Significance of serum follistatin-like 1 as a potential biomarker in relation to 3-month cognitive impairment after acute intracerebral hemorrhage: A prospective observational cohort study
Bibliographic record
Abstract
Follistatin-like 1 (FSTL1) participates in neuroinflammation. This study was conducted to investigate whether serum FSTL1 levels are associated with cognitive impairment following acute intracerebral hemorrhage (ICH). In this prospective cohort study of supratentorial ICH, 309 patients were randomly allocated to study group (206 cases) and validation group (103 cases) according to 2:1 ratio. Serum samples were obtained at admission of patients so as to measure FSTL1 levels. The Montreal Cognitive Assessment Scale was applied for assessing cognitive status at poststroke 3 months, with the score of <26 signifying cognitive impairment. An independent correlation was confirmed between serum FSTL1 levels and Montreal Cognitive Assessment Scale scores (β, -0.184; 95% confidence interval (CI), -0.314-0.054; variance inflation factor, 1.453; P = .006). Serum FSTL1 levels were substantially higher in patients with cognitive impairment than in the remainders (median, 9.8 vs 6.2 ng/mL; P < .001). Serum FSTL1 levels, in linear relation to cognitive impairment likelihood (P = .105), were independently predictive of cognitive impairment (odds ratio, 1.115; 95% confidence interval, 1.029-1.208; P = .008). Association of serum FSTL1 levels with cognitive impairment was negligibly affected by age, sex, drinking, and more (all P for interaction > .05). The model, which encompassed serum FSTL1, National Institutes of Health Stroke Scale scores and hematoma volume, performed well under the receiver operating characteristic curve, calibration curve and decision curve, and using the Hosmer-Lemeshow test. This model was validated in the validation group. Admission serum FSTL1 levels following ICH are intimately associated with cognitive impairment, suggesting that serum FSTL1 may be an appealing predictive factor of cognitive impairment subsequent to ICH.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".