Relationship between remnant cholesterol and risk of heart failure in participants with diabetes mellitus: Reply
Bibliographic record
Abstract
The Authors Reply: We appreciate the comments on our paper.1 Previous studies showed that patients with diabetes mellitus (DM) had more than two-fold higher risk of developing heart failure (HF) than patients without DM.2,3 Moreover, there was evidence displaying that the occurrence of HF in participants with DM increased their mortality risk by 10-fold, with the 5-year survival rate being only 12.5%.4 Thus, our study targeted patients with DM to evaluate the relationship between remnant cholesterol (RC) and risk of HF. However, we agreed with their comments on participants with acute coronary syndrome and future endeavors to specify diabetes patients with and without coronary heart disease would be worthwhile. Regarding the concern about competing events of mortality, we indeed performed a sensitivity analysis by using a competing risk model and taking all-cause deaths as the competing events of HF.1 The death rates for the low, moderate, and high RC groups were 13.4%, 12.1%, and 12.6%, respectively. Results were largely similar to findings from our main analysis, as shown in Table 4 in our paper. These results further supported robustness of our findings and conclusions. Conflict of interest: None declared.
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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 | 0.051 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.005 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.020 | 0.023 |
| Insufficient payload (model declined to judge) | 0.015 | 0.011 |
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".