Serum lipoprotein phospholipase A2 level has diagnostic value for cognitive impairment in type II diabetes patients with white matter hyperintensity
Bibliographic record
Abstract
This prospective study investigated the relationship between the lipoprotein-associated phospholipase A2 (Lp-PLA2) level and cognitive impairment (CI) in type II diabetes mellitus (TIIDM) patients with white matter hyperintensity (WMH). A total of 87 TIIDM patients diagnosed with WMH were included in this study. They were grouped into CI group and noncognitive impairment (NCI) group based on the MoCA scales. The serum Lp⁃PLA2 levels and MoCA scores of the patients with WMH were compared with those of control (Ctl). Logistic regression was used to analyze the risk factors affecting CI and diagnostic value of serum Lp⁃PLA2 for CI. The WMH group had significantly higher serum level of Lp⁃PLA2 and significantly lower MoCA score than Ctl group. There were significant differences in serum levels of homocysteine, high-density lipoprotein cholesterol (HDL-C) and Lp⁃PLA2 (P < 0.05) between the groups. Logistic regression showed that HDL-C, homocysteine and Lp⁃PLA2 were the risk factors for CI in the patients (P < 0.05); receiver operating characteristic curve analysis showed that HDL-C and Lp⁃PLA2 had significant diagnostic value for CI in WMH patients. Therefore, Lp⁃PLA2 can be assessed in the elderly as a screening to identify putative CI patents for preventive treatment and management.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".