Assessment of auditory perceptual functions in patients with Parkinson’s disease
Bibliographic record
Abstract
BACKGROUND: Hearing impairments are manifestations of Parkinson's disease (PD). We aimed to assess central auditory processing (CAP) functions with PD and their predictors. METHODS: This was a cross-sectional study. It included 35 patients (male = 21; female = 14). The severity of PD was assessed using modified Hoehn and Yahr Scale. The severities of depression and cognitive manifestations were assessed using Beck Depression Inventory II (BDI-II) and Mini Mental State Examination (MMSE) and Montreal Cognitive Assessment (MoCA). Participants underwent audiometry and testing of CAP using dichotic digit (DDT), duration pattern (DPT) and speech in noise (SPIN) tests. RESULTS: Patients had mean age at presentation of 56.66 ± 11.05 yrs and mean duration of PD of 4.77 ± 2.73 yrs. Among were ~69% of patients were in early stages of the disease. Compared to controls (n = 25), patients had poor cognition [MMSE: 20.98 ± 2.36, P = 0.001; MoCA: 18.41 ± 3.00, P = 0.001], hearing impairment at high frequencies (4000 HZ), higher speech reception threshold (SRT) (P = 0.001) and worse performance in DDT (P = 0.0001), DPT (P = 0.0001) and SPIN (P = 0.001). These impairments were independently correlated with cognitive deficits (DDT: P = 0.036; DPT: P = 0.050, SPIN: P = 0.023). CONCLUSIONS: CAP dysfunctions occur in early stages of PD. They include impairments in auditory discrimination, spatial perception, binaural integration, temporal ordering or sequencing, and selective attention. The DDT, DPT and SPIN are useful battery measures for testing CAP with PD. Dopamine deficiencies in PD at different auditory pathway levels including the brainstem and cortico-subcortical levels and neurodegenerative diffuse PD pathology can be the causes of CAP impairments.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.002 | 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".