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Understanding clinical risk scores in 4 days. Day 2: Prediction

Ami Banerjee
Last edited 20th April 2011

As well as diagnosing disease, it may be important to predict which patients need more investigation or more treatment. The term, “clinical prediction rule”, is often used to describe the best combination of medical signs, symptoms, and other findings in predicting the probability of a specific disease or outcome. Therefore, they can be used in diagnosis as in the last article, or they can estimate the risk of a specific outcome, and therefore help in decision-making.

To form prediction rules, researchers look at a group of patients suspected of having a specific disease or outcome. They then compare the value of clinical findings available to the clinician versus the results of more intensive testing or the results of delayed clinical follow up.

Previous studies have shown that giving clinicians information in the form of risk scores in isolation may not influence clinical practice. GPs routinely underuse risk scores and have suggested that computerized risk prediction for multiple diseases simultaneously and the integration of lifestyle recommendations may improve their uptake.

Clinical prediction rules are most effective when implemented as part of a pathway within hospital policies and guidelines, as shown in the case of pneumonia and the more rigorously the rules are implemented, the more successful they are at improving outcomes.

The CHADS(2) score is an example of a clinical risk score to help in deciding whether to start warfarin in patients with atrial fibrillation to prevent stroke. Patients are classified by their clinical history, getting 1 point each for Congestive cardiac failure, Hypertension, Age>75 years, Diabetes and 2 points for Stroke. Patients with scores of 2 or more should get warfarin, as long as they have no contraindications. A recent improvement on this score, the CHA(2)DS(2)-VASc has added 3 additional factors (history of vascular disase, sex and age 65-74) to improve the prediction of risk so that only people who are really at negligible risk of stroke do not get warfarin.

Other examples of risk scores used in this way are Wells scores for deep vein thrombosis and pulmonary embolism and CURB-65 in pneumonia.

Understanding clinical risk scores in 4 days. Day 1: Diagnosis

Ami Banerjee
Last edited 20th April 2011

Risk is arguably one of the most central concepts in clinical medicine. Patients want to know their risk of a particular disease or perhaps even death. Clinicians are interested in which patients are at highest risk of disease and complications. Researchers want to establish the way in which new treatments change the risk of disease. Clinical risk scores use available information to predict the risk of a particular clinical scenario. Risk scores cannot replace clinical judgment but they can guide it. There are hundreds of risk scores available to clinicians and many are available online as risk calculators and are widely used by patients. In this 4-day series, I will cover the 4 types of clinical risk score.


Some diseases are easy to diagnose because they are well-defined. For example, infection with HIV is diagnosed by a positive HIV test. However, not all diseases are so easy to diagnose or have such clearly defined criteria. Lack of diagnostic certainty can lead to inappropriate treatment and can even lead to abuse of the social benefits system by some unscrupulous parents in the case of attention deficit hyperactivity disorder(ADHD)

Diagnostic scores can be helpful in identifying disease, but also in describing severity of disease. In depression, the Beck’s depression inventory (BDI) is a score which describes the severity of depression on a continuous scale, with 0–9 indicating minimal depression, 10–18: mild depression, 19–29: moderate depression and 30–63 indicating severe depression. A score of at least 10 on the Beck Depression Inventory is the generally accepted threshold for the indication of possible depression.

The mini-mental test score (MMTS) is the most commonly used diagnostic test to assess cognitive function. Scores of 25-30 out of 30 are considered normal. NICE classify 21-24 as mild, 10-20 as moderate and <10 as severe impairment.

Diagnostic scores must be tested and validated in well-defined populations because the scores may perform differently in different patient groups. For example, the BDI above is good at diagnosing depression in post-stroke patients.

The term “clinical prediction rules” is often used to describe the use of clinical findings (history, physical examination, and test results) to make a diagnosis, OR to predict an outcome. This article from Annals in Internal Medicine sums up what you need to know about diagnostic scores before you use them on your patients.

Are conferences any good at disseminating evidence?

Ami Banerjee
Last edited 1st April 2011

The questions of how best to train and educate doctors during medical school and throughout their careers have been difficult to answer for hundreds of years. I was reflecting on this over the last couple of weeks as I attended two overseas conferences. Like most conferences, these meetings aim to bring doctors and scientists up-to-date with the latest research developments in their fields of interest within medicine and the health sciences. They both had top-level speakers and excellent programmes, and both had substantial e-learning and other online resources. Lectures and conferences are the mainstay of teaching and continuing medical education in medicine and many other disciplines, but are they good at what they set out to do? This is a question particularly pertinent to evidence-based medicine, because what it ultimately aims to do is disseminate the best evidence and enable its uptake in clinical practice.

We know that people can learn over the internet using e-modules, video-conferencing and other modalities equally well, but I think there are two reasons why conferences persist. First and foremost, in a world of compulsory continuing medical education, they offer convenience. They are the easiest (and most passive way) to disseminate evidence from research. Secondly, they offer the chance to network (and relax) with peers and opinion leaders which even market leaders like TED.com will find it difficult to emulate.

As educational budgets are cut throughout the NHS and doctors increasingly fund their own continuing medical education, the reality is that pharmaceutical or other industry-sponsored educational events are likely to grow and not decrease, and more safeguards will be needed to avoid a reduction in educational content and an increase in drug company promotional material. As postgraduate deaneries are threatened, there are fears for the standards of training of doctors, but we should be equally worried about who is going to pay for the teaching in the new NHS. The Medical Students International Network (MedSIN) is remarkably forward-thinking about trying to avoid private industry sponsorship of education in medical schools. However, in a difficult economic climate, even with increasing tuition fees, industry-sponsored undergraduate education may rear its head.

There is a role for conferences in the dissemination of research and in promoting evidence-based practice and knowledge translation, but they should not be the only way we keep up-to-date. What is the best way to learn? As some UK public health trainees, say in a recent article: “In order to retain its position as a leader in the field of public health, the UK needs to adapt its training programme to better reflect today's challenges.”

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