Clinical characteristics of dry eye in patients with type 2 diabetic peripheral neuropathy
Bibliographic record
Abstract
AIM: To investigate the clinical features of dry eye in patients with type 2 diabetes mellitus complicated with peripheral neuropathy.METHOD: Prospective cohort study. A total of 192 patients with type 2 diabetes were enrolled in the Department of Endocrinology, Shuguang Hospital Affiliated to Shanghai University of Traditional Chinese Medicine from July 2021 to March 2022. The right eyes of all patients were selected as the observation eye, among which 122 patients were diagnosed with diabetic peripheral neuropathy(DPN)and 70 patients were diagnosed with non-diabetic peripheral neuropathy(NDPN). The score of ocular surface disease index(OSDI), tear meniscus height, tear meniscus width, corneal epithelial thickness, corneal endothelial cell density, tear secretion test(Schirmer Ⅰ test, SⅠt), corneal sensitivity, meibomian gland function status score, tear film breakup time(BUT), corneal fluorescein sodium staining score and Toronto clinical scoring system(TCSS)score were compared between two groups. The correlation between OSDI score and TCSS score in type 2 diabetes patients was analyzed as well.RESULTS: The morbidity of dry eye in the DPN group(55 eyes, 45.1%)was significantly higher than that of NDPN group(20 eyes, 28.6%; χ2=5.094, P=0.024), BUT and corneal sensitivity score of DPN were lower than NDPN group(P<0.001), meanwhile, corneal staining score and meibomian gland function score were higher than NDPN group(P<0.001). OSDI scores of all subjects were negatively correlated with TCSS scores(rs=-0.233, P=0.002), and OSDI scores of DPN group were negatively correlated with TCSS scores(rs=-0.511, P<0.001), but there was no significant correlation between the two scores of NDPN patients(rs=0.007, P=0.957).CONCLUSIONS: DPN patients are more likely to develop dry eye than NDPN patients. OSDI score is not an accurate evaluation index for type 2 diabetes patients, especially for DPN patients.
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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 | 0.001 |
| 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 | 0.000 |
| 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".