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A Nomogram for Optimizing Sarcopenia Screening in Community-dwelling Older Adults: AB3C Model
Shuai-Wen Huang1, Hong Long2, Zhong-Min Mao3
1Department of General Medicine, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, P. R. China; Department of Geriatrics, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, P. R. China; Department and Institute of Infectious Disease, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
A new AB3C model effectively predicts sarcopenia risk in older adults. This easy-to-use tool aids early detection, improving public health outcomes for community-dwelling seniors.
Area of Science:
- Gerontology
- Public Health
- Epidemiology
Background:
- Sarcopenia is a significant risk factor for mortality in older adults, necessitating early detection for public health benefits.
- Current community-based models for predicting sarcopenia risk are not well-established.
- Identifying effective screening tools is crucial for managing sarcopenia in aging populations.
Purpose of the Study:
- To develop and validate a nomogram for predicting sarcopenia risk in community-dwelling older adults in China.
- To compare the performance of the developed nomogram against existing sarcopenia screening models.
- To establish a reliable and accessible tool for early sarcopenia detection in community settings.
Main Methods:
- A cross-sectional study involving 966 community-dwelling older adults.
- Participants were divided into training (678) and validation (288) sets.
- Logistic regression identified predictors (age, BMI, calf circumference, CHF, COPD) for the AB3C nomogram, with performance assessed by calibration, discrimination (AUC), and clinical utility.
Main Results:
- The AB3C nomogram demonstrated excellent calibration and discrimination in both training (AUC=0.930) and validation (AUC=0.897) sets.
- Key predictors identified were age, body mass index, calf circumference, congestive heart failure, and chronic obstructive pulmonary disease.
- The AB3C model significantly outperformed SARC-F, Ishii, and Calf circumference models in sensitivity and AUC.
Conclusions:
- The AB3C model is an effective, easy-to-apply, and cost-effective nomogram for predicting sarcopenia risk.
- This tool can optimize sarcopenia screening strategies within community settings.
- Early detection and intervention for sarcopenia can be enhanced through the use of the AB3C model.
