ABSTRACT Introduction: Acute kidney injury (AKI) is a common postoperative complication (postoperative AKI, [PO-AKI]), occurring in up to 35% of non-cardiac surgery. Some biomarkers have shown value in early identification but are underused in clinical practice due to their high cost. The SPARK score and the hemoglobin-to-red cell distribution width ratio (Hb/RDW) have emerged as accessible alternatives for predicting PO-AKI. Objective: To evaluate studies on SPARK predictors and hematological biomarkers for risk stratification of PO-AKI in non-cardiac surgery. Methods: An integrative review was conducted across four databases (PubMed/MEDLINE, LILACS, Embase, and Web of Science), covering publications between 2019 and 2025 in Portuguese and English. Studies including adults undergoing non-cardiac surgery were included. The selection process was documented using a PRISMA 2020 flow diagram. Results: Six studies were included. The SPARK score showed an AUC ranging from 0.69 to 0.81 in external validations, with superior performance in modified models for specific populations. The Hb/RDW index demonstrated good accuracy (AUC 0.714; sensitivity 72.7%; specificity 70.8%) in elderly orthopedic patients, with lower values associated with increased risk of PO-AKI. Discussion: The effectiveness of SPARK depends on the population profile, highlighting the importance of external validation and contextual adjustments. Hb, RDW, and the Hb/RDW ratio appear to be promising tools to complement SPARK. Conclusion: The application of SPARK may be limited in different contexts. Simple biomarkers such as Hb, RDW, and Hb/RDW show good predictive potential and may improve the early identification of patients at risk for PO-AKI.
Abstract Introduction: Postnatal growth profile is believed to have an impact on the risk of later obesity and of cardiovascular and kidney disease. We aimed to study the association between different trajectories of weight gain during infancy and early childhood and the renal function in prepubertal children. Methods: Longitudinal study of 1,004 children aged 7–9 years, divided into four groups of weight gain trajectories from birth to 6 years (I: eutrophic/reference; II: early-onset persistent accelerated weight gain; III: childhood-onset accelerated weight gain; and IV: early transient weight gain). Glomerular filtration rate (GFR) was estimated by several formulas using serum creatinine (Cr) and/or cystatin C (CysC), and by 24-hour creatinine clearance (CrCl). Results: Individuals in trajectory I presented the lowest Cr and CysC and the highest estimated GFR (eGFR) values, while trajectory II included those with the lowest eGFR, estimated by the Filler and Le Bricon formulas. Trajectory I individuals presented the lowest absolute CrCl values, while those in trajectory II presented the highest values. In multivariate linear regression models adjusted for age, sex, birth weight-for-gestational-age category, blood pressure, and current body mass index, trajectory III was associated with an eGFR that was 2.68 to 3.75 mL/min/1.73 m2 lower than that of trajectory I in the two models based on CysC. Conclusions: Children with early-onset persistent or childhood-onset accelerated weight gain presented significantly lower eGFR, which supports the influence of childhood growth patterns on later kidney function.
Abstract Objective: Identifying reliable biomarkers to predict mortality in hemodialysis patients is essential for risk stratification and clinical decision-making. This study evaluated the prognostic value of the serum uric acid-to-creatinine ratio (SUA/SCr), C-reactive protein-to-albumin ratio (CAR), neutrophil percentage-to-albumin ratio (NPAR), and lactate dehydrogenase (LDH). Methods: This retrospective cohort study included 138 maintenance hemodialysis patients with at least 6 months of dialysis vintage (2017–2025). Demographic, biochemical, and hematological data were obtained from medical records. Dialysis adequacy was assessed using Kt/Vurea. Mortality predictors were analyzed using ROC curves, logistic regression, and survival analysis. Results: The mean age of the study population was 60.6 ± 15.1 years, and 50.7% were female. Deceased patients were significantly older than survivors (65.1 ± 16.2 vs. 58.9 ± 14.5 years; p = 0.032). The median hemodialysis vintage was 63.5 months, and 55.1% of patients used a hemodialysis catheter. Mortality was significantly higher among catheter users (p = 0.002). Deceased patients exhibited higher levels of CRP, SUA/SCr, CAR, and NPAR, along with lower albumin levels (all p < 0.001), as well as higher ferritin levels (p = 0.043). ROC analysis identified LDH ≥ 165.5, CAR ≥ 3.1, and NPAR ≥ 18.15 as optimal cut-off values associated with increased mortality risk. In multivariable analysis, CAR, NPAR, LDH, continuous SUA/SCr, and vascular access type were independent predictors of mortality. Kaplan–Meier analysis demonstrated significantly reduced survival in high-risk groups. Conclusion: Elevated SUA/SCr, CAR, NPAR, and LDH levels are significantly associated with mortality in hemodialysis patients. CAR, NPAR, continuous SUA/SCr, LDH, and catheter use independently predict all-cause mortality.
