利用马尔可夫模型分析血液透析患者从非定植到定植和金黄色葡萄球菌菌血症的动态变化。

Daniela Montoya-Urrego, J. M. Vanegas, J. N. Jiménez, Difariney González-Gómez
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A two-state recurrent continuous-time Markov model was constructed to model transition dynamics from non-colonization to S. aureus colonization in hemodialysis patients. Subsequently, the model was applied to a third state of bacteremia. Results Of 178 patients on hemodialysis, 30.3% were colonized by S. aureus. Transition intensity from non-colonization to colonization was three times higher (0.21; CI: 0.14-0.29) than from colonization to non-colonization (0.07; CI: 0.05-0.11). The colonization risk increased in patients with previous infections (HR: 2.28; CI: 0.78-6.68), hospitalization (HR: 1.29; CI: 0.56-2.99) and antibiotics consumption (HR: 1.17; CI: 0.53-2.58). Mean non-colonized state duration was 10.9 months, while in the colonized state was 5.2 months. In the 3-state model, it was found that patients colonized were more likely to develop S. aureus infection (13.9%). 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引用次数: 0

摘要

背景 血液透析患者经常被金黄色葡萄球菌定植,导致严重感染,死亡率很高。然而,随着时间的推移,人们对从非定植到定植或菌血症的转变知之甚少。本研究旨在分析金黄色葡萄球菌的定植行为,确定从非定植状态过渡到定植状态或菌血症的概率,以及一些协变量的影响。方法 该研究于 2017 年 10 月至 2019 年 10 月期间在麦德林一家高复杂性医院的透析室进行。首次测量是为了评估金黄色葡萄球菌定植情况,2 个月和 6 个月后进行了随访测量。对菌血症的演变进行了为期 12 个月的监测。构建了一个双状态循环连续时间马尔可夫模型,以模拟血液透析患者从未定菌到金黄色葡萄球菌定菌的过渡动态。随后,该模型被应用于菌血症的第三种状态。结果 在 178 名血液透析患者中,30.3% 的患者被金黄色葡萄球菌定植。从非定植到定植的转变强度(0.21;CI:0.14-0.29)比从定植到非定植的转变强度(0.07;CI:0.05-0.11)高三倍。既往感染(HR:2.28;CI:0.78-6.68)、住院(HR:1.29;CI:0.56-2.99)和使用抗生素(HR:1.17;CI:0.53-2.58)的患者的定植风险增加。非定植状态的平均持续时间为 10.9 个月,定植状态的平均持续时间为 5.2 个月。在三状态模型中发现,定植患者更容易感染金黄色葡萄球菌(13.9%)。结论 发现从非定植到定植的过渡可能性更大,这与先前感染等因素有关。此外,与未定植菌落的患者相比,定植菌落的患者更容易发生菌血症。这些结果凸显了对金黄色葡萄球菌定植进行监测和适当管理的重要性,以防止出现菌血症等严重并发症,并改善这一易感人群的预后。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Analysis of the dynamics of transition from non-colonization to colonization and Staphylococcus aureus bacteremia in hemodialysis patients using Markov models.
Background Hemodialysis patients are frequently colonized by Staphylococcus aureus, leading to severe infections with high mortality rates. However, little is known about transition from non-colonization to colonization or bacteremia over time. The aim was to analyze the behavior of S. aureus colonization, identifying the probability of transition from non-colonized to colonized state or bacteremia, and the influence of some covariates. Methods The study was conducted in a dialysis unit associated with a high complexity hospital in Medellín between October 2017 and October 2019. An initial measurement was taken to evaluate S. aureus colonization, and follow-up measurements were performed 2 and 6 months later. Bacteremia evolution was monitored for 12 months. A two-state recurrent continuous-time Markov model was constructed to model transition dynamics from non-colonization to S. aureus colonization in hemodialysis patients. Subsequently, the model was applied to a third state of bacteremia. Results Of 178 patients on hemodialysis, 30.3% were colonized by S. aureus. Transition intensity from non-colonization to colonization was three times higher (0.21; CI: 0.14-0.29) than from colonization to non-colonization (0.07; CI: 0.05-0.11). The colonization risk increased in patients with previous infections (HR: 2.28; CI: 0.78-6.68), hospitalization (HR: 1.29; CI: 0.56-2.99) and antibiotics consumption (HR: 1.17; CI: 0.53-2.58). Mean non-colonized state duration was 10.9 months, while in the colonized state was 5.2 months. In the 3-state model, it was found that patients colonized were more likely to develop S. aureus infection (13.9%). Conclusion A more likely transition from non-colonization to colonization was found, which increases with factors such as previous infection. In addition, the development of bacteremia was more likely in colonized than in non-colonized patients. These results underline the importance of surveillance and proper management of S. aureus colonization to prevent serious complications, such as bacteremia, and improve prognosis in this vulnerable population.
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