Department of Gastrointestinal Surgery, Department of Clinical Nutrition, Beijing Shijitan Hospital, Capital Medical University, Beijing, 100038, China.
National Clinical Research Center for Geriatric Diseases, Xuanwu Hospital, Capital Medical University, Beijing, 100053, China.
J Transl Med. 2023 Feb 25;21(1):154. doi: 10.1186/s12967-023-04008-7.
The relationship between muscle and prognosis, especially that between muscle distribution across different body parts, and the related prognosis is not well established.
To investigate the relationship between muscle distribution and all-cause and cause-specific mortality and their potential modifiers.
Longitudinal cohort study. C-index, IDI, and NRI were used to determine the best indicator of prognosis. COX regression analysis was performed to explore the relationship between variables and outcomes. Interaction and subgroup analyses were applied to identify the potential modifiers.
A total of 5052 participants (weighted: 124,841,420) extracted from the NHANES 2003-2006 of median age 45 years and constituting 50.3% men were assessed. For validation, we included 3040 patients from the INSCOC cohort in China.
Muscle mass and distribution. KEY RESULTS: COX regression analysis revealed that upper limbs (HR = 0.41, 95% CI 0.33-0.51), lower limbs (HR = 0.54, 95% CI 0.47-0.64), trunk (HR = 0.71, 95% CI, 0.59-0.85), gynoid (HR = 0.47, 95% CI 0.38-0.58), and total lean mass (HR = 0.55, 95% CI 0.45-0.66) were all associated with the better survival of participants (P < 0.001). The changes in the lean mass ratio of the upper and lower limbs and the lean mass ratio of the android and gynoid attenuated the protective effect of lean mass. Age and sex acted as potential modifiers, and the relationship between lean mass and the prognosis was more significant in men and middle-aged participants when compared to that in other age groups. Sensitive analyses depicted that despite lean mass having a long-term impact on prognosis (15 years), it has a more substantial effect on near-term survival (5 years).
Muscle mass and its distribution affect the prognosis with a more significant impact on the near-term than that on the long-term prognosis. Age and sex acted as vital modifiers.
肌肉与预后之间的关系,尤其是不同身体部位的肌肉分布与相关预后之间的关系,尚未得到充分证实。
探究肌肉分布与全因死亡率和特定原因死亡率之间的关系及其潜在的调节因素。
纵向队列研究。使用 C 指数、IDI 和 NRI 来确定最佳预后指标。采用 COX 回归分析探讨变量与结局之间的关系。进行交互作用和亚组分析,以确定潜在的调节因素。
从 2003-2006 年 NHANES 中提取了中位年龄为 45 岁、男性占 50.3%的 5052 名参与者(加权:124841420 人)进行评估。为了验证,我们纳入了中国 INSCOC 队列中的 3040 名患者。
肌肉量和分布。
COX 回归分析显示,上肢(HR=0.41,95%CI 0.33-0.51)、下肢(HR=0.54,95%CI 0.47-0.64)、躯干(HR=0.71,95%CI 0.59-0.85)、臀区(HR=0.47,95%CI 0.38-0.58)和总瘦体重(HR=0.55,95%CI 0.45-0.66)均与参与者的生存获益相关(P<0.001)。上肢和下肢瘦体重比例以及腹型和臀型瘦体重比例的变化减弱了瘦体重的保护作用。年龄和性别是潜在的调节因素,与其他年龄组相比,瘦体重与预后的关系在男性和中年参与者中更为显著。敏感性分析表明,尽管瘦体重对预后有长期影响(15 年),但它对近期生存的影响更为显著(5 年)。
肌肉量及其分布与预后相关,对近期预后的影响大于对长期预后的影响。年龄和性别是重要的调节因素。