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Record W4411276022 · doi:10.1681/asn.0000000764

Kidney Parameters with Tirzepatide in Obesity with or without Type 2 Diabetes

2025· article· en· W4411276022 on OpenAlexaff
Hiddo J.L. Heerspink, Allon N. Friedman, Petter Bjornstad, Daniël H. van Raalte, David Z.I. Cherney, Dachuang Cao, Luis‐Emilio García‐Pérez, Adam Stefański, Ibrahim Turfanda, Mathijs C. Bunck, Imane Benabbad, Ryan Griffin, Carolina Piras de Oliveira

Bibliographic record

VenueJournal of the American Society of Nephrology · 2025
Typearticle
Languageen
FieldMedicine
TopicDiet and metabolism studies
Canadian institutionsToronto General HospitalUniversity Health Network
FundersEli Lilly and Company
KeywordsType 2 diabetesObesityMedicineDiabetes mellitusKidneyKidney diseaseInternal medicineEndocrinologyNephrologyUrology

Abstract

fetched live from OpenAlex

Key Points People with obesity and/or type 2 diabetes are at higher risk of progressive kidney function loss. We assessed the association of tirzepatide use with kidney function parameters in people with overweight/obesity with or without type 2 diabetes. Tirzepatide treatment was associated with urine albumin-to-creatinine reduction after 24 weeks, which was sustained through week 72, and no change in eGFR. Background Tirzepatide, a once-weekly, glucose-dependent insulinotropic polypeptide and glucagon-like peptide-1 receptor agonist, showed kidney-protective effects in people with type 2 diabetes at high cardiovascular disease risk. In this post hoc analysis of the SURMOUNT-1 and SURMOUNT-2 trials, we assessed the association of tirzepatide use with kidney function parameters in people with overweight/obesity with or without type 2 diabetes. Methods In SURMOUNT-1, participants with overweight or obesity without type 2 diabetes were randomized to tirzepatide 5, 10, and 15 mg or placebo. In SURMOUNT-2, participants with type 2 diabetes were randomized to tirzepatide 10 and 15 mg or placebo. For this analysis, all tirzepatide groups were pooled in each trial. Assessments included change from baseline to week 72 for urine albumin-to-creatinine ratio (UACR) and eGFR. eGFR was assessed using creatinine-based eGFR, cystatin-C–based eGFR, and creatinine-cystatin-C–based eGFR (Cr-Cys-C-eGFR). Results In SURMOUNT-1 ( N =2539) and SURMOUNT-2 ( N =938), the median (25th–75th percentile) baseline UACR was 6.0 (4.0–11.0) mg/g and 13.0 (6.0–35.1) mg/g, respectively. UACR estimated difference for tirzepatide versus placebo, at week 72 was−8.4% (95% confidence interval [CI], −14.7 to −1.6) for SURMOUNT-1 and −31.1% (95% CI, −40.9 to −19.7) for SURMOUNT-2. The UACR change was more pronounced among participants with baseline UACR ≥30 mg/g with placebo-corrected changes from baseline at week 72 of −42.3% (95% CI, −60.8 to −15.0) in SURMOUNT-1 and −55.2% (95% CI, −68.5 to −36.4) in SURMOUNT-2, respectively. In SURMOUNT-1, tirzepatide was associated with increased eGFR based on cystatin-C–based eGFR or Cr-Cys-C-eGFR estimation equations, with mean differences versus placebo at week 72 of 3.2 ml/min per 1.73 m 2 (95% CI, 2.1 to 4.3) and 1.9 ml/min per 1.73 m 2 (95% CI, 0.9 to 2.9), respectively. In SURMOUNT-2 at week 72, increases in both tirzepatide and placebo groups were observed for Cys-C or Cr-Cys-C-eGFR, with no between-group differences. Conclusions In participants with obesity/overweight with or without type 2 diabetes, tirzepatide was associated with reduced albuminuria without adverse changes in eGFR. Clinical Trial registry name and registration number: SURMOUNT-1: NCT04184622; SURMOUNT-2: NCT04657003.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.013
GPT teacher head0.277
Teacher spread0.264 · 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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Citations17
Published2025
Admission routes1
Has abstractyes

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