Influence of the metabolic and inflammatory profile in patients with frozen shoulder - systematic review and meta-analysis.

BACKGROUND

Frozen Shoulder (FS), also known as adhesive shoulder capsulitis, is characterized by a fibrotic inflammatory process of unknown origin, with the most prominent symptoms being pain, stiffness, and reduced joint mobility.

METHODS

The systematic review and meta-analysis presented herein provide insights into the pathogenesis of this condition, as well as common metabolic biomarkers potentially implicated in FS, such as glycated hemoglobin (HbA1c), and inflammatory biomarkers, including interleukins (IL-1, IL-6) and tumor necrosis factor alpha (TNF-α). Dyslipidemia and hormonal factors, such as thyroid dysfunctions, are also examined.

RESULTS

A total of 7,499 individuals were included in the meta-analysis, and one additional study collected 28,416 blood samples from individuals with FS from biobanks. The meta-analysis of metabolic variables showed that HbA1c was the most significantly elevated marker in FS, with a standardized mean difference (SMD) of μ^ = 0.3970 (95% CI: 0.0998 to 0.6943), indicating a moderate effect. Glucose showed a mean difference of -0.28 (95% CI: -0.60 to 0.05), which was not statistically significant, suggesting that short-term fluctuations in glucose levels may not be as relevant as long-term metabolic control. Cholesterol had a standardized difference of 0.278 (95% CI: 0.171 to 0.385), being significantly higher in FS. For triglycerides, the SMD was μ^ = 1.0318 (95% CI: -1.0027 to 3.0664), indicating high heterogeneity and preventing a clear conclusion. Hypothyroidism was also evaluated, with a total SMD of 0.067, a total variance of 0.0021, and a 95% confidence interval of -0.024 to 0.158, confirming no association between FS and thyroid function. Regarding inflammatory biomarkers, IL-1β was the most predominant, showing significantly higher levels in FS, with an SMD of μ^ = 2.2671 (95% CI: 0.5750 to 3.9591). TNF-α had a mean difference of μ^ = 0.7814 (95% CI: 0.1013 to 1.4615), reflecting a significant difference from zero (z = 2.2520, p = 0.0243). Finally, IL-6 did not show a significant association, with an SMD of μ^ = 1.6721 (95% CI: -0.9368 to 4.2810).

CONCLUSION

This meta-analysis highlights the role of metabolic dysfunction and chronic inflammation in the pathogenesis of FS. HbA1c and cholesterol were the most associated metabolic biomarkers, while IL-1β and TNF-α showed a strong link to inflammation and fibrosis. The heterogeneity in triglycerides and IL-6 underscores the need for studies with standardized methodologies and subgroup analyses. Future research should focus on biomarker progression, patient stratification, and new therapeutic strategies targeting metabolic and immune modulation, considering FS within a broader metabolic-inflammatory framework to improve its classification and treatment.