ArticleBMJ (Clinical research ed.)2014
Predicting risk of upper gastrointestinal bleed and intracranial bleed with anticoagulants: cohort study to derive and validate the QBleed scores.
Article in BMJ (Clinical research ed.), 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 44 papers, 5 of them syntheses that pooled it.
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Who cites it
44 citing papers in PubMed, 5 syntheses or guidelines pooled it, 102 citations in OpenAlex.
- Anticoagulation quality through time in therapeutic range in Sub-Saharan Africa: a systematic review and meta-analysis.Frontiers in medicine · 2025Pooled it
- Risk Factors for Anticoagulant-Associated Intracranial Hemorrhage: A Systematic Review and Meta-analysis.Neurocritical care · 2023Pooled it
- Association of Antisecretory Drugs with Upper Gastrointestinal Bleeding in Patients Using Oral Anticoagulants: A Systematic Review and Meta-Analysis.The American journal of medicine · 2022Pooled it
- Different strategies for pharmacological thromboprophylaxis for lower-limb immobilisation after injury: systematic review and economic evaluation.Health technology assessment (Winchester, England) · 2019Pooled it
- Opportunities and challenges in developing risk prediction models with electronic health records data: a systematic review.Journal of the American Medical Informatics Association : JAMIA · 2017Pooled it
- Aspirin, cardiovascular events, and major bleeding in older adults: extended follow-up of the ASPREE trial.European heart journal · 2025Trial
- Trial
- Development of a clinical prediction model for an international normalised ratio ≥ 4·5 in hospitalised patients using vitamin K antagonists.British journal of haematology · 2018Trial
- Prevention of Gastrointestinal Bleeding in Patients Receiving Direct Oral Anticoagulants: A Narrative Review and Practical Framework for Prescribers.Clinics and practice · 2026Review
- Article
- Balancing the risk of major bleeding against vascular disease risk in people without atherosclerotic disease.Heart (British Cardiac Society) · 2025Article
- Challenges in detecting and predicting adverse drug events via distributed analysis of electronic health record data from German university hospitals.PLOS digital health · 2025Article
- A new score for predicting intracranial hemorrhage in patients using anticoagulant drugs.Frontiers in neurology · 2025Article
- Observational
- Bleeding Risk Prediction in Patients Treated with Antithrombotic Drugs According to the Anatomic Site of Bleeding, Indication for Treatment, and Time Since Treatment Initiation.TH open : companion journal to thrombosis and haemostasis · 2024Article
- Review
- Gastrointestinal bleeding during anticoagulation with direct oral anticoagulants compared to vitamin K antagonists.Global cardiology science & practice · 2022Article
- Predictive Value of HAS-BLED Score Regarding Bleeding Events and Graft Survival following Renal Transplantation.Journal of clinical medicine · 2022Article
- Development of a multicomponent implementation strategy to reduce upper gastrointestinal bleeding risk in patients using warfarin and antiplatelet therapy, and protocol for a pragmatic multilevel randomized factorial pilot implementation trial.Implementation science communications · 2022Article
- Management dilemmas in restarting anticoagulation after gastrointestinal bleeding.Proceedings (Baylor University. Medical Center) · 2022Article
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Authors and funding
2 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectiveTo develop and validate risk algorithms (QBleed) for estimating the absolute risk of upper gastrointestinal and intracranial bleed for patients with and without anticoagulation aged 21-99 years in primary care.
designOpen cohort study using routinely collected data from general practice linked to hospital episode statistics data and mortality data during the five year study period between 1 January 2008 and 1 October 2013.
setting565 general practices in England contributing to the national QResearch database to develop the algorithm and 188 different QResearch practices to validate the algorithm. All 753 general practices had data linked to hospital episode statistics and mortality data at individual patient level. ENDPOINT: Gastrointestinal bleed and intracranial bleed recorded on either the linked mortality data or the linked hospital records.
participantsWe studied 4.4 million patients in the derivation cohort with 16.4 million person years of follow-up. During follow-up, 21,641 patients had an incident upper gastrointestinal bleed and 9040 had an intracranial bleed. For the validation cohort, we identified 1.4 million patients contributing over 4.9 million person years of follow-up. During follow-up, 6600 patients had an incident gastrointestinal bleed and 2820 had an intracranial bleed. We excluded patients without a valid Townsend score for deprivation and those prescribed anticoagulants in the 180 days before study entry. RISK FACTORS: Candidate variables recorded on the general practice computer system before entry to the cohort, including personal variables (age, sex, Townsend deprivation score, ethnicity), lifestyle variables (smoking, alcohol intake), chronic diseases, prescribed drugs, clinical values (body mass index, systolic blood pressure), and laboratory test results (haemoglobin, platelets). We also included previous bleed recorded before entry to the study.
resultsThe final QBleed algorithms incorporated 21 variables. When applied to the validation cohort, the algorithms in women explained 40% of the variation for upper gastrointestinal bleed and 58% for intracranial bleed. The corresponding D statistics were 1.67 and 2.42. The receiver operating curve statistic values were 0.77 and 0.86. The sensitivity values for the top 10th of men and women at highest risk were 38% and 51%, respectively. There were similar results for men.
conclusionThe QBleed algorithms provided valid measures of absolute risk of gastrointestinal and intracranial bleed in patients with and without anticoagulation as shown by the performance of the algorithms in a separate validation cohort. Further research is needed to evaluate the clinical outcomes and the cost effectiveness of using these algorithms in primary care.
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