Vitamin B<sub><sub>12</sub></sub>deficiency and hyperhomocysteinaemia in outpatients with stroke or transient ischaemic attack: a cohort study at an academic medical centre
Bibliographic record
Abstract
Objective We sought to assess the current magnitude of the opportunity for secondary stroke prevention with B vitamins. Design A cohort study. Setting The Urgent TIA (Transient Ischaemic Attack) Clinic at an academic medical centre. Main outcome measures We assessed the prevalence of biochemical vitamin B12deficiency (B12Def, serum B12<156 pmol/L), hyperhomocysteinaemia (HHcy; plasma total homocysteine [tHcy] >14 µmol/L) and metabolic B12deficiency (MetB12Def, serum B12<258 pmol/L and HHcy) between 2002 and 2017, by age group and by stroke subtype. Results Data were available in 4055 patients. B12Def was present in 8.2% of patients overall; it declined from 10.9% of patients referred before 2009 to 5.4% thereafter (p=0.0001). MetB12Def was present in 10.6% of patients, and HHcy was present in 19.1% of patients. Among the patients aged ≥80 years, MetB12Def was present in 18.1% and HHcy in 35%. Among the 3410 patients whose stroke subtype was determined, HHcy was present in 18.4% of patients: 23.3% of large artery atherosclerosis, 18.1% of cardioembolic, 16.3% of small vessel disease, 10.8% of other unusual aetiologies and 13.6% of undetermined subtypes (p=0.0001). Conclusions Despite a decline in our referral area since 2009, B12Def, MetB12Def and HHcy remain common in patients with stroke/TIA. Because these conditions are easily treated and have serious consequences, all patients with stroke/TIA should have their serum B12and tHcy measured.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".