Olfactory function, neurofilament light chain, and cognitive trajectory: A 12‐year follow‐up of the Shanghai Aging Study
Bibliographic record
Abstract
Abstract This study aimed to determine whether blood neurofilament light chain (NfL) modifies the association of olfactory dysfunction (OD) with long‐term cognitive decline. A total of 1125 non‐demented older adults in the Shanghai Aging Study were evaluated for baseline olfaction (12‐item Sniffin’ Sticks Smell Test) and cognitive trajectory by a 12‐year follow‐up. Baseline blood NfL was quantified using Single Molecular Array assay, and dichotomized into low and high levels based on the median value of concentration. The Mini‐Mental State Examination (MMSE) and Telephone Interview for Cognitive Status‐40 were used to assess participants’ cognitive function. Cognitive decline was ascertained when dementia was diagnosed or documented in the medical record during follow‐up, or the MMSE declining rate (slope) was 1.0 SD larger than the group mean. OD participants presented a steeper trajectory of MMSE score (p interaction = 0.004) and a high risk of cognitive decline (adjusted HR [95% CI], 1.82 [1.11, 2.98]) only in those with high NfL. Participants with combined OD and high NfL showed the highest risk of cognitive decline (adjusted HR, 2.43 [1.20, 4.92]). OD, especially in combination with high blood NfL concentration, may be able to identify individuals who later incur cognitive deterioration.
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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) | 0.001 | 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 | 0.000 | 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".