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Record W2905361067 · doi:10.1111/dom.13613

The effects of incretin‐based therapies on β‐cell function and insulin resistance in type 2 diabetes: A systematic review and network meta‐analysis combining 360 trials

2018· review· en· W2905361067 on OpenAlexaff
Shanshan Wu, Le Gao, Andrea Cipriani, Yi Huang, Zhirong Yang, Jun Yang, Shuqing Yu, Yuan Zhang, Sanbao Chai, Zilu Zhang, Feng Sun, Siyan Zhan

Bibliographic record

VenueDiabetes Obesity and Metabolism · 2018
Typereview
Languageen
FieldMedicine
TopicDiabetes Treatment and Management
Canadian institutionsMcMaster University
FundersChina Scholarship CouncilCambridge TrustNational Natural Science Foundation of ChinaNational Institute for Health and Care Research
KeywordsMedicineIncretinInsulin resistanceType 2 diabetesInternal medicinePlaceboMeta-analysisSubgroup analysisCochrane LibraryLixisenatideInsulinRandomized controlled trialDiabetes mellitusConfidence intervalSitagliptinExenatideGastroenterologyEndocrinologyPathology

Abstract

fetched live from OpenAlex

AIM: To evaluate the comparative effects of incretin-based therapies, including glucagon-like peptide-1 receptor agonists (GLP-1 RAs) and dipeptidyl peptidase-4 inhibitors (DPP-4Is), on β-cell function and insulin resistance in patients with type 2 diabetes mellitus (T2DM). MATERIALS AND METHODS: Medline, Embase, the Cochrane Library and www.clinicaltrials.gov were searched for randomized controlled trials (RCTs) with a duration of at least 4 weeks. Network meta-analysis was performed, followed by subgroup analysis and meta-regression. The Grading of Recommendations Assessment, Development and Evaluation (GRADE) system was used to assess the quality of evidence. Outcomes of interest include homeostasis model assessment for β cell function (HOMA-β) and insulin resistance (HOMA-IR), fasting C-peptide and fasting plasma glucose (FPG). Weighted mean difference (WMD) with 95% confidence interval (CI) was calculated as the measure of effect size. RESULTS: A total of 360 RCTs (74% at least double-blinded) with 157 696 patients were included. Incretin-based therapies were compared with six other classes of glucose-lowering drugs or with placebo. Compared with placebo, a significant increase in HOMA-β and fasting C-peptide was detected for GLP-1RAs (WMD = 20.31 [95% CI, 16.34-24.39] with low quality; WMD = 0.16 ng/mL [95% CI, 0.03-0.29] with low quality) and for DPP-4Is (WMD = 9.90 [95% CI, 8.27-11.61] with moderate quality; WMD = 0.09 ng/mL [95% CI, 0.04-0.14] with moderate quality) separately, while a significant reduction in HOMA-IR and FPG were found in favour of GLP-1RAs (WMD = -0.67 [95% CI, -1.08 to -0.27] with low quality; WMD = -1.04 mmol/L [95% CI, -1.26 to -0.83] with moderate quality) and DPP-4Is (WMD = -0.23 [95% CI, -0.38 to -0.08] with low quality; WMD = -0.77 mmol/L [95% CI, -0.98 to -0.57] with moderate quality), respectively. CONCLUSIONS: Incretin-based therapies not only show an increase in HOMA-β and fasting C-peptide level, but also achieve a reduction in HOMA-IR and FPG in comparison with placebo. Although GRADE scores indicate low to moderate for most comparisons, incretin-based therapies seem to be an advisable option for long-term treatment to preserve β-cell function.

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)0.019
metaresearch head score (Gemma)0.032
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: Meta-analysis
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.025
Threshold uncertainty score0.098

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0190.032
Meta-epidemiology (narrow)0.0030.002
Meta-epidemiology (broad)0.0250.048
Bibliometrics0.0080.009
Science and technology studies0.0010.001
Scholarly communication0.0030.002
Open science0.0020.002
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.0030.000

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 head0.035
GPT teacher head0.290
Teacher spread0.255 · 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 designMeta-analysis
Domainnot available
GenreReview

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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Citations46
Published2018
Admission routes1
Has abstractyes

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