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Analysis of the dynamics of transition from non-colonization to colonization and Staphylococcus aureus bacteremia in hemodialysis patients using Markov models. [version 2; peer review: 2 approved with reservations]
- Source :
- F1000Research. 13:837
- Publication Year :
- 2024
- Publisher :
- London, UK: F1000 Research Limited, 2024.
-
Abstract
- 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 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 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.
Details
- ISSN :
- 20461402
- Volume :
- 13
- Database :
- F1000Research
- Journal :
- F1000Research
- Notes :
- Revised Amendments from Version 1 In this revised version, we addressed the reviewers' comments and made significant improvements in several sections. In the Introduction, we expanded the explanation of the role, relevance, and appropriateness of using the Markov model in studying the dynamics of Staphylococcus aureus colonization and infection in hemodialysis patients. In addition, we refined the Methods section to clarify how transition periods were calculated using the transition matrix Q, emphasizing the assumption of temporal homogeneity inherent to Markov models. In the Results section, we added details of the exclusion of some patients, and added colonization and infection data from patients in the Extended data, to provide a clearer presentation of the findings. The Discussion was enriched, now including a detailed explanation of the limitations in our study, related to the clinical implications of our findings, the dialysis unit where the study was conducted, the sample size, and the temporality of our study. New “Extended Data” was added, including the code used for the Markov model analysis and additional data detailing the colonization and infection status of patients at different time points. The References section was updated to include new relevant sources supporting the reviews conducted and discussion points. These updates undoubtedly improve the clarity, reproducibility, and clinical relevance of the study., , [version 2; peer review: 2 approved with reservations]
- Publication Type :
- Academic Journal
- Accession number :
- edsfor.10.12688.f1000research.151896.2
- Document Type :
- research-article
- Full Text :
- https://doi.org/10.12688/f1000research.151896.2