Our study aimed to systematically analyse the risk factors of coronavirus disease 2019 (COVID-19) patients with severe disease. An electronic search in eight databases to identify studies describing severe or critically ill COVID-19 patients from 1 January 2020 to 3 April 2020. In the end, we meta-analysed 40 studies involving 5872 COVID-19 patients. The average age was higher in severe COVID-19 patients (weighted mean difference; WMD = 10.69, 95%CI 7.83–13.54). Patients with severe disease showed significantly lower platelet count (WMD = −18.63, 95%CI −30.86 to −6.40) and lymphocyte count (WMD = −0.35, 95%CI −0.41 to −0.30) but higher C-reactive protein (CRP; WMD = 42.7, 95%CI 31.12–54.28), lactate dehydrogenase (LDH; WMD = 137.4, 95%CI 105.5–169.3), white blood cell count（WBC), procalcitonin（PCT）, D-dimer, alanine aminotransferase (ALT), aspartate aminotransferase (AST) and creatinine（Cr）. Similarly, patients who died showed significantly higher WBC, D-dimer, ALT, AST and Cr but similar platelet count and LDH as patients who survived. These results indicate that older age, low platelet count, lymphopenia, elevated levels of LDH, ALT, AST, PCT, Cr and D-dimer are associated with severity of COVID-19 and thus could be used as early identification or even prediction of disease progression.

Background: COVID-19-induced acute respiratory distress syndrome (ARDS) can result in tissue damage and multiple organ dysfunction, especially in kidney transplant recipients (KTRs) receiving immunosuppressive drugs. Presently, single-cell research on COVID-19-induced ARDS is considerably advanced, yet knowledge about ARDS in KTRs is still constrained. Methods: Single-cell RNA sequencing (scRNA-seq) analysis was performed to construct a comprehensive single-cell immune landscape of the peripheral blood mononuclear cells (PBMCs) of eight patients with COVID-19-induced ARDS, five KTRs with COVID-19-induced ARDS, and five healthy individuals. Subsequently, we conducted a comprehensive bioinformatics analysis, including cell clustering, enrichment analysis, trajectory analysis, gene regulatory network analysis, and cell–cell interaction analysis, to investigate the heterogeneity of the immune microenvironment in KTRs with ARDS. Result: Our study revealed that KTRs exhibit significant heterogeneity with COVID-19-induced ARDS compared with those of other individuals, with significant reductions in T cells, as well as an abnormal proliferation of B cells and monocytes. In the context of dual influences from immunosuppression and viral infection, KTRs exhibited more specific plasma cells, along with significant enrichment of dysfunctional GZMB and XAF1 double-positive effector T cells and IFI27-positive monocytes. Additionally, robust communication existed among T cells and monocytes in cytokine signaling. These effects impede the process of immune reconstitution in KTR patients. Conclusion: Our findings suggest that KTRs with COVID-19-induced ARDS show elevated antibody levels, impaired T cell differentiation, and dysregulation of innate immunity. In summary, this study provides a theoretical foundation for a comprehensive understanding of COVID-19-induced ARDS in KTRs.

Background Since the emergence of COVID-19 at the end of 2019, the disease has led to widespread acute respiratory distress syndrome (ARDS), particularly among kidney transplant recipients (KTRs), who are at increased risk due to long-term immunosuppressive therapy. This study aims to explore the differences in immune responses between kidney transplant recipients and non-kidney transplant recipients in COVID-19-induced ARDS to identify potential therapeutic targets for improving outcomes. Single-cell RNA sequencing was performed on 108,320 cells derived from peripheral blood samples to construct a global single-cell map of COVID-19 induced ARDS in kidney transplant recipients(ARDS^KT), COVID-19 induced ARDS in non transplant recipients(ARDS^NKT), and healthy controls. Subsequently, using cellular clustering analysis, we obtained single-cell maps of different cell types. We employed enrichment analysis to determine the pathways involved in different subpopulations and focused on the role of key immune cells such as monocytes, megakaryocytes, B cells, and CD8⁺ T cells in the pathogenesis of ARDS. Significant immune differences were observed between ARDS^KT and ARDS^NKT. In ARDS^KT, the S100A9⁺ MK subpopulation, which activates the NF-κB signaling pathway, was elevated, promoting inflammation. In contrast, the S100A12⁺ monocyte subpopulation that activates the chemokine signaling pathway was more abundant in ARDS^NKT, reflecting a stronger inflammatory response, while its abundance was reduced in ARDS^KT due to immunosuppression. The CXCR4⁺ B subpopulation, crucial for adaptive immunity, was significantly reduced in ARDS^KT. Additionally, the XAF1⁺ Teff subpopulation, associated with apoptosis, was more abundant in ARDS^KT, potentially impairing immune recovery. This study highlights the immune differences between ARDS^KT and ARDS^NKT, revealing the impact of immunosuppression on immune dysregulation. These findings suggest that targeting specific immune pathways can improve therapeutic strategies for ARDS^KT.

Dengue fever poses a significant diagnostic and therapeutic challenge in immunocompromised hosts, particularly in solid organ transplant recipients. We rep

Scrub typhus, a re-emerging zoonosis caused by Orientia tsutsugamushi, can present with severe, life-threatening complications, including multi-organ dysfu

Background: The triglyceride-glucose (TyG) index is a recognized surrogate marker of insulin resistance. However, validated reference intervals (RIs) for the TyG index in large, general healthy populations are currently lacking, limiting its standardized application in clinical practice. Methods: This retrospective study established and validated TyG index RIs using data from adults (≥18 years) undergoing routine health examinations. The derivation cohort included individuals without known diabetes, dyslipidemia, or obesity. The TyG index was calculated as ln[fasting triglyceride (mg/dL) × fasting blood glucose (mg/dL)/2]. After outlier exclusion, we analyzed the age-TyG relationship using restricted cubic splines and threshold analysis to determine optimal age stratification. Gender- and age-specific RIs were defined as the 2.5th–97.5th percentiles. An independent cohort of 127,143 healthy individuals was used for validation, with success defined as <10% of values falling outside the proposed RIs. Results: A total of 201,623 individuals were initially screened for the derivation cohort. Analysis revealed a significant nonlinear relationship between TyG and age, with an inflection point at 64.21 years, justifying stratification into 18–64 and ≥64-year groups. The overall RI was 7.47–8.90. Stratified RIs were: 7.47–8.91 for males aged 18–64, 7.46–8.90 for females aged 18–64, 7.44–8.90 for males aged ≥64, and 7.50–8.90 for females aged ≥64. In the independent validation cohort, only 4.76% to 5.37% of values fell outside the corresponding RIs, confirming their robustness. Conclusion: This study establishes and validates age- and gender-stratified reference intervals for the TyG index in a large Chinese healthy population. These intervals, benchmarked against a critical age threshold of 64 years, provide a reliable standard for clinical interpretation and enhance the utility of the TyG index in metabolic risk assessment.