Risk of chronic kidney disease defined by decreased estimated glomerular filtration rate in individuals with different prediabetic phenotypes: results from a prospective cohort study in China
Bibliographic record
Abstract
Objective We aimed to investigate the effects of prediabetes and its phenotypes of impaired fasting glucose (IFG), impaired glucose tolerance (IGT) and elevated glycated hemoglobin A 1 c (EHbA 1c ) on chronic kidney disease (CKD) occurrence, and define the cut-off point of each glycemic index that significantly increases the risk of CKD. Research design and methods In this prospective cohort study, 6446 non-diabetic subjects aged 40 years and over were followed over a period of 3 years to track the new onset of CKD. Cox regression was used to assess the association of prediabetes and its phenotypes with CKD. Receiver operating characteristic curves were used to define the cut-off point of each glycemic index that significantly increases the occurrence of CKD. Population attributable risk percent was calculated to estimate the contribution of prediabetes to CKD. Results Compared to subjects with normal glucose tolerance, patients with prediabetes significantly increased the risk of development of CKD (HR=2.33 (1.19–4.55)). Specifically, this increased risk of CKD development was observed in patients with IFG, IGT and EHbA 1c . The cut-off points shown to significantly increase the risk of CKD are fasting plasma glucose of 5.63 mmol/L, 2-hour plasma glucose of 6.80 mmol/L and HbA 1c of 5.6%. The contribution of prediabetes to CKD occurrence in the study population was 60.6%. Conclusions This result suggests that the stricter criteria might be needed to define normal plasma glucose level in China that would not be predisposed to diabetic complications, particularly CKD.
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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 | 0.001 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".