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Record W2195765052 · doi:10.1515/jpem-2015-0284

The shortened combined clonidine and arginine test for growth hormone deficiency is practical and specific: a diagnostic accuracy study

2015· article· en· W2195765052 on OpenAlexaff
Reem Al Khalifah, Lina Moisan, Helen Bui

Bibliographic record

VenueJournal of Pediatric Endocrinology and Metabolism · 2015
Typearticle
Languageen
FieldMedicine
TopicGrowth Hormone and Insulin-like Growth Factors
Canadian institutionsMcGill University Health CentreMontreal Children's Hospital
Fundersnot available
KeywordsClonidineMedicineGrowth hormone deficiencyArginineStimulationGrowth hormoneInternal medicineEndocrinologyHormoneBiochemistry

Abstract

fetched live from OpenAlex

BACKGROUND: The growth hormone (GH) stimulation protocols for clonidine and arginine tests are non-standardized and can be lengthy. We examined the specificity of both tests using a shorter duration of timed samples: 90 min for clonidine and 60 min for arginine. METHODS: We retrospectively studied all children who had GH stimulation with clonidine and arginine to test for GH deficiency (GHD). We compared the diagnostic accuracy of both reference and new shortened test (index). RESULTS: We reviewed 243 charts (11.4±4.1 years old; 74.5% males). The combined reference test was performed on 159 children, 29 (18.3%) tested positive for GHD on the combined index test, Kappa 0.98, false positive rate 1 (0.8%), specificity 0.99, 95th CI (0.96-1), and p=1.0. The specificity of both the clonidine and arginine single index tests was 0.98%. CONCLUSIONS: The shortened clonidine and arginine stimulation index tests have good specificity. This is a viable option for testing children for GHD.

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)0.004
metaresearch head score (Gemma)0.019
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 score0.004
Threshold uncertainty score0.020

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.019
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0010.000
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 head0.041
GPT teacher head0.310
Teacher spread0.269 · 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".

Quick stats

Citations7
Published2015
Admission routes1
Has abstractyes

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