Clusters of Multiple Complex Chronic Conditions: A Latent Class Analysis of Children at End of Life
Clusters of Multiple Complex Chronic Conditions: A Latent Class Analysis of Children at End of Life
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DOI：
10.1016/j.jpainsymman.2015.12.310
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发表时间：
2016-05-01
影响因子：
4.7
通讯作者：
Bruce, Donald J.
中科院分区：
文献类型：
--
作者：
Lindley, Lisa C.;Mack, Jennifer W.;Bruce, Donald J.
上下文儿童在生命的尽头往往会经历多种复杂的慢性疾病，据报道，超过50%的儿童患有两种或两种以上的疾病。这些复杂的慢性疾病不太可能以完全一致的方式发生在儿童生命的尽头。以前的工作没有充分考虑到模式的多种条件时，评估这些儿童的护理。该研究的目的是了解复杂的慢性疾病的集群中存在的儿童在生命的最后一年。参与者是2007年至2008年加州医疗补助数据的1423名儿科死者。使用潜在类别分析来识别患有多种复杂慢性疾病（神经系统、心血管、呼吸系统、肾脏、胃肠道、血液、代谢、先天性、癌症）的儿童群体。采用多项Logistic回归分析人口学特征与班级归属的关系。产生了四种潜在类别：医学脆弱（31%）;神经系统（32%）;癌症（25%）;和心血管（12%）。三个类别的特征是100%的可能性有一个复杂的慢性疾病加上低或中等的可能性有其他八个条件。四个班级呈现出独特的人口统计学特征。这项分析提出了一种新的方式来理解儿童中多种复杂慢性病的模式，可以为不同群体提供量身定制和有针对性的临终关怀。(C)2016年美国临终关怀和姑息医学学会。爱思唯尔公司出版All rights reserved.
Context. Children at end of life often experience multiple complex chronic conditions with more than 50% of children reportedly having two or more conditions. These complex chronic conditions are unlikely to occur in an entirely uniform manner in children at end of life. Previous work has not fully accounted for patterns of multiple conditions when evaluating care among these children.Objectives. The objective of the study was to understand the clusters of complex chronic conditions present among children in the last year of life.Methods. Participants were 1423 pediatric decedents from the 2007 to 2008 California Medicaid data. A latent class analysis was used to identify clusters of children with multiple complex chronic conditions (neurological, cardiovascular, respiratory, renal, gastrointestinal, hematologic, metabolic, congenital, cancer). Multinomial logistic regression analysis was used to examine the relationship between demographic characteristics and class membership.Results. Four latent classes were yielded: medically fragile (31%); neurological (32%); cancer (25%); and cardiovascular (12%). Three classes were characterized by a 100% likelihood of having a complex chronic condition coupled with a low or moderate likelihood of having the other eight conditions. The four classes exhibited unique demographic profiles.Conclusion. This analysis presented a novel way of understanding patterns of multiple complex chronic conditions among children that may inform tailored and targeted end-of-life care for different clusters. (C) 2016 American Academy of Hospice and Palliative Medicine. Published by Elsevier Inc. All rights reserved.