereas the frequency of delirium was 36%. A multivariate analysis demonstrated that individuals with MCI were at a significantly higher risk of postoperative delirium (OR = 6.33, p = 0.002). Preoperative cortisol, postoperative cortisol and IL-2 plasma levels were higher in the MCI group as compared to non-MCI subjects. CONCLUSION: MCI is associated with a higher risk of postoperative delirium. Perioperative cortisol and inflammatory alterations observed in MCI may provide a physiological explanation for this increased risk.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".