Effect of interactions between C peptide levels and insulin treatment on clinical outcomes among patients with type 2 diabetes mellitus
Bibliographic record
Abstract
BACKGROUND: A recently halted clinical trial showed that intensive treatment of type 2 diabetes mellitus was associated with increased mortality. Given the phenotypic heterogeneity of diabetes, therapy targeted at insulin status may maximize benefits and minimize harm. METHODS: In this longitudinal cohort study, we followed 503 patients with type 2 diabetes who were free of cardiovascular disease from 1996 until data on mortality and cardiovascular outcomes were censored in 2005. Phenotype-targeted therapy was defined as use of insulin therapy in patients with a fasting plasma C peptide level of 0.2 nmol/L or less and no insulin therapy in patients with higher C peptide levels. RESULTS: The mean age of the cohort was 54.4 (standard deviation 13.1) years, and 56% were women. The mean duration of diabetes was 4.6 years (range 0-35.9 years). Of the 503 patients, 110 (21.9%) had a low C peptide level and 111 (22.1%) were given insulin. Based on their C peptide status, 338 patients (67.2%) received phenotype-targeted therapy (non-insulin-treated, high C peptide level [n = 310] or insulin-treated, low C peptide level [n = 28]), and 165 patients (32.8%) received non-phenotype-targeted therapy (non-insulin-treated, low C peptide level [n = 82] or insulin-treated, high C peptide level [n = 83]). Compared with the insulin-treated, low-C-peptide referent group, the insulin-treated, high-C-peptide group was at a significantly higher risk of cardiovascular events (hazard ratio [HR] 2.85, p = 0.049) and death (HR 3.43, p = 0.043); the risk was not significantly higher in the other 2 groups. These differences were no longer significant after adjusting for age, sex and diabetes duration. INTERPRETATION: Patients with low C peptide levels who received insulin had the best clinical outcomes. Patients with normal to high C peptide levels who received insulin had the worst clinical outcomes. The results suggest that phenotype-targeted insulin therapy may be important in treating diabetes.
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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 | 0.006 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| 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".