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Record W2809166521 · doi:10.2337/db18-1052-p

Real-World Health Outcomes of Insulin Glargine 300 U/mL (Gla-300) vs. Insulin Glargine 100 U/mL (Gla-100) in Patients with Type 1 (T1D) and Type 2 Diabetes (T2D) in the Canadian LMC Diabetes Patient Registry—The REALITY Study

2018· article· en· W2809166521 on OpenAlexaboutno aff
Alexander Abitbol, Ruth E. Brown, Dishay Jiandani, Luc Sauriol, Ronnie Aronson

Bibliographic record

VenueDiabetes · 2018
Typearticle
Languageen
FieldMedicine
TopicDiabetes Treatment and Management
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineHypoglycemiaInternal medicineInsulin glargineInsulinEndocrinologyType 2 diabetesInsulin detemirBasal (medicine)Diabetes mellitusType 1 diabetesCohortWeight lossObesity

Abstract

fetched live from OpenAlex

This retrospective cohort study evaluates real-world health outcomes in patients with T1D and T2D initiating Gla-300 or Gla-100 as part of their usual therapy in the largest specialist-led clinic group in Canada, between January 2015 and August 2017. The primary outcome was HbA1c change at 3-6 months. Four separate cohorts were evaluated. In the T1D cohort, 299 patients transferred from Gla-100 to Gla-300 had a significant HbA1c reduction of -0.2 ± 1.2%, with no change in weight, hypoglycemia or basal insulin dose (Table). Similarly, 488 patients with T2D transferred from Gla-100 to Gla-300 had a significant HbA1c reduction of -0.47 ± 1.37%, with no change in weight, hypoglycemia or basal insulin dose. In patients with T2D transferred from NPH or detemir (n=343), Gla-300 had a significantly greater reduction in HbA1c than Gla-100 (-0.30 ± 2.2%), with no change in weight, hypoglycemia or basal insulin dose in either group. For insulin-naïve T2D patients (n=1448), there were no significant differences between Gla-300 and Gla-100 in adjusted HbA1c or weight. Patients with T1D and T2D in a national specialist-led registry, who transferred from their usual basal insulin to Gla-300, significantly reduced their HbA1c, without increasing weight, basal insulin dose, nor hypoglycemia incidence. Disclosure A. Abitbol: Research Support; Self; JDRF, JA DeSeve Foundation, Lexicon Pharmaceuticals, Inc., Sanofi. Speaker's Bureau; Self; Sanofi. Research Support; Self; GlaxoSmithKline plc., Merck & Co., Inc.. Consultant; Self; Merck & Co., Inc.. Speaker's Bureau; Self; Merck & Co., Inc.. Research Support; Self; Novo Nordisk Inc.. Consultant; Self; Novo Nordisk Inc.. Speaker's Bureau; Self; Novo Nordisk Inc.. Research Support; Self; Pfizer Inc., AstraZeneca. Consultant; Self; AstraZeneca. Speaker's Bureau; Self; AstraZeneca. Research Support; Self; Senseonics, Gilead Sciences, Inc.. Speaker's Bureau; Self; Amgen Inc., Janssen Pharmaceuticals, Inc.. Consultant; Self; Janssen Pharmaceuticals, Inc.. Employee; Self; LMC Diabetes & Endocrinology. Speaker's Bureau; Self; LMC Diabetes & Endocrinology, Valeant Pharmaceuticals International, Inc.. Consultant; Self; Valeant Pharmaceuticals International, Inc.. R.E. Brown: None. D. Jiandani: None. L. Sauriol: Employee; Self; Sanofi. R. Aronson: Other Relationship; Self; Novo Nordisk Inc., Janssen Pharmaceuticals, Inc., Sanofi, AstraZeneca. Research Support; Self; Eli Lilly and Company, Becton, Dickinson and Company, Merck & Co., Inc., Senseonics, Boehringer Ingelheim Pharmaceuticals, Inc..

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)0.003
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 score0.342
Threshold uncertainty score0.688

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.002
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.016
GPT teacher head0.269
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
Published2018
Admission routes1
Has abstractyes

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