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Record W3108273361 · doi:10.2217/rme-2020-0057

Platelet-Rich Plasma for the Treatment of Adolescent Late-Stage Femoral Head Necrosis: A Case Report

2020· article· en· W3108273361 on OpenAlexaboutno aff
Shuo Luan, Cuicui Liu, Caina Lin, Chao Ma, Shaoling Wu

Bibliographic record

VenueRegenerative Medicine · 2020
Typearticle
Languageen
FieldMedicine
TopicBone and Joint Diseases
Canadian institutionsnot available
FundersNational Natural Science Foundation of China
KeywordsMedicineFemoral headStage (stratigraphy)Magnetic resonance imagingPlatelet-rich plasmaSurgeryRadiological weaponHarris Hip ScoreVisual analogue scaleTherapeutic effectOsteoarthritisRadiologyArthroplastyInternal medicinePlateletPathology

Abstract

fetched live from OpenAlex

Osteonecrosis of femoral head (ONFH) is a disabling and intractable disease. Previous studies reported the increasing failure rates of total hip arthroplasty in younger patients, thus there should be special considerations for the adolescents. In this paper, we present a case of an adolescent female with late-stage glucocorticoid-induced ONFH (according to the Association Research Circulation Osseous classification system, Association Research Circulation Osseous IV). The patient received five consecutive ultrasound-guided intra-articular injections of platelet-rich plasma, and the therapeutic effects were assessed by visual analog scale, joint range of motion, Western Ontario and McMaster Universities Osteoarthritis Index, Harris Hip Score and magnetic resonance imaging. At 9-month follow-up, clinical and radiological reassessments demonstrated favorable outcomes. This case highlights the therapeutic potential of platelet-rich plasma injections for the late-stage ONFH, especially for adolescent 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)0.001
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 score0.003
Threshold uncertainty score0.003

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 studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0030.002
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 head0.112
GPT teacher head0.349
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

Citations7
Published2020
Admission routes1
Has abstractyes

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