Understanding clinical risk scores in 4 days. Day 1: Diagnosis
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.
LESSON 1: DIAGNOSIS: IS IT DISEASE?
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.
Alzheimer's and brain scans: not needed yet
"We have some of the best scientists and facilities in the world and today's announcement will help ensure we continue to be at the cutting edge of life sciences."
An advanced computer programme compares a patient's brain scan with a database of 1,200 existing images of brains already affected by the disease. Scientists say early tests show the new technique is 85% accurate and can deliver results in just 24 hours.
In relation to diagnosis the word accurate keeps cropping up, and when it does we normally reveal the test is useless. If you want a precursor then see why Autism can’t be diagnosed with brain scans in the guardian last year. It's seems to be a modern feature of news stories that there seems to be little checking of the original data.
This is what Kings College have to say:
The 'Automated MRI' software automatically compares or benchmarks someone’s brain scan image against 1200 others, each showing varying stages of Alzheimer’s disease. This collection of images is thought to be the largest of its kind in the world.
The scan has been developed by scientists at the IoP, together with colleagues from the Karolinska Hospital in Stockholm.
The system is being 'field tested' over the next 12 months with patients attending SLaM memory services in Croydon, Lambeth and Southwark. The ‘field test’ will also provide a supply of research grade images, which has important implications for the development of the next generation of drugs for dementia and individualised treatments.
My assumptions for now, given after searching 35 news articles without a single reference to any study, is that 85% accurate refers to the proportion of people with established disease who have a positive brain scan. This figure, if it is the correct interpretation, bears no resemblance to the real question that needs to be asked? If I have a positive brain scan do I have Alzheimer’s?
I'm not sure how these news stories help us, but for now, I'm glad I can still spot nonsense when I see it. When I can't, it looks like I'll need the Brain scan.
Special educational needs-a problem with the diagnostic test?
Just over one in five pupils – 1.7 million school-age children in England – are identified as having special educational needs. An Ofsted report
this week claims that half of children in UK schools have been labelled incorrectly as “special educational needs” or SEN. There has been much debate in the media about whether this was to raise extra revenue for schools or to save money on teachers’ wages.
Given the implications on the child, the parents and the educational system, I was amazed how difficult it was to find out about how SEN is diagnosed. In practice, children with SEN encompass a wide variety of conditions from autism and dyslexia to ADHD. SEN are defined by one website as:
• significantly greater difficulty in learning than the majority of children of their age;
• a disability which prevents or hinders them from making use of educational facilities of a kind generally provided for children of the same age in schools within the area
• Is under compulsory school age and falls within the definition above or would do so if special educational provision was not made for them.
Even though it is in the field of education and not directly health-related, I was reminded of problems in inaccurate diagnosis in evidence-based medicine. The issues of money and stakeholder interests are no different to the conflicts of interest often found in health research. However the major issue is that children who have been falsely diagnosed with SEN are “false positives”. Therefore the way we are diagnosing SEN is not specific enough. Surely there needs to be a debate about the way we diagnose SEN?