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Record W7018083825

Comparative effectiveness of oral antihyperglycemic agents in patients with diabetes and chronic kidney disease

2018· dissertation· en· W7018083825 on OpenAlexafffundabout

Bibliographic record

VenueMspace (University of Manitoba) · 2018
Typedissertation
Languageen
FieldMedicine
TopicDiabetes Treatment and Management
Canadian institutionsUniversity of Manitoba
FundersCanadian Frailty Network
KeywordsMetforminKidney diseaseDiabetes mellitusGlycemicType 2 diabetesPropensity score matchingCreatinine
DOInot available

Abstract

fetched live from OpenAlex

We sought to compare the safety of sulfonylureas to other oral antihyperglycemic agents (OHAs) in patients with type 2 diabetes (T2DM) and examine whether chronic kidney disease (CKD) is an effect modifier. Using Manitoba Center for Health Policy data, we identified adults with an incident OHA prescription between 2006 and 2016 (monotherapy; add-on to metformin [combotherapy]), and a serum creatinine test. We conducted comparisons with Cox models in propensity score matched cohorts. In 1,777 matched monotherapy pairs, sulfonylureas were associated with all-cause mortality (HR 1.44; 95% CI 1.05 – 1.97) vs. metformin where CKD was an effect modifier (p<0.001) as sulfonylureas performed worse in patients without CKD. In 1,266 matched combotherapy pairs, sulfonylureas were associated with all-cause mortality (HR 2.40; 95% CI 1.15 – 5.02) vs. other OHAs. CKD was not an effect modifier for other comparisons. Our evidence supports metformin as monotherapy, and discourages sulfonylureas as add-on therapy for glycemic control.

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)0.005
metaresearch head score (Gemma)0.011
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.006
Threshold uncertainty score0.024

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.011
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.011
GPT teacher head0.226
Teacher spread0.215 · 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 designSystematic review
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

Citations0
Published2018
Admission routes3
Has abstractyes

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