Association of Diabetes with Greater Mid-Term Cognitive Decline After Carotid Surgery
Bibliographic record
Abstract
Background/Objectives: Long-term cognitive outcomes after carotid surgery are influenced by diabetes and intraoperative changes. We aimed to analyze the postoperative cognitive changes in diabetic patients and nondiabetic patients after carotid endarterectomy (CEA). Additionally, major cardiovascular and cerebrovascular events (MACCEs) and the incidence of mortality at two years after surgery were assessed. Methods: We enrolled 37 diabetic and 67 nondiabetic patients undergoing elective carotid surgery. Intraoperatively, routine monitoring was completed with NIRS (near-infrared spectroscopy) and an Entropy monitor was used for neuromonitoring. The lowest cerebral tissue saturation levels during the cross-clamp period (rSO2lowestclamp) and the degree of desaturation were calculated. We used MMSE (Mini-Mental State Examination) and MoCA (Montreal Cognitive Assessment) to assess cognitive function. Cognitive change was defined as one standard deviation (SD) change from the preoperative test scores. Results: The MMSE and MoCA were available for 103 patients at three months and for 90 patients at 12 months after discharge. Compared with nondiabetic patients, diabetic patients exhibited greater decreases in MoCA scores (p = 0.028 and p = 0.042 at the 3rd and 12th months, respectively). Cognitive improvement was lower in the DM group than in the control group at the 12th month (18.75% vs. 42.86%, respectively; p = 0.029). The mean rSO2 in the pre-clamping period (67.4% vs. 74.6% in diabetic and in nondiabetic patients, respectively; p = 0.011) was lower in diabetic patients. Furthermore, MACCEs at the 24th month were observed at a higher rate in diabetic patients (p = 0.040). Conclusions: Diabetic patients demonstrated greater risks for cognitive decline, MACCEs, and mortality at two years after surgery.
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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 | 0.000 | 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 | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".