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Record W4399687969 · doi:10.2337/db24-120-or

120-OR: Efficacy of Tirzepatide in Achieving the Composite Endpoints of Glycemic, Blood Pressure, and Lipid Goals in SURMOUNT-2

2024· article· en· W4399687969 on OpenAlexaboutno aff
Naveed Sattar, ALICE Y.Y. CHENG, Imane Benabbad, Clare J. Lee, Sophia Kyoungah See, John Leech, Donna Mojdami

Bibliographic record

VenueDiabetes · 2024
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicEicosanoids and Hypertension Pharmacology
Canadian institutionsnot available
Fundersnot available
KeywordsGlycemicMedicineBlood pressureInternal medicineIntensive care medicineDiabetes mellitusEndocrinology

Abstract

fetched live from OpenAlex

In the SURMOUNT-2 (SM-2) trial of adults with overweight/obesity and type 2 diabetes (T2D), tirzepatide (TZP), a once weekly GIP/GLP-1 receptor agonist, significantly reduced body weight (BW) in conjunction with a reduced calorie diet and increased physical activity. This post-hoc analysis assessed the proportion of participants achieving composite endpoints of BP <130/80 mm Hg, non-HDL <130 mg/dl, and three HbA1c thresholds of <7%, < 6.5% and <5.7% at 72 weeks. Logistic regression with missing value imputed by mixed model repeated measures, using the efficacy estimand, assessed participants who achieved the composite endpoints, in the 10mg (N=312) or 15mg (N=311) TZP groups, versus placebo (PBO) (N=315). Overall baseline mean BW was 100.7 kg, BMI 36.1kg/m2, HbA1c 8.02%, BP 130.5/79.8 mm Hg and non-HDL 132.5 mg/dl. For 15mg TZP, 33.8%, 32.8%, and 25.9% of participants achieved the composite endpoints versus 7.5%, 3.9%, and 0.7% of PBO at 72 weeks (Fig). Findings for the TZP 10mg group were similar to those observed in the 15mg group. In people with T2D and overweight/obesity, higher proportion of participants receiving TZP achieved clinically meaningful composite endpoints, which included BP, lipids and HbA1c goals compared to PBO. This suggests that TZP can help achieve multiple clinical goals, in addition to meaningful weight loss, important for improving cardiometabolic health. Disclosure N. Sattar: Other Relationship; Abbott, Amgen Inc., AstraZeneca, Boehringer-Ingelheim, Eli Lilly and Company, AbbVie Inc. Consultant; Menarini-Ricerche. Other Relationship; Novartis AG, Novo Nordisk, Pfizer Inc., Roche Diagnostics, American Diabetes Association, Medscape. A.Y.Y. Cheng: Advisory Panel; Abbott. Speaker's Bureau; Amgen Inc., AstraZeneca, Bausch Health. Advisory Panel; Bayer Inc. Speaker's Bureau; Abbott, Bayer Inc. Research Support; Applied Therapeutics Inc. Advisory Panel; Boehringer-Ingelheim. Speaker's Bureau; Boehringer-Ingelheim, Dexcom, Inc. Advisory Panel; Dexcom, Inc., Eli Lilly and Company. Speaker's Bureau; Eli Lilly and Company. Advisory Panel; Eisai Inc. Speaker's Bureau; GlaxoSmithKline plc. Advisory Panel; HLS Therapeutics Inc. Speaker's Bureau; HLS Therapeutics Inc., Insulet Corporation. Advisory Panel; Insulet Corporation, Janssen Pharmaceuticals, Inc. Speaker's Bureau; Janssen Pharmaceuticals, Inc., Medtronic. Advisory Panel; Novo Nordisk. Speaker's Bureau; Novo Nordisk. Research Support; Novo Nordisk. Speaker's Bureau; Pfizer Inc. Advisory Panel; Sanofi. Speaker's Bureau; Sanofi. Research Support; Sanofi. Advisory Panel; Takeda Canada, AstraZeneca, Sanofi. Consultant; Abbott, AstraZeneca, Bayer Inc., Boehringer-Ingelheim, Dexcom, Inc., Eisai Inc., Eli Lilly and Company, Insulet Corporation, HLS Therapeutics Inc., Janssen Pharmaceuticals, Inc., Novo Nordisk, Sanofi, Takeda Pharmaceutical Company Limited. I. Benabbad: Employee; Eli Lilly and Company. C. Lee: Employee; Eli Lilly and Company. Stock/Shareholder; Eli Lilly and Company. S. See: Employee; Eli Lilly and Company. J. Leech: Employee; Eli Lilly and Company. D. Mojdami: Employee; Eli Lilly and Company.

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)0.001
metaresearch head score (Gemma)0.001
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 score0.006
Threshold uncertainty score0.021

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0060.001

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 head0.010
GPT teacher head0.262
Teacher spread0.253 · 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".

Quick stats

Citations0
Published2024
Admission routes1
Has abstractyes

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