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Mortality risk prediction in lupus patients complicated with invasive infection in the emergency department: LUPHAS score

BACKGROUND: Infection remains a major cause of morbidity and mortality in patients with systemic lupus erythematosus (SLE). This study aimed to establish a clinical prediction model for the 3-month all-cause mortality of invasive infection events in patients with SLE in the emergency department. MET...

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Autores principales: Wu, Wanlong, Ma, Jun, Zhou, Yuhong, Tang, Chao, Zhao, Feng, Sun, Fangfang, Xu, Wenwen, Chen, Jie, Ye, Shuang, Chen, Yi
Formato: Online Artículo Texto
Lenguaje:English
Publicado: SAGE Publications 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6831971/
https://www.ncbi.nlm.nih.gov/pubmed/31723357
http://dx.doi.org/10.1177/1759720X19885559
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author Wu, Wanlong
Ma, Jun
Zhou, Yuhong
Tang, Chao
Zhao, Feng
Sun, Fangfang
Xu, Wenwen
Chen, Jie
Ye, Shuang
Chen, Yi
author_facet Wu, Wanlong
Ma, Jun
Zhou, Yuhong
Tang, Chao
Zhao, Feng
Sun, Fangfang
Xu, Wenwen
Chen, Jie
Ye, Shuang
Chen, Yi
author_sort Wu, Wanlong
collection PubMed
description BACKGROUND: Infection remains a major cause of morbidity and mortality in patients with systemic lupus erythematosus (SLE). This study aimed to establish a clinical prediction model for the 3-month all-cause mortality of invasive infection events in patients with SLE in the emergency department. METHODS: SLE patients complicated with invasive infection admitted into the emergency department were included in this study. Patient’s demographic, clinical, and laboratory characteristics on admission were retrospectively collected as baseline data and compared between the deceased and the survivors. Independent predictors were identified by multivariable logistic regression analysis. A prediction model for all-cause mortality was established and evaluated by receiver operating characteristic (ROC) curve analysis. RESULTS: A total of 130 eligible patients were collected with a cumulative 38.5% 3-month mortality. Lymphocyte count <800/ul, urea >7.6mmol/l, maximum prednisone dose in the past ⩾60 mg/d, quick Sequential Organ Failure Assessment (qSOFA) score, and age at baseline were independent predictors for all-cause mortality (LUPHAS). In contrast, a history of hydroxychloroquine use was protective. In a combined, odds ratio-weighted LUPHAS scoring system (score 3–22), patients were categorized to three groups: low-risk (score 3–9), medium-risk (score 10–15), and high-risk (score 16–22), with mortalities of 4.9% (2/41), 45.9% (28/61), and 78.3% (18/23) respectively. ROC curve analysis indicated that a LUPHAS score could effectively predict all-cause mortality [area under the curve (AUC) = 0.86, CI 95% 0.79–0.92]. In addition, LUPHAS score performed better than the qSOFA score alone (AUC = 0.69, CI 95% 0.59–0.78), or CURB-65 score (AUC = 0.69, CI 95% 0.59–0.80) in the subgroup of lung infections (n = 108). CONCLUSIONS: Based on a large emergency cohort of lupus patients complicated with invasive infection, the LUPHAS score was established to predict the short-term all-cause mortality, which could be a promising applicable tool for risk stratification in clinical practice.
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spelling pubmed-68319712019-11-13 Mortality risk prediction in lupus patients complicated with invasive infection in the emergency department: LUPHAS score Wu, Wanlong Ma, Jun Zhou, Yuhong Tang, Chao Zhao, Feng Sun, Fangfang Xu, Wenwen Chen, Jie Ye, Shuang Chen, Yi Ther Adv Musculoskelet Dis When Rheumatology and Infectious Disease Come Together BACKGROUND: Infection remains a major cause of morbidity and mortality in patients with systemic lupus erythematosus (SLE). This study aimed to establish a clinical prediction model for the 3-month all-cause mortality of invasive infection events in patients with SLE in the emergency department. METHODS: SLE patients complicated with invasive infection admitted into the emergency department were included in this study. Patient’s demographic, clinical, and laboratory characteristics on admission were retrospectively collected as baseline data and compared between the deceased and the survivors. Independent predictors were identified by multivariable logistic regression analysis. A prediction model for all-cause mortality was established and evaluated by receiver operating characteristic (ROC) curve analysis. RESULTS: A total of 130 eligible patients were collected with a cumulative 38.5% 3-month mortality. Lymphocyte count <800/ul, urea >7.6mmol/l, maximum prednisone dose in the past ⩾60 mg/d, quick Sequential Organ Failure Assessment (qSOFA) score, and age at baseline were independent predictors for all-cause mortality (LUPHAS). In contrast, a history of hydroxychloroquine use was protective. In a combined, odds ratio-weighted LUPHAS scoring system (score 3–22), patients were categorized to three groups: low-risk (score 3–9), medium-risk (score 10–15), and high-risk (score 16–22), with mortalities of 4.9% (2/41), 45.9% (28/61), and 78.3% (18/23) respectively. ROC curve analysis indicated that a LUPHAS score could effectively predict all-cause mortality [area under the curve (AUC) = 0.86, CI 95% 0.79–0.92]. In addition, LUPHAS score performed better than the qSOFA score alone (AUC = 0.69, CI 95% 0.59–0.78), or CURB-65 score (AUC = 0.69, CI 95% 0.59–0.80) in the subgroup of lung infections (n = 108). CONCLUSIONS: Based on a large emergency cohort of lupus patients complicated with invasive infection, the LUPHAS score was established to predict the short-term all-cause mortality, which could be a promising applicable tool for risk stratification in clinical practice. SAGE Publications 2019-11-05 /pmc/articles/PMC6831971/ /pubmed/31723357 http://dx.doi.org/10.1177/1759720X19885559 Text en © The Author(s), 2019 http://www.creativecommons.org/licenses/by-nc/4.0/ This article is distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 License (http://www.creativecommons.org/licenses/by-nc/4.0/) which permits non-commercial use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access pages (https://us.sagepub.com/en-us/nam/open-access-at-sage).
spellingShingle When Rheumatology and Infectious Disease Come Together
Wu, Wanlong
Ma, Jun
Zhou, Yuhong
Tang, Chao
Zhao, Feng
Sun, Fangfang
Xu, Wenwen
Chen, Jie
Ye, Shuang
Chen, Yi
Mortality risk prediction in lupus patients complicated with invasive infection in the emergency department: LUPHAS score
title Mortality risk prediction in lupus patients complicated with invasive infection in the emergency department: LUPHAS score
title_full Mortality risk prediction in lupus patients complicated with invasive infection in the emergency department: LUPHAS score
title_fullStr Mortality risk prediction in lupus patients complicated with invasive infection in the emergency department: LUPHAS score
title_full_unstemmed Mortality risk prediction in lupus patients complicated with invasive infection in the emergency department: LUPHAS score
title_short Mortality risk prediction in lupus patients complicated with invasive infection in the emergency department: LUPHAS score
title_sort mortality risk prediction in lupus patients complicated with invasive infection in the emergency department: luphas score
topic When Rheumatology and Infectious Disease Come Together
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6831971/
https://www.ncbi.nlm.nih.gov/pubmed/31723357
http://dx.doi.org/10.1177/1759720X19885559
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