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Record W4401710176 · doi:10.1177/10225536241277604

Inadequate anticoagulation and hyperuricemia cause knee pain after platelet-rich plasma injection: A retrospective study

2024· article· en· W4401710176 on OpenAlexaboutno aff
Chen Yang, Hongxun Sang, Song Wu, Haobin Zhang, Yi Zhang, Hongxing Li

Bibliographic record

VenueJournal of orthopaedic surgery · 2024
Typearticle
Languageen
FieldMedicine
TopicPeriodontal Regeneration and Treatments
Canadian institutionsnot available
FundersNational Natural Science Foundation of China
KeywordsMedicineOsteoarthritisPlatelet-rich plasmaRetrospective cohort studyPlateletHeparinInternal medicineAnticoagulantGastroenterologyAnesthesiaSurgeryPathology

Abstract

fetched live from OpenAlex

OBJECTIVES: Platelet-rich plasma treatment delays the need for total knee replacement in patients with knee osteoarthritis. However, its use and preparation remain controversial. The aim of this study was to investigate the relationship between anticoagulant use in the preparation of platelet-rich plasma and post-treatment pain in patients with knee osteoarthritis. Additionally, we explored the efficacy of platelet-rich plasma over medium- and long-term follow-up periods and identified other factors that may affect treatment outcomes. METHODS: In this retrospective study, 225 patients with knee osteoarthritis, who underwent knee platelet-rich plasma treatment from June 2021 to January 2022, were examined at three study centres. Patients were categorised, based on the type and amount of anticoagulant used during platelet-rich plasma preparation, into 4% sodium citrate (SC) 0.6 mL, 4% SC 1 mL, 4% SC 2 mL, heparin 0.1 mL, and heparin 0.2 mL groups. We analysed the patients' basic information, pain after treatment, and inflammatory markers (i.e., interleukin 6, tumour necrosis factor-α, and hypersensitive C-reactive protein) in the joint fluid via enzyme-linked immunosorbent assay and joint fluid crystallisation. Additionally, we assessed the patients' Western Ontario and McMaster University scores and minimal clinically significant differences after treatment. RESULTS: Patients in the 4% SC 0.6 mL and heparin 0.1 mL groups experienced less pain after platelet-rich plasma treatment than did patients in the high-dose anticoagulant group. The joint fluid of patients with pain in these groups had lower levels of inflammatory markers. Patients treated with SC had slightly better medium- and long-term therapeutic outcomes than did patients treated with heparin. Patients with poorly controlled hyperuricemia also experienced pain after platelet-rich plasma treatment. CONCLUSIONS: The results suggest that platelet-rich plasma prepared using high-dose anticoagulants or administered to patients with poorly controlled hyperuricaemia may lead to moderate-to-severe knee pain and joint effusion after joint puncture therapy. Platelet-rich plasma had a therapeutic effect on knee osteoarthritis; however, its efficacy gradually decreased over time. SC anticoagulant is more suitable for platelet-rich plasma preparation than is heparin. Further studies are needed to understand the safety and the various factors influencing platelet-rich plasma therapy.

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 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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.029
Threshold uncertainty score0.508

Codex and Gemma teacher scores by category

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

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 head0.275
Teacher spread0.253 · 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 teacher head, 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

Citations3
Published2024
Admission routes1
Has abstractyes

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