It has been demonstrated that fibrin clots generated from plasma samples obtained from patients with prior thromboembolic events are denser and less susceptible to lysis. Such a prothrombotic fibrin clot phenotype has been suggested as a new risk factor for venous thromboembolism, but its prognostic value is unclear. To assess whether abnormal clot properties can predict recurrent deep-vein thrombosis (DVT), we studied 320 consecutive patients aged 18 to 70 years following the first-ever DVT. Plasma clot properties were evaluated after 3 months of anticoagulant treatment since the index event. A mean duration of anticoagulation was 10 months (range, 4-20). Recurrent DVT was observed in 77 patients (25%; 6.6%/year) during a median follow-up of 44 months. Recurrences of DVT were associated with faster formation (-9% lag phase) of denser fibrin networks (-12% fibrin clot permeability [K_s]) and 4% higher maximum absorbance of plasma clots (ΔAbs), that displayed impaired fibrinolytic degradation (+25% prolonged clot lysis time [CLT]) and 5% slower rate of increase in D-dimer levels during clot degradation (D-D_rate, all p<0.05). Proximal DVT alone, higher C-reactive protein, D-dimer, peak thrombin, lower K_s, shorter lag phase, decreased D-D_rate and prolonged CLT were independent predictors of recurrences (all p96 min) were at the highest risk of recurrent DVT (OR, 15.8; 95% CI, 7.5-33.5). Kaplan-Meier curves showed that reduced K_s and prolonged CLT predicted recurrent DVT. We demonstrated that unfavourably altered clot properties may predict recurrent DVT after anticoagulation withdrawal. Key points Formation of more compact plasma fibrin clots associated with impaired susceptibility to lysis predisposes to recurrent DVT. Determination of plasma clot phenotype prior to anticoagulation withdrawal might help identify patients at elevated risk of DVT recurrence.

Recently, several studies explored associations between type 1 diabetes (T1DM) and microbiota. The aim of our study was to assess the colonic microbiota structure according to the metabolic control in T1DM patients treated with insulin pumps. We studied 89 T1DM patients (50.6% women) at the median age of 25 (IQR, 22–29) years. Pielou’s evenness (p = 0.02), and Shannon’s (p = 0.04) and Simpson’s diversity indexes (p = 0.01), were higher in patients with glycosylated hemoglobin (HbA1c) ≥ 53 mmol/mol (7%). There were no differences in beta diversity between groups. A linear discriminant analysis effect size (LEfSe) algorithm showed that one family (Ruminococcaceae) was enriched in patients with HbA1c < 53 mmol/mol, whereas one family (Streptococcaceae) and four species (Ruminococcus torques, unclassified species of Lactococcus, Eubacteroim dolichum, and Coprobacillus cateniformis) were enriched in patients with HbA1c ≥ 53 mmol/mol. We found that at class level, the following pathways according to Kyoto Encyclopedia of Genes and Genomes were enriched in patients with HbA1c < 53 mmol/mol: bacterial motility proteins, secretion system, bacterial secretion system, ribosome biogenesis, translation proteins, and lipid biosynthesis, whereas in patients with HbA1c ≥ 53 mmol/mol, the galactose metabolism, oxidative phosphorylation, phosphotransferase system, fructose, and mannose metabolism were enriched. Observed differences in alpha diversity, metabolic pathways, and associations between bacteria and HbA1c in colonic flora need further investigation.

Background. Lipohypertrophy (LH) of subcutaneous tissue is an insulin-induced complication occurring in patients with diabetes. We aimed to define the prevalence of LH and identify its risk factors in type 1 diabetes (T1DM) patients treated with continuous subcutaneous insulin infusion (CSII). Materials and Methods. The study included 79 consecutive CSII-treated T1DM patients. The diagnose of LH was based on ultrasonography (US) as a reference method, physical examination was also performed. Clinical characteristics were available from the medical records. Results. The median age of patients was 28years (interquartile range [IQR], 2430.5) with a body mass index (BMI) of 24.5±3.5kg/m², HbA_1c 7.1 (IQR, 6.78.1), T1DM duration 15 (920) years, and CSII use duration of 8year (IQR, 511). LH was detected by US in 75 (94.9) patients. This value was much higher than this obtained by visual assessment (n=39, 49.4) or palpation (n=59, 74.7). In univariate analyses, the following risk factors for occurrence of 5 and more LH lesions were identified: the ratio of insulin dose to body mass exceeding 0.7IU/kg (OR, 3.69; 95 CI, 1.4310.01) and the total daily insulin dose (OR, 1.05; 95 CI, 1.021.09). A higher dose of insulin per kg remained a significant risk factor of LH amount in multivariate analysis. Conclusion. This selected T1DM cohort treated with CSII had a very high prevalence of LH. US assessment should be considered as a reference method for LH screening in T1DM patients. The identified risk factors for the number of LH lesions were related to insulin dosing.

Post-thrombotic syndrome (PTS) is a common complication of deep vein thrombosis (DVT). Little is known about the involvement of adipokines in the pathogenesis of DVT. We evaluated whether adipokines can predict PTS. In a prospective cohort study, 320 DVT patients aged 70 years or less were enrolled. Serum adiponectin, leptin and resistin levels were measured three months since the index first-ever DVT. After 2 years’ follow-up PTS was diagnosed in 83 of 309 available patients (26.9%) who had 13.9% lower adiponectin and 16% higher leptin levels compared with the remainder (both p < 0.0001). No PTS-associated differences in C-reactive protein, fibrinogen, D-dimer, plasminogen activator inhibitor-1 and resistin were observed. The multivariable logistic regression adjusted for age, sex, obesity and tissue plasminogen activator (tPa) showed that lower adiponectin (odds ratio [OR], 0.42; 95% confidence interval [CI], 0.31–0.56) and higher leptin levels (OR, 1.49; 95% CI, 1.31–1.69) are independent predictors for PTS. Obesity-stratified logistic regression analysis confirmed that lower adiponectin (OR, 0.49; 95% CI, 0.38–0.64) and higher leptin (OR, 1.41; 95% Cl, 1.25–1.58) levels predicted PTS. Our findings showed that lower adiponectin and higher leptin measured 3 months after DVT, regardless of obesity, can independently predict PTS, which suggests novel links between adipokines and thrombosis.

Background Compact fibrin clots relatively resistant to lysis are observed in patients at increased risk of venous thromboembolism (VTE) including malignancy. The citrullinated histone H3 (H3Cit) predicts VTE in cancer patients. Objectives We performed a cohort study to investigate whether abnormal clot properties predict cancer diagnosis following unprovoked VTE. Methods In 369 consecutive patients aged <70 years without malignancy detected during routine screening, we determined plasma clot permeability (K_s) and clot lysis time (CLT), along with several prothrombotic markers and H3Cit after 2 to 8 months since VTE. Results During follow-up (median, 37; interquartile range, 33-39 months), malignancy was diagnosed in 22 patients (6%), who were older. This group had denser fibrin networks (−13% K_s), impaired fibrinolysis (+25.5% CLT), increased endogenous thrombin potential (ETP,+7%), soluble P-selectin (+40.3%), and H3Cit (+169.2%) measured off anticoagulation after median 4 months since VTE. The K_s and CLT correlated with H3Cit (r = −.58 and r = .31, P < .05, respectively). The Kaplan–Meier survival analysis showed that reduced K_s (the first quartile, ≤6.2 × 10⁻⁹ cm²), prolonged CLT (the top quartile, >106 min), and higher ETP (the top quartile, >1657 nM × min) were predictors of cancer diagnosed during follow-up. The multivariable Cox proportional hazards model showed that patients with the prothrombotic clot phenotype (low K_s and long CLT) had the highest risk of cancer diagnosis [hazard ratio(HR), 23.4; 95% confidence interval (CI), 6.67-82.15]. Conclusions Prothrombotic clot properties following unprovoked VTE might help identify patients at risk of a diagnosis of cancer within the first 3 years of follow-up.

Introduction. Many studies have evaluated the relationship between diabetes and microbiota. In animal models, the dipeptidyl peptidase-4 inhibitors altered the gut microbiota. We investigated whether linagliptin alters the gastrointestinal flora in humans. Materials and methods. This prospective cohort study enrolled 24 patients: 5 patients with maturity onset diabetes of the young associated with HNF1A mutation and 19 patients with type 2 diabetes mellitus. Stool samples were collected at baseline and 4 weeks after treatment intensification with either linagliptin or a sulphonylurea alongside current treatment. Faecal 16S rRNA was analysed by next-generation sequencing. Results. Nine patients initiated linagliptin whereas 15 patients initiated or increased the dose of a sulphonylurea. After linagliptin treatment, we did not observe changes in taxa in L2–L7 based on analysis of composition of microbiomes (ANCOM). The same held true for pairwise alpha diversity (Shannon diversity, p = 0.59; Pielou’s measure of evenness, p = 0.68; and observed operational taxonomic units [OTUs], p = 0.77) and beta diversity distances (unweighted UniFrac, p = 0.99; weighted UniFrac, p = 0.93; Bray-Curtis, p = 0.98; and Jaccard, p = 0.99). Similarly, after sulphonylurea intensification, we did not observe changes in taxa in L2–L7 in ANCOM, nor were there changes in alpha diversity (Shannon diversity, p = 0.19; Pielou’s measure of evenness, p = 0.21; and observed OTUs, p = 0.42) or beta diversity distances (unweighted UniFrac, p = 0.99; weighted UniFrac, p = 0.99; Bray-Curtis, p = 1; and Jaccard, p = 0.99). Conclusion. We did not observe changes in colonic microbiota 4 weeks after addition of linagliptin to current diabetes treatment. Further studies are required to determine whether linagliptin influences the colonic microbiota in humans. Introduction. Many studies have evaluated the relationship between diabetes and microbiota. In animal models, the dipeptidyl peptidase-4 inhibitors altered the gut microbiota. We investigated whether linagliptin alters the gastrointestinal flora in humans. Materials and methods. This prospective cohort study enrolled 24 patients: 5 patients with maturity onset diabetes of the young associated with HNF1A mutation and 19 patients with type 2 diabetes mellitus. Stool samples were collected at baseline and 4 weeks after treatment intensification with either linagliptin or a sulphonylurea alongside current treatment. Faecal 16S rRNA was analysed by next-generation sequencing. Results. Nine patients initiated linagliptin whereas 15 patients initiated or increased the dose of a sulphonylurea. After linagliptin treatment, we did not observe changes in taxa in L2–L7 based on analysis of composition of microbiomes (ANCOM). The same held true for pairwise alpha diversity (Shannon diversity, p = 0.59; Pielou’s measure of evenness, p = 0.68; and observed operational taxonomic units [OTUs], p = 0.77) and beta diversity distances (unweighted UniFrac, p = 0.99; weighted UniFrac, p = 0.93; Bray-Curtis, p = 0.98; and Jaccard, p = 0.99). Similarly, after sulphonylurea intensification, we did not observe changes in taxa in L2–L7 in ANCOM, nor were there changes in alpha diversity (Shannon diversity, p = 0.19; Pielou’s measure of evenness, p = 0.21; and observed OTUs, p = 0.42) or beta diversity distances (unweighted UniFrac, p = 0.99; weighted UniFrac, p = 0.99; Bray-Curtis, p = 1; and Jaccard, p = 0.99). Conclusion. We did not observe changes in colonic microbiota 4 weeks after addition of linagliptin to current diabetes treatment. Further studies are required to determine whether linagliptin influences the colonic microbiota in humans.