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Record W3093635194 · doi:10.2337/dbi20-0040

SGLT2 Inhibition for CKD and Cardiovascular Disease in Type 2 Diabetes: Report of a Scientific Workshop Sponsored by the National Kidney Foundation

2020· review· en· W3093635194 on OpenAlexfundno aff
Katherine R. Tuttle, Frank C. Brosius, Matthew A. Cavender, Paola Fioretto, Kevin Fowler, Hiddo J.L. Heerspink, Tom Manley, Darren K. McGuire, Mark E. Molitch, Amy K. Mottl, Leigh Perreault, Sylvia E. Rosas, Peter Rossing, Laura Solá, Volker Vallon, Christoph Wanner, Vlado Perkovic

Bibliographic record

VenueDiabetes · 2020
Typereview
Languageen
FieldMedicine
TopicDiabetes Treatment and Management
Canadian institutionsnot available
FundersCenters for Disease Control and PreventionNational Institutes of HealthDuke Clinical Research InstituteEisaiAstellas PharmaNovo NordiskSteno Diabetes Center CopenhagenEdwards LifesciencesProvidence Health CareIronwood Pharmaceuticals, IncorporatedBoston Scientific CorporationBristol-Myers SquibbEli Lilly and CompanyAstraZenecaCSL BehringGilead SciencesBayer HealthCareNational Institute of Diabetes and Digestive and Kidney DiseasesSanofiEsperion TherapeuticsGlaxoSmithKlineAmgenPfizerUniversity of Michigan
KeywordsFoundation (evidence)MedicineType 2 diabetesDiabetes mellitusDiseaseIntensive care medicineKidney diseaseInternal medicineEndocrinologyPolitical scienceLaw

Abstract

fetched live from OpenAlex

Diabetes is the most frequent cause of chronic kidney disease (CKD), leading to nearly half of all cases of kidney failure requiring replacement therapy. The principal cause of death among patients with diabetes and CKD is cardiovascular disease (CVD). Sodium/glucose cotransporter 2 (SGLT2) inhibitors were developed to lower blood glucose levels by inhibiting glucose reabsorption in the proximal tubule. In clinical trials designed to demonstrate the CVD safety of SGLT2 inhibitors in type 2 diabetes mellitus (T2DM), consistent reductions in risks for secondary kidney disease end points (albuminuria and a composite of serum creatinine doubling or 40% estimated glomerular filtration rate decline, kidney failure, or death), along with reductions in CVD events, were observed. In patients with CKD, the kidney and CVD benefits of canagliflozin were established by the CREDENCE (Canagliflozin and Renal Events in Diabetes With Established Nephropathy Clinical Evaluation) trial in patients with T2DM, urinary albumin-creatinine ratio >300 mg/g, and estimated glomerular filtration rate of 30 to <90 mL/min/1.73 m2. To clarify and support the role of SGLT2 inhibitors for treatment of T2DM and CKD, the National Kidney Foundation convened a scientific workshop with an international panel of more than 80 experts. They discussed the current state of knowledge and unanswered questions in order to propose therapeutic approaches and delineate future research. SGLT2 inhibitors improve glomerular hemodynamic function and are thought to ameliorate other local and systemic mechanisms involved in the pathogenesis of CKD and CVD. SGLT2 inhibitors should be used when possible by people with T2DM to reduce risks for CKD and CVD in alignment with the clinical trial entry criteria. Important risks of SGLT2 inhibitors include euglycemic ketoacidosis, genital mycotic infections, and volume depletion. Careful consideration should be given to the balance of benefits and harms of SGLT2 inhibitors and risk mitigation strategies. Effective implementation strategies are needed to achieve widespread use of these life-saving medications.

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)0.018
metaresearch head score (Gemma)0.008
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.018
Threshold uncertainty score0.095

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0180.008
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.003
Bibliometrics0.0010.001
Science and technology studies0.0030.001
Scholarly communication0.0040.003
Open science0.0020.004
Research integrity0.0150.016
Insufficient payload (model declined to judge)0.0040.002

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 head0.041
GPT teacher head0.304
Teacher spread0.263 · 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 designNot applicable
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

Citations124
Published2020
Admission routes1
Has abstractyes

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