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Record W2585285068 · doi:10.1302/2058-5241.2.160004

Platelet-rich plasma (PRP) for knee disorders

2017· review· en· W2585285068 on OpenAlex
Mohammad Shahid, Rik Kundra

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueEFORT Open Reviews · 2017
Typereview
Languageen
FieldMedicine
TopicPeriodontal Regeneration and Treatments
Canadian institutionsSt. Michael's Hospital
Fundersnot available
KeywordsPlatelet-rich plasmaArticular cartilageMedicinePlateletPlasmapheresisOsteoarthritisPlatelet lysateCoagulationAutologous bloodSynovial fluidSurgeryInternal medicinePathologyImmunologyAntibody

Abstract

fetched live from OpenAlex

Abstract Platelet-rich plasma (PRP) is an autologous blood product with platelet concentrations above baseline values. The process involves the extraction of blood from the patient which is then centrifuged to obtain a concentrated suspension of platelets by plasmapheresis. It then undergoes a two-stage centrifugation process to separate the solid and liquid components of the anticoagulated blood. PRP owes its therapeutic use to the growth factors released by the platelets which are claimed to possess multiple regenerative properties. In the knee, PRP has been used in patients with articular cartilage pathology, ligamentous and meniscal injuries. There is a growing body of evidence to support its use in selected indications and this review looks at the most recent evidence. We also look at the current UK National Institute of Health & Clinical Excellence (NICE) guidelines with respect to osteoarthritis and the use of PRP in the knee. Cite this article: EFORT Open Rev 2017;2:28–34. DOI: 10.1302/2058-5241.2.160004.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.966
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0040.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.002

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 head0.293
GPT teacher head0.488
Teacher spread0.195 · 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