To cite this article: Tick LW, Doggen CJM, Rosendaal FR, Faber WR, Bousema MT, Mackaay AJC, van Balen P, Kramer MHH. Predictors of the post-thrombotic syndrome with non-invasive venous examinations in patients 6 weeks after a first episode of deep vein thrombosis. J Thromb Haemost 2010; 8: 2685-92.Summary. Background: Post-thrombotic syndrome (PTS) is a chronic complication of deep vein thrombosis (DVT) affecting a large number of patients. Because of its potential debilitating effects, identification of patients at high risk for the development of this syndrome is relevant, and only a few predictors are known. Objectives: To assess the incidence and potential predictors of PTS. Methods: We prospectively followed 111 consecutive patients for 2 years after a first episode of objectively documented DVT of the leg. With non-invasive venous examinations, residual thrombosis, valvular reflux, calf muscle pump function and venous outflow resistance were assessed at 6 weeks, 3 months, 6 months, 1 year, and 2 years. The Clinical, Etiologic, Anatomic, and Pathophysiologi classification was used to record the occurrence and severity of PTS. Regression analysis with area under the receiver operating characteristic (ROC) curve was performed to identify potential predictors. Results: The cumulative incidence of PTS was 46% after 3 months, and the incidence and severity did not increase further. Men appeared to be at increased risk as compared with women (risk ratio [RR] 1.4, 95% confidence interval [CI] 0.9-2.2), as were patients over 50 years as compared with younger patients (RR 1.4%, 95% CI 0.9-2
HLA-DP alleles can be classified into functional T cell epitope (TCE) groups. TCE-1 and TCE-2 are clearly defined, but TCE-3 still represents an heterogeneous group. Because polymorphisms in HLA-DP influence the presented peptidome, we investigated whether the composition of peptides binding in HLA-DP may be used to refine the HLA-DP group classification. Peptidomes of human HLA-DP-typed B cell lines were analyzed with mass spectrometry after immunoaffinity chromatography and peptide elution. Gibbs clustering was performed to identify motifs of binding peptides. HLA-DP peptide-binding motifs showed a clear association with the HLA-DP allele-specific sequences of the binding groove. Hierarchical clustering of HLA-DP immunopeptidomes was performed to investigate the similarities and differences in peptidomes of different HLA-DP molecules, and this clustering resulted in the categorization of HLA-DP alleles into 3-DP peptidome clusters (DPC). The peptidomes of HLA-DPB1*09:01, -10:01, and -17:01 (TCE-1 alleles) and HLA-DPB1*04:01, -04:02, and -02:01 (TCE-3 alleles) were separated in two maximal distinct clusters, DPC-1 and DPC-3, respectively, reflecting their previous TCE classification. HLA-DP alleles categorized in DPC-2 shared certain similar peptide-binding motifs with DPC-1 or DPC-3 alleles, but significant differences were observed for other positions. Within DPC-2, divergence between the alleles was observed based on the preference for different peptide residues at position 9. In summary, immunopeptidome analysis was used to unravel functional hierarchies among HLA-DP alleles, providing new molecular insights into HLA-DP classification.
We have developed a practical model for predicting the probability of death, survival with major disability, and functional recovery in patients who are comatose 24 hours after severe head injury. The model performed well in an external setting, indicating that measures to avoid statistical overfitting were successful.
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