Internal and Emergency Medicine最新文献

Inborn errors of immunity (IEI) entail a diverse group of disorders resulting from hereditary or de novo mutations in single genes, leading to immune dysregulation. This study explores the clinical utility of next-generation sequencing (NGS) techniques in diagnosing monogenic immune defects. Eight patients attending the immunodeficiency clinic and with unclassified antibody deficiency were included in the analysis. Clinical records, immune characteristics, and family histories were reviewed, and a target gene panel (TGP) sequencing was performed to identify pathogenic variants. TGPs identified seven variants in TNFRSF13B (TACI), CARMIL2, STAT1, STAT3, and ORAI1 genes. These findings provided definitive diagnoses and proper prognostic assessment. Patients exhibited a wide range of clinical manifestations, including recurrent infections, autoimmune cytopenias, and organ-specific complications. The genetic diversity observed highlights the importance of genetic testing in diagnosing IEIs and tailoring treatments. This study underscores the role of TGPs in diagnosing IEIs, revealing significant genetic heterogeneity and phenotypic variability. They offer a precise tool for identifying underlying genetic defects, facilitating personalized medicine approaches, and eventually improving patient outcomes. The findings emphasize the need for comprehensive genetic testing to uncover novel pathogenic variants, enhancing our understanding of immune system dysfunction. NGS is a critical tool for the management of IEI, enabling precise diagnosis and personalized treatment strategies. Despite resource limitations, the progressive affordability is likely to expand its clinical utility, ultimately improving patient care and advancing the field of immunology. In the meantime, accurate phenotypic assessment is essential for resource optimization and case prioritization.

Multi-trauma presents significant challenges due to the complexity of injuries and high mortality rates. Early identification and intervention are crucial for improving outcomes in these critically injured patients. This retrospective study analyzed clinical data from multi-trauma patients admitted to the emergency department of Huiyang Sanhe Hospital between January 10, 2020, and September 30, 2022. Univariate and multivariate logistic regression analyses were conducted to identify independent predictors of hospital mortality. A prediction model was developed based on these prognostic markers, visualized using a nomogram, and its discriminative ability and clinical benefit were evaluated. A total of 124 multi-trauma patients were included in the study, with a hospital mortality rate of 26.7%. Univariate and multivariate logistic regression analyses identified trauma-induced coagulopathy (TIC) (OR 4.238, 95% CI 1.46-12.28), blood urea nitrogen (BUN) (OR 1.397, 95% CI 1.09-1.78), and Glasgow Coma Scale (GCS) score (OR 0.720, 95% CI 0.61-0.85) as independent factors of hospital mortality. Therefore, a nomogram incorporating TIC, BUN, and GCS score was constructed and demonstrated excellent predictive performance and clinical impact (AUC 0.898, 95% CI 0.834-0.962). The nomogram developed in this study provided a practical tool for early prediction of hospital mortality in multi-trauma patients. By focusing on TIC, BUN, and GCS score, this model may facilitate rapid bedside assessment and timely intervention. However, further multicenter, prospective studies are required to validate its performance and applicability.