ArticleMedical science monitor : international medical journal of experimental and clinical research2025
Predictive Factors for Post-Thrombotic Syndrome in Patients with Deep Vein Thrombosis Treated with AngioJet Pharmacomechanical Thrombectomy: A Retrospective Single-Center Study.
Article in Medical science monitor : international medical journal of experimental and clinical research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
2 citing papers in PubMed.
- Evaluation of venous anatomy after treatment with an intraluminal tissue debulking system in a porcine model.Journal of vascular surgery. Venous and lymphatic disorders · 2026Article
- Machine learning-based prediction of post-thrombotic syndrome in unprovoked lower extremity deep vein thrombosis: a two-center study incorporating uric acid and clinical risk factors.European journal of medical research · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
BACKGROUND Deep venous thrombosis (DVT) is one of the most common peripheral vascular diseases. AngioJet pharmacomechanical thrombectomy has been widely used to treat DVT. This study evaluated outcomes of patients with DVT after pharmacomechanical thrombectomy and determined potential risk factors associated with prognosis. MATERIAL AND METHODS A retrospective review was conducted to enroll patients with DVT who received AngioJet pharmacomechanical thrombectomy from July 2018 to May 2020. Clinical data and outcome measures, including baseline demographic information, procedure details, adverse events, incidence of post-thrombotic syndrome (PTS), and Villalta scores were collected. The logistic regression modeling began with a univariate analysis to identify factors with statistically significant differences. Multivariate analysis revealed predictive factors of the development of PTS. RESULTS Eighty-nine patients were recruited and divided into 2 groups according to the presence of PTS: 22 patients in the PTS group and 67 patients in the non-PTS group. All cases were technically successful. Total median dosage of thrombolytic agents was 260 million units (range, 160-440 million units) and median duration of hospital stay was 5 days (range, 2-15 days). No major adverse events were observed. Univariate analysis showed statistical significance for all factors tested, except age, sex, and leg varicosities at baseline between the groups. Multivariate logistic regression confirmed that only time from onset to treatment (OR=1.745; 95% CI=1.316-2.315) was associated with incidence of PTS after pharmacomechanical thrombectomy. CONCLUSIONS AngioJet pharmacomechanical thrombectomy is an effective therapeutic approach for DVT. Time from onset to treatment was an independent factor in predicting development of PTS.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.