کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
5881274 1147780 2016 7 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Original ArticleClusters of Multiple Complex Chronic Conditions: A Latent Class Analysis of Children at End of Life
ترجمه فارسی عنوان
مقالات اصلی مقیاس های پیچیده چندگانه شرایط مزمن: یک تجزیه و تحلیل کلاس بستری کودکان در پایان زندگی
کلمات کلیدی
شرایط مزمن پیچیده، تجزیه و تحلیل کلاس پنهان، اطفال، فرزندان، پایان زندگی،
موضوعات مرتبط
علوم زیستی و بیوفناوری علم عصب شناسی عصب شناسی
چکیده انگلیسی

ContextChildren 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.ObjectivesThe objective of the study was to understand the clusters of complex chronic conditions present among children in the last year of life.MethodsParticipants 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.ResultsFour 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.ConclusionThis 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.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Journal of Pain and Symptom Management - Volume 51, Issue 5, May 2016, Pages 868-874
نویسندگان
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