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Record W2172438155 · doi:10.1007/s13300-015-0142-y

IDegLira Versus Alternative Intensification Strategies in Patients with Type 2 Diabetes Inadequately Controlled on Basal Insulin Therapy

2015· article· en· W2172438155 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueDiabetes Therapy · 2015
Typearticle
Languageen
FieldMedicine
TopicDiabetes Treatment and Management
Canadian institutionsUniversity of Toronto
FundersNovo Nordisk FondenNovo Nordisk
KeywordsMedicineLiraglutideInsulin glargineInsulin degludecType 2 diabetesInsulin aspartHypoglycemiaInternal medicineInsulinGlycated hemoglobinLixisenatideDiabetes mellitusGlucagon-like peptide 1 receptorEndocrinologyAgonist

Abstract

fetched live from OpenAlex

IDegLira is a once-daily combination of insulin degludec (IDeg) and liraglutide. Trials directly comparing IDegLira with alternative strategies for intensifying basal insulin are ongoing. While awaiting results, this analysis compared indirectly how different strategies affected glycated hemoglobin (HbA1c) and other outcomes. A pooled analysis of five completed Novo Nordisk randomized clinical trials in patients with type 2 diabetes inadequately controlled on basal insulin was used to compare indirectly IDegLira (N = 199) with: addition of liraglutide to basal insulin (N = 225) [glucagon-like peptide-1 receptor agonist (GLP-1RA) add-on strategy]; basal–bolus (BB) insulin [insulin glargine (IGlar) + insulin aspart] (N = 56); or up-titration of IGlar (N = 329). A supplementary analysis was performed with the BB arm including patients who received IGlar or IDeg as basal insulin in the relevant trial (N = 210). All trials had comparable inclusion/exclusion criteria and baseline characteristics. Individual patient-level data were analyzed using multivariable statistical models with potential baseline heterogeneity accounted for using explanatory variables. At end of study, differences between IDegLira and BB or up-titrated IGlar, respectively, were as follows: reduction in HbA1c −0.30%, 95% confidence interval (–0.58; −0.01) and −0.65% (−0.83; −0.47); change in body weight −6.89 kg (−7.92; −5.86) and −4.04 kg (−4.69; −3.40) all in favor of IDegLira. Confirmed hypoglycemia rate was 122.8 (90.7; 166.1), 1060.8 (680.2; 1654.4), and 286.1 (231.1; 354.1) events/100 patient-years for IDegLira, BB, and up-titrated IGlar, respectively. Odds ratios for achieving HbA1c <7.0%, <7.0% without hypoglycemia, and <7.0% without hypoglycemia and no weight gain were greater with IDegLira versus up-titrated IGlar. The supplementary analysis yielded similar results to the main analysis. Results with IDegLira were similar to those for the ‘GLP-1RA add-on’ arm. These results suggest that IDegLira may be more effective, with lower hypoglycemia rates and less weight gain, than up-titrated basal insulin or BB in patients uncontrolled on basal insulin.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.159
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.043
GPT teacher head0.278
Teacher spread0.235 · 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