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Cited by 574

The DOI matches its Crossref record; 55 of the 55 references it cites were found in a registry or an index.

Knee osteoarthritis: pathophysiology and current treatment modalities

Open access
Mora, Juan C, Przkora, Rene, Cruz-Almeida, Yenisel·2018·Journal of Pain Research

Abstract

For decades, multiple attempts to fully understand knee osteoarthritis pathophysiology and natural history have been attempted. Despite the extensive amount of research regarding this topic, there are still marked controversies. This multifactorial condition gets influenced by local, systemic, and external factors and its progression and/or response to treatments widely varies from patient to patient. Multiple therapies have been studied in the past, low impact physical activity seems to be supported by all the current medical societies while other interventions have shown conflicting findings. Newer therapies and routes of administration are under investigation and some of them have shown promising preliminary reports. This review intends to give an overview of the current knowledge of pathophysiology and non-surgical therapies available for knee osteoarthritis.

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Crossref · 10.2147/jpr.s154002

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Metadata

Authors
Mora, J. C., Przkora, R., & Cruz-Almeida, Y.
Venue
Journal of Pain Research
Published
2018-10
Volume
Volume 11
Pages
2189-2196
ISSN
1178-7090 (ISSN-L)
OpenAlex
W2894885260
Cited by
574
References
55
FWCI
31.19
Type
journal article
Language
en
Open access
gold

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CoChat. (2026). Citation check: Knee osteoarthritis: pathophysiology and current treatment modalities. https://app.cochat.ai/papers/10.2147/jpr.s154002
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Mora, J. C., Przkora, R., & Cruz-Almeida, Y. (2018). Knee osteoarthritis: pathophysiology and current treatment modalities. Journal of Pain Research. https://doi.org/10.2147/jpr.s154002

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.