Yan Liu1, Li-Yun He1, Tian-Cai Wen1, Shi-Yan Yan1, Wen-Jing Bai1, Bao-Yan Liu2. 1. Institute of Basic Research in Clinical Medicine, China Academy of Chinese Medical Sciences, Beijing, 100700, China. 2. Institute of Basic Research in Clinical Medicine, China Academy of Chinese Medical Sciences, Beijing, 100700, China. baoyanjournal@163.com.
Abstract
OBJECTIVE: To determine whether patterns of enterovirus 71 (EV71)-associated hand, foot, and mouth disease (HFMD) were classified based on symptoms and signs, and explore whether individual characteristics were correlated with membership in particular pattern. METHODS: Symptom-based latent class analysis (LCA) was used to determine whether patterns of EV71-HFMD existed in a sample of 433 cases from a clinical data warehouse system. Logistic regression was then performed to explore whether demographic, and laboratory data were associated with pattern membership. RESULTS: LCA demonstrated a two-subgroup solution with an optimal fit, deduced according to the Bayesian Information Criterion minima. Hot pattern (59.1% of all patients) was characterized by a very high fever and high endorsement rates for classical HFMD symptoms (i.e., rash on the extremities, blisters, and oral mucosa lesions). Non-hot pattern (40.9% of all patients) was characterized by classical HFMD symptoms. The multiple logistic regression results suggest that white blood cell counts and aspartate transaminase were positively correlated with the hot pattern (adjust odds ratio=1.07, 95% confidence interval: 1.006-1.115; adjust odds ratio=1.051, 95% confidence interval: 1.019-1.084; respectively). CONCLUSIONS: LCA on reported symptoms and signs in a retrospective study allowed different subgroups with meaningful clinical correlates to be defined. These findings provide evidence for targeted prevention and treatment interventions.
OBJECTIVE: To determine whether patterns of enterovirus 71 (EV71)-associated hand, foot, and mouth disease (HFMD) were classified based on symptoms and signs, and explore whether individual characteristics were correlated with membership in particular pattern. METHODS: Symptom-based latent class analysis (LCA) was used to determine whether patterns of EV71-HFMD existed in a sample of 433 cases from a clinical data warehouse system. Logistic regression was then performed to explore whether demographic, and laboratory data were associated with pattern membership. RESULTS: LCA demonstrated a two-subgroup solution with an optimal fit, deduced according to the Bayesian Information Criterion minima. Hot pattern (59.1% of all patients) was characterized by a very high fever and high endorsement rates for classical HFMD symptoms (i.e., rash on the extremities, blisters, and oral mucosa lesions). Non-hot pattern (40.9% of all patients) was characterized by classical HFMD symptoms. The multiple logistic regression results suggest that white blood cell counts and aspartate transaminase were positively correlated with the hot pattern (adjust odds ratio=1.07, 95% confidence interval: 1.006-1.115; adjust odds ratio=1.051, 95% confidence interval: 1.019-1.084; respectively). CONCLUSIONS: LCA on reported symptoms and signs in a retrospective study allowed different subgroups with meaningful clinical correlates to be defined. These findings provide evidence for targeted prevention and treatment interventions.
Entities:
Keywords:
Chinese medicine; enterovirus A; foot and mouth disease; hand; human; pattern classification
Authors: Xiuhui Li; Xi Zhang; Jianbo Ding; Yi Xu; Dan Wei; Yimei Tian; Wei Chen; Jihan Huang; Tao Wen; Shuangjie Li Journal: Evid Based Complement Alternat Med Date: 2014-02-27 Impact factor: 2.629
Authors: Phan Van Tu; Nguyen Thi Thanh Thao; David Perera; Khanh Huu Truong; Nguyen Thi Kim Tien; Tang Chi Thuong; Ooi Mong How; Mary Jane Cardosa; Peter Charles McMinn Journal: Emerg Infect Dis Date: 2007-11 Impact factor: 6.883