Plasma Neurofilament Light Chain as a Predictive Biomarker for Post-stroke Cognitive Impairment: A Prospective Cohort Study
Bibliographic record
Abstract
Background Plasma neurofilaments light chain (pNfL) is a marker of axonal injury. The purpose of this study was to examine the role of pNfL as a predictive biomarker for post-stroke cognitive impairment (PSCI). Methods A prospective single-center observational cohort study was conducted at the General Hospital of Western Theater Command between July 1, 2017 and December 31, 2019. Consecutive patients ≥18 years with first-ever acute ischemic stroke (AIS) of anterior circulation within 24 h of symptom onset were included. PSCI was defined by the Montreal Cognitive Assessment (MOCA) (MOCA < 26) at 90 days after stroke onset. Results A total of 1,694 patients [male, 893 (52.70%); median age, 64 (16) years] were enrolled in the cohort analysis, and 1,029 (60.70%) were diagnosed with PSCI. Patients with PSCI had significantly higher pNfL [median (IQR), 55.96 (36.13) vs. 35.73 (17.57) pg/ml; P < 0.001] than Non-PSCI. pNfL was valuable for the prediction of PSCI (OR 1.044, 95% CI 1.038–1.049, P < 0.001) after a logistic regression analysis, even after adjusting for conventional risk factors including age, sex, education level, NIHSS, TOAST classification, and infarction volume (OR 1.041, 95% CI 1.034–1.047, P < 0.001). The optimal cutoff value of the pNfL concentration was 46.12 pg/ml, which yielded a sensitivity of 71.0% and a specificity of 81.5%, with the area under the curve (AUC) at 0.785 (95% CI 0.762–0.808, P < 0.001). Conclusion This prospective cohort study showed that the pNfL concentration within 48 h of onset was an independent risk factor for PSCI 90 days after an anterior circulation stroke, even after being adjusted for potential influencing factors regarded as clinically relevant. Clinical Trial Registration www.chictr.org.cn , identifier ChiCTR1800020330.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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".