Aleksej A. Noskov

Objective . To substantiate the concept of perioperative infectious risk by analyzing current approaches to classifying complications, methods for predicting them, and the key factors influencing surgical outcomes. Materials and Methods. We conducted an analytical review based on expert judgement and a systematic search of publications from the preceding 10 years in PubMed and Lens.org. The analysis included data on the epidemiology of infectious complications, classification systems (CDC, Clavien-Dindo, Accordion), prognostic scores (ASA, SOFA, ACS-NSQIP, SORT), laboratory markers (CRP, IL-6, procalcitonin, neutrophil-tolymphocyte ratio), and machine learning models (PERISCOPE AI, Random Forest, SVM, ensemble methods). Results . The risk of infectious complications was shown to be determined by the cumulative effect of modifiable and nonmodifiable factors related to both the patient and the healthcare facility. Laboratory markers demonstrated high prognostic value: IL-6 levels above 432 pg/mL and CRP 150 mg/L on postoperative day 3 were statistically significantly associated with adverse outcomes. Advanced prognostic tools provided high accuracy: the AUROC for ACS-NSQIP reached 0.80, and for PERISCOPE AI, 0.82–0.91. The use of scoring systems and machine learning made it possible to identify high-risk patients before clinical symptoms appeared. Conclusion . Risk of perioperative infections is multifactorial and requires an integrated approach to risk stratification, incorporating clinical data, risk assessment scales, laboratory markers, and AI models. The use of structured prognostic tools enables early identification of complications, optimize prevention, and reduce mortality.

Objective. To develop and externally validate the models for predicting in-hospital mortality and septic complications in patients with COVID-19. Material and methods. This study was conducted in accordance with the TRIPOD guidelines. A retrospective derivation cohort included patients hospitalized between April 2020 and December 2021. External validation was performed in a cohort of patients hospitalized during the period of Omicron variant predominance (January—February 2022). Results. The final model included age, SpO2, respiratory rate, and Glasgow Coma Scale score. The derivation cohort included 488 patients, while the validation cohort comprised 382 patients. During external validation, AUROC for in-hospital mortality was 0.798 (95% CI 0.752—0.845), while AUROC for sepsis and septic shock were 0.680 and 0.704, respectively. Calibration was good for mortality and less pronounced for other outcomes. Conclusion. Original model demonstrates stable discriminative performance and acceptable calibration for predicting in-hospital mortality in patients with COVID-19.

COVID-19 remains one of the most significant causes of hospital admissions and deaths, frequently associated with septic complications. Reliable and simple prognostic tools are required to identify patients at high risk of developing sepsis and death early on. Aim of the study. To evaluate the prognostic ability of the REMS, NEWS, NEWS2, qSOFA, and SIRS criteria in predicting sepsis, septic shock, and mortality in patients with COVID-19. Materials and methods. A retrospective study was performed on 870 patients with confirmed COVID-19 who were hospitalized in anesthesiology and intensive care units. REMS, NEWS, NEWS2, qSOFA, and SIRS scores were calculated for each patient upon admission. The predictive ability of the scales was evaluated using ROC analysis, temporal associations were assessed using the Cox proportional hazards model, and the cumulative risk of outcome was assessed using the Kaplan–Meier method. Results. The REMS scale demonstrated satisfactory predictive ability for mortality and septic shock (AUC = 0.780 and 0.724, respectively) and unsatisfactory for sepsis (AUC = 0.677), p < 0.0001. The NEWS, NEWS2, qSOFA, and SIRS scales showed unsatisfactory results for all outcomes. The Kaplan–Meier analysis showed that patients with high REMS scores developed sepsis or septic shock earlier and had shorter survival ( p < 0.0001). The Cox model identified REMS as the scale with the highest risk ratio (RR 1.215; 95% CI 1.178–1.254) and concordance index (C = 0.656). Conclusion. The REMS, NEWS, NEWS2, qSOFA, and SIRS rapid scales have a statistically significant prognostic value, but only the REMS provides a satisfactory accuracy in predicting septic shock and death in patients with COVID-19. The study was limited by its single-center and retrospective design.

INTRODUCTION: Despite the widespread use of rapid risk stratification scales, their prognostic value for the COVID-19 (COronaVIrus Disease 2019) remains unclear. OBJECTIVE: To evaluate the prognostic performance of rapid scoring systems in predicting mortality and adverse outcomes (ICU admission, organ support, or death) in patients with COVID-19. MATERIALS AND METHODS: A literature search was conducted in PubMed, eLIBRARY.RU and ScienceGate for studies published from January 2019 to January 2025. Prospective and retrospective observational studies were included. Prognostic accuracy was assessed via meta-analysis of AUROC (Area Under the Receiver Operating Characteristic Curve). Data synthesis and quality assessment were performed using MedCalc 20.027, Microsoft Excel 2019 and the GRADE approach. RESULTS: Sixty observational studies (mostly cohort and retrospective designs) with 619,494 patients were included. Five scoring systems were analyzed for predicting in-hospital mortality: NEWS, NEWS2, REMS, qSOFA, and SIRS. REMS showed the highest prognostic value (AUC = 0.808; 95% CI: 0.776–0.839), while SIRS showed the lowest (AUC = 0.662; 95% CI: 0.596–0.728). The NEWS, NEWS2, and qSOFA scores demonstrated fair performance (AUC ranging from 0.722 to 0.782). High heterogeneity was observed across studies (I² > 96%, p < 0.1). The same five tools were evaluated for predicting severe COVID-19. NEWS and NEWS2 were the most accurate (AUC = 0.778; 95% CI: 0.707–0.849 and 0.738–0.819, respectively). REMS also showed fair performance (AUC = 0.733; 95% CI: 0.708–0.757) with minimal heterogeneity (I² = 0%, p > 0.1), whereas qSOFA and SIRS were less accurate. Heterogeneity remained high for NEWS, NEWS2, and qSOFA. CONCLUSIONS: This systematic review and meta-analysis indicate that REMS, NEWS, NEWS2, and qSOFA have acceptable prognostic value for predicting mortality and severe outcomes in COVID-19 patients. REMS was most effective for mortality prediction, while NEWS and NEWS2 were more suitable for identifying patients at risk of severe disease. These findings support the use of rapid scoring systems in clinical risk stratification.

Background. Despite ample research on the coronavirus infection sequence and therapy, the incidence of adverse outcomes remains very high. Sepsis stands among the major factors greatly complicating treatment and increasing the risk of death. A timely identification of highrisk sepsis patients is a cornerstone of effective sepsis prevention.Objectives. A comparative prognostic power assessment between the quick Sequential Organ Failure Assessment (qSOFA) scale, National Early Warning Score (NEWS), Initial Prehospital Rapid Emergency Medicine Score (REMS) and the Systemic Inflammatory Response Syndrome (SIRS) criteria for sepsis detection in anaesthetic intensive care patients with a diagnosis: SARS-CoV-2, virus unidentified.Methods. A retrospective observational study included 166 patients over 18-year age with unconfirmed infection (ICD-10 code U07.2). The qSOFA, NEWS, REMS and SIRS point estimates were obtained from each patient. The patients were retrospectively divided in two cohorts by sepsis presence (Sepsis-3 criteria) to determine the express scales power in evaluating the risk of sepsis (estimated as area under ROC curve, AUROC).Results. Data on 102 patients were included in the final analysis. Fifty-eight (57%) patients were terminal, and 55 (54%) developed sepsis. The estimates are as follows: NEWS — AUROC 0.848 [95% confidence interval (CI) 0.764–0.912], sensitivity 76.36% [95% CI 63.0–86.8], specificity 82.98% [95% CI 69.2–92.4], optimal cut-off threshold >5 points; qSOFA — AUROC 0.700 [95% CI 0.602–0.787], sensitivity 76.36% [95% CI 63.0–86.8], specificity 61.70% [95% CI 46.4–75.5], optimal cut-off threshold >0 points; REMS — AUROC 0.739 [95% CI 0.643–0.821], sensitivity 69.09% [95% CI 55.2–80.9], specificity 65.96% [95% CI 50.7–79.1], optimal cut-off threshold >5 points; SIRS criteria — AUROC 0.723 [95% CI 0.626–0.807], sensitivity 98.18% [95% CI 90.3–100.0], specificity 31.91% [95% CI 19.1–47.1], optimal cut-off threshold >0 points.Conclusion. The NEWS scale revealed a good prognostic power to estimate the risk of sepsis in patients with suspected COVID-19 disease. The qSOFA, REMS scales and SIRS criteria possess a good calibration capacity, albeit insufficient resolution, which limits their prognostic value.

Introduction. Novel coronavirus disease is often accompanied by sepsis. This leads us to search of sepsis prediction tools. Objectives. Comparison of REMS, NEWS, qSOFA scales and SIRS criteria in sepsis prediction for patients with confirmed SARS-CoV-2 infection. Materials and methods. 167 medical cards retrospective analysis of patients with confirmed SARS-CoV-2 infection on admission to ICU. Results. In sepsis prediction only NEWS (0,819 [95% CI 0.738–0,884]) showed resolution high enough to serve as supplemental clinical information. REMS (0.798 [95% CI 0.715–0.866]), qSOFA (0.716 [95% CI 0.626–0.795]) and SIRS criteria (0.710 [95% CI 0.620–0.790]) showed insufficient resolution in sepsis prediction for patients with SARS-CoV-2. NEWS in pairwise comparison showed significantly better resolution than qSOFA (p = 0.002) and SIRS criteria (p = 0.013). All scales showed good calibration. Conclusions. Only NEWS scale showed good resolution and calibration and can be used as supplemental clinical information in sepsis prediction for patients with SARS-CoV-2 infection.