<scp>CSF NFL</scp> in a Longitudinally Assessed <scp>PD</scp> Cohort: Age Effects and Cognitive Trajectories
Bibliographic record
Abstract
BACKGROUND: Neurofilament light protein is an unspecific biofluid marker that reflects the extent of neuronal/axonal damage and thereby offers the chance monitor disease severity and progression. The objective of this study was to investigate cerebrospinal fluid (CSF) levels of neurofilament light protein in Parkinson's disease (PD) patients with clinical trajectories of motor and cognitive function longitudinally. METHODS: ), and 71 healthy controls. Participants were followed up longitudinally for up to 8 years. RESULTS: At baseline, mean CSF neurofilament light protein levels were highest in PD patients with cognitive impairment (Montreal Cognitive Assessment score ≤ 25; 1207 pg/mL) but also higher in PD patients with normal cognitive function (757 pg/mL) compared with healthy controls (593 pg/mL; P ≤ 0.001). In healthy controls and in PD patients older age was associated with higher CSF levels of neurofilament light protein (P ≤ 0.001). In PD patients, male gender, older age at onset, longer disease duration, higher Hoehn and Yahr stages, higher UPDRS-III scores, and lower Montreal Cognitive Assessment scores were associated with higher CSF levels of neurofilament light protein (P < 0.01). In patients who developed cognitive impairment during study, CSF neurofilament light protein levels prior to conversion to cognitive impairment were not significantly different compared with CSF neurofilament light protein levels of patients who remained cognitively normal. CONCLUSIONS: Increased CSF levels of neurofilament light protein are associated with cognitive decline and motor impairment in PD. However, this increase seems not a very early event and does not mark the conversion to cognitive impairment beforehand. Therefore, the predictive value needs to be discussed critically. © 2020 International Parkinson and Movement Disorder Society.
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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".