Interplay between worsening kidney function and cardiovascular events in patients with type 2 diabetes: an analysis from the ACCORD trial
Bibliographic record
Abstract
INTRODUCTION: Patients with type 2 diabetes (T2D) have an increased risk of worsening kidney function (WKF) over time compared with patients without diabetes. Data evaluating the inter-relation between WKF, cardiovascular risk, and clinical events are scarce. We aim to study the association of WKF with subsequent cardiovascular events and the probabilities of transition from WKF to hospitalization or death according to patients' risk. We have used a large population of patients with T2D and a high cardiovascular risk enrolled in the Action to Control Cardiovascular Risk in Diabetes Study. RESEARCH DESIGN AND METHODS: ) follow-up time of 5.0 (4.1-5.7) years. RESULTS: Patients who experienced WKF were slightly older, more frequently women, and had longer diabetes duration. Patients experiencing WKF, regardless of baseline kidney function, had a higher risk of subsequent cardiovascular events, including the composite of cardiovascular death or hospitalization for heart failure (HHF), with ≈2-fold higher risk. Joint modeling showed that renal function deterioration frequently occurs even among patients who did not experience a cardiovascular event. In multistate models, patients with a medium-high cardiovascular risk (compared with those with a low cardiovascular risk) are at higher risk of HHF or cardiovascular death first (HR=4.76, 95% CI 3.63 to 6.23) than of WKF first (HR=1.37, 95% CI 1.21 to 1.56); remarkably, the risk of cardiovascular death or HHF is highest after a WKF event (HR=6.20, 95% CI 2.71 to 14.8). CONCLUSIONS: In patients with T2D and a high cardiovascular risk, WKF occurs in more than 10% of patients and is independently associated with risk of subsequent cardiovascular events, irrespective of baseline eGFR. Preventing serious WKF and the transition from WKF to HHF or cardiovascular death is an important objective of future trials. TRIAL REGISTRATION NUMBER: NCT00000620.
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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 | 0.007 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.004 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".