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Dataset Information

Longitudinal non-targeted metabolomic profiling of urine samples for monitoring of kidney transplantation patients.


ABSTRACT: The assessment of kidney function within the first year following transplantation is crucial for predicting long-term graft survival. This study aimed to develop a robust and accurate model using metabolite profiles to predict early long-term outcomes in patient groups at the highest risk of early graft loss. A group of 61 kidney transplant recipients underwent thorough monitoring during a one-year follow-up period, which included a one-week hospital stay and follow-up assessments at three and six months. Based on their 12-month follow-up serum creatinine levels: Group 2 had levels exceeding 1.5 mg/dl, while Group 1 had levels below 1.5 mg/dl. Metabolites were detected by mass spectrometer and first pre-processed. Univariate and multivariate statistical analyses were employed to identify s

SUBMITTER: Yozgat I 

PROVIDER: S-EPMC10791079 | biostudies-literature | 2024 Dec

REPOSITORIES: biostudies-literature