Evidence map›Paper›PMID 42491313›Full record

ArticleOrthopaedic journal of sports medicine2026

Health Disparities in Orthobiologics: Factors Influencing Access to Platelet-Rich Plasma for Knee Osteoarthritis.

Mohamed Addani, Jennifer Arthurs, Sadiq Haque, Andreea Geamanu, Lindsay Beaman, Shane Shapiro, Zubin Master

Abstract read
In one paragraph

Article in Orthopaedic journal of sports medicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Mohamed AddaniClinical and Translational Science, Mayo Clinic Graduate School of Biomedical Sciences, Mayo Clinic, Rochester, Minnesota, USA.ORCID https://orcid.org/0000-0003-0813-2078
Jennifer ArthursClinical Regenerative Medicine, Mayo Clinic, Jacksonville, Florida, USA.ORCID https://orcid.org/0000-0001-9691-4365
Sadiq HaqueDepartment of Orthopedics and Sports Medicine, Wayne State University School of Medicine, Detroit, Michigan, USA.
Andreea GeamanuDepartment of Orthopedics, Detroit Medical Center, Detroit, Michigan, USA.
Lindsay BeamanBiomedical Ethics Research Program, Mayo Clinic, Rochester, Minnesota, USA.ORCID https://orcid.org/0000-0002-2729-1050
Shane ShapiroClinical Regenerative Medicine, Mayo Clinic, Jacksonville, Florida, USA.ORCID https://orcid.org/0000-0001-5753-0625
Zubin MasterDepartment of Social Sciences and Health Policy, Division of Public Health Sciences, Wake Forest University School of Medicine, Winston-Salem, North Carolina, USA.ORCID https://orcid.org/0000-0002-3462-4546

Funding

Mayo Clinic Center for Clinical and Translational Science (CCaTS UL1 Supplement - Dr. Timothy Curry)UL1TR002377 · NCATS · MAYO CLINIC ROCHESTER · PI VESNA D GAROVIC · 2017 to 2026
$78.4M
Identifying salient factors that influence physician practices in mitigating patient misinformationR01AG083464 · NIA · WAKE FOREST UNIVERSITY HEALTH SCIENCES · PI MASTER, ZUBIN · 2024 to 2025
$1.4M
NCATS NIH HHS UL1 TR002377NIA NIH HHS R01 AG083464
6 · The paper itself

Abstract

Background: Platelet-rich plasma (PRP) is an emerging therapy that demonstrates potential benefits for knee osteoarthritis (OA); however, the accessibility of PRP remains limited, in part, because its use is not covered by insurance. Purpose: To identify factors contributing to health disparities in PRP treatment for knee OA using machine learning models. Study Design: Cross-sectional study; Level of evidence, 3. Methods: The authors collected data from electronic medical records at 2 upper Midwest medical centers (Mayo Clinic and Detroit Medical Center) from 2022 to 2023 encompassing demographic, socioeconomic, and clinical factors. Data collection encompassed age, sex, race, ethnicity, area deprivation index, marital status, income, rurality, insurance, employment, language, religion, treatment site, and region. Logistic regression and random forest models were applied to 3667 samples (80% training, 20% testing), comparing PRP recipients against a standard care group. Models were evaluated using 10-fold cross-validation to ensure robust performance assessment. Results: Logistic regression revealed that increased age, widowed status, lower income, rural residence, unemployment/disability, and Medicaid/Medicare insurance were associated with lower odds of receiving PRP. Upper-middle income, contracted insurance, and treatment at the Mayo-Arizona and Mayo-Florida sites were associated with higher odds. The model achieved areas under the curve of 0.83 (training set) and 0.82 (testing set). Random forest analysis identified distance to care, age, area deprivation index, income, and treatment site as top predictors, with areas under the curve of 0.92 (training) and 0.87 (testing). Conclusion: The current study demonstrated that both models discerned key barriers (income, distance to care, retirement status) and facilitators (regional differences) affecting PRP accessibility. These findings provide potential policy initiatives aimed at improving PRP access for underserved demographics, offering a quantitative blueprint to foster equitable access to regenerative therapies for knee OA.

Indexed as

clinical medicine by anatomic regionclinical medicine by specialty interestgeneralhealth equity, biologic healing enhancementkneeNSAIDSplatelet-rich plasmareplacementresearch (in vivo or in vitro)

Identifiers

PMID42491313
PMCPMC13376439

What OpenQuestion holds

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LicenceCC BY-NC-ND
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.