Suppr超能文献

犬利什曼病复发:通过混合效应逻辑回归确定的风险因素。

Relapses in canine leishmaniosis: risk factors identified through mixed-effects logistic regression.

机构信息

Animal Health Department, Faculty of Veterinary Medicine, Complutense University of Madrid, Madrid, Spain.

Department of Quantitative Methods, Universidade Federal Do Estado Do Rio de Janeiro, Rio de Janeiro, Brazil.

出版信息

Parasit Vectors. 2024 Aug 22;17(1):357. doi: 10.1186/s13071-024-06423-1.

Abstract

BACKGROUND

Canine leishmaniosis (CanL), caused by Leishmania infantum, is an important vector-borne parasitic disease in dogs with implications for human health. Despite advancements, managing CanL remains challenging due to its complexity, especially in chronic, relapsing cases. Mathematical modeling has emerged as a powerful tool in various medical fields, but its application in understanding CanL relapses remains unexplored.

METHODS

This retrospective study aimed to investigate risk factors associated with disease relapse in a cohort of dogs naturally infected with L. infantum. Data from 291 repeated measures of 54 dogs meeting the inclusion criteria were included. Two logistic mixed-effects models were created to identify clinicopathological variables associated with an increased risk of clinical relapses requiring a leishmanicidal treatment in CanL. A backward elimination approach was employed, starting with a full model comprising all potential predictors. Variables were iteratively eliminated on the basis of their impact on the model, considering both statistical significance and model complexity. All analyses were conducted using R software, primarily employing the lme4 package, and applying a significance level of 5% (P < 0.05).

RESULTS

This study identified clinicopathological variables associated with an increased risk of relapses requiring a leishmanicidal treatment. Model 1 revealed that for each 0.1 increase in the albumin/globulin ratio (A/G) ratio, the odds of requiring treatment decreased by 45%. Conversely, for each unit increase in the total clinical score (CS), the odds of requiring treatment increase by 22-30%. Indirect immunofluorescence antibody test (IFAT) was not a significant risk factor in model 1. Model 2, incorporating individual albumin and globulins values, showed that dogs with high IFAT titers, hyper beta-globulinemia, hypoalbuminemia, anemia, and high CS were at increased risk of relapse. Both models demonstrated a good fit and explained a substantial amount of variability in treatment decisions.

CONCLUSIONS

Dogs exhibiting higher CS, dysproteinemia, anemia, and high IFAT titers are at increased risk of requiring leishmanicidal treatment upon clinical relapse in CanL. Regular monitoring and assessment of risk factors prove essential for early detection of relapses and effective intervention in CanL cases. The contrasting findings between the two models highlight the complexity of aspects influencing treatment decisions in this disease and the importance of tailored management strategies to improve outcomes for affected dogs.

摘要

背景

犬利什曼病(CanL)是由利什曼原虫引起的一种重要的媒介传播寄生虫病,对人类健康有影响。尽管取得了进展,但由于其复杂性,特别是在慢性、复发性病例中,管理 CanL 仍然具有挑战性。数学建模已成为各种医学领域的有力工具,但在理解 CanL 复发方面的应用仍未得到探索。

方法

本回顾性研究旨在调查一组自然感染利什曼原虫的犬中与疾病复发相关的风险因素。纳入了符合纳入标准的 54 只犬的 291 次重复测量数据。创建了两个逻辑混合效应模型,以确定与 CanL 复发性需要利什曼杀治疗相关的临床相关变量。采用向后消除法,从包含所有潜在预测因子的完整模型开始。根据对模型的影响,逐步消除变量,同时考虑统计学意义和模型复杂性。所有分析均使用 R 软件进行,主要使用 lme4 包,并采用 5%的显著性水平(P<0.05)。

结果

本研究确定了与需要利什曼杀治疗的复发风险增加相关的临床相关变量。模型 1 显示,白蛋白/球蛋白(A/G)比值每增加 0.1,需要治疗的可能性就降低 45%。相反,总临床评分(CS)每增加一个单位,需要治疗的可能性就增加 22-30%。间接免疫荧光抗体试验(IFAT)在模型 1 中不是一个显著的风险因素。纳入个体白蛋白和球蛋白值的模型 2 显示,IFAT 滴度高、β-球蛋白血症、低白蛋白血症、贫血和高 CS 的犬复发风险增加。两个模型都表现出良好的拟合度,并解释了治疗决策中大量的变异性。

结论

在 CanL 中,CS 较高、蛋白血症、贫血和 IFAT 滴度高的犬在临床复发时需要利什曼杀治疗的风险增加。定期监测和评估风险因素对于早期发现复发和有效干预 CanL 病例至关重要。两个模型之间的对比结果突出了影响治疗决策的各个方面的复杂性,以及制定针对个体的管理策略以改善受影响犬的预后的重要性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0595/11342489/a11d11adfb38/13071_2024_6423_Fig1_HTML.jpg

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验