Development of an Algorithm to Predict Appendicular Lean Mass Index From Regional Spine and Hip Dxa Scans.

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Tác giả: Mackenzie R Alexiuk, Clara Bohm, William D Leslie, Krista Rossum, Navdeep Tangri

Ngôn ngữ: eng

Ký hiệu phân loại: 343.0746 Military, defense, public property, public finance, tax, commerce (trade), industrial law

Thông tin xuất bản: United States : Journal of clinical densitometry : the official journal of the International Society for Clinical Densitometry , 2025

Mô tả vật lý:

Bộ sưu tập: NCBI

ID: 643365

 INTRODUCTION: Sarcopenia is characterized by progressive muscle loss with reduced physical function and/or reduced muscle strength. Operational definitions of sarcopenia include a measurement of muscle mass, most often from dual-energy X-ray absorptiometry (DXA)-derived appendicular lean mass. Appendicular lean mass can be derived from whole-body dual-DXA scans
  however, these scans are performed less commonly than hip and spine scans as part of clinical care. The objective of our study was to develop an algorithm to predict appendicular lean mass index (ALMI) from regional spine and hip dual-energy X-ray absorptiometry (DXA) scans. METHODS: We performed a retrospective cross-sectional study using a subset of patients from the Manitoba Bone Mineral Density Registry who had hip, spine, and whole-body DXA scans at the same visit. We developed the algorithm using the following candidate covariates: age, sex, height, weight, DXA-derived spine and hip fat fraction, DXA-derived spine and hip tissue thickness. We internally validated the algorithm using the bootstrap method. Mean bootstrap parameter estimates were used as the final equation. RESULTS: DXA scans from 676 patients were included in the analytic dataset. Mean ALMI was 6.73 (SD 1.43) kg/m CONCLUSION: Hip and spine DXA scans can be used to predict appendicular lean mass index. Future studies should test whether these predictions can be used to assess relationships between sarcopenia and other clinical conditions.
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