Derivation and validation of the QBleed algorithms to predict the risk of bleeding
What is the aim of the study and why is it important?
To 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.
QBleed is updated regularly to ensure the algorithms remain calibrated to the current population since the incidence of disease and the prevalence of risk factors changes over time. The updates also enable the algorithm to take account of improvements to data quality (for example increases in the completeness of recording of risk factors such as ethnicity or laboratory values) and also allows adaptations to any changes which might be required to improve the predictive power of the tool or the population to which is applied.
How is the research being done?
We developed and validated a new set of risk prediction algorithms to predict risk of gastrointestinal and intracranial bleed in new users of anticoagulants (rather than existing users). We wanted to develop algorithms that quantify absolute risk of bleed, which can be communicated to patients to aid decision making in the consultation, automatically populated from the patients record and integrated into general practice computer systems, and updated readily over time, as the pattern of prescribing of both anticoagulant drug classes may change.
Location of research
Date on which research approved
Project reference ID
Generic ethics approval reference
Are all data accessed are in anonymised form?
Brief summary of the dataset to be released (including any sensitive data)
Risk factors for bleeding linked to outcomes recorded on GP, hospital or mortality records
What were the main findings?
We developed and validated two models (collectively known as the QBleed algorithms) to identify patients at high risk of gastrointestinal or intracranial bleed. The QBleed algorithms incorporate predictor variables that are associated with an increased risk of haemorrhagic events, including sociodemographic variables, lifestyle, morbidity, drugs, and laboratory test results such as abnormal platelet function. The algorithms can be applied to any adult in a primary care setting regardless of whether they have had a previous bleed and have the advantage of evaluating risk in new users of oral anticoagulants, which is likely to be the highest risk period for bleeding.
The QBleed algorithms are intended to help inform decisions within the consultation about the risks and benefits of patients in primary care using anticoagulants. For example, the doctor can assess the patient’s five year risk of stroke using QStroke or five year risk of thrombosis using QThrombosis against the risk of bleed with or without anticoagulation using QBleed. The doctor and patient also can review factors that might ameliorate the risks, such as amending concurrent drugs. Overall this could help the doctor and patient assess whether the balance of risks and benefits is likely to be favourable or not given the patient’s profile.
Implications and Impact
The QBleed algorithms provide an estimate of absolute risk of two types of bleed for each year for each of the next five years. The algorithms are designed to be used before anticoagulant treatment is started using information already available at the time, rather than to guide the continuing use of anticoagulants, taking into account changes in treatment during follow-up. The algorithms to quantify risk of intracranial bleed performed better than the algorithms to predict upper gastrointestinal bleed.
No external funding
Professor Julia Hippisley-Cox, Professor Carol Coupland, Dr Peter Brindle
Predicting risk of upper gastrointestinal bleed and intracranial bleeding with anticoagulants: prospective cohort study to derive and validate the QBleed score
Authors: Hippisley-Cox J, Coupland CA.
Ref: BMJ 2014; 349; g4606.
ORBIT Bleeding Risk Score and QBleed
Authors: Hippisley-Cox J.
Ref: European Heart Journal 2015; 09;29.
The performance of seven QPrediction risk scores in an independent external sample of patients from general practice: a validation study
Authors: Hippisley-Cox J, Coupland CA, Brindle P
Ref: BMJ Open 2014;4(8):e005809