Correlation between plasma homocysteine level and impaired glucose tolerance in patients with peripheral neuropathy
Bibliographic record
Abstract
Objective To investigate the correlation between plasma homocysteine level and impaired glucose tolerance(IGT) patients in peripheral neuropathy. Methods 80 patients with IGT were selected according to the results of routine nerve conduction test, including 40 patients associated with peripheral neuropathy (IGT-PN), and 40 patients without peripheral neuropathy (IGT-NPN). Besides, 40 healthy subjects were selected as control. Plasma homocysteine levels were measured in the three groups by enzyme rate method. The severity of neuropathy was scored and graded by the Toronto Clinical Scoring System (TCSS). Results Plasma homocysteine levels were significantly higher in the all IGT groups than those in the control group. The plasma homocysteine level in the IGT-PN group (14.2±2.7) μmol/L was significantly higher than that in the IGT-NPN group (12.3±2.6) μmol/L (P<0.05). Regression analysis showed that plasma homocysteine level had independent effects on IGT with peripheral neuropathy. Plasma homocysteine level was positively correlated with TCSS score. Conclusions Plasma homocysteine may play an important role in the pathogenesis of peripheral neuropathy in patients with IGT, and their level may be associated with the severity of peripheral neuropathy. Key words: Homocysteine; Impaired glucose tolerance; Peripheral neuropathy; Toronto clinical scoring system
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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 | 0.000 | 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) | 0.001 | 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".