Physiology in Medicine: neuromuscular consequences of diabetic neuropathy
Bibliographic record
Abstract
Diabetic polyneuropathy (DPN) refers to peripheral nerve dysfunction as a complication of diabetes mellitus. This condition is relatively common and is likely a result of vascular and/or metabolic disturbances related to diabetes. In the early or less severe stages of DPN it typically results in sensory impairments but can eventually lead to major dysfunction of the neuromuscular system. Some of these impairments may include muscle atrophy and weakness, slowing of muscle contraction, and loss of power and endurance. Combined with sensory deficits these changes in the motor system can contribute to decreased functional capacity, impaired mobility, altered gait, and increased fall risk. There is no pharmacological disease-modifying therapy available for DPN and the mainstay of treatment is linked to treating the diabetes itself and revolves around strict glycemic control. Exercise therapy (including aerobic, strength, or balance training-based exercise) appears to be a promising preventative and treatment strategy for patients with DPN and those at risk. The goal of this Physiology in Medicine article is to highlight important and overlooked dysfunction of the neuromuscular system as a result of DPN with an emphasis on the physiologic basis for that dysfunction. Additionally, we sought to provide information that clinicians can use when following patients with diabetes or DPN including support for the inclusion of exercise-based therapy as an effective, accessible, and inexpensive form of treatment.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".