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Record W2282623102 · doi:10.1136/bmj.i610

Dipeptidyl peptidase-4 inhibitors and risk of heart failure in type 2 diabetes: systematic review and meta-analysis of randomised and observational studies

2016· review· en· W2282623102 on OpenAlexafffund
Ling Li, Sheyu Li, Ke Deng, Jiali Liu, Per Olav Vandvik, Pujing Zhao, Longhao Zhang, Jiantong Shen, Małgorzata M Bała, Zahra Sohani, Evelyn M. Wong, Jason W. Busse, Shanil Ebrahim, Germán Málaga, Lorena P Rios, Yingqiang Wang, Qunfei Chen, Gordon Guyatt, Xin Sun

Bibliographic record

VenueBMJ · 2016
Typereview
Languageen
FieldMedicine
TopicDiabetes Treatment and Management
Canadian institutionsMcMaster Children's HospitalHospital for Sick ChildrenUniversity of British ColumbiaMcMaster UniversityUniversity of Toronto
FundersCanadian Institutes of Health ResearchNational Natural Science Foundation of China
KeywordsMedicineObservational studyMeta-analysisOdds ratioType 2 diabetesInternal medicineRandomized controlled trialHeart failureRelative riskPlaceboSitagliptinConfidence intervalCohort studyDiabetes mellitusPathologyEndocrinologyAlternative medicine

Abstract

fetched live from OpenAlex

OBJECTIVES: To examine the association between dipeptidyl peptidase-4 (DPP-4) inhibitors and the risk of heart failure or hospital admission for heart failure in patients with type 2 diabetes. DESIGN: Systematic review and meta-analysis of randomised and observational studies. DATA SOURCES: Medline, Embase, Cochrane Central Register of Controlled Trials, and ClinicalTrials.gov searched up to 25 June 2015, and communication with experts. ELIGIBILITY CRITERIA: Randomised controlled trials, non-randomised controlled trials, cohort studies, and case-control studies that compared DPP-4 inhibitors against placebo, lifestyle modification, or active antidiabetic drugs in adults with type 2 diabetes, and explicitly reported the outcome of heart failure or hospital admission for heart failure. DATA COLLECTION AND ANALYSIS: Teams of paired reviewers independently screened for eligible studies, assessed risk of bias, and extracted data using standardised, pilot tested forms. Data from trials and observational studies were pooled separately; quality of evidence was assessed by the GRADE approach. RESULTS: Eligible studies included 43 trials (n=68,775) and 12 observational studies (nine cohort studies, three nested case-control studies; n=1,777,358). Pooling of 38 trials reporting heart failure provided low quality evidence for a possible similar risk of heart failure between DPP-4 inhibitor use versus control (42/15,701 v 33/12,591; odds ratio 0.97 (95% confidence interval 0.61 to 1.56); risk difference 2 fewer (19 fewer to 28 more) events per 1000 patients with type 2 diabetes over five years). The observational studies provided effect estimates generally consistent with trial findings, but with very low quality evidence. Pooling of the five trials reporting admission for heart failure provided moderate quality evidence for an increased risk in patients treated with DPP-4 inhibitors versus control (622/18,554 v 552/18,474; 1.13 (1.00 to 1.26); 8 more (0 more to 16 more)). The pooling of adjusted estimates from observational studies similarly suggested (with very low quality evidence) a possible increased risk of admission for heart failure (adjusted odds ratio 1.41, 95% confidence interval 0.95 to 2.09) in patients treated with DPP-4 inhibitors (exclusively sitagliptin) versus no use. CONCLUSIONS: The relative effect of DPP-4 inhibitors on the risk of heart failure in patients with type 2 diabetes is uncertain, given the relatively short follow-up and low quality of evidence. Both randomised controlled trials and observational studies, however, suggest that these drugs may increase the risk of hospital admission for heart failure in those patients with existing cardiovascular diseases or multiple risk factors for vascular diseases, compared with no use.

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 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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.640
Threshold uncertainty score0.707

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0100.001
Bibliometrics0.0000.001
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 head0.115
GPT teacher head0.373
Teacher spread0.258 · 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 teacher head, 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".

Quick stats

Citations236
Published2016
Admission routes2
Has abstractyes

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