Blood neurofilament light chain in Parkinson disease and atypical parkinsonisms
Bibliographic record
Abstract
BACKGROUND: Neurofilament light chain (NfL), an index of neuroaxonal injury, is a promising diagnostic and prognostic fluid biomarker with high translational value in many neurodegenerative disorders. Blood NfL measurement has been an exciting and active field of research in idiopathic Parkinson disease (PD) and atypical parkinsonisms. However, blood NfL levels in these parkinsonisms from existing literature were inconsistent. No comprehensive meta-analysis has ever been conducted. METHODS: Three major biomedical electronic databases PubMed, Embase, and Web of Science were comprehensively searched from inception to July 10, 2020. This protocol will be prepared based on the guidelines recommended by the statement of Preferred Reporting Items for Systematic Review and Meta-Analysis Protocols (PRISMA-P). Original observational studies that measured blood (serum/plasma) NfL concentrations in patients with parkinsonisms (multiple system atrophy [MSA], progressive supranuclear palsy [PSP], corticobasal syndrome [CBS], and dementia with Lewy bodies [DLB]), and healthy controls (HCs) will be included. Quality assessment of the included studies will be performed using the Newcastle Ottawa Scale (NOS). Meta-analyses will be conducted using the STATA software version 13.0. The standardized mean differences as the measure of effect size and 95% confidence intervals were calculated for each comparison of blood NfL levels. Heterogeneity analysis, sensitivity analysis, publication bias, subgroup analysis, and meta-regression analysis will be carried out to test the robustness of the results. RESULTS: The meta-analysis will obtain the effect sizes of blood NfL levels in the following comparisons: PD versus HC, MSA versus HC, PSP versus HC, CBS versus HC, DLB versus HC, MSA versus PD, PSP versus PD, CBS versus PD, and DLB versus PD. CONCLUSIONS: The present meta-analysis will provide the quantitative evidence of NfL levels in idiopathic PD and atypical parkinsonisms, hoping to facilitate differential diagnoses in clinical practice. REGISTRATION NUMBER: INPLASY202070091.
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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 | 0.009 | 0.022 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.008 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 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".