Choice of clinical criteria for assessing the risk of complications in patients with inflammatory pulmonary diseases (a literature review)

Abstract

The development of clinical criteria for diagnosis and prediction of complication risks is one of the priority areas in modern thoracic surgery. Despite the introduction of new medical technologies, the incidence of complications in purulent-destructive lung diseases remains high, which is due to changes in the microbial landscape, increasing antibiotic resistance, and the emergence of new infectious threats, including COVID-19. The aim of this study was to conduct an analytical review of foreign literature on the selection of clinical criteria for diagnosis and prediction of complication risks in patients with inflammatory lung diseases. A total of 50 English-language sources indexed in the PubMed database from 2015 to 2025 were reviewed. Methods of analysis and synthesis of scientific information, systematization of clinical and laboratory data, and identification of the most informative prognostic criteria were applied. The review presents current approaches to the selection of clinical, etiopathogenetic, instrumental, and laboratory criteria for assessing complication risks. Three main groups of prognostic factors were identified: microbiological, anatomical, and comorbid. Special attention is paid to complex clinical cases of descending necrotizing mediastinitis and empyema, as well as modern methods of pathogen identification, including metagenomic sequencing. The selection of clinical criteria for assessing complication risks requires a multidisciplinary approach and individualization based on etiology, anatomical features, and concomitant pathology. Systematization of existing criteria allows optimization of diagnostic algorithms, improvement of treatment outcomes, and reduction of postoperative complication rates. Promising directions include the development of predictive models based on artificial intelligence and the implementation of molecular genetic methods for pathogen identification.