Sodium-Glucose Cotransporter 2 Inhibitors and Risk of Hyperkalemia in People With Type 2 Diabetes: A Meta-Analysis of Individual Participant Data From Randomized, Controlled Trials
Bibliographic record
Abstract
Background: Hyperkalemia increases risk of cardiac arrhythmias and death and limits the use of renin-angiotensin-aldosterone system (RAAS) inhibitors and mineralocorticoid receptor antagonists (MRAs), which improve clinical outcomes in people with chronic kidney disease (CKD) and/or systolic heart failure. Sodium-glucose cotransporter 2 (SGLT2) inhibitors reduce the risk of cardiorenal events in people with type 2 diabetes at high cardiovascular risk or with CKD. However, their effect on hyperkalemia has not been systematically evaluated. / Methods: A meta-analysis was conducted using individual participant data from randomized, double-blind, placebo-controlled clinical outcome trials with SGLT2 inhibitors in people with type 2 diabetes at high cardiovascular risk and/or with CKD, in which serum potassium levels were routinely measured. The primary outcome was time to serious hyperkalemia, defined as central laboratory determine serum potassium ≥6.0 mmol/L, with other outcomes including investigator-reported hyperkalemia events and hypokalemia (serum potassium ≤3.5 mmol/L). Cox regression analyses were performed to estimate treatment effects from each trial with hazards ratios (HR) and corresponding 95% CI pooled using random effects models to obtain summary treatment effects, overall and across key subgroups. / Results: Results from six trials were included comprising 49,875 participants assessing four SGLT2 inhibitors. 1,754 participants developed serious hyperkalemia and an additional 1,119 investigator-reported hyperkalemia events were recorded. SGLT2 inhibitors reduced the risk of serious hyperkalemia (HR 0.84, 95% CI 0.76-0.93), an effect consistent across studies (P-heterogeneity=0.71). The incidence of investigator-reported hyperkalemia was also lower with SGLT2 inhibitors (HR 0.80, 95% CI 0.68-0.93; P-heterogeneity=0.21). Reductions in serious hyperkalemia were observed across a range of subgroups including baseline kidney function, history of heart failure, RAAS inhibitor, diuretic and MRA use. SGLT2 inhibitors did not increase the risk of hypokalemia (HR 1.04, 95% CI 0.94-1.15; P-heterogeneity=0.42). / Conclusions: SGLT2 inhibitors reduce the risk of serious hyperkalemia in people with type 2 diabetes at high cardiovascular risk and/or with CKD, without increasing the risk of hypokalemia.
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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 | 0.021 | 0.035 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.019 | 0.057 |
| Bibliometrics | 0.005 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".