Analysis of the dynamics of transition from non-colonization to colonization and Staphylococcus aureus bacteremia in hemodialysis patients using Markov models. [version 3; peer review: 2 approved]
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 coloni...
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F1000 Research Ltd
2025-01-01
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| author | Difariney González-Gómez J Natalia Jiménez Johanna M Vanegas Daniela Montoya-Urrego |
| author_facet | Difariney González-Gómez J Natalia Jiménez Johanna M Vanegas Daniela Montoya-Urrego |
| author_sort | Difariney González-Gómez |
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| description | 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. |
| format | Article |
| id | doaj-art-af6554db284b4a7889e720dff33f3390 |
| institution | Kabale University |
| issn | 2046-1402 |
| language | English |
| publishDate | 2025-01-01 |
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| spelling | doaj-art-af6554db284b4a7889e720dff33f33902025-01-08T01:00:03ZengF1000 Research LtdF1000Research2046-14022025-01-0113176351Analysis of the dynamics of transition from non-colonization to colonization and Staphylococcus aureus bacteremia in hemodialysis patients using Markov models. [version 3; peer review: 2 approved]Difariney González-Gómez0J Natalia Jiménez1https://orcid.org/0000-0002-9183-1912Johanna M Vanegas2Daniela Montoya-Urrego3https://orcid.org/0000-0002-9326-4341Grupo de investigación Demografía y Salud, Facultad Nacional de Salud Pública, Universidad de Antioquia, Medellín, Antioquia, ColombiaGrupo de investigación en Microbiología Básica y aplicada (MICROBA), Escuela de Microbiología, Universidad de Antioquia, Medellín, Antioquia, ColombiaEscuela de Ciencias de la Salud, Universidad Pontificia Bolivariana, Medellín, Antioquia, ColombiaGrupo de investigación en Microbiología Básica y aplicada (MICROBA), Escuela de Microbiología, Universidad de Antioquia, Medellín, Antioquia, ColombiaBackground 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.https://f1000research.com/articles/13-837/v3Markov models Multistate models Staphylococcus aureus Hemodialysis Colonization Bacteremia.eng |
| spellingShingle | Difariney González-Gómez J Natalia Jiménez Johanna M Vanegas Daniela Montoya-Urrego Analysis of the dynamics of transition from non-colonization to colonization and Staphylococcus aureus bacteremia in hemodialysis patients using Markov models. [version 3; peer review: 2 approved] F1000Research Markov models Multistate models Staphylococcus aureus Hemodialysis Colonization Bacteremia. eng |
| title | Analysis of the dynamics of transition from non-colonization to colonization and Staphylococcus aureus bacteremia in hemodialysis patients using Markov models. [version 3; peer review: 2 approved] |
| title_full | Analysis of the dynamics of transition from non-colonization to colonization and Staphylococcus aureus bacteremia in hemodialysis patients using Markov models. [version 3; peer review: 2 approved] |
| title_fullStr | Analysis of the dynamics of transition from non-colonization to colonization and Staphylococcus aureus bacteremia in hemodialysis patients using Markov models. [version 3; peer review: 2 approved] |
| title_full_unstemmed | Analysis of the dynamics of transition from non-colonization to colonization and Staphylococcus aureus bacteremia in hemodialysis patients using Markov models. [version 3; peer review: 2 approved] |
| title_short | Analysis of the dynamics of transition from non-colonization to colonization and Staphylococcus aureus bacteremia in hemodialysis patients using Markov models. [version 3; peer review: 2 approved] |
| title_sort | analysis of the dynamics of transition from non colonization to colonization and staphylococcus aureus bacteremia in hemodialysis patients using markov models version 3 peer review 2 approved |
| topic | Markov models Multistate models Staphylococcus aureus Hemodialysis Colonization Bacteremia. eng |
| url | https://f1000research.com/articles/13-837/v3 |
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