Respiratory sarcopenia
Conditions
Interventions
Third research:Joint Training Group:traditional core strength combined with respiratory muscle training
Third research:Core Training Group:traditional core strength
Third research: Control Group:Health education
First research: Observation group (screening elderly people with different degrees of respiratory muscle atrophy and related risk factors):NA
Second research: Construction and Effect Evaluation of Respiratory Sarcopenia Prediction Model Based on BP Neural Network. :NA
Sponsors
Beijing Sport University
Eligibility
Sex/Gender
Female
Age
60 Years to 80 Years
Inclusion criteria
Inclusion criteria: (1) Elderly people aged 60 and above; (2) Have the ability to walk independently; (3) There are chronic diseases other than chronic respiratory diseases but they are well controlled.
Exclusion criteria
Exclusion criteria: (1) Chronic respiratory diseases (2) There are obvious pathogenic factors with low respiratory tract muscle mass, such as lung tumors, pulmonary edema, bronchiectasis, diaphragmatic paralysis, neuromuscular diseases and congenital morphological abnormalities. (3) Patients with severe muscle, bone and joint diseases or deformities, and severe osteoporosis; (4) Early postoperative period (5) Visual or hearing impairment; (6) Cancer progression stage.
Design outcomes
Primary
| Measure | Time frame |
|---|---|
| Diaphragm range of motion;Diaphragm thickness;Lung function;Respiratory muscle strength; | — |
Secondary
| Measure | Time frame |
|---|---|
| Muscle strength;Flexibility;Balance ability;Cardiopulmonary endurance;Bone mineral density;Arteriosclerosis;Basic information;Questionnaire survey; | — |
Countries
China
Contacts
Public ContactLi Chaojun/ Wang Yan
Beijing Zhongguancun Hospital Beijing Sport University
Outcome results
None listed