Prevalence of Muscle Cramps in Patients With Diabetes
Bibliographic record
Abstract
There are limited epidemiological studies addressing the prevalence of muscle cramps in the general population and diseases like diabetes (1). Common long-term complications of diabetes, such as neuropathy and nephropathy, have been associated with higher rates of muscle cramps (2). We aimed to determine the prevalence and characteristics of muscle cramps in patients with diabetes compared with healthy volunteers. Frequency, severity (using visual analog scale [VAS]), duration, and disability due to muscle cramps were evaluated, as is standard in clinical trials. Information about each patient’s clinical status was collected, including patient demographics, neuropathy (diagnosed using established clinical and electrophysiological criteria and quantitated using the Toronto Clinical Neuropathy Score) (3), diabetes complications, duration and type of diabetes, concurrent cramp-inducing (β-blockers, diuretics, statins) and cramp-protecting (quinine, calcium channel blockers, antiepileptics) medications, and markers of glycemic control (HbA1c). Baseline demographics and cramp characteristics for 269 patients with diabetes (type 1 diabetes, n = …
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".