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Record W2334389758 · doi:10.1055/s-0034-1374990

Dapagliflozin bei Patienten mit Typ-2-Diabetes und bestehender kardiovaskulärer Erkrankung: Hypotonie und Verträglichkeit in Bezug auf Volumenverlust

2014· article· de· W2334389758 on OpenAlexaff
TWA de Bruin, LA Leiter, WT Cefalu, I Gause-Nilsson, Eva Johnsson, SJ Parikh, Katja Rohwedder

Bibliographic record

VenueDiabetologie und Stoffwechsel · 2014
Typearticle
Languagede
FieldMedicine
TopicDiabetes Treatment and Management
Canadian institutionsSt. Michael's Hospital
Fundersnot available
KeywordsDapagliflozinMedicineGynecologyType 2 diabetesDiabetes mellitusEndocrinology

Abstract

fetched live from OpenAlex

Hintergrund und Ziele: Der selektive SGLT-2-Hemmer Dapagliflozin zur Behandlung von T2DM, erhöht die renale Glukoseausscheidung und führt zu einer leichten osmotischen Diurese. In 2 Studien an unzureichend kontrollierten T2DM-Patienten (HbA1c 7,0 – 10,0%) mit kardiovaskulärer Vorerkrankung wurde Dapagliflozin 10 mg als Zusatztherapie zur üblichen Behandlung mit Plazebo verglichen (Studie 1: NCT01031680, n = 922, Studie 2: NCT01042977, n = 964). Veröffentlichte Ergebnisse zeigten eine stärkere Senkung von HbA1c, Gewicht und systolischem Blutdruck unter Dapagliflozin im Vergleich zu Plazebo. Über 52 Wochen wurde Dapagliflozin zudem gut vertragen.

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.741
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0010.002
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0000.005

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 head0.021
GPT teacher head0.266
Teacher spread0.245 · 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; both teacher heads agree on what is shown here.

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".

Quick stats

Citations0
Published2014
Admission routes1
Has abstractyes

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