Immunopathology of Neuropsychiatric Systemic Lupus Erythematosus

Hirohata, Shunsei

doi:10.1007/978-3-319-76496-2_3

Cited by 1 publication

(1 citation statement)

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“…Thus, dealing with a chronic illness such as LE can have negative consequences on the lives of individuals; they have a higher rate of absenteeism and incapacity to work and many of them have a permanent disability (Ekblom‐Kullberg, Kautiainen, Alha, Leirisalo‐Repo, & Julkunen, ). It is also associated with cognitive problems, with patients experiencing mild cognitive dysfunction such as attention and concentration difficulties, memory disturbances and delusions (Hirohata, ). In addition, chronic physical pain associated with the disease significantly limits physical function (Sarmanova, Abisheva, & Magzumova, ).…”

Section: Introductionmentioning

confidence: 99%

The relations of quality of life in patients with lupus erythematosus: Regression models versus qualitative comparative analysis

Rioja

Valero‐Moreno

Giménez-Espert

et al. 2019

Journal of Advanced Nursing

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Background Lupus erythematosus (LE) is an autoimmune disease that can have negative repercussions on the quality of life (QL) of those who suffer from it. The QL can be influenced by socio‐demographic factors are related to the disease itself. Aims To analyse the associative power of socio‐demographic (age and sex) and medical variables (type of lupus, diagnostic time and symptomatically associated with lupus) on the QL in patients with lupus by comparing linear relations models and models based on comparative qualitative fuzzy analysis. Design This is a retrospective cross‐sectional design. Participants The sample consisted of 161 patients (88.4% female) diagnosed with LE between the ages of 18–66 years. Methods Data were collected between 2015 ‐ 2017 using the Lupus Erythematosus Quality of Life Questionnaire. Two different statistical methodologies were used: traditional regression models and qualitative comparative analysis models of fuzzy sets. Results The results of the regression model suggest that none of the variables considered could explain the QL of these patients. On the other hand, the results of the fuzzy models suggest that being female, young and a shorter time to diagnosis explain higher levels of QL in these types of patients. Conclusions Since nurses are the people who interact most with patients, detecting risk groups of patients with lupus respect to their QL. This can help develop intervention programs from a nursing perspective.

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Section: Introductionmentioning

confidence: 99%