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Background Hyperlactatemia is common in intensive care unit (ICU) patients. The aim of our retrospective observational study was to analyse the impact of serum lactate on admission on mortality in patients with acute kidney injury (AKI) treated with renal replacement therapy (RRT). Methods During the study period of 4 years, 2939 patients were admitted to the ICU, 503 patients were diagnosed with AKI and 209 of them required RRT. After excluding patients on chronic dialysis and with known malignant disease, we retrospectively analysed 154 patients. Hyperlactatemia was defined as a serum lactate concentration above 4 mmol/L on admission to the ICU. Results The mean age of patients was 62.8 years, and 69.5% were men. The mean Charlson Comorbidity Index (CCI) on admission to the ICU was 3.7 and fifty-six (36.4%) patients had acute hyperlactatemia. All included patients had AKI stage 3 and were treated with RRT, 125 (81.2%) with continuous RRT and 29 (18.8%) with intermittent hemodialysis. The mean length of stay in the ICU was 15.7 ± 13 days and 118 (76.6%) patients died during the 60-day observation period. A Kaplan-Meier survival analysis showed that the survival rate was statistically significantly lower in the group of patients with hyperlactatemia (log-rank; p  = 0.032). The univariate Cox regression analysis showed that serum lactate on admission to the ICU significantly predict 60-day survival (HR 1.075; 95%CI 1.015–1.140; p  = 0.014). In the multivariate Cox regression analysis, which included age, gender, diabetes, hypertension, chronic kidney disease, estimated glomerular filtration rate, serum lactate, CCI and C-reactive protein, only age (HR 1.031; 95%CI 1.007–1.056; p  = 0.011) and serum lactate (HR 1.067; 95%CI 1.004–1.134; p  = 0.035) were independent predictors of mortality. Conclusion Our study underscores the independent association between hyperlactatemia of more than 4 mmol/L on admission to the ICU and increased 60-day mortality in patients with AKI treated with RRT. These findings, which have significant implications for the management and prognosis of critically ill patients with AKI, provide a new understanding of the role of serum lactate in patient outcomes. Trial registration Name of the registry: ClinicalTrials.gov; Trial registration number: NCT06565403; Date of registration, followed by the words 'Retrospectively registered': August, 19,2024; URL of trial registry record: https://clinicaltrials.gov/study/NCT06565403.

The efficiency of universal electric motors that are widely used in home appliances can be improved by optimizing the geometry of the rotor and the stator. Expert designers traditionally approach this task by iteratively evaluating candidate designs and improving them according to their experience. However, the existence of reliable numerical simulators and powerful stochastic optimization techniques make it possible to automate the design procedure. We present a comparative study of six stochastic optimization algorithms in designing optimal rotor and stator geometries of a universal electric motor where the primary objective is to minimize the motor power losses. We compare three methods from the domain of evolutionary computation, generational evolutionary algorithm, steady-state evolutionary algorithm and differential evolution, two particle-based methods, particle-swarm optimization and electromagnetism-like algorithm, and a recently proposed multilevel ant stigmergy algorithm. By comparing their performance, the most efficient method for solving the problem is identified and an explanation of its success is offered.[PUBLICATION ABSTRACT]