Abstract WMP120: Vascular Risk Factor Reduction Is Associated With Corneal Nerve Regeneration In Patients With Tia And Ischemic Stroke
Bibliographic record
Abstract
Background and Purpose: Vascular risk factors are associated with transient ischemic attack (TIA), acute ischemic stroke (AIS) and corneal nerve damage. We have assessed if an improvement in vascular risk factors in patients with TIA and AIS is associated with corneal nerve regeneration. Methods: Patients with TIA or AIS and control subjects underwent assessment of clinical and vascular risk factors and corneal confocal microscopy (CCM) at baseline and 1-year follow up. Results: Eighty-one patients with TIA (n=28), AIS (n=53) and control subjects (n=56) were studied. Systolic blood pressure (SBP)( P =0.000), diastolic blood pressure (DBP) ( P =0.000) and HbA1 c (P=0.000) were significantly higher and HDL ( P =0.000), corneal nerve fiber length (CNFL) (P=0.000), corneal nerve fiber density (CNFD) (P=0.000) and corneal nerve branch density (CNBD) (P=0.003) were significantly lower in patients with TIA/AIS compared to controls. At follow up, there was a significant decrease in triglycerides (-0.37 mmol/l, P=0.005), total cholesterol (-1.12 mmol/l, P=0.000); LDL-cholesterol (-1.08 mmol/l, P=0.000), SBP (-24.76 mmHg, P=0.000), DBP (-14.24 mmHg, P=0.000) and HbA1 c (-0.50 mmol/l, P=0.027) and an increase in HDL (0.10 mmol/l, P=0.010), CNFL (1.48 mm/mm 2 , P=0.018), CNFD (1.66 no./mm 2 , P=0.024), and CNBD (26.90 no./mm 2 , P=0.000). The improvement in lipids and blood pressure was associated with an increase in corneal nerve parameters ( P <0.05). Conclusions: An improvement in vascular risk factors in patients with TIA or AIS is associated with corneal nerve regeneration. CCM could be used to assess the effectiveness of risk factor reduction in patients with TIA or AIS.
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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 | 0.000 | 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) | 0.003 | 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".