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Record W2913306188 · doi:10.1136/bmjopen-2018-022577

Comparative safety of the sodium glucose co-transporter 2 (SGLT2) inhibitors: a systematic review and meta-analysis

2019· review· en· W2913306188 on OpenAlexafffund
Jennifer Donnan, Catherine Grandy, Eugene Chibrikov, Carlo A. Marra, Kris Aubrey‐Bassler, Karissa Johnston, Michelle Swab, Jenna Haché, Daniel Curnew, Hai V. Nguyen, John‐Michael Gamble

Bibliographic record

VenueBMJ Open · 2019
Typereview
Languageen
FieldMedicine
TopicDiabetes Treatment and Management
Canadian institutionsUniversity of WaterlooMemorial University of Newfoundland
FundersNewfoundland and Labrador Centre for Applied Health ResearchCanadian Diabetes Association
KeywordsDapagliflozinMedicineCanagliflozinEmpagliflozinRelative riskInternal medicinePlaceboMeta-analysisDiabetic ketoacidosisAcute kidney injuryRandomized controlled trialSubgroup analysisDiabetes mellitusType 2 diabetesConfidence intervalEndocrinologyInsulin

Abstract

fetched live from OpenAlex

Objective To estimate the association between the use of sodium glucose co-transporter-2 (SGLT2) inhibitors and postmarket harms as identified by drug regulatory agencies. Design We conducted a systematic review and meta-analysis of randomised controlled trials (RCT). Six large databases were searched from inception to May 2018. Random effects models were used to estimate pooled relative risks (RRs). Intervention SGLT2 inhibitors, compared with placebo or active comparators. Primary outcomes Acute kidney injury (AKI), diabetic ketoacidosis (DKA), urinary tract infections (UTI), bone fractures and lower limb amputations. Results We screened 2418 citations of which 109 were included. Most studies included one of four SGLT2 inhibitors, dapagliflozin, canagliflozin, empagliflozin and ipragliflozin. When compared with placebo, SGLT2 inhibitors were found to be significantly protective against AKI (RR=0.59; 95% CI 0.39 to 0.89; I2=0.0%), while no difference was found for DKA (RR 0.66; 95% CI 0.30 to 1.45, I2=0.0%), UTI (RR 1.02; 95% CI 0.95 to 1.09, I2=0.0%) or bone fracture (RR 0.87; 95% CI 0.69 to 1.09, I2=1.3%). Three studies reported on amputation, with one finding a significant increase risk. No increased risk for either outcome was found when compared with active controls. Subgroup analysis did show an increased risk of UTI with dapagliflozin only (RR 1.21; 95% CI 1.02 to 1.43, I2=0.0%), but no other analysis supported an increased risk of AKI, DKA, UTI or fracture. Conclusions Current evidence from RCTs does not suggest an increased risk of harm with SGLT2 inhibitors as a class over placebo or active comparators with respect to AKI, DKA, UTI or fracture. However, wide CIs for many comparisons suggest limited precision, and therefore clinically important adverse events cannot be ruled out. Dapagliflozin, appears to independently increase the risk of UTI, although the mechanism for this intraclass variation in risk is unclear. PROSPERO registration number CRD42016038715.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.019
metaresearch head score (Gemma)0.048
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: Meta-analysis
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.027
Threshold uncertainty score0.103

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0190.048
Meta-epidemiology (narrow)0.0030.002
Meta-epidemiology (broad)0.0270.035
Bibliometrics0.0080.007
Science and technology studies0.0010.001
Scholarly communication0.0040.002
Open science0.0020.001
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.0040.000

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 head0.230
GPT teacher head0.455
Teacher spread0.225 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designMeta-analysis
Domainnot available
GenreReview

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".

Quick stats

Citations219
Published2019
Admission routes2
Has abstractyes

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