Urinary AD7c-NTP is Associated With Cognitive Recovery After Ischemic Stroke
Bibliographic record
Abstract
Urinary Alzheimer-associated neuronal thread protein (AD7c-NTP) is regarded as a biomarker for β-amyloid protein deposition in Alzheimer disease (AD). The value of AD7c-NTP in predicting post-stroke cognitive recovery was worth exploring. In total, 224 patients with first-ever stroke were enrolled in this retrospective study. Cognitive assessment was evaluated by Mini-Mental State Examination (MMSE), and cognitive improvement was defined as MMSE scores ≥27 or 4-score elevation at 3-month follow-up after stroke. The AD7c-NTP level was 0.68±0.40 ng/mL in the 135 patients with cognitive improvement, while the AD7c-NTP level was 1.49±0.99 ng/mL in the 89 patients without improvement ( P <0.001). Those displaying better cognitive recovery also had younger ages, higher MMSE scores, and lower NIHSS scores on admission. In multivariable logistic regression analysis, AD7c-NTP concentration (OR=9.14, 95% CI: 4.52-18.49, P <0.001), age (OR=1.04, 95% CI: 1.01-1.08, P =0.012), and NIHSS score on admission (OR=1.17, 95% CI: 1.07-1.28, P <0.001) remained the independent risk factors affecting cognitive recovery. The area under the receiver operating characteristics curve for AD7c-NTP in predicting unfavorable cognitive function was 0.80 (sensitivity: 0.73 and specificity: 0.84). Urinary AD7c-NTP is a valuable biomarker associated with post-stroke cognitive recovery. It might be adopted to discriminate coexisting AD pathology from vascular cognitive impairment.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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".