Diabetes, Glycated Hemoglobin (<scp>HbA1c)</scp>, and Neuroaxonal Damage in Parkinson's Disease (<scp>MARK‐PD Study</scp>)
Bibliographic record
Abstract
BACKGROUND: Diabetes is associated with incidence and prevalence of Parkinson's disease (PD). Furthermore, glycated hemoglobin (HbA1c) levels have been linked with motor function and progression. OBJECTIVES: We evaluated the relationship between prevalent diabetes and HbA1c levels with serum neurofilament light chain (NfL) levels as marker of neuroaxonal damage. METHODS: NfL concentrations were analyzed with Simoa in serum of 195 PD patients with available HbA1c values. Motor (MDS-UPDRS III, Hoehn & Yahr [H&Y]) and cognitive (Montreal Cognitive Assessment [MoCA]) function was assessed and vascular comorbidities were documented from medical records. RESULTS: PD patients with prevalent diabetes had higher serum NfL levels and lower MoCA scores independent of age, body mass index (BMI), and vascular risk factors. Furthermore, diabetes was associated with higher H&Y stages in unadjusted and age/BMI-adjusted models. Higher HbA1c levels were associated with increased NfL in unadjusted and age/BMI-adjusted models. CONCLUSIONS: In PD patients, diabetes and high HbA1c are associated with increased neuroaxonal damage and cognitive impairment. © 2022 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson 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 | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".