Plasma sDPP4 (Soluble Dipeptidyl Peptidase-4) and Cognitive Impairment After Noncardioembolic Acute Ischemic Stroke
Bibliographic record
Abstract
Background: DPP4 (dipeptidyl peptidase-4) inhibitors have been proven to promote neuronal regeneration, reverse the development of cognitive deficits. However, the association of circulating soluble form (sDPP4 [soluble DPP4]) with poststroke cognitive impairment (PSCI) is unclear. We aimed to investigate the association between plasma sDPP4 levels and PSCI in patients with ischemic stroke. Methods: A total of 600 noncardioembolic stroke patients were included based on a preplanned ancillary study from the CATIS (China Antihypertensive Trial in Acute Ischemic Stroke). We used the Montreal Cognitive Assessment to evaluate cognitive function at 3 months follow-up after ischemic stroke. Binary logistic regression analyses were performed to investigate the association of plasma sDPP4 levels with subsequent PSCI. We further calculated integrated discrimination improvement and category-free net reclassification improvement to investigate the incremental prognostic effect of plasma sDPP4 beyond the basic model with conventional risk factors. Results: Plasma sDPP4 was inversely associated with PSCI after ischemic stroke, and the adjusted odds ratio (95% CI) for the highest versus lowest quartile of sDPP4 was 0.49 (0.29–0.81; P for trend=0.011). Each 1-SD increase of logarithm-transformed plasma sDPP4 concentration was associated with 17% (odds ratio, 0.83 [95% CI, 0.70–0.99]) lower risk of PSCI. Adding plasma sDPP4 to the basic model notably improved risk reclassification for PSCI, as shown by a category-free net reclassification improvement of 19.10% (95% CI, 2.52%–35.68%; P =0.03) and integrated discrimination improvement of 0.79% (95% CI, 0.13%–1.46%; P =0.02). Conclusions: Higher plasma sDPP4 levels were associated with decreased risk of cognitive impairment after noncardioembolic ischemic stroke.
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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) | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".