Development and Progression of Polyneuropathy Over 5 Years in Patients With Type 2 Diabetes
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVES: There is a need for knowledge regarding the natural course of diabetic polyneuropathy (DPN), a complication in type 2 diabetes (T2D). The aim of this study was to examine the development of DPN over time. METHODS: Patients with newly diagnosed T2D, recruited from a national cohort, and controls without diabetes of similar age and sex, underwent sensory phenotyping in 2016-2018. The Toronto consensus criteria were used to classify patients into possible, probable, and confirmed DPN. For this 5-year, observational, follow-up, cohort study, all participants were invited to a reexamination combining bedside sensory examination, quantitative sensory testing (QST), nerve conduction studies (NCSs), and skin biopsies measuring intraepidermal nerve fiber density (IENFD) in order to compare phenotypic and diagnostic changes over time. RESULTS: -scores at follow-up, and worsening of nerve parameters at follow-up correlated with higher baseline triglycerides. DISCUSSION: In patients with well-regulated T2D, the proportion of patients with confirmed DPN increased over 5 years driven by progression from probable DPN. A large proportion of patients progressed, and a smaller proportion regressed on nerve parameters. Higher triglycerides correlated with this progression and may constitute a risk factor.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".