Renal effectiveness and safety of the sodium-glucose cotransporter-2 inhibitors: a population-based cohort study
Bibliographic record
Abstract
Introduction To assess the comparative effectiveness and safety of renal-related outcomes associated with sodium-glucose cotransporter-2 inhibitors (SGLT2-i) initiation among patients with type 2 diabetes using real-world data. Research design and methods We conducted a population‐based cohort study using administrative healthcare data from Alberta (AB), Canada and primary care data from the Clinical Practice Research Datalink (CPRD), UK. From a cohort of new metformin users, we identified initiators of a SGLT2-i or dipeptidyl peptidase-4 inhibitor (DPP4-i) between January 1, 2014 and March 30, 2018 (AB) or between January 1, 2013 and November 29, 2018 (CPRD). Initiators of an SGLT2-i or DPP4-i were followed until death, disenrolment, therapy discontinuation, or study end date. The effectiveness outcome was renal disease progression, defined as a composite of new-onset macroalbuminuria, serum creatinine doubling with estimated glomerular filtration rate of ≤45 mL/min/1.73 m 2 , renal replacement therapy, hospital admission or death from renal causes. The safety outcome was hospitalization due to acute kidney injury (AKI). We adjusted for confounding using high-dimensional propensity score matching and estimated HRs using Cox proportional hazards regression. Aggregate data from each database were combined by random-effects meta‐analysis. Results Among the 29 465 included patients (20 564 AB, 8901 CPRD), 37.5% were new SGLT2-i users in AB and 21.3% in CPRD. Compared with DPP4 initiators, SGLT2-i initiators were associated with a reduced risk of renal disease progression (pooled HR 0.79, 95% CI 0.62 to 1.00); however, there was no significant difference in the risk of AKI (pooled HR 0.89, 95% CI 0.58 to 1.36). These findings were consistent with other exposure definitions and antidiabetic comparators. Conclusions Our findings support a renoprotective effect of SGLT2-i without an increased risk of AKI, compared with clinically relevant active comparators.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".