Abstract TMP119: High Homocysteine Level is not Associated With White Matter Changes, Dementia nor Mortality After Ischemic Stroke
Bibliographic record
Abstract
Background: Association between high homocysteine level and cerebral small-vessel disease has been implicated in cross-sectional studies, but results from longitudinal studies have been less clear. The aim of this study was to investigate whether homocysteine level at 3-months poststroke relates to the occurrence of white matter changes (WMC), the surrogate of cerebral small-vessel disease. We also investigated whether it relates to the prognosis after ischemic stroke regarding the risk of dementia at 3-months and mortality in long-term follow-up. Methods: A total of 321 consecutive acute ischemic stroke patients aged 55 to 85 were included in the study and followed up to 12 years. Plasma homocysteine level and occurrence of WMC in MRI were measured 3 months poststroke and dementia according to DSM-III was evaluated at the same time. Findings: The median homocysteine level was 13.50 μmol/l (interquartile range [IQR] 10.60-18.50 μmol/l). Total of 81 patients (25.2%) had homocysteine level above 18.50 μmol/l. In logistic regression analysis, homocysteine level above 18.50 μmol/l was not associated with severe WMC nor with dementia at 3 months poststroke. In Kaplan-Meier analysis, homocysteine level above 18.50 μmol/l was not associated with survival in 12-year follow-up. For further analysis, the group was divided in quartiles according to homocysteine level. The quartiles did not differ in occurrence of severe WMC at baseline, in the risk of dementia at 3 months, nor in the risk of mortality in 12-year follow-up. Interpretation: In our poststroke cohort homocysteine level is not associated with WMC. Further, it does not relate to impaired prognosis manifested as dementia at 3 months or mortality in 12-year follow-up.
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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) | 0.000 | 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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".