Sodium–Glucose co-Transporter 2 Inhibitors in Severe Estimated Glomerular Filtration Rate Deterioration Across Cardiovascular-Kidney-Metabolic Conditions: A Pooled Analysis of Randomized Trials
Bibliographic record
Abstract
AIMS: ), and whether such eGFR deterioration modified the effect of SGLT2i across CKM populations. METHODS AND RESULTS: ). Factors independently associated with a higher risk of eGFR deterioration were lower baseline eGFR and higher albuminuria, whereas allocation to SGLT2i was protective. eGFR deterioration was independently associated with a nearly twofold higher risk of subsequent cardiovascular outcomes and mortality. The beneficial impact of SGLT2i treatment on cardiovascular outcomes and mortality was maintained irrespective of patients experiencing eGFR deterioration (interaction-p >0.1 for all outcomes). Patients who experienced eGFR deterioration were more likely to permanently discontinue treatment, without significant differences in treatment discontinuation rates between the SGLT2i and placebo groups. CONCLUSIONS: Severe eGFR deterioration during follow-up was associated with an increased risk of subsequent cardiovascular events and mortality. SGLT2i reduced the probability and were beneficial irrespective of severe eGFR deterioration.
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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 | 0.022 | 0.025 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.019 | 0.031 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.003 | 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".