Serum γ‐glutamyltransferase and associated damage among a She Chinese population
Bibliographic record
Abstract
OBJECTIVE: It has been suggested that serum γ-glutamyltransferase is independently associated with cardiovascular mortality and atherosclerosis. The present study is to investigate the relationship between serum γ-glutamyltransferase and potential associated damage in an adult She Chinese population. METHOD: A multistage, stratified, cluster, random sampling method was used to select an ethnically representative group of individuals aged 20-80 years in the general population. Brachial-ankle pulse-wave velocity was used to assess arterial stiffness in the general population and the Toronto Clinical Neuropathy Scoring System was used to detect diabetic peripheral polyneuropathy among populations with diabetes. RESULTS: A total of 5385 subjects were entered into the analysis. Serum γ-glutamyltransferase levels were classified into four groups using the 25th, 50th and 75th percentiles as cut points (males: < 20, 20-29, 29-52 and > 52 U/l; females: < 13, 13-18, 18-25 and > 25 U/l). As compared with the first quartile, the relative risks of arterial stiffness were 1.418, 1.667 and 2.394 in the other three categories, respectively (test for trend P < 0.05). After adjustment in five models, serum γ-glutamyltransferase was still a risk factor of arterial stiffness. We found inverted U-shape curves in both genders and the third quartile (male: 29 52 U/l; female: 18-25 U/l) had the highest odds ratios of 1.640 and 1.529, respectively. CONCLUSIONS: We demonstrated that high serum γ-glutamyltransferase concentrations were directly associated with the increased risk of arterial stiffness, in general, and with peripheral polyneuropathy in subjects with diabetes in an ethnic She Chinese population. Alcohol use, gender, BMI and blood pressure were related to serum γ-glutamyltransferase and were involved in the relationship between serum γ-glutamyltransferase and brachial-ankle pulse-wave velocity.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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 teacher head, 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".