To investigate the link between early excessive tacrolimus blood levels (trough concentration surpassing 20 ng/mL within the first week after surgery) and long-term graft performance in renal transplant patients, and to build a risk estimation algorithm for identifying individuals prone to such early supratherapeutic concentrations. This investigation was designed as a single-center, retrospective cohort analysis encompassing 210 kidney graft recipients (105 overexposed, 105 unexposed) after propensity score matching. Renal functional metrics (eGFR and cystatin C) and rates of infectious complications over the 12-month follow-up were evaluated using linear mixed-effects modeling, with multiple imputation. A Cox proportional hazards regression employing LASSO-based predictor selection was constructed to estimate the probability of developing early supratherapeutic levels. Recipients in the overexposed category displayed significantly poorer eGFR at postoperative days 7, 30, and 90 (adjusted mean differences: −11.32, −10.20, and −10.75 mL/min/1.73 m², respectively) and correspondingly higher cystatin C values (0.83, 0.36, and 0.36 mg/L). By the conclusion of the first year, eGFR continued to be reduced (−7.54 mL/min/1.73 m², P = 0.038) while cystatin C remained elevated (0.40 mg/L, P = 0.043) in this group. The cumulative incidence of infections at one year was substantially higher among overexposed individuals (80.0% vs 52.3%; adjusted OR = 4.27, P < 0.001). The derived predictive tool highlighted three dominant risk factors: carrying the CYP3A5 *3/*3 genotype (HR = 2.19), a raised C-reactive protein on the first postoperative day (HR = 1.27), and an increased weight-adjusted tacrolimus dose (HR = 1.58), yielding a C-index of 0.716 and an optimism-corrected C-index of 0.728. Early tacrolimus levels in the supratherapeutic range are independently associated with worse graft functional recovery and a greater burden of infectious events during the initial year post-transplantation. A prediction instrument incorporating genotypic, inflammatory biomarker, and dosing data holds promise for enabling the timely identification of high-risk recipients.
