Potential associated factors of postoperative neurocognitive dysfunction in elderly patients: precursor of BDNF and mature BDNF in serum
Bibliographic record
Abstract
BACKGROUND: With the acceleration of population aging in China, the incidence of postoperative neurocognitive dysfunction (PND) will continue to rise. AIM: We aim to evaluate whether the precursor of brain-derived neurotrophic factor (proBDNF) and mature brain-derived neurotrophic factor (mBDNF) are associated with PND in elderly patients. METHODS: Eighty-six patients who were scheduled for elective orthopedic surgery under general anesthesia were ultimately enrolled. Referring to previous studies, the patients were divided into the PND group and the non-PND group with the Montreal Cognitive Assessment (MoCA) scale on postoperative day 7. The Spearman test was used to determine the correlations between mBDNF, proBDNF, and PND. RESULTS: All the participants possessed normal cognitive function before surgery. Compared with those in the nPND group, proBDNF, mBDNF, proBDNF*mBDNF, and MoCA score (all P < 0.001) were lower in the PND group after surgery. The Spearman test showed PND was correlated with postoperative proBDNF (correlation coefficient = -0.391; P = 0.001), mBDNF (correlation coefficient = -0.295; P = 0.006), proBDNF*mBDNF (correlation coefficient = -0.479; P < 0.001), and the ratios of proBDNF (correlation coefficient = -0.388; P < 0.001) and mBDNF (correlation coefficient, -0.375; P < 0.001) from before to after surgery. DISCUSSION: In this study, PND was significantly associated with postoperative proBDNF and mBDNF; the diagnostic value of postoperative mBDNF combined with proBDNF was superior to that of either index alone. CONCLUSIONS: The PND was significantly associated with postoperative proBDNF and mBDNF. TRIAL REGISTRATION: Chinese Clinical Trial Registry (ChiCTR1800017415, registered date: 07/29/2018), http://www.chictr.org.cn .
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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 | 0.001 | 0.007 |
| 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 | 0.001 |
| 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".