High preoperative blood oxaloacetate and 2-aminoadipic acid levels are associated with postoperative delayed neurocognitive recovery
Bibliographic record
Abstract
Introduction This study aimed to identify preoperative blood biomarkers related to development of delayed neurocognitive recovery (dNCR) following surgery. Methods A total of 67 patients (≥65 years old) who underwent head and neck tumor resection under general anesthesia were assessed using the Mini-Mental State Examination (MMSE) and Montreal Cognitive Assessment (MoCA). Preoperative serum metabolomics were determined using widely targeted metabolomics technology. Results Of the 67 patients, 25 developed dNCR and were matched to 25 randomly selected patients from the remaining 42 without dNCR. Differential metabolites were selected using the criteria of variable importance in projection > 1.0 in orthogonal partial least squares discrimination analysis, false discovery rate <0.05, and fold-change >1.2 or <0.83 to minimize false positives. Preoperative serum levels of oxaloacetate (OR: 1.054, 95% CI: 1.027–1.095, P = 0.001) and 2-aminoadipic acid (2-AAA) (OR: 1.181, 95% CI: 1.087–1.334, P = 0.001) were associated with postoperative dNCR after adjusting for anesthesia duration, education, and age. Areas under the curve for oxaloacetate and 2-AAA were 0.86 (sensitivity: 0.84, specificity: 0.88) and 0.86 (sensitivity: 0.84, specificity: 0.84), respectively. High levels of preoperative oxaloacetate and 2-AAA also were associated with postoperative decreased MoCA (β: 0.022, 95% CI: 0.005–0.04, P = 0.013 for oxaloacetate; β: 0.077, 95%CI: 0.016–0.137, P = 0.014 for 2-AAA) and MMSE (β: 0.024, 95% CI: 0.009–0.039, P = 0.002 for oxaloacetate; β: 0.083, 95% CI: 0.032–0.135, P = 0.002 for 2-AAA) scores after adjusting for age, education level, and operation time. Conclusion High preoperative blood levels of oxaloacetate and 2-AAA were associated with increased risk of postoperative dNCR. Clinical trial registration https://classic.clinicaltrials.gov/ct2/show/NCT05105451 , identifier NCT05105451.
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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 | 0.001 |
| 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 | 0.000 | 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".