Other Titles
Symposium: Identifying symptom clusters in chronic illness
Abstract
Latent class analysis is able to identify three distinct lymphedema symptom classes with lower, moderate and severe symptom class. Identification of symptom classes is a priority to predict high-risk populations for physiologic outcomes of limb volume and lymph fluid level as well as daily function, social and affective wellbeing.
Notes
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Sigma Membership
Unknown
Lead Author Affiliation
New York University, New York, New York, USA
Type
Presentation
Format Type
Text-based Document
Study Design/Type
N/A
Research Approach
N/A
Keywords:
Breast Cancer, Latent Class Analysis, Symptoms
Recommended Citation
Fu, Mei R., "Latent class analysis of lymphedema symptoms and phenotypic characterization" (2018). INRC (Congress). 272.
https://www.sigmarepository.org/inrc/2018/presentations_2018/272
Conference Name
29th International Nursing Research Congress
Conference Host
Sigma Theta Tau International
Conference Location
Melbourne, Australia
Conference Year
2018
Rights Holder
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Acquisition
Proxy-submission
Latent class analysis of lymphedema symptoms and phenotypic characterization
Melbourne, Australia
Latent class analysis is able to identify three distinct lymphedema symptom classes with lower, moderate and severe symptom class. Identification of symptom classes is a priority to predict high-risk populations for physiologic outcomes of limb volume and lymph fluid level as well as daily function, social and affective wellbeing.