Corneal nerve fiber measures independently predict progression from MCI to dementia: Follow‐up of the Qatar Longitudinal Study Cohort
Bibliographic record
Abstract
Abstract Background There is an urgent need for biomarkers of neurodegeneration to identify individuals with MCI at higher risk for developing dementia. Corneal confocal microscopy (CCM) is a non‐invasive imaging biomarker which has identified corneal nerve loss in individuals with mild cognitive impairment (MCI) and dementia. This study assessed the predictive capability of CCM and MRI brain volumetry for progression from participants with MCI to dementia. Method In this prospective study, participants aged 50‐85 with MCI underwent assessment of clinical dementia rating (CDR), Montreal cognitive assessment (MoCA), MRI brain volumetry and CCM at baseline and CDR and MoCA at 1‐4 year follow‐up. Result The study cohort comprised 107 participants with MCI aged 68.4±7.7 years. Over a median follow‐up of 2.4 years, 33 of 107 participants (30.8%) with MCI progressed to dementia. Corneal nerve fibre density (P<0.0001), branch density (P<0.0001) and length (P<0.0001) were significantly lower in MCI participants who progressed to dementia. Reduced baseline corneal nerve fiber density (≤25 fiber/mm2), length (≤15 mm/mm2) and branch density (≤44 branches/mm2) accurately predicted future dementia (area under the curve (AUC) = 71‐74%, P≤0.0001). Reduced baseline intra‐cranial volume percentage (ICV %), hippocampus (≤0.44%), whole brain (≤69.4%), frontal lobe (≤10.8%), amygdala (≤0.17%), cortical gray matter (≤29%), thalamus (≤0.90%) and increased ventricle (≥3.0%) volume predicted future dementia (AUC = 65‐78%, P<0.05), whilst temporal, parietal, occipital lobe, entorhinal cortex, cingulate gyrus and brainstem did not. The adjusted odds ratios (AOR) for progression to dementia were 5.1‐11.1 times higher with abnormal corneal nerve fiber measures (P<0.05), 5.9 higher with abnormal hippocampal volume (P<0.05) and 10.8 times higher with whole‐brain volume (P<0.05). Conclusion The predictive capability of CCM is comparable to hippocampal and whole brain volume for progression to dementia in individuals with MCI.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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) | 0.002 | 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".