Montoya-Urrego Daniela, Vanegas Johanna M, Jiménez J Natalia, González-Gómez Difariney
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.
F1000Res. 2025 Jan 6;13:837. doi: 10.12688/f1000research.151896.1. eCollection 2024.
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.
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.
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%).
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.
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。
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。
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%）。
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。
