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 m2, 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 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 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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 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".