The risk for post-thrombotic syndrome of subjects with deep vein thrombosis in an Indonesian referral hospital: a retrospective cohort study

Diagnostic and prognostic potential of long non-coding RNA NORAD in patients with acute deep vein thrombosis and its role in endothelial cell function

BACKGROUND

Deep venous thrombosis (DVT) is the common clinical cardiovascular disease, and easily develops into post-thrombotic syndrome (PTS). The study aimed to examine the clinical value of long non-coding RNA NORAD gene in the development of DVT and PTS. In vitro, the underlying mechanism was explored.

METHODS

Serum levels of lncRNA NORAD gene in 85 DVT cases and 85 healthy individuals were tested. The role of lncRNA NORAD gene in human umbilical vein endothelial cells (HUVECs) proliferation, migration and inflammation was examined. The candidate downstream target gene was predicted via bioinformatic analysis. Gene ontology (GO) analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis were done for the function annotation and pathway enrichment.

RESULTS

LncRNA NORAD gene was at high expression in the serum of DVT patients, it can distinguish DVT patients from healthy controls with the area under the curve of 0.919. Elevated expression of lncRNA NORAD gene in PTS patients was detected, DVT cases with high expression of lncRNA NORAD gene were more susceptible to PTS. LncRNA NORAD gene knockdown promoted HUVECs' proliferation, migration while suppressing cell apoptosis and inflammation. MiR-93-5p served as a target of lncRNA NORAD gene, and its overexpression reversed the role of lncRNA NORAD gene in the biological function of HUVECs. The target genes of miR-93-5p were enriched in HIF-1 signaling, TGF-beta signaling and PI3K-Akt signaling, protein-protein interaction (PPI) network indicated STAT3, MAPK1 to be the key targets.

CONCLUSIONS

Upregulation of expression of lncRNA NORAD gene was a potential diagnostic biomarker for DVT and related to the development of PTS. LncRNA NORAD/miR-93-5p axis was involved in the progress of DVT through regulating endothelial cell function.

A systematic evaluation and meta-analysis of early prediction of post-thrombotic syndrome

Objective

Post-thrombotic syndrome (PTS) is the most common long-term complication in patients with deep venous thrombosis, and the prevention of PTS remains a major challenge in clinical practice. Some studies have explored early predictors and constructed corresponding prediction models, whereas their specific application and predictive value are controversial. Therefore, we conducted this systematic evaluation and meta-analysis to investigate the incidence of PTS and the feasibility of early prediction.

Methods

We systematically searched databases of PubMed, Embase, Cochrane and Web of Science up to April 7, 2023. Newcastle-Ottawa Scale (NOS) was used to evaluate the quality of the included articles, and the OR values of the predictors in multi-factor logistic regression were pooled to assess whether they could be used as effective independent predictors.

Results

We systematically included 20 articles involving 8,512 subjects, with a predominant onset of PTS between 6 and 72 months, with a 2-year incidence of 37.5% (95% CI: 27.8-47.7%). The results for the early predictors were as follows: old age OR = 1.840 (95% CI: 1.410-2.402), obesity or overweight OR = 1.721 (95% CI: 1.245-2.378), proximal deep vein thrombosis OR = 2.335 (95% CI: 1.855-2.938), history of venous thromboembolism OR = 3.593 (95% CI: 1.738-7.240), history of smoking OR = 2.051 (95% CI: 1.305-3.224), varicose veins OR = 2.405 (95% CI: 1.344-4.304), and baseline Villalta score OR = 1.095(95% CI: 1.056-1.135). Meanwhile, gender, unprovoked DVT and insufficient anticoagulation were not independent predictors. Seven studies constructed risk prediction models. In the training set, the c-index of the prediction models was 0.77 (95% CI: 0.74-0.80) with a sensitivity of 0.75 (95% CI: 0.68-0.81) and specificity of 0.69 (95% CI: 0.60-0.77). In the validation set, the c-index, sensitivity and specificity of the prediction models were 0.74(95% CI: 0.69-0.79), 0.71(95% CI: 0.64-0.78) and 0.72(95% CI: 0.67-0.76), respectively.

Conclusions

With a high incidence after venous thrombosis, PTS is a complication that cannot be ignored in patients with venous thrombosis. Risk prediction scoring based on early model construction is a feasible option, which helps to identify the patient's condition and develop an individualized prevention program to reduce the risk of PTS.