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Record W3030936041 · doi:10.1155/2020/4827072

Myalgia and Hematuria in Association with Clonidine and Arginine Administration for Growth Hormone Stimulation Tests

2020· article· en· W3030936041 on OpenAlexaff
Meghan Glibbery, Adam Fleming, Rahul Chanchlani, Olufemi Ajani, Norma Marchetti, Alexa Marr, M. Constantine Samaan

Bibliographic record

VenueCase Reports in Medicine · 2020
Typearticle
Languageen
FieldMedicine
TopicGrowth Hormone and Insulin-like Growth Factors
Canadian institutionsImpactUniversity of OttawaHamilton Health SciencesMcMaster UniversityMcMaster Children's Hospital
Fundersnot available
KeywordsMedicineClonidinemyalgiaArginineStimulationGrowth hormoneGrowth hormone deficiencyAdverse effectInternal medicineEndocrinologyHormone

Abstract

fetched live from OpenAlex

Growth hormone deficiency (GHD) in children has significant impacts on growth and metabolism. Two-agent GH stimulation tests are commonly used to diagnose GHD, and these tests are generally considered safe. We report the case of a 5-year 5-month-old boy with a history of anaplastic ependymoma who underwent GH stimulation testing for growth deceleration using clonidine and arginine. He developed bilateral calf myalgia and gross hematuria within 24 hours of the tests. Myalgia and hematuria resolved spontaneously. Importantly, the literature review and database searches for hematuria identified 6 cases with clonidine and 20 cases with arginine. This case highlights an unusual combination of adverse reactions to clonidine and arginine in children undergoing GH stimulation testing to assess for GHD. Pediatric endocrinologists need to be aware of the potential for these side effects to allow appropriate management, and further studies are needed to clarify the mechanisms and frequency of these side effects. We recommend that patients and families need to be counselled about hematuria as an association of GH testing with these medications.

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)0.003
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 score0.003
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0010.001
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 head0.023
GPT teacher head0.285
Teacher spread0.262 · 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

Citations4
Published2020
Admission routes1
Has abstractyes

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