Prognostic significance of peripheral neutrophils and lymphocytes in early untreated Parkinson’s disease: an 8-year follow-up study
Bibliographic record
Abstract
BACKGROUND: To explore whether peripheral blood neutrophils and lymphocytes are associated with longitudinal motor and cognitive decline in patients with early Parkinson's disease (PD) and, to uncover the disease-specific mechanisms underlying these associations. METHODS: Data were obtained from the Parkinson's Progression Markers Initiative cohort. We included 376 patients with recently diagnosed, drug-naïve PD and 178 matched healthy controls. The patients underwent annual assessments, including the Movement Disorder Society Unified Parkinson's Disease Rating Scale (MDS-UPDRS) part 3 test to measure motor function and the Montreal Cognitive Assessment (MoCA) to measure cognitive function, for up to 8 years of follow-up. Dopamine transporter (DAT) imaging was performed at baseline and the 1-year, 2-year and 4-year follow-up visits. RESULTS: At baseline, patients with PD showed higher neutrophil and lower lymphocyte counts, resulting in a higher neutrophil-to-lymphocyte ratio (NLR) than that in healthy controls. Higher neutrophil counts were associated with a greater increase in MDS-UPDRS part 3 scores in patients with PD (estimate: 0.25, 95% CI: 0.12 to 0.37, p<0.001). Correspondingly, higher neutrophil levels were related to a greater reduction in DAT activity in the caudate (estimate: -0.007, 95% CI: -0.014 to -0.001, p=0.046) and putamen (estimate: -0.0039, 95% CI: -0.0077 to -0.0002, p=0.042). However, there were no significant effects of lymphocyte count and NLR on changes in the MDS-UPDRS part 3 and MoCA scores and striatal DAT uptake over time. CONCLUSION: Among the blood biomarkers, only a higher neutrophil count was associated with faster motor progression along with accelerated nigrostriatal dopaminergic degeneration in patients with PD. The impact of neutrophils and lymphocytes on longitudinal cognitive changes remains unclear. TRIAL REGISTRATION NUMBER: NCT01141023.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| 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".