Traumatic cervical spinal cord injury (SCI) frequently leads to severe neurological deficits. Early decompressive surgery, when performed shortly after the injury, is believed to improve outcomes. However, the impact of surgical timing, calculated from the moment of injury, and injury characteristics on neurological recovery remains poorly understood. This study aims to assess the impact of early decompressive surgery and injury characteristics on neurological recovery in traumatic cervical SCI patients. A retrospective case-control study was conducted at the 108 Central Military Hospital in Hanoi, Vietnam, between January 2018 and June 2023. Data collected included demographics, injury characteristics, time from injury to decompression surgery, and clinical outcomes at the 1-year follow-up. Among the 193 patients initially screened, 156 met the inclusion criteria. Neurological recovery was observed in 44.2 % of patients. Early decompression within 24 h significantly improved recovery outcomes (OR = 3.12, p = 0.006). Injury at C1–C3 levels, longer spinal cord injury length, and severe spinal canal stenosis were associated with poorer recovery (OR = 0.34, p = 0.015; OR = 0.21, p < 0.001; OR = 0.34, p = 0.009, respectively). Prolonged ICU stay correlated with worse recovery (OR = 0.90, p = 0.002). Early decompressive surgery, thorough assessment of injury characteristics, and minimizing ICU stay duration are critical for improving neurological recovery. These findings highlight the importance of timely surgery and strategic clinical management in enhancing recovery outcomes in traumatic cervical SCI patients.

BACKGROUND:Early bacterial infections are a common and clinically significant complication after living donor liver transplantation. However, clinically usable tools for early individualized risk stratification remain limited in routine clinical practice. MATERIAL AND METHODS:This single-center retrospective cohort study included 205 adult patients who underwent LDLT between October 1, 2017, and October 31, 2025. All patients had complete 30-day follow-up for outcome ascertainment. Early bacterial infection was defined as a microbiologically confirmed infection occurring within 30 days after transplantation. Univariable and multivariable logistic regression analyses were performed to identify independent predictors. Model performance was evaluated using receiver operating characteristic (ROC) analysis, bootstrap-based calibration, and decision curve analysis. Static and web-based dynamic nomograms were constructed based on the final model. RESULTS:Early bacterial infections occurred in 45 patients (21.9%). Higher pre-transplant MELD score, post-transplant blood transfusion, bile leakage, and longer intensive care unit (ICU) stay were independently associated with infection risk. The dynamic risk stratification tool demonstrated good discrimination (AUC=0.792, 95% CI 0.716-0.867), good calibration on internal bootstrap validation (MAE and MSE), and favorable net clinical benefit on decision curve analysis. The web-based dynamic nomogram enabled real-time individualized risk estimation using routinely available clinical variables. CONCLUSIONS:We developed and internally validated a dynamic risk stratification tool for early bacterial infections after LDLT, implemented as static and web-based dynamic nomograms. The tool reflects evolving postoperative risk rather than prediction at a fixed time point, with good apparent performance. However, its true performance and generalizability remain uncertain, and external validation is required before clinical application.