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使用马尔可夫模型分析血液透析患者从非定植到定植及菌血症的转变动态。

Analysis of the dynamics of transition from non-colonization to colonization and bacteremia in hemodialysis patients using Markov models.

作者信息

Montoya-Urrego Daniela, Vanegas Johanna M, Jiménez J Natalia, González-Gómez Difariney

机构信息

Grupo de investigación en Microbiología Básica y aplicada (MICROBA), Escuela de Microbiología, Universidad de Antioquia, Medellín, Antioquia, Colombia.

Escuela de Ciencias de la Salud, Universidad Pontificia Bolivariana, Medellín, Antioquia, Colombia.

出版信息

F1000Res. 2025 Jan 6;13:837. doi: 10.12688/f1000research.151896.1. eCollection 2024.

Abstract

BACKGROUND

Hemodialysis patients are frequently colonized by , 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 colonization, identifying the probability of transition from non-colonized to colonized state or bacteremia, and the influence of specific covariates.

METHODS

The study was conducted in a dialysis unit associated with a tertiary care hospital in Medellín between October 2017 and October 2019. An initial measurement was taken to evaluate 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 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 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 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 colonization to prevent serious complications, such as bacteremia, and improve prognosis in this vulnerable population.

摘要

背景

血液透析患者常被[具体细菌名称未给出]定植,导致严重感染且死亡率高。然而,对于随时间从非定植状态转变为定植状态或菌血症的情况知之甚少。目的是分析[具体细菌名称未给出]的定植行为,确定从非定植状态转变为定植状态或菌血症的概率,以及特定协变量的影响。

方法

该研究于2017年10月至2019年10月在麦德林一家三级护理医院的透析单元进行。进行了初始测量以评估[具体细菌名称未给出]的定植情况,并在2个月和6个月后进行了随访测量。对菌血症演变进行了12个月的监测。构建了一个两状态递归连续时间马尔可夫模型,以模拟血液透析患者从非定植状态到[具体细菌名称未给出]定植状态的转变动态。随后,将该模型应用于菌血症的第三种状态。

结果

在178例血液透析患者中,30.3%被[具体细菌名称未给出]定植。从非定植状态到定植状态的转变强度(0.21;可信区间:0.14 - 0.29)是非定植状态到定植状态转变强度(0.07;可信区间:0.05 - 0.11)的三倍。既往有感染(风险比:2.28;可信区间:0.78 - 6.68)、住院(风险比:1.29;可信区间:0.56 - 2.99)和使用抗生素(风险比:1.17;可信区间:0.53 - 2.58)的患者定植风险增加。非定植状态的平均持续时间为10.9个月,而定植状态的平均持续时间为5.2个月。在三状态模型中,发现定植患者更有可能发生[具体细菌名称未给出]感染(13.9%)。

结论

发现从非定植状态到定植状态的转变更有可能发生,且会因既往感染等因素而增加。此外,定植患者发生菌血症的可能性高于非定植患者。这些结果强调了监测和妥善管理[具体细菌名称未给出]定植以预防严重并发症(如菌血症)以及改善这一脆弱人群预后的重要性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ea22/11812933/f19d504722e7/f1000research-13-176351-g0000.jpg

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