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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.027 | 0.004 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".