Effect of diabetes control status on the progression of Parkinson’s disease: A prospective study
Bibliographic record
Abstract
OBJECTIVE: To evaluate whether the control status of type 2 diabetes mellitus (DM) influences the progression of Parkinson's disease (PD). METHODS: We conducted a prospective cohort study from March 2009 to August 2020. Patients at baseline were categorized into DM and non-DM groups, and those with DM were further classified into the well and poorly controlled DM groups based on the 7.0% of glycated hemoglobin (HbA1C) levels. Multivariate Cox proportional hazards regression models were used to explore the predictors for PD-related outcomes by hazard ratios (HRs) and 95% confidence intervals (CIs). RESULTS: Of the 379 patients enrolled, 49 (12.9%) had DM, and 22 of DM (44.9%) were poorly controlled. The adjusted HRs were 2.060 (95% CI 1.165-3.641) for United Rating Scale (UPDRS) III score increased ≥14 in the poorly controlled-DM group, and 1.066 (95% CI 0.572-1.986) in the well-controlled DM group, relative to the non-DM group (p trend = 0.025), after adjusting for sex, age, age of onset, body mass index, and UPDRS III and Montreal Cognitive Assessment (MoCA) scores at baseline. The adjusted HRs were 2.079 (95% CI 1.212-3.566) for reaching Hoehn & Yahr stage ≥3 in the poorly controlled DM group, and 0.879 (95% CI 0.413-1.871) in the well-controlled DM group, compared with the non-DM group (p trend = 0.021). Time to death or time to MoCA 3-point decrease were not significantly different among the three groups. INTERPRETATION: Poorly controlled DM is an independent risk factor contributing to motor progression in PD. Our study highlights the importance of adequate control of diabetes in 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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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".