Background Lower extremity arterial disease (LEAD) remains a major cause of amputation, even after successful endovascular revascularization therapy (EVT). The prognostic associations of the pan-immune inflammatory value (PIV) and fibrinogen-to-albumin ratio (FAR) in LEAD remain unclear. This study investigated the associations of PIV and FAR with amputation risk and evaluated their incremental prognostic value beyond established clinical variables. Methods In this multicenter retrospective cohort study, 1,082 patients with LEAD who underwent EVT at four tertiary hospitals in Southwest China between January 2018 and July 2023 were analyzed. Restricted cubic spline (RCS) analyses and Cox proportional hazards regression models were used to evaluate the associations of PIV and FAR with amputation risk. Exploratory cut-off values were derived using receiver operating characteristic (ROC) curve analysis. The incremental prognostic value of adding PIV and FAR to clinical variables was assessed using time-dependent ROC analysis. Results During a median follow-up of 31 months, 198 (18.3%) patients experienced amputation. RCS revealed significant nonlinear associations of PIV and FAR with amputation risk ( p for nonlinearity < 0.001). After multivariable adjustment, higher levels of both biomarkers remained independently associated with increased amputation risk (Z-PIV: HR = 1.379; Z-FAR: HR = 1.176; both p < 0.001). The addition of PIV and FAR to the clinical model enhanced time-dependent discrimination; the AUC(t) increased from 0.771 to 0.819 at 1 year, 0.766 to 0.806 at 2 years, and 0.762 to 0.807 at 3 years (all adjusted p < 0.001). Fine-Gray competing-risk analyses yielded consistent results after accounting for death as a competing event. Conclusion PIV and FAR were independently associated with amputation risk in patients with LEAD who underwent EVT. The addition of these biomarkers to established clinical variables provided incremental prognostic value and may offer additional prognostic information for risk stratification.
Objectives To investigate the prognostic value of the systemic immune-inflammation index (SII), lactate-to-albumin ratio (LAR), and D-dimer for in-hospital adverse outcomes in patients with acute pulmonary embolism (APE). Methods This single-center retrospective cohort study screened 248 patients with computed tomography pulmonary angiography-confirmed APE between June 2022 and February 2026; 151 patients were included after 97 exclusions. Predictors were defined using the first measurements obtained within 24 hours after admission and before anticoagulation, thrombolysis, vasopressor therapy, or any related adverse event. The primary outcome was an in-hospital composite of intensive care unit transfer, shock or vasopressor use, cardiopulmonary resuscitation, catheter-based therapy or thrombolysis, and fatal outcome (in-hospital death or withdrawal of life-sustaining treatment after irreversible deterioration). Multiple imputation and logistic regression were used to construct and compare an sPESI model, a biomarker model, and a combined model. Performance was assessed using receiver operating characteristic curves, calibration analysis, bootstrap internal validation, and decision curve analysis. Results Among 151 patients, 37 (24.5%) experienced the composite outcome and 114 did not. SII, LAR, and D-dimer remained associated with the outcome after adjustment for sPESI. Model 2 had an AUC of 0.891, compared with 0.637 for model 1 and 0.661 for ESC risk classification. Adding sPESI or ESC classification to model 2 increased the AUC to 0.912 and 0.900, respectively, without a significant further improvement in discrimination (P=.221 and P=.409). The bootstrap-corrected AUC for model 2 was 0.885, the Brier score was 0.091, and internal decision-curve analysis showed potential net benefit. Conclusions Admission SII, LAR, and D-dimer were associated with in-hospital adverse outcomes and remained associated after adjustment for sPESI. The exploratory three-biomarker model may complement sPESI and ESC risk classification, but multicenter external validation is required before clinical application.
Background Early detection of sepsis-induced coagulopathy (SIC) is of great clinical significance, as its closely correlates with disease progression in patients with sepsis. In the present study, we focused on mining the major coagulation factors that participate in the development and progression of SIC, and exploring the potential regulatory networks of these core factors. Method Meta-analysis was performed to explore the association between SIC and mortality. eQTLs significantly associate with sepsis-related 28-day mortality and pQTLs were analyzed, to mine the significant sites or genes. Mendelian randomization (MR) was then applied to evaluate the role of coagulation factors in SIC and to explore their genetic regulation via DNA sequence analysis. Moreover, QGRS Mapper combined with ThT fluorescence assays were used to detect G-quadruplexes (G4s) structures within coagulation factor genes. Results Sepsis patients with SIC exhibited higher sequential organ failure assessment (SOFA) scores and increased 28-day mortality compared to those without SIC. MR and clinical analyses demonstrated that PAI-1 serves as a major contributor to higher sepsis incidence and 28-day mortality. Notably, the PAI-1 rs1799762 genetic polymorphism alters this biological effect. Mechanistically, G4-forming capacity negatively correlates with PAI-1 expression. In particular, the 5G/5G genotype was associated with a higher G4-forming propensity in the PAI-1 gene, which in turn weakened gene transcription and lowered PAI-1 expression relative to other genotypes. Conclusion G4s formation in the PAI-1 gene modulates circulating PAI-1 levels and may serve as a novel prognostic marker and therapeutic target for sepsis severity assessment, particularly in patients with SIC.
Background Continuous ultrasound was done on newly admitted hip fracture patients to evaluate post-fracture anticoagulation efficacy, perioperative lower limb deep vein thrombosis timing, and thrombosis distribution/prognosis in those on different thromboprophylaxis. Methods This randomized clinical trial enrolled patients with fresh hip fractures (age >18 years; injury-to-admission time ≤24 h). Eligible patients without thrombosis on admission ultrasound were randomly assigned in a 2:1 ratio to the anticoagulation group or the non-anticoagulation group. The anticoagulation group received nadroparin calcium (Fraxiparine, 3800 IU/0.4 mL subcutaneously once daily) plus mechanical thromboprophylaxis with an intermittent plantar pressure pump. The non-anticoagulation group received mechanical thromboprophylaxis alone. Bilateral lower extremity venous ultrasound was performed daily throughout hospitalization. Venous blood was collected at four time points (admission, 1 day pre-op, 1 day post-op, 3 days post-op) for routine blood tests and D-dimer measurement. Thrombosis type, occurrence time, location, and laterality were recorded. This intensive ultrasound surveillance protocol was used solely for research purposes and is not the standard. Results This study included 330 patients (193 females, 137 males), mean age 67.39 ± 16.69 years (18-94 years), injury-to-admission time ≤24 h, mean preoperative waiting time 3.48 ± 1.68 days, mean hospital stay 7.19 ± 2.64 days. There were 178 (53.9%) femoral neck fractures and 152 (46.1%) intertrochanteric and subtrochanteric fractures. Six patients with post-admission proximal thrombosis had pre-procedure inferior vena cava filter implantation; no pulmonary embolism occurred during hospitalization. Anticoagulant group (201 patients): 42 (20.89%) pre-op thrombosis, 81 (40.29%) post-op thrombosis. Non-anticoagulant group (129 patients): 26 (20.15%) pre-op thrombosis, 55 (42.64%) post-op thrombosis. Conclusions Continuous ultrasound surveillance reveals that days 2–3 post-injury and the first postoperative day represent the periods of highest thrombotic risk in patients with acute hip fractures. However, because most detected DVTs were distal and asymptomatic, and no pulmonary embolism or death occurred in either group, the clinical value of routine, protocol-driven ultrasound screening has yet to be established. Selective screening guided by symptoms or high-risk features may offer a more clinically appropriate strategy. Future studies should determine whether early DVT detection in this population translates into improved patient-important outcomes.
BackgroundSarcopenia is observationally linked to venous thromboembolism, but the causal architecture and underlying biological pathways remain largely unclear. This study investigated the causal effects of sarcopenia-related traits on lower extremity deep vein thrombosis (DVT) and quantified potential mediating mechanisms.MethodsWe performed two-sample bidirectional Mendelian randomization (MR) and two-step mediation MR using large-scale GWAS data from UK Biobank, EMBL-EBI, and FinnGen. Exposures included appendicular lean mass (ALM), leg fat-free mass (LFM), hand grip strength, and walking pace. Eighteen candidate mediators were screened for indirect pathways.ResultsGenetically predicted higher ALM was significantly associated with increased DVT risk (FinnGen: OR = 1.288, 95% CI: 1.215-1.365, P < 0.001). Similar positive associations were observed for LFM (OR = 1.920-1.954, P < 0.001). By contrast, muscle functional traits - grip strength and walking pace - demonstrated no consistent causal effects. Reverse MR confirmed a unidirectional relationship. Body mass index (BMI) emerged as a pivotal mediator, accounting for 7.58% - 10.50% of the ALM-DVT effect and 52.74% - 62.73% of the LFM-DVT effect. Notably, the independent effect of ALM was largely attenuated after adjusting for metabolic confounders in multivariable MR.ConclusionGenetic predisposition to high muscle mass, rather than functional strength, increases DVT risk. This relationship appears to be significantly driven by metabolic adiposity, suggesting that the "muscle-vascular-coagulation" interaction is partly explained by body-size-related metabolic burden. Risk stratification should integrate muscle mass evaluation with comprehensive metabolic health assessments.
