Latent class analysis of lymphedema symptoms and phenotypic characterization
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Mei R. Fu, PhD, RN, FAAN, Rory Meyers College of Nursing, New York University, New York, New York, USA
- Sigma Affiliation
- Upsilon
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- New York University, New York, New York, USA
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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.
29th International Nursing Research Congress: Innovative Global Nursing Practice and Education Through Research and Evidence-based Practice, July 19-23, 2018. Melbourne, Australia.
This record is part of an event symposium session. To locate other records associated with this symposium session, search the repository using the session key labeled as “Other Identifiers” in this record, or search by the symposium title. Items submitted to a conference/event were evaluated/peer-reviewed at the time of abstract submission to the event. No other peer-review was provided prior to submission to the Henderson Repository, unless otherwise noted.
Type | Presentation |
Acquisition | Proxy-submission |
Review Type | Abstract Review Only: Reviewed by Event Host |
Format | Text-based Document |
Evidence Level | N/A |
Research Approach | N/A |
Keywords | Breast Cancer; Latent Class Analysis; Symptoms |
Name | 29th International Nursing Research Congress |
Host | Sigma Theta Tau International |
Location | Melbourne, Australia |
Date | 2018 |
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