ReviewExperimental and therapeutic medicine2021
Prediction of bleeding events using the VTE-BLEED risk score in patients with venous thromboembolism receiving anticoagulant therapy (Review).
Review in Experimental and therapeutic medicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 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
8 citing papers in PubMed.
- Machine learning in bleeding risk assessment for low-molecular-weight heparin or fondaparinux: a predictive model study.Scientific reports · 2026Observational
- Management of venous thrombosis in sickle cell disease: a comparative study on the use of direct oral anticoagulants and warfarin.Research and practice in thrombosis and haemostasis · 2026Article
- External validation of a prediction model for bleeding events in anticoagulated cancer patients with venous thromboembolism (PredictAI).Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico · 2025Article
- Bleeding in patients hospitalized with acute pulmonary embolism in Brazil.Clinics (Sao Paulo, Brazil) · 2025Article
- Development and validation of a nomogram for predicting bleeding risk in patients with pulmonary embolism.Frontiers in medicine · 2025Article
- Perioperative Anticoagulation in Patients with Cancer.Current oncology reports · 2023Review
- OUTPATIENT TREATMENT OF PULMONARY EMBOLISM - A SINGLE-CENTER EXPERIENCE.Acta clinica Croatica · 2022Article
- Prophylaxis of cancer-associated venous thromboembolism with low-molecular-weight heparin-tinzaparin: Real world evidence.Oncology letters · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Venous thromboembolism (VTE) is a major healthcare problem due to its high incidence, significant mortality rate from pulmonary embolism, high recurrence rate and morbidity from long-term complications. After a first episode of VTE all patients must receive anticoagulant treatment for 3 months. Further anticoagulation is recommended in patients without transient risk factors for VTE or patients with active cancer, if they are not at a high risk for bleeding. The VTE-BLEED risk score was created with the purpose of enabling a better stratification of the bleeding risk during stable anticoagulation after a first VTE. Currently, it is the most validated risk score in VTE settings (selected and non-selected cohorts). It has a good prediction power for major bleeding events in patients receiving any of the currently available classes of oral anticoagulants, and it can identify patients at risk of intracranial and fatal bleeding events. The aim of our review was to highlight the strengths of the VTE-BLEED risk score, to acknowledge its weak points and to properly position its use in current medical practice.
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.