Depression is associated with the nonmotor symptoms of Parkinson's disease: A comparative analysis
Bibliographic record
Abstract
Abstract Background and aims The nonmotor symptoms (NMS) of Parkinson's disease (PD) and their potential role in early diagnosis are recent debates. Herein, we aimed to investigate the association between depression and NMS of PD including sleep disorders, hyposexuality, hyposmia, constipation, and orthostatic hypotension. Methods A total of 93 PD patients with depression and 67 PD patients without depression were included in the study, and NMS were compared between the two groups. Furthermore, the possible associations between depression severity measured by Beck Depression Inventory (BDI) and NMS were investigated using linear regression or binary logistic regression models controlled for possible confounders. Eventually, we performed a subgroup analysis in each mild, moderate, and severe depression group. Results Orthostatic hypotension, constipation, and hyposexuality showed a significant difference between PD patients with and without depression ( p < 0.001, p = 0.029, and p < 0.001, respectively). The BDI score was significantly associated with hyposexuality, Montreal cognitive assessment (MoCA), and Pittsburgh Sleep Quality ( p = 0.016, p = 0.010, and p = 0.011, respectively); however, after adjustments for possible confounders, the associations of the BDI score with the MoCA score and hyposexuality remained significant ( p = 0.015 and p = 0.019, respectively). Considering subgroup analysis, a similar pattern of significant results was observed particularly in the severe group. Conclusions This study suggests a possible association between depression in PD patients and some NMS observed in the course of PD. These findings could be beneficial for early diagnosis of the disease, which eventually could make a considerable difference in the management of PD patients. Additional interventional longitudinal studies are warranted to explore how controlling depression could impact the NMS of patients with PD.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".