The Relationship between Glycosylated Hemoglobin and Cognitive Dysfunction after Acute Ischemic Stroke
Bibliographic record
Abstract
Background: Stroke takes the second place among worldwide causes of morbidity and mortality. Significant attention was paid to the relationship between Glycosylated hemoglobin (HbA1c) and cognitive functions in patients with acute ischemic stroke (AIS). This study aims at assessing the relationship between post stroke cognitive impairment (PSCI) and HbA1c levels as well as other factors that may predict cognitive decline in those patients. Patients and Methods: 110 patients with a diagnosis of AIS were included in this study. Cognitive functions were evaluated after 3 months of the onset using the Montreal Cognitive Assessment scale (MoCA). Demographic, clinical features, laboratory parameters including HbA1C level as well as imaging findings were analyzed and relationship with PSCI were determined. Results: PSCI was significantly related to Type 2 diabetes mellitus (P < 0.001) and to Sphincter dysfunction (P 0.04). Elevated HbA1c level and lower levels of high density lipoprotein (HDL) were significant in the group of PSCI (P value <0.001 and 0.021 respectively), as well as increased carotid intima media thickness (CIMT) on Carotid Doppler examination (P value 0.013). The increase of CIMT and higher levels of HbA1c were independent risk factors for cognitive dysfunction in acute ischemic stroke patients, with odds ratio of 0.002 (0, 0.145), 2.088 (1.601, 2.723) respectively, (95% confidence interval). Conclusion: The occurrence of PSCI was independently related to higher Glycosylated hemoglobin levels and increased CIMT. Careful evaluation of these factors help clinician to intervene early and develop better treatment modalities.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".