The impact of Type 2 diabetes in Parkinson’s disease
Bibliographic record
Abstract
Abstract Importance Type 2 diabetes (T2DM) is an established risk factor for developing Parkinson’s disease (PD) but its effect on disease progression is not well understood. Objective To examine the effects of co-morbid T2DM on Parkinson’s disease progression and quality of life. Design We analysed data from the Tracking Parkinson’s study, a large multi-centre prospective study in the UK. Participants The study included 1930 adults with recent onset PD, recruited between February 2012 and May 2014, and followed up regularly thereafter. Exposure A diagnosis of pre-existing T2DM was based on self-report at baseline. After controlling for confounders, an evaluation of how T2DM affects PD was performed by comparing symptom severity scores; and analyses using multivariable mixed models was used to determine the effects of T2DM on Parkinson’s disease progression. Main Outcomes and Measures The impact of T2DM on Parkinson’s disease severity was derived from scores collected using the Movement Disorders Society Unified Parkinson’s Disease Rating Scale (MDS-UPDRS), Non-Motor Symptoms Scale (NMSS), Montreal Cognitive Assessment (MoCA), Questionnaire for impulsive-compulsive disorders in PD (QUIP), Leeds Anxiety and Depression Scale (LADS), and Schwab and England ADL scale. Results We identified 167 (8.7%) patients with PD and T2DM (PD+T2DM) and 1763 (91.3%) with PD without T2DM (PD). Patients with T2DM had more severe motor symptoms, as assessed by MDS-UPDS III 25.8 (0.9) vs 22.5 (0.3) p=0.002, had significantly faster motor symptom progression over time (p=0.012), and T2DM was an independent predictor for the development of substantial gait impairment (HR 1.55, CI 1.07-2.23, p=0.020). Patients were more likely to have loss of independence (OR 2.08, CI 1.34-3.25, p=0.001); and depression (OR 1.62, CI 1.10-2.39, p=0.015), and developed worsening mood (p=0.041) over time compared to the PD group. T2DM was also an independent predictor for the development mild cognitive impairment (HR 1.7, CI 1.24-2.51, p=0.002) over time Conclusions and relevance T2DM is associated with faster disease progression in PD, highlighting an interaction between these two diseases. As it is a potentially modifiable, metabolic state, with multiple peripheral and central targets for intervention, it may represent a target for ameliorating parkinsonian symptoms, and progression to disability and dementia. Key points Question What is the impact of Type 2 diabetes on Parkinson’s disease progression? Findings In this prospective study of 1930 patients with recent onset PD, T2DM is an independent risk factor for more severe motor features, non-motor symptoms, and poorer quality of life; and importantly is associated with faster motor and non-motor symptom progression, and increases the risk of developing cognitive impairment. Meaning T2DM is identified as a new factor that alters Parkinson’s disease progression. T2DM predicts both motor and non-motor symptom progression in PD and is associated with poorer quality of life, highlighting an interaction of two chronic disease states. This highlights a particular need for improved treatment in this subgroup of patients with Parkinson’s.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".