Correlation between lipoprotein-associated phospholipase A2 and poststroke mild cognitive impairment
Bibliographic record
Abstract
OBJECTIVES: This study aimed to investigate the correlation between serum lipoprotein-associated phospholipase A2 (Lp-PLA2) and poststroke mild cognitive impairment (PSMCI). METHODS: The patients included in the study were divided into PSMCI (68 cases) and cognitively normal (CN) (218 cases) groups and followed up for six months. Demographic and clinical data were collected. A logistic regression analysis was performed to determine whether Lp-PLA2 is an independent risk factor for PSMCI. Spearman's correlation analysis was used to examine the correlation between Lp-PLA2 levels and Montreal Cognitive Assessment (MoCA) scores. A receiver operating characteristic (ROC) curve analysis was performed to determine the diagnostic threshold value of Lp-PLA2 for PSMCI. RESULTS: Serum Lp-PLA2 levels were significantly higher in the PSMCI group than in the CN group. The logistic regression analysis showed that Lp-PLA2 was an independent risk factor for PSMCI (OR = 1.05, 95% CI = 1.03-1.07). Spearman's correlation analysis revealed a significant correlation between the Lp-PLA2 levels and MoCA scores (R = -0.49). The area under the ROC curve for Lp-PLA2 was 0.849, and the threshold value for PSMCI occurrence was 236.8 ng/ml. CONCLUSIONS: Elevated serum Lp-PLA2 is an independent risk factor for PSMCI and may serve as a potential biomarker for PSMCI.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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) | 0.000 | 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".