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Record W3159780534 · doi:10.1101/2021.03.17.21253796

SGLT2 inhibitors and the risk of diabetic ketoacidosis among adults with Type 2 Diabetes: A systematic review and meta-analysis

2021· review· en· W3159780534 on OpenAlexaff
Michael Colacci, John Fralick, Ayodele Odutayo, Michael Fralick

Bibliographic record

VenuemedRxiv · 2021
Typereview
Languageen
FieldMedicine
TopicDiabetes Treatment and Management
Canadian institutionsSt. Michael's HospitalUniversity of CalgarySinai Health SystemUniversity of Toronto
Fundersnot available
KeywordsDiabetic ketoacidosisMedicineRandomized controlled trialObservational studyRelative riskMeta-analysisInternal medicineDiabetes mellitusPlaceboHazard ratioConfidence intervalInsulinEndocrinology

Abstract

fetched live from OpenAlex

ABSTRACT Importance The risk of diabetic ketoacidosis (DKA) with sodium-glucose cotransporter-2 (SGLT2) inhibitors is unclear. Objective To examine the risk of DKA with SGLT2 inhibitors in both observational studies and large clinical trials. Data Sources Searches of PubMed, EMBASE and CENTRAL (inception to 15 April 2019) without language restrictions; conference proceedings; and reference lists. Study Selection Randomized controlled trials and observational studies that quantified the rate of diabetic ketoacidosis with an SGLT2 inhibitor in comparison to another diabetes medication or placebo. Data Extraction and Synthesis Two independent investigators abstracted study data and assessed the quality of evidence. Data were pooled using random effects models with the Hartung-Knapp-Sidik-Jonkman method. Main Outcome and Measures Absolute event rates and hazard ratios for diabetic ketoacidosis were extracted from each study. Results Seven randomized trials encompassing 42,375 participants and five cohort studies encompassing 318,636 participants were selected. Among the 7 randomized controlled trials, the absolute rate of DKA among patients randomized to an SGLT2 inhibitor ranged from 0.6 to 2.2 events per 1000 person years. Four randomized trials were included in the meta-analysis, and compared to placebo or comparator medication, SGLT2 inhibitors had a 2.4-fold higher risk of DKA (Relative Risk⍰[RR] =⍰2.46 [95% CI, 1.16-5.21]; I2⍰=⍰0%; P⍰= 0.54). Among the 5 observational studies, the absolute rate of DKA associated with SGLT2 inhibitor use ranged from 0.6 to 4.9 per 1000 person years and a 1.7-fold higher rate of DKA compared to another diabetes medication (RR⍰=⍰1.74 [95% CI, 1.01-2.93]; I2⍰=⍰45%; P⍰= 0.12). Conclusions and Relevance In adults with type 2 diabetes, SGLT2 inhibitors increase the risk of DKA in both observational studies and large randomized clinical trials. Registration CRD42019146855 Funding Source None KEY MESSAGES ‐ Case reports and observational studies have suggested that SGLT2 inhibitors may be associated with an increased risk of DKA, but this finding has not been reproduced in older meta-analyses of randomized controlled trials. ‐ In this systematic review and meta-analysis of randomized trials and observational studies including over 350,000 patients, SGLT2 inhibitors were found to be associated with twice the risk of diabetic ketoacidosis versus placebo or a comparator medication. ‐ Patients receiving an SGLT2 inhibitors should be counselled on this risk and provided with appropriate sick-day medication management.

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)0.016
metaresearch head score (Gemma)0.033
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 score0.022
Threshold uncertainty score0.085

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0160.033
Meta-epidemiology (narrow)0.0030.002
Meta-epidemiology (broad)0.0220.036
Bibliometrics0.0080.009
Science and technology studies0.0010.001
Scholarly communication0.0040.002
Open science0.0020.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0030.000

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 head0.024
GPT teacher head0.269
Teacher spread0.244 · 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

Citations2
Published2021
Admission routes1
Has abstractyes

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