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Record W1965212674 · doi:10.1517/17425255.4.6.783

Octreotide LAR for the treatment of acromegaly

2008· review· en· W1965212674 on OpenAlexaff
Sophie Vallette, Omar Serri

Bibliographic record

VenueExpert Opinion on Drug Metabolism & Toxicology · 2008
Typereview
Languageen
FieldMedicine
TopicPituitary Gland Disorders and Treatments
Canadian institutionsHôpital Notre-Dame
Fundersnot available
KeywordsAcromegalyOctreotideMedicineInternal medicineSomatostatinIntensive care medicineGrowth hormoneHormone

Abstract

fetched live from OpenAlex

BACKGROUND: Somatostatin analogs previously considered as adjuvant therapy in acromegaly are increasingly used as a first-line therapy in selected cases. OBJECTIVE: To review the octreotide LAR pharmacological and clinical data, and discuss the impact of this agent on current treatment regimens. METHODS: We reviewed PubMed publications since the first use of octreotide LAR in acromegaly, and historical articles related to the discovery and development of this molecule. We chose, for efficacy and safety data, reviews, clinical and randomized controlled trials that included >or=10 patients. RESULTS/CONCLUSION: Octreotide LAR controls acromegaly in approximately 50-60% of patients by inhibiting GH and IGF-I secretion, and by reducing tumor size. This drug is well tolerated in most patients.

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)0.000
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: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.004
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0010.001
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 head0.067
GPT teacher head0.383
Teacher spread0.317 · 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

Citations11
Published2008
Admission routes1
Has abstractyes

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