Nutrients, Vol. 17, Pages 3134: Impact of Nutritional Status on Clinical Outcomes of Patients Undergoing PRGF Treatment for Knee Osteoarthritis—A Prospective Observational Study

Nutrients, Vol. 17, Pages 3134: Impact of Nutritional Status on Clinical Outcomes of Patients Undergoing PRGF Treatment for Knee Osteoarthritis—A Prospective Observational Study

Nutrients doi: 10.3390/nu17193134

Authors:
Paola De Luca
Giulio Grieco
Simona Landoni
Eugenio Caradonna
Valerio Pascale
Enrico Ragni
Laura de Girolamo

Background: Osteoarthritis (OA) is a major global health issue, increasing with aging and obesity. Current therapies mainly address symptoms without modifying disease progression. Platelet-rich growth factor (PRGF) therapy has potential regenerative effects through high cytokines and growth factors, but the outcomes of these therapies remain heterogeneous. This study explores the relationship between patient nutritional status, PRGF characteristics, and clinical outcomes in knee OA treatment. Methods: Baseline anthropometric, metabolic, and nutritional assessments of 41 patients with knee OA who underwent PRGF treatment were conducted. Blood samples were analyzed for metabolic and inflammatory markers. PRGF composition was assessed by protein content and extracellular vesicle (EV) markers. KOOS and VAS pain scores were collected at 2, 6, and 12 months. Responders improved KOOS by ≥10 points. An elastic-net regularized logistic model allowed the identification of the predictors of treatment response. Results: KOOS and VAS scores improved significantly at all follow-ups. At 2 months, the PRGF of responder patients showed higher PRGF G-CSF levels; at 12 months, increased CD49e and HLA-ABC expression. Higher BMI correlated with increased IL-6, IL-1ra, and resistin in PRGF samples. Hypercholesterolemic patients displayed altered EV profiles, with elevated levels of CD8 but reduced CD49e, HLA-ABC, CD42a, and CD31. Multivariate analysis identified BMI, biceps fold, fat percentage, red blood cell, platelet, and neutrophil counts as predictors of early response. Conclusions: Metabolic and immunological factors influence PRGF composition and clinical efficacy in knee OA. Baseline body composition and hematological parameters as key predictors of response, highlighting the potential of personalized PRGF therapy.

​Background: Osteoarthritis (OA) is a major global health issue, increasing with aging and obesity. Current therapies mainly address symptoms without modifying disease progression. Platelet-rich growth factor (PRGF) therapy has potential regenerative effects through high cytokines and growth factors, but the outcomes of these therapies remain heterogeneous. This study explores the relationship between patient nutritional status, PRGF characteristics, and clinical outcomes in knee OA treatment. Methods: Baseline anthropometric, metabolic, and nutritional assessments of 41 patients with knee OA who underwent PRGF treatment were conducted. Blood samples were analyzed for metabolic and inflammatory markers. PRGF composition was assessed by protein content and extracellular vesicle (EV) markers. KOOS and VAS pain scores were collected at 2, 6, and 12 months. Responders improved KOOS by ≥10 points. An elastic-net regularized logistic model allowed the identification of the predictors of treatment response. Results: KOOS and VAS scores improved significantly at all follow-ups. At 2 months, the PRGF of responder patients showed higher PRGF G-CSF levels; at 12 months, increased CD49e and HLA-ABC expression. Higher BMI correlated with increased IL-6, IL-1ra, and resistin in PRGF samples. Hypercholesterolemic patients displayed altered EV profiles, with elevated levels of CD8 but reduced CD49e, HLA-ABC, CD42a, and CD31. Multivariate analysis identified BMI, biceps fold, fat percentage, red blood cell, platelet, and neutrophil counts as predictors of early response. Conclusions: Metabolic and immunological factors influence PRGF composition and clinical efficacy in knee OA. Baseline body composition and hematological parameters as key predictors of response, highlighting the potential of personalized PRGF therapy. Read More

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