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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

2022· article· en· W4223640637 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueCirculation · 2022
Typearticle
Languageen
FieldMedicine
TopicPotassium and Related Disorders
Canadian institutionsLunenfeld-Tanenbaum Research InstituteUniversity Health Network
Fundersnot available
KeywordsHyperkalemiaType 2 diabetesKidney diseaseDiabetes mellitusClinical trialDiseaseRisk factor

Abstract

fetched live from OpenAlex

Background: Hyperkalemia increases risk of cardiac arrhythmias and death and limits the use of renin-angiotensin-aldosterone system inhibitors and mineralocorticoid receptor antagonists, which improve clinical outcomes in people with chronic kidney disease 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 chronic kidney disease. 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 or with chronic kidney disease in whom serum potassium levels were routinely measured. The primary outcome was time to serious hyperkalemia, defined as central laboratory–determined 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 and corresponding 95% CIs pooled with random-effects models to obtain summary treatment effects, overall and across key subgroups. Results: Results from 6 trials were included comprising 49 875 participants assessing 4 SGLT2 inhibitors. Of these, 1754 participants developed serious hyperkalemia, and an additional 1119 investigator-reported hyperkalemia events were recorded. SGLT2 inhibitors reduced the risk of serious hyperkalemia (hazard ratio, 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 (hazard ratio, 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, and use of renin-angiotensin-aldosterone system inhibitor, diuretic, and mineralocorticoid receptor antagonist. SGLT2 inhibitors did not increase the risk of hypokalemia (hazard ratio, 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 or with chronic kidney disease without increasing the risk of hypokalemia.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.005
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.368
Threshold uncertainty score0.602

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0050.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.085
GPT teacher head0.301
Teacher spread0.216 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it