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Abstract 4118762: Large-scale multinational trends in the use of cardioprotective antihyperglycemic agents as first-line therapy in patients with type 2 diabetes and cardiovascular disease: a LEGEND-T2DM study

2024· article· en· W4404324549 on OpenAlexaff
Phyllis Thangaraj, Arya Aminorroaya, Lovedeep Dhingra, Aline Pedroso Camargos, Jin Zhou, Clair Blacketer, Fan Bu, Yi Chai, Shounak Chattopadhyay, David A Dorr, Talita Duarte‐Salles, Wallis C. Y. Lau, Yuntian Liu, Yuan Lu, Kenneth K. C. Man, Evan Minty, Lauren Richter, Joseph S. Ross, Nigam H. Shah, Patrick Ryan, Martijn J. Schuemie, George Hripcsak, Harlan M. Krumholz, Marc A. Suchard, Rohan Khera

Bibliographic record

VenueCirculation · 2024
Typearticle
Languageen
FieldMedicine
TopicDiabetes Management and Research
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsMedicineDiseaseDiabetes mellitusType 2 diabetesType 2 Diabetes MellitusInternal medicineFirst lineTraditional medicineEndocrinology

Abstract

fetched live from OpenAlex

Background: US guidelines for type 2 diabetes (T2DM) recommend metformin as first-line anti-hyperglycemic therapy (AHT), but prioritizing the use of AHTs that reduce cardiovascular disease (CVD) risk – GLP1-RAs and SGLT2is – is increasingly suggested for people with CVD. We examine the multinational use patterns of GLP1-RAs, SGLT2is, DPP4is, and sulfonylureas (SUs) as first-line therapies for patients with CVD. Methods: In 10 US and 6 non-US databases between 2016 and 2021 mapped to a common data model [A], we measured yearly initiation of GLP1-RAs, SGLT2is, DPP4is, and SUs as first-line AHTs in patients with T2DM with and without CVD [B]. We also compared the initiation of the drug classes as second-line after metformin. We calculated the annual rate of change in proportional initiation of each drug class as first-line AHT and assessed differences in trends as group x time interactions in linear mixed models. Results: Across all data sources, 3.3 million patients with T2DM used GLP1-RAs, SGLT2is, DPP4is, or SUs as first-line AHTs, and 3.9m initiated these drug classes as second-line AHT after metformin. Within the first-line cohort, 1.4m (41%) had established CVD compared with 1.2m (31%) in the second-line cohort. For GLP1-RAs and SGLT2is, the annual rate of their relative use as first-line agents increased among patients with T2DM with CVD (GLP1RAs: ranging 1.3-5.4% in US [C] and 0.3-0.8% in non-US [D], SGLT2is: 2.1-12.9% in US [E] and 8.1-10.6% in non-US databases [F]). There was a larger relative increase in the use of SGLT2i and a smaller increase in GLP1RA use in CVD vs non-CVD cohorts (P interaction <.001). While there was a larger increase in GLP1RAs uptake in the US cohorts, SGLT2i use increased more in non-US cohorts ([C-F], P interaction <.001 for all, except .01 for SGLT2i). Of note, across cohorts, the uptake of GLP1RA and SGLT2i as first-line was higher than second-line use among those with CVD (P interaction <.001). In contrast, DPP4i and SU use as first-line was lower than GLP1RA and SGLT2is and decreased over time (P<.001). Conclusions: In a large-scale multinational, federated cohort of patients with T2DM, the use of cardioprotective agents increased as first-line AHT, with variation in SGLT2i and GLP1RAs uptake across study cohorts.

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)0.005
metaresearch head score (Gemma)0.008
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 score0.047
Threshold uncertainty score0.093

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.008
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0010.005
Science and technology studies0.0010.000
Scholarly communication0.0020.001
Open science0.0020.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.001

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 head0.041
GPT teacher head0.290
Teacher spread0.249 · 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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Citations0
Published2024
Admission routes1
Has abstractyes

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