Is Serum VEGF-A Level an Indicator of Early-Onset Poststroke Depression?
Bibliographic record
Abstract
Background and Objectives: Poststroke depression (PSD) is a psychiatric complication occurring after a stroke, and is known to negatively impact quality of life. In the present study, the possible relationship between serum vascular endothelial growth factor (VEGF-A) levels and early-onset PSD, as well as the predictive value of serum VEGF-A levels for early-onset PSD, were investigated. Materials and Methods: The study included 88 individuals diagnosed with acute ischemic stroke (AIS). Demographic data, clinical characteristics, and serum VEGF-A levels were recorded, and radiological images were examined to determine the lesion locations. The National Institutes of Health Stroke Scale (NIHSS), Montreal Cognitive Assessment (MoCA), and Hamilton depression scale (HAMD-17) were administered to the patients. Furthermore, serum VEGF-A levels were measured in all participants. Results: Although the body mass index (BMI) and VEGF-A levels were similar between the groups, MoCA scores were lower [(19.2 ± 4.4) vs. (22.3 ± 3), p = 0.001] and NIHSS scores were higher [18 (8–28) vs. 14 (3–24), p = 0.006] in individuals with PSD than in those without it. When the patients with PSD were categorized into three groups, patients with severe PSD had higher NIHSS scores [26 (23–27) vs. 15 (8–23), p = 0.006] and lower MoCA scores [(14.3 ± 1) vs. (20.9 ± 3.8), p = 0.005] than those with mild PSD. Moreover, VEGF-A levels and lesion localization were similar between mild, moderate, and severe PSD groups (p = 0.130). The MoCA score was negatively (r = −0.498, p < 0.001) correlated and the NIHSS score was positively correlated (r = 0.497, p < 0.001) with the HAMD-17 score. Conclusions: Our findings suggest that longitudinal studies in large cohorts including healthy control groups are needed to examine the possibility of using serum VEGF-A level as a marker for predicting early-onset PSD.
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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".