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Record W3158972764 · doi:10.1210/jendso/bvab048.838

Efficacy and Safety of SGLT2 Inhibitors in Diabetic Kidney Transplant Patients: Review of the Current Literature

2021· article· en· W3158972764 on OpenAlexaffabout
Shirley Shuster, Zeyana Al-Hadhrami, Sara Awad, Sarah Moore, Khaled Shamseddin

Bibliographic record

VenueJournal of the Endocrine Society · 2021
Typearticle
Languageen
FieldMedicine
TopicDiabetes Treatment and Management
Canadian institutionsKingston Health Sciences CentreQueen's University
Fundersnot available
KeywordsMedicineEmpagliflozinCanagliflozinRenal functionKidney diseaseInternal medicineDapagliflozinPopulationDiabetes mellitusGlycemicUrologyType 2 diabetesEndocrinology

Abstract

fetched live from OpenAlex

Abstract Introduction: SGLT2 inhibitors are oral hypoglycemic medications used in type 2 diabetes mellitus (T2DM). They act by blocking glucose and sodium reabsorption in the proximal renal tubules. In patients with T2DM and cardiovascular disease, SGLT2 inhibitors have been shown to improve glycemic control, promote weight loss, and reduce major adverse cardiovascular events (MACE). They have also been shown to have favorable renal outcomes in patients with chronic kidney disease (CKD) reducing albuminuria and progression to end-stage renal disease; however, all studies have excluded kidney transplant patients. The objective of this review was to determine the efficacy and safety of SGLT2 inhibitors in the kidney transplant population. Methods: We conducted a literature review to identify studies which assessed the use of SGLT2 inhibitors in kidney transplant patients with either T2DM or new onset diabetes after transplant (NODAT). The outcomes assessed included blood pressure, glycemic control, body weight, kidney function, proteinuria and complications. Results: Nine studies, which included 144 patients, were extracted for review. These included x4 case series, x3 cohort studies, x1 randomized control trial (RCT), and x1 case report. The largest study was a prospective RCT from Norway, which assessed empagliflozin versus placebo in 44 patients. Majority of patients had NODAT (n=92) or T2DM (n=50). All patients had estimated glomerular filtration rate (eGFR) >30mL/min/1.73m2 and HbA1C >6.5%. The most commonly used SGLT2 inhibitors were empagliflozin (n=82), canagliflozin (n=34), and dapagliflozin (n=28). SGLT2 inhibitor use in kidney transplant patients was found to demonstrate a small or non-significant reduction in blood pressure, modest improvement in glycemic control and decrease in insulin resistance, and moderate-to-significant weight reduction. It also resulted in stable graft function and one study demonstrated a reduction in proteinuria. The most common adverse effect was urinary tract infection (n=13). There were no cases of diabetic ketoacidosis or development of new ischemic lower limb ulcerations or amputations. Conclusion: Our literature review suggests beneficial outcomes of SGLT2 inhibitor use in diabetic kidney transplant patients, with no significant adverse effects or complications. Given the limited evidence in this population, we are launching a prospective study in kidney transplant patients with either T2DM or NODAT, and with eGFR ≥30mL/min/1.73m2, to assess the efficacy and safety of SGLT2 inhibitor use in this population. To our knowledge, this will be the first prospective study in Canada assessing SGLT2 inhibitor use in diabetic kidney transplant patients.

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)0.003
metaresearch head score (Gemma)0.010
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.007
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.010
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0050.003
Bibliometrics0.0070.009
Science and technology studies0.0000.001
Scholarly communication0.0020.002
Open science0.0020.001
Research integrity0.0010.001
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 head0.006
GPT teacher head0.249
Teacher spread0.243 · 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 designSystematic review
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

Citations0
Published2021
Admission routes2
Has abstractyes

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