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Record W2547717306 · doi:10.3899/jrheum.160190

Efficacy of Short-term Teriparatide for Hip Osteonecrosis

2016· letter· en· W2547717306 on OpenAlexvenueno aff
Felice Galluccio, Marco Matucci‐Cerinic

Bibliographic record

VenueThe Journal of Rheumatology · 2016
Typeletter
Languageen
FieldMedicine
TopicBone and Joint Diseases
Canadian institutionsnot available
FundersUniversità degli Studi di Firenze
KeywordsMedicineTeriparatideTerm (time)OsteoporosisBone Density Conservation AgentsSurgeryInternal medicineBone densityBone mineral

Abstract

fetched live from OpenAlex

To the Editor: Osteonecrosis of the femoral head is the result of the lack or decrease of blood supply to the bone leading to bone and cartilage cellular death, fracture, and finally collapse of articular surface1. The pathogenesis is still unclear, but it seems that it is the result of a variety of traumatic and atraumatic factors such as genetic predisposition and metabolic factors. Risk factors are high-dosage glucocorticoids, alcohol abuse, venous stasis, adipocyte hypertrophy, alteration of circulating lipids, and other diseases that facilitate intravascular coagulation and thrombus formation2. Nonsurgical treatment is limited and consists of physical therapy and rehabilitation, protected weight-bearing, hyperbaric therapy, and the use of nonsteroidal antiinflammatory drugs (NSAID), bisphosphonates, nifedipine, and lipid-lowering agents3. Unfortunately, these treatments have shown not a real efficacy, but only partial results on pain or delaying fracture and articular collapse4. Teriparatide (TPT), a recombinant synthetic version of the human parathyroid hormone (PTH), is a bone anabolic … Address correspondence to Dr. F. Galluccio, SOD Reumatologia, Viale Pieraccini 18, Villa Monnatessa, 50139 Florence, Italy. E-mail: felicegalluccio{at}gmail.com

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)0.001
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Non-randomized trial · Consensus signal: none
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.010
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0100.007
Insufficient payload (model declined to judge)0.0020.002

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 head0.032
GPT teacher head0.301
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 designNon-randomized trial
Domainnot available
GenreCommentary

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

Citations6
Published2016
Admission routes1
Has abstractyes

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