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Record W2794058777 · doi:10.14740/jem.v8i1.491

Steroid-Induced Hyperglycemia Successfully Treated With Once-Weekly Dulaglutide in an Old Patient With Type 2 Diabetes

2018· article· en· W2794058777 on OpenAlexvenueno aff
Hidetaka Hamasaki, Shingo Morimitsu

Bibliographic record

VenueJournal of Endocrinology and Metabolism · 2018
Typearticle
Languageen
FieldMedicine
TopicDiabetes Treatment and Management
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineDulaglutideHyperglucagonemiaInternal medicineGlycemicEndocrinologyPostprandialType 2 diabetesPrednisoloneDiabetes mellitusInsulinGlucagon-like peptide 1 receptorGlucagonExenatideReceptorAgonist

Abstract

fetched live from OpenAlex

Glucocorticoids induce hyperglycemia in case of pancreatic alpha- and beta-cell dysfunction. Glucagon-like peptide-1 receptor agonists (GLP-1RA) may prevent steroid-induced hyperglycemia by improving hyperglucagonemia and insulin secretion. An 85-year-old man was treated with oral prednisolone for chronic hypersensitivity pneumonitis, and his glycemic control deteriorated after the initiation of steroid therapy. After the administration of dulaglutide injection, his glycemic control was improved and we could discontinue insulin therapy. Both fasting and postprandial plasma glucagon levels were significantly suppressed by a GLP-1RA, dulaglutide. GLP-1RAs therapy may be a useful strategy for the treatment of steroid-induced hyperglycemia. J Endocrinol Metab. 2018;8(1):10-12 doi: https://doi.org/10.14740/jem491w

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)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Case report · Consensus signal: Case report
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0020.002
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 head0.014
GPT teacher head0.252
Teacher spread0.238 · 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 designCase report
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

Citations1
Published2018
Admission routes1
Has abstractyes

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