Association between bone mineral content and sarcopenia in hospitalized patients with type 2 diabetes mellitus: a cross-sectional study.
Type 2 diabetes mellitus (T2DM) increases the risk of sarcopenia, which independently contributes to bone fragility, especially among the elderly. Bone mineral content (BMC) is a parameter that helps in the assessment and monitoring of bone mass. This study aims to identify the correlation between BMC and sarcopenia in hospitalized patients with T2DM.
A total of 1,135 inpatients admitted with T2DM in this study and classified into two groups (sarcopenia and non-sarcopenia group). A comparative analysis of clinical data and body composition was performed between the two groups. A multivariable logistic regression model was used to assess the independent association of BMC with sarcopenia.
The sarcopenia group showed a lower BMC level than the non-sarcopenia group (P < 0.001). The BMC level was correlated with a history of sarcopenia (P < 0.001). The receiver operator characteristic (ROC) curve analysis showed a medium ability of BMC in predicting sarcopenia (area under the ROC curve=0.760). The optimal cut-off level for BMC to predict sarcopenia was found to be < 2.86 kg. Finally, in the multivariable logistic regression model, a BMC level < 2.86 kg was significantly associated with sarcopenia [odds ratio (OR) = 4.994, 95% confidence interval [CI] 3.130-7.967, P < 0.001]. Additional analyses revealed that lower BMC level was associated with an increased risk of sarcopenia irrespective of the subgroup of age (including elderly group and non-elderly group).
Our results confirmed that in hospitalized patients with T2DM, BMC levels are inversely associated with sarcopenia and may therefore serve as a biomarker for sarcopenia discrimination. But additional studies are needed to confirm and further elucidate our results.
A total of 1,135 inpatients admitted with T2DM in this study and classified into two groups (sarcopenia and non-sarcopenia group). A comparative analysis of clinical data and body composition was performed between the two groups. A multivariable logistic regression model was used to assess the independent association of BMC with sarcopenia.
The sarcopenia group showed a lower BMC level than the non-sarcopenia group (P < 0.001). The BMC level was correlated with a history of sarcopenia (P < 0.001). The receiver operator characteristic (ROC) curve analysis showed a medium ability of BMC in predicting sarcopenia (area under the ROC curve=0.760). The optimal cut-off level for BMC to predict sarcopenia was found to be < 2.86 kg. Finally, in the multivariable logistic regression model, a BMC level < 2.86 kg was significantly associated with sarcopenia [odds ratio (OR) = 4.994, 95% confidence interval [CI] 3.130-7.967, P < 0.001]. Additional analyses revealed that lower BMC level was associated with an increased risk of sarcopenia irrespective of the subgroup of age (including elderly group and non-elderly group).
Our results confirmed that in hospitalized patients with T2DM, BMC levels are inversely associated with sarcopenia and may therefore serve as a biomarker for sarcopenia discrimination. But additional studies are needed to confirm and further elucidate our results.