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Record W4379260635 · doi:10.1007/s13300-023-01423-3

Real-World Effects of Second-Generation Versus Earlier Intermediate/Basal Insulin Analogues on Rates of Hypoglycemia in Adults with Type 1 and 2 Diabetes (iNPHORM, US)

2023· article· en· W4379260635 on OpenAlexaff
Jason Black, Stewart B. Harris, Bridget Ryan, Guangyong Zou, Alexandria Ratzki‐Leewing

Bibliographic record

VenueDiabetes Therapy · 2023
Typearticle
Languageen
FieldMedicine
TopicDiabetes Management and Research
Canadian institutionsRobarts Clinical TrialsWestern University
FundersSanofi Pasteur
KeywordsMedicineHypoglycemiaBasal (medicine)Diabetes mellitusBasal insulinInternal medicineInsulinType 1 diabetesEndocrinologyType 2 diabetes

Abstract

fetched live from OpenAlex

INTRODUCTION: Second-generation basal insulin analogues have been shown to reduce hypoglycemia in several trials and observational studies of select populations; however, it remains unclear whether these results persist in real-world settings. Using self-reported hypoglycemia events, we assessed whether second-generation basal insulin analogues reduce rates of hypoglycemia events (non-severe/severe; overall/daytime/nocturnal) compared to earlier intermediate/basal insulin analogues among people with insulin-treated type 1 or 2 diabetes. METHODS: We used prospectively collected data from the Investigating Novel Predictions of Hypoglycemia Occurrence Using Real-World Models (iNPHORM) panel survey. This US-wide, 1-year internet-based survey assessed hypoglycemia experiences and related sociodemographic and clinical characteristics of people with diabetes (February 2020-March 2021). We estimated population-average rate ratios for hypoglycemia comparing second-generation to earlier intermediate/basal insulin analogues using negative binomial regression, adjusting for confounders. Within-person variability of repeated observations was addressed with generalized estimating equations. RESULTS: Among iNPHORM participants with complete data, N = 413 used an intermediate/basal insulin analogue for ≥ 1 month during follow-up. After adjusting for baseline and time-updated confounders, average second-generation basal insulin analogue users experienced a 19% (95% CI 3-32%, p = 0.02) lower rate of overall non-severe hypoglycemia and 43% (95% CI 26-56%, p < 0.001) a lower rate of nocturnal non-severe hypoglycemia compared to earlier intermediate/basal insulin users. Overall severe hypoglycemia rates were similar among second-generation and earlier intermediate/basal insulin users (p = 0.35); however, the rate of severe nocturnal hypoglycemia was reduced by 44% (95% CI 10-65%, p = 0.02) among second-generation insulin users compared to earlier intermediate/basal insulin users. CONCLUSION: Our real-world results suggest second-generation basal insulin analogues reduce rates of hypoglycemia, especially nocturnal non-severe and severe events. Whenever possible and feasible, clinicians should prioritize prescribing these agents over first-generation basal or intermediate insulin in people with type 1 and 2 diabetes.

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)0.007
metaresearch head score (Gemma)0.016
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 score0.009
Threshold uncertainty score0.039

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.016
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
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 head0.023
GPT teacher head0.294
Teacher spread0.271 · 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

Citations5
Published2023
Admission routes1
Has abstractyes

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