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 cor...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.展开更多
基金Supported by the Nation Health and Family Planning Commission of China(No.2012ZX10005009)Fundamental Research Funds for the Central Public Welfare Research Institutes(No.Z0474)National Natural Science Foundation of China(No.81503679)
文摘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.
