Prevalence and risk factors of sexual dysfunction in patients with Parkinson's disease
Bibliographic record
Abstract
Objective To investigate the prevalence and related factors of sexual dysfunction (SD) in patients with Parkinson's disease. Methods A total of 411 patients with Parkinson' disease in Nanjing Brain Hospital were analyzed retrospectively. The ICD-10 diagnostic criteria for SD was used to evaluate SD.The Unified Parkinson's Disease Rating Scale (UPDRS) part Ⅲ, Hoehn and Yahr (H&Y) staging, Non-motor Symptoms Questionnaire (NMS-Quest), Parkinson's Disease Sleep Scale (PDSS), Hamilton Anxiety Rating Scale (HAMA), Hamilton Rating Scale for Depression (HRSD) and Montreal Cognitive Assessment (MoCA) were used to evaluate patients. Results SD was found in 145(35.3%) patients and the prevalence was higher in male than in female. Patients with SD had older age, longer duration, severer motor symptoms, and higher scores of UPDRS-Ⅲ, HAMD, HAMA and NMS-Quest (all P<0.05). In male patients, SD was positively associated with age, duration of disease, UPDRS-Ⅲ, H-Y stage, HAMD, HAMA and NMS (r=0.127, 0.303, 0.240, 0.236, 0.181, 0.221 and 0.302, all P<0.05). In female patients, SD was positively associated with duration of disease, HAMD, HAMA and NMS (r=0.194, 0.163, 0.189 and 0.178, all P<0.05). The forward binary Logistic regression analysis indicated that female gender (OR=0.539, P<0.05), duration of disease (OR=1.133, P<0.05), NMS (OR=1.104, P<0.05) and history of exposure to heavy metals (OR=5.268, P<0.05) were associated with SD. Conclusions SD is a common complication in patients with Parkinson's disease, and a great attention should be paid to its screening and diagnosis. Key words: Parkinson disease; Sexual dysfunction, physiological; Questionnaire
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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".