Igor Borisovich Zabolotskikh

INTRODUCTION: Opioid-induced respiratory depression (OIRD) and related complications remain a key concern of postoperative analgesia, particularly in high perioperative-risk patients with obesity and type 2 diabetes mellitus (T2DM). OBJECTIVE: To compare the respiratory safety and clinico-economic outcomes of postoperative analgesia with morphine, trimeperidine, and Tafalgin in high-risk patients. MATERIALS AND METHODS: A retrospective secondary analysis of two datasets: a pharmacoepidemiological cohort of 6,000 patients (2,000 each in the Tafalgin, morphine, and trimeperidine groups) and a regional pharmacoeconomic cohort of 1,500 patients with T2DM and obesity (180, 675, and 645, respectively). Event rates were compared using Pearson's χ2 test, with Fisher's exact test for rare events, calculating relative risk (RR) and 95% CI; Tafalgin served as reference. RESULTS: Groups were comparable in baseline characteristics and surgical structure (all p > 0.05). The 6-month pneumonia rate was 1.15 % with Tafalgin vs 8.20 % with morphine (RR 7.13; 95% CI 4.63–10.98; p < 0.001) and 7.45 % with trimeperidine (RR 6.48; 95% CI 4.19–10.01; p < 0.001). In the regional cohort, complication rates were 5.56, 19.41, and 18.45 % (RR 3.49 and 3.32; p < 0.001). In class II–III obesity (BMI ≥ 35.0 kg/m2), Tafalgin's advantage increased with obesity severity: the number needed to treat (NNT) versus morphine fell from 4.2 to 3.1. Over a 12-month horizon, total direct costs per patient were lower with Tafalgin by 4,528–4,994 RUB, corresponding to a dominant strategy. CONCLUSIONS: Tafalgin use was associated with fewer respiratory complications and lower total direct costs than morphine and trimeperidine, with differences most pronounced in high-risk patients. Results should be interpreted in view of the retrospective and aggregated nature of the source data.

INTRODUCTION: Postoperative complications under diagnosis-related group (DRG) reimbursement increase hospital costs and prolong ward and intensive care unit (ICU) stay, which additional payments may not fully offset. OBJECTIVES: To quantify the impact of complications on hospital and ICU length of stay (LOS, ICU LOS), estimate related hospital costs, and model the economic effect of a risk prediction model. MATERIALS AND METHODS: Retrospective multicentre cohort study of the STOPRISK registry (n = 11,081 episodes). Complications were defined by 19 binary indicators (18 tabulated). Outcomes: LOS, ICU LOS and in-hospital mortality as median (Q1; Q3). Economic modelling was an exploratory scenario cost–consequence analysis with return on investment (ROI) from the hospital perspective; resource cost equivalents 6,040 RUB/ward day and 66,225 RUB/ICU day. RESULTS: Complications occurred in 508/11,081 (4.58 %), death in 70 (0.63 %) and ICU stay in 3,428 (30.9 %); 946 events were recorded (1.86 per affected patient). All 18 complications had higher median LOS and ICU LOS; the largest increases were wound dehiscence (+23 days), sepsis (+19) and pulmonary embolism (+18). Additional resource costs per event were 109,000–777,000 RUB; the total annual event-related burden was 328.2 million RUB. In the base-case A + B scenario (δ = 20 %) annual savings were 54.1 million RUB, ROI 10.8× and payback 1.1 months; across the δ = 10–30 % range, 29.8–73.0 million RUB, ROI 6.0–24.3× and 0.5–2.0 months. Complication rates were 3.14 % (< 65 years) and 8.06 % (≥ 65 years); failure-to-rescue ≈13.8 %. CONCLUSIONS: Postoperative complications generate substantial event-related resource burden through longer LOS and ICU LOS, with patients ≥ 65 years contributing a disproportionately high share of costs. Under the specified assumptions, risk stratification and clinical pathways may be economically justified from the hospital perspective; the benefit depends on actual use of the tool, case-mix, tariffs and ICU occupancy. The findings are exploratory and require prospective validation.

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.

Perioperative respiratory risk represents a major interdisciplinary challenge, as postoperative pulmonary complications (PPCs) are associated with increased mortality, prolonged hospital stay, and higher healthcare costs. Heterogeneity in the definitions of complications complicates the interpretation of the literature; initiatives such as Standardised Endpoints in Perioperative Medicine (StEP) and the European Society of Anaesthesiology working group on European definitions have proposed harmonised definitions and severity grading systems, thereby improving comparability across studies and clinical applicability of results. This narrative review synthesises data on the epidemiology of PPCs, patient- and procedure-related risk factors, methods of risk stratification and prevention, and presents contemporary prognostic models ranging from clinical risk scores to machine learning algorithms, with particular emphasis on validation requirements and reporting standards. Practical implications include the need to apply StEP definitions with severity grading alongside discrete registry-based outcomes according to the NSQIP (National Surgical Quality Improvement Program) classification, to perform external validation of predictive models, and to implement bundled preventive strategies throughout all phases of perioperative care in high-risk populations. Integration of standardised outcomes, validated risk models, and multistage preventive interventions, including the use of machine learning algorithms, provides a foundation for reducing the incidence of PPCs and improving long-term outcomes.

Perioperative malnutrition and protein-energy wasting remain key modifiable risk factors for complications, prolonged hospital stay, and increased costs in surgical patients. The updated 2026 FAR guidelines on perioperative nutritional support systematize evidence from 2021–2025 and present a comprehensive multidisciplinary approach to diagnosing and correcting malnutrition at all stages of surgical care. In contrast to the 2021 version, the new edition introduces a two-step model for nutritional assessment: expanded risk screening (NRS-2002, MUST, MST, and others) complemented by formal malnutrition diagnosis according to GLIM criteria, incorporating phenotypic and etiologic features as well as instrumental assessment of sarcopenia and clinical frailty. This enables a shift from simple risk stratification to outcome prediction and individualized selection of nutritional support strategies. The guidelines emphasize the pivotal role of the preoperative phase, including prehabilitation: correction of nutritional deficits, use of oral nutritional supplements and, when indicated, immunonutrition combined with exercise training and educational interventions. The postoperative section maintains a focus on early enteral nutrition and refines criteria for tolerance, options for direct oral feeding after selected procedures, and indications for supplemental and peripheral parenteral nutrition. For the first time, a distinct post-discharge phase is outlined, with recommendations on continued oral nutritional supplements in high-risk patients. Dedicated sections address the use of specialized formulas (lipid emulsions, omega-3 fatty acids, glutamine, fiber-enriched enteral feeds) and the prevention of refeeding syndrome, including identification of high-risk groups and initial treatment algorithms. The guidelines are fully integrated with ERAS principles, positioning nutritional support as an essential component of the patient pathway rather than an isolated module. The final section provides quality indicators and metrics for the delivery of nutritional and metabolic care, forming a foundation for the development of local protocols, clinical audit, and continuous improvement of practice In Russian surgical wards and intensive care units.

INTRODUCTION: Older age is recognized as an independent risk factor for adverse perioperative outcomes; however, quantitative data on the impact of early old age (65–75 years) on 30-day postoperative complications in a multicenter Russian cohort are lacking. OBJECTIVE: To determine whether older age (65–75 years) is associated with the incidence, pattern, severity, and timing of 30-day postoperative complications and mortality compared with patients aged 18–64 years undergoing elective abdominal surgery. MATERIALS AND METHODS: A multicenter prospective cohort study was conducted (secondary analysis of the STOPRISK database, NCT03945968; STROBE). From 2019 to 2024, 12,000 patients from 38 centers across the Russian Federation were enrolled. After exclusions, the analytical sample comprised 10,915 patients: 18–64 years (n = 8,119) and 65–75 years (n = 2,796). The primary outcome was any 30-day postoperative complication (ESA/ESICM). Secondary outcomes were 30-day mortality, complication severity (Clavien-Dindo), and timing of occurrence. RESULTS: The 30-day complication rate in patients aged 65–75 years was more than twice that in the 18–64-year group (7.15 vs 3.09 %), and 30-day mortality was more than threefold higher (1.18 vs 0.33 %). The greatest relative risk increase was observed for postoperative delirium (RR 7.55), acute myocardial infarction (RR 5.08), arrhythmias (RR 4.26), and acute kidney injury (RR 3.87). The distribution of complication severity according to Clavien-Dindo did not differ between groups, most complications in both groups occurred within the first 5 days. After multivariable adjustment, older age remained an independent predictor of any complications, severe complications, and mortality. CONCLUSIONS: Older age (65–75 years) is an independent predictor of postoperative complications and mortality following elective abdominal surgery, increasing the risk of complications 1.7-fold and the risk of death 2.2-fold after confounder adjustment. The identified profile of high-risk specific complications supports the need for targeted perioperative management protocols in elderly patients.

Highlights This review introduces for the first time an integrative conceptual model of high perioperative cardiac risk, combining three key components: surgical risk, patient vulnerability, and dynamic monitoring, enabling a systematic approach to patient stratification prior to noncardiac surgery. It demonstrates a critical gap between the high predictive accuracy of modern machine learning models (AUROC > 0.90) and the lack of their clinical validation in real-world practice, particularly in the Russian population, highlighting the need for a national risk calculator. For the first time in Russian literature, the role of MINS (myocardial injury after noncardiac surgery) as a major driver of postoperative mortality (contributing 3.9% to overall mortality) is analyzed in detail, justifying the shift from reactive to preventive perioperative cardiac risk management based on routine monitoring of high-sensitivity troponins and natriuretic peptides. Abstract This review focuses on contemporary approaches to the assessment and management of perioperative cardiac risk in patients undergoing non-cardiac surgery. The topic's relevance stems from the high frequency of major adverse cardiovascular events (MACE), a leading cause of perioperative mortality. The work analyzes the paradigm shift from the question “is surgery feasible?” to the strategy “how to improve outcomes?” which includes pre-operative optimization (prehabilitation), active monitoring, and a multidisciplinary approach. Based on a literature search, the epidemiology and key risk factors are reviewed, with detailed classifications and definitions of complications (MACE, myocardial injury after noncardiac surgery (MINS), intraoperative critical incidents). Particular attention is paid to the role of biomarkers (NT-proBNP/BNP for prediction, high-sensitivity troponin for diagnosing MINS) and hemodynamic control in risk stratification and early detection of myocardial injury. A comparative analysis of prognostic tools is conducted: from traditional clinical scales (Lee index, NSQIP) to modern machine learning models demonstrating high accuracy. Problems with validation, clinical interpretability, and the integration of these tools into routine practice are noted. Contemporary recommendations for risk minimization, based on staged personalized assessment, patient optimization, and active postoperative monitoring, are summarized. The conclusion emphasizes the need to develop integrative, transparent, and clinically applicable algorithms that combine data from scales, biomarkers, and dynamic monitoring to transition from reactive to preventive management of perioperative cardiac risk.

Introduction. Anesthetic safety in children remains one of the key challenges of modern clinical practice. Despite advances in monitoring and procedural standardization, the risk of intraoperative critical incidents (CI) in children remains significantly higher than in adults. Simple non-invasive tools for preoperative risk assessment based on key physiological parameters require validation. Objective. To analyze breath-holding test (BHT) after deep inspiration as a predictor of intraoperative CI in children undergoing mechanical ventilation (MV). Material and methods. A prospective study enrolled 135 children aged 5—10 years scheduled for elective abdominal surgery under general anesthesia with MV. Preoperative triple BHT was administered, and mean value used for analysis. Recording intraoperative CIs was the primary objective of intraoperative monitoring. Predictive value of BHT for CIs was assessed using ROC curves. Results. Intraoperative CIs were identified in 20.7% of patients. Shorter BHT after deep inspiration was significantly associated with higher incidence of intraoperative CI. AUC was 0.847 for overall critical incidents, 0.903 for hemodynamic, and 0.853 for respiratory events (p<0.001). Optimal cutoff values for BHT were ≤28 seconds for overall and hemodynamic incidents and ≤27 seconds for respiratory incidents. Conclusion. BHT after deep inspiration is a simple, noninvasive, and informative method for preoperative risk stratification and demonstrates high predictive value for intraoperative CI in mechanically ventilated pediatric patients.

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.

The development of protein-energy malnutrition (PEM) syndrome is a pressing issue in surgical settings. The risk of malnutrition developing is determined in the majority of patients admitted to surgical wards. 30–70% of patients demonstrate signs of PEM upon admission, and during treatment, this syndrome can progress, reaching 50–60%. The severity of PEM is closely connected with clinical outcome indicators: length of stay in the intensive care unit and hospital increases, infectious complications occur more frequently, and treatment costs increase significantly. These guidelines, based on the principles of evidence-based medicine, describe methods for diagnosing and correction of PEM at all stages of surgical treatment. Also practical algorithms and criteria for evaluation the quality of nutritional and metabolic support during the perioperative period are included in this paper.