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Record W4404244341 · doi:10.1177/20543581241293202

Single Center Experience With Sodium-Glucose Co-Transporter-2 Inhibitors (SGLT2i) in Kidney Transplant Recipients With Diabetes

2024· article· en· W4404244341 on OpenAlexaff
Albi Angjeli, Tess Montada-Atin, Rosane Nisenbaum, Niki Dacouris, Michelle M. Nash, G. V. Ramesh Prasad, Jeffrey S. Zaltzman

Bibliographic record

VenueCanadian Journal of Kidney Health and Disease · 2024
Typearticle
Languageen
FieldMedicine
TopicRenal Transplantation Outcomes and Treatments
Canadian institutionsUniversity of TorontoSt. Michael's Hospital
Fundersnot available
KeywordsMedicineDiabetes mellitusSodiumTransporterInternal medicineKidney transplantationSingle CenterNephrologyTransplantationUrologyEndocrinologyBiochemistryChemistry

Abstract

fetched live from OpenAlex

Background: Sodium-glucose co-tranporter-2 inhibitors have been shown to be safe and effective in patients with type 2 diabetes for improving glycemia. Furthermore large, randomized control trials have shown cardiovascular and renal benefits. However, limited safety and efficacy data is available in kidney transplant patients with diabetes. Objective: To investigate the safety and efficacy of SGLT2i use on stability of renal function in adult kidney transplant recipients (KTR) with type 2 diabetes mellitus (DM2) or New Onset Diabetes After Transplantation (NODAT). Design: We performed a single center, retrospective cohort study pre- and post-SGLT2i exposure. Patients: Adults with DM2 or NODAT who received a living or deceased kidney transplant (Tx) and started on an SGLT2i post-Tx were reviewed. Patients who had type 1 diabetes were excluded. Measurements and Methods: The baseline was the SGLT2i start date. We reviewed available data from 24 months (M) before and after SGLT2i initiation. The primary endpoints were the effects of SGLT2i use on stability of renal function using serum creatinine and eGFR, change in urine albumin excretion(uACR), and glycosylated hemoglobin (A1C). Secondary endpoints compared blood pressure, body mass index and adverse reactions at baseline and quarterly after SGLT2i initiation. Results: 125 KTRs were included in cohort: NODAT (52, 42%), DM2 (73, 58%); female (33, 27%); mean age at Tx 55 years (25-75); LD (56, 45%), DD (69, 55%); mean duration of Tx (6.8 years, 0.1-42.5); study follow-up (1.8 years, 0.3-4.9). The mean eGFR remained stable pre-SGLT2i at 64.6 mL/min/1.73m 2 , vs post at 64.3 mL/min/1.73m 2 . There was no difference in mean A1C after SGLT2i initiation. The slope of uACR using natural log transformation pre-SGLT2i compared with post-SGLT2i slope reduced from +0.7 (0.03, 0.11) to -0.04 (-0.01, -0.35) mg/mmol/3mths ( P = .002). The risk of developing new genital mycotic infections among all patients was 4% (95% CI 1.3%-9.1%) While there was no significant difference in UTI before (13.6%) and after (12%) SGLT2i use ( P = .68), there was a higher risk of UTI seen in patients with a previous history of UTI (23.5%) vs no previous history (10.2%) post initiation. There was no significant increase in AKI pre 8%, post 10.4%, P = .51. There was a single DKA event pre- and post-SGLT2. Limitations: The limitations of this study include its retrospective nonrandomized nature. Conclusion: In this retrospective analysis, SGLT2i use in KTR appears to be safe and efficacious with stable renal function and glycemic control, alongside improvements in uACR. There was a low risk of new genital yeast infections after SGLT2i start. UTI occurrence was higher in patients with a previous history of UTI compared with those with no previous history.

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)0.002
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.015
GPT teacher head0.270
Teacher spread0.255 · 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 designObservational
Domainnot available
GenreEmpirical

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".

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Citations1
Published2024
Admission routes1
Has abstractyes

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