Presence of Neuropathic Pain May Explain Poor Performances on Olfactory Testing in Diabetes Mellitus Patients
Bibliographic record
Abstract
Olfactory dysfunction in neurodegenerative conditions such as Parkinson's syndrome and Alzheimer's disease can hallmark disease onset. We hypothesized that patients with diabetes mellitus, a condition featuring peripheral and central neurodegeneration, would have decreased olfaction abilities. We examined participants with diabetic peripheral neuropathy, participants with diabetes without diabetic peripheral neuropathy, and control participants in blinded fashion using standardized Sniffin' Sticks. Diabetic peripheral neuropathy severity was quantified using the Utah Early Neuropathy Scale. Further subcategorization of diabetic peripheral neuropathy based on presence of neuropathic pain was performed with Douleur Neuropathique 4 Questionnaires. Participants with diabetes had decreased olfactory sensitivity, impaired olfactory discrimination abilities, and reduced odor identification skills when compared with controls. However, loss of olfaction ability was, at least partially, attributed to presence of neuropathic pain on subcategory assessment, although pain severity was not associated with dysfunction. Those participants with diabetes without diabetic peripheral neuropathy and those with diabetic peripheral neuropathy without neuropathic pain had similar olfactory function as controls in general. The presence of neuropathic pain, associated with limited attention and concentration, may explain at least a portion of the olfactory dysfunction witnessed in the diabetic patient population.
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 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 | 0.001 | 0.002 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".