Relationship between diabetic peripheral neuropathy and retinal nerve fiber layer thinning
Bibliographic record
Abstract
Objective To measure the retinal nerve fiber layer (RNF) thickness in patients with non-proliferative diabetic retinopathy (NPDR) of different severity peripheral neuropathy,and explore the correlation between RNFL thickness and severity of diabetic peripheral neuropathy.Methods Seventy-eight patients with NPDR diagnosed by fundus fluorescein angiography (FFA) were included in this study.Normal control group containing 50 cases,The level of neuropathy was assessed in 78 participants using Toronto clinical scoring system (TCSS).Participants were stratified into four neuropathy groups:none,mild,moderate,and severe.The mean RNFL thickness and the superior,inferior,nasal and temporal retinal nerve fiber layer thicknesses were measured at 3.45 mm diameter around,the optic nerve head using optical coherence tomography (OCT).RNFL thickness difference was estimate according to the analysis of DPN degree between the teams,and analysis evaluation retinopathy to the influence of RNFL thickness.Results Compared normal control group with mild,moderate,and severe DPN group,there were statistical differences in the mean and superior,inferior of quadrant of RNFL (P ＜0.05 for all); No DPN group and normal control group comparison,only inferior quadrant RNFL thickness had statistical difference (P ＜0.05).According to the degree of retinopathy,compared with normal control group,moderate and severe NPDR group mean,superior,inferior of quadrant RNFL thickness difference had statistical significance (P ＜0.05 for all); Mild NPDR group and normal control group comparison,inferior quadrant RNFL thickness had statistical difference(P ＜0.05).Conclusions RNFL thinning is associated with peripheral neuropathy in NPDR patients.With DPN symptoms appear and aggravating,RNFL thickness obviously thin.This is a simple method to speculation RNFL thickness change based on simple assessment of DPN,bring convenience for clinical work. Key words: Diabetic peripheral neuropathy; Diabetic retinopathy; Optical coherence tomography; Retinal nerve fiber layer thinning
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".