Back

Incidence and factors associated with infections in kidney transplant recipients at the tertiary hospital, Thailand.

Phacharoen, S.; Prawang, A.; Kanchanasurakit, S.; Phonphok, K.; Duangrithi, D.; Petchcharee, P.; Sangsanit, W.; Jintasataporn, R.

2026-09-30 infectious diseases
10.64898/2026.09.28.26364156 medRxiv
Show abstract

Background/Aims: In medical practice, the rising prevalence of infections in kidney transplant recipients (KTRs) is a notable concern. However, understanding the incidence and risk factors associated with infections in KTRs remains limited. This study aims to assess the incidence and factors associated infection among KTRs. Additionally, we also investigate the median time of each infection among KTRs. Methods: A retrospective cohort study was conducted from 1 January 2018- 31 December 2022 at Thailand's tertiary hospital. We performed univariable and multivariable logistic regression analyses to identify potential risk factors related infection and investigated for the incidence and median time of each infection among KTRs. Results: A total of 179 participants were included in this study. Our findings reveal the kidney from living donor was protective factor for infection among KTRs (aOR 0.063, 95% CI 0.005-0.792; p = 0.032). Urinary tract infections (UTIs)showed as the predominant pathogenic manifestation among KTRs (43%). The median time of UTIs, cytomegalovirus (CMV) infection and pneumocystis pneumonia (PCP) were 16, 57 and 94.5 days, respectively. Conclusions: Our study establishes that receiving a kidney from a living donor is a protective factor against post-kidney transplant infections. Particularly urinary tract infections were most common of infection. Monitoring urinary tract infections post-transplantation is recommended. Moreover, awareness of UTI, CMV infection and PCP should be concerned during 2-3 months after transplantation. However, due to a small sample size; we recommend to increase the number of particular participants in further investigations.

Matching journals

The top 9 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.