Serum neurofilament light chain and postural instability/gait difficulty (PIGD) subtypes of Parkinson’s disease in the MARK-PD study
Bibliographic record
Abstract
The PIGD (postural instability / gait difficulty) subtype of Parkinson´s disease (PD) is associated with faster cognitive and motor decline. So far, there are no quantifiable biomarkers to aid clinical subtyping. Neurofilament light chain (NfL) is a highly specific marker of neuro-axonal damage and can be assessed in blood. Here, we investigated if serum NfL concentrations are associated with PIGD subtype and PIGD scores in PD patients at advanced disease stages. Furthermore, we evaluated if serum NfL is associated with motor and cognitive function assessed with MDS-UPDRS part III and Montreal cognitive assessment (MoCA). Serum NfL levels were analyzed with Single Molecule Assays (Simoa) in blood of 223 PD patients from the bioMARKers in Parkinson's Disease (MARK-PD) study. Serum NfL concentrations were higher in PIGD patients independent of age, sex and disease duration. In linear regression analysis, serum NfL levels were associated with MoCA, MDS-UPDRS III and PIGD scores in unadjusted models, but remained significant after adjustment only with PIGD scores. In conclusion, increased serum NfL levels were associated with PIGD subtype and PIGD scores in patients with advanced PD.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".