ArticleArchives of medical science : AMS2024
The correlation between coagulation biomarkers, bone turnover markers, and bone mineral density in Chinese adults aged ≥ 50 years.
Article in Archives of medical science : AMS, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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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.
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Who cites it
3 citing papers in PubMed.
- An explainable machine learning model for predicting osteoporotic fragility fractures: a retrospective study in South China.Frontiers in medicine · 2026Article
- Exploring the Association Between Platelet Count, the Systemic Immune Inflammation Index, and Fracture Risk in Postmenopausal Women with Osteoporosis: A Cross-Sectional Study.Journal of clinical medicine · 2025Article
- Blood coagulation disorders associated with transient global amnesia (TGA): a cause or consequence?Archives of medical science : AMS · 2025Article
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Authors and funding
11 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Introduction: Osteoporosis patients undergoing surgery often have significant bleeding, which is closely related to coagulation function. This study aimed to assess the correlation between bone turnover markers (BTMs), bone mineral density (BMD), and coagulation biomarkers. Material and methods: Cases meeting the inclusion criteria were included from our center from January 2020 to December 2021. The relationships between coagulation biomarkers, BTMs, and BMD were investigated by Spearman correlation analysis and canonical correlation analysis (CCA). Consequently, age, bone mass stage, 25-hydroxyvitamin D (25-(OH)D), and BMD were included as independent variables in the logistic regression model. Furthermore, the international normalized ratio (INR), fibrinogen, platelets, and D-dimer levels were set as dependent variables in the regression analysis. Finally, multivariable regressions were conducted to adjust for differences in demographics and comorbidities among groups. Results: A total of 306 patients were included in the study. Significant differences were observed in prothrombin time, fibrinogen, INR, D-dimer, and platelets ( Conclusions: For the Chinese population aged 50 and above, attention should be paid to alterations in coagulation biomarkers.
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Registered trials
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