RESUMEN
Objective: This retrospective cohort study aimed to investigate the composition and diversity of lung microbiota in patients with severe pneumonia and explore its association with short-term prognosis. Methods: A total of 301 patients diagnosed with severe pneumonia underwent bronchoalveolar lavage fluid metagenomic next-generation sequencing (mNGS) testing from February 2022 to January 2024. After applying exclusion criteria, 236 patients were included in the study. Baseline demographic and clinical characteristics were compared between survival and non-survival groups. Microbial composition and diversity were analyzed using alpha and beta diversity metrics. Additionally, LEfSe analysis and machine learning methods were employed to identify key pathogenic microorganism associated with short-term mortality. Microbial interaction modes were assessed through network co-occurrence analysis. Results: The overall 28-day mortality rate was 37.7% in severe pneumonia. Non-survival patients had a higher prevalence of hypertension and exhibited higher APACHE II and SOFA scores, higher procalcitonin (PCT), and shorter hospitalization duration. Microbial α and ß diversity analysis showed no significant differences between the two groups. However, distinct species diversity patterns were observed, with the non-survival group showing a higher abundance of Acinetobacter baumannii, Klebsiella pneumoniae, and Enterococcus faecium, while the survival group had a higher prevalence of Corynebacterium striatum and Enterobacter. LEfSe analysis identified 29 distinct terms, with 10 potential markers in the non-survival group, including Pseudomonas sp. and Enterococcus durans. Machine learning models selected 16 key pathogenic bacteria, such as Klebsiella pneumoniae, significantly contributing to predicting short-term mortality. Network co-occurrence analysis revealed greater complexity in the non-survival group compared to the survival group, with differences in central genera. Conclusion: Our study highlights the potential significance of lung microbiota composition in predicting short-term prognosis in severe pneumonia patients. Differences in microbial diversity and composition, along with distinct microbial interaction modes, may contribute to variations in short-term outcomes. Further research is warranted to elucidate the clinical implications and underlying mechanisms of these findings.
Asunto(s)
Líquido del Lavado Bronquioalveolar , Microbiota , Humanos , Masculino , Femenino , Pronóstico , Estudios Retrospectivos , Persona de Mediana Edad , Anciano , Líquido del Lavado Bronquioalveolar/microbiología , Neumonía/microbiología , Neumonía/mortalidad , Bacterias/clasificación , Bacterias/genética , Bacterias/aislamiento & purificación , Secuenciación de Nucleótidos de Alto Rendimiento , Pulmón/microbiología , Pulmón/patología , Metagenómica , Aprendizaje AutomáticoRESUMEN
BACKGROUND: With the implementation of the 11th edition of the International Classification of Diseases (ICD-11) and the publication of the metabolic dysfunction-associated fatty liver disease (MAFLD) nomenclature in 2020, it is important to establish consensus for the coding of MAFLD in ICD-11. This will inform subsequent revisions of ICD-11. METHODS: Using the Qualtrics XM and WJX platforms, questionnaires were sent online to MAFLD-ICD-11 coding collaborators, authors of papers, and relevant association members. RESULTS: A total of 890 international experts in various fields from 61 countries responded to the survey. We also achieved full coverage of provincial-level administrative regions in China. 77.1% of respondents agreed that MAFLD should be represented in ICD-11 by updating NAFLD, with no significant regional differences (77.3% in Asia and 76.6% in non-Asia, p = 0.819). Over 80% of respondents agreed or somewhat agreed with the need to assign specific codes for progressive stages of MAFLD (i.e. steatohepatitis) (92.2%), MAFLD combined with comorbidities (84.1%), or MAFLD subtypes (i.e., lean, overweight/obese, and diabetic) (86.1%). CONCLUSIONS: This global survey by a collaborative panel of clinical, coding, health management and policy experts, indicates agreement that MAFLD should be coded in ICD-11. The data serves as a foundation for corresponding adjustments in the ICD-11 revision.
Asunto(s)
Clasificación Internacional de Enfermedades , Enfermedad del Hígado Graso no Alcohólico , Humanos , Enfermedad del Hígado Graso no Alcohólico/epidemiología , Enfermedad del Hígado Graso no Alcohólico/clasificación , Encuestas y Cuestionarios , Salud GlobalRESUMEN
Chronic liver disease (CLD) is a leading health problem impacting the quality of life globally. China shares a major global burden of CLD-including alcoholic liver disease, nonalcoholic fatty liver disease/metabolic dysfunction-associated fatty liver disease, and drug-induced liver injury, except for chronic viral hepatitis. Several exogenous toxins or endogenous metabolic insults trigger hepatic pathology toward steatosis, inflammation, and fibrosis, which, if left untreated, may culminate in liver cirrhosis. Oxidative stress is a common pathomechanism underlying all phenotypes of toxic liver injury; thus, these may be brought under a unified entity, viz. toxic liver disease (TLD). Therefore, a common strategy to treat TLD is to use antioxidants as hepatoprotective agents. The cornerstone for treating fatty liver disease is lifestyle modification, diet, exercise, and behavioral therapy, along with the limited use of pharmacological agents. Available preclinical and clinical evidence indicates that silymarin is a hepatoprotective agent with established antioxidant, anti-inflammatory, antifibrotic effects. An international expert panel of clinicians was convened to discuss combining alcoholic liver disease, nonalcoholic fatty liver disease/metabolic dysfunction-associated fatty liver disease, drug-induced liver injury, and liver cirrhosis under the single definition of TLD, based on the shared pathologic mechanism of oxidative stress. The panel highlighted the significance of silymarin as an antioxidant treatment for TLD.