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Record W3034389451 · doi:10.2337/db20-1224-p

1224-P: Validation of a New Diabetes Staging System (DSS) for Type 2 Diabetes (T2D) Using Data from Three Cardiovascular Outcomes Trials (CVOTs)

2020· article· en· W3034389451 on OpenAlexaboutno aff
M. Saeed Dar, Christoph Wanner, Nikolaus Marx, Odd Erik Johansen, Anne Pernille Ofstad, Michaela Mattheus, Stefan Kaspers, Jyothis T. George, Julio Rosenstock, Darren K. McGuire, Sami Bég

Bibliographic record

VenueDiabetes · 2020
Typearticle
Languageen
FieldMedicine
TopicDiabetes Treatment and Management
Canadian institutionsnot available
Fundersnot available
KeywordsLinagliptinMedicineStage (stratigraphy)PlaceboType 2 diabetesInternal medicineDiabetes mellitusKidney diseaseIncidence (geometry)Intensive care medicineOncologyPathologyEndocrinologyAlternative medicine

Abstract

fetched live from OpenAlex

More than 400 million people have T2D but an intuitive staging system like TNM used in oncology that predicts survival based on stage is lacking. DSS is designed to fill this void, facilitate communication and management and predict survival. DSS uses discrete CV events (none to ≥3: stage 1 to 4), end-stage renal disease (stage 5) and microvascular complications (none to ≥3: A to D) to stage T2D patients. It is hypothesized that higher DSS stage is associated with higher mortality. We used three large CVOTs (CAROLINA, n=6014, pooled linagliptin and glimepiride; CARMELINA, n=3792, pooled linagliptin and placebo; and the placebo group of EMPA-REG OUTCOME, n= 2300, with information available) that included patients with T2D with or without CVD and chronic kidney disease. By use of investigator reported baseline conditions, we categorized patients into DSS stages and calculated incidence rates (IR) for all-cause death. We observed a pattern of increasing IR for death with more advanced DSS stage, although with overlapping confidence intervals, with some variations between trials (Figure). A pattern of eGFR<60 ml/min/1.73m2 impacting in more advanced stages were observed across trials, whereas the pattern for HbA1c was less clear. Higher DSS stage appeared to be associated with increased mortality across all three CVOT trials but needs validation in the general T2D populations. Disclosure M. Dar: None. C. Wanner: Advisory Panel; Self; Eli Lilly and Company, Merck & Co., Inc., Mundipharma International. Consultant; Self; Boehringer Ingelheim (Canada) Ltd., Sanofi Genzyme. Speaker’s Bureau; Self; AstraZeneca. Other Relationship; Self; Boehringer Ingelheim International GmbH. N. Marx: Other Relationship; Self; Amgen, AstraZeneca, Bayer Vital, Boehringer Ingelheim International GmbH, Daiichi Sankyo, Kowa Research Institute, Inc., Medtronic, Merck Sharp & Dohme Corp., Novo Nordisk A/S, Pfizer Inc., Sanofi-Aventis. O. Johansen: Employee; Self; Boehringer Ingelheim International GmbH. A. Ofstad: Employee; Self; Boehringer Ingelheim International GmbH. M. Mattheus: None. S. Kaspers: Employee; Self; Boehringer Ingelheim International GmbH. J.T. George: Employee; Self; Boehringer Ingelheim International GmbH. J. Rosenstock: Research Support; Self; AstraZeneca, Bristol-Myers Squibb, Genentech, Inc., GlaxoSmithKline plc., Lexicon Pharmaceuticals, Inc., Oramed Pharmaceuticals, PegBio Co., Ltd., Pfizer Inc., REMD Biotherapeutics. Other Relationship; Self; Applied Therapeutics, Boehringer Ingelheim Pharmaceuticals, Inc., Eli Lilly and Company, Intarcia Therapeutics, Janssen Pharmaceuticals, Inc., Novo Nordisk Inc., Sanofi. D.K. McGuire: Consultant; Self; Afimmune, Applied Therapeutics, Merck Sharp & Dohme Corp., Metavant. Other Relationship; Self; AstraZeneca, Boehringer Ingelheim Pharmaceuticals, Inc., Eisai Co., Ltd., Eli Lilly and Company, Esperion Therapeutics, Inc., GlaxoSmithKline plc., Janssen Pharmaceuticals, Inc., Lexicon Pharmaceuticals, Inc., Merck & Co., Inc., Novo Nordisk A/S, Pfizer Inc., Sanofi-Aventis. S.A. Beg: None.

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)0.023
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 score0.019
Threshold uncertainty score0.101

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0190.023
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.004
Bibliometrics0.0010.002
Science and technology studies0.0000.001
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0050.001

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 head0.228
GPT teacher head0.343
Teacher spread0.115 · 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".

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Citations0
Published2020
Admission routes1
Has abstractyes

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