Introduction
Sickle cell disease, including sickle cell anemia, affects millions of people worldwide, with a disproportionate impact on individuals of black African or black Caribbean backgrounds. This genetic disorder can have lifelong health implications, ranging from increased susceptibility to infections and stroke to anemia and excruciating pain crises.
While strides have been made to improve the quality of life for those with sickle cell disease, research efforts remain significantly underfunded.
As we observe Sickle Cell Awareness Month, let's explore how artificial intelligence (AI) is playing a pivotal role in transforming the diagnosis, treatment, and management of this condition, offering new hope to those affected.
What is sickle cell disease?
Before we dive into AI-driven advancements, let’s quickly touch on exactly what sickle cell disease is.
In individuals with this condition, red blood cells take on an atypical shape due to a genetic mutation, resembling sickles rather than the typical biconcave disks. These abnormal cells can clump together, impeding their movement through the bloodstream and potentially blocking blood vessels leading to infections, stroke, anemia, and episodes of intense pain known as sickle cell crises.
While some carriers of the genetic trait may remain free of symptoms, for others, it's a lifelong battle. Around 300 million people worldwide carry the sickle cell mutation, and over 7 million suffer from the disease itself.
Is there a cure?
The only known cure for sickle cell disease is a bone marrow transplant. But it’s not a one-size-fits-all solution. Not everyone with sickle cell disease has a relative who is a close enough genetic match to be a donor. And the treatment tends to be most effective in children and poses significantly greater risks for adults.
Fortunately, there are ways to alleviate symptoms, such as pharmaceutical treatments and blood transfusions. Nevertheless, managing the lifelong condition requires complex, evolving treatments and frequent medical interventions.
How AI can help
Early Diagnosis with AI.
One of the major hurdles in treating sickle cell disease is early diagnosis. AI is helping here by analyzing medical records, genetic data, and clinical symptoms to identify individuals at risk. Machine learning algorithms can detect patterns and predict the likelihood of a patient developing related conditions, such as sickle cell anemia and sickle cell retinopathy, allowing for timely interventions.
Personalized Treatment Plans.
Recognizing that no two individuals with sickle cell anemia are identical, AI systems monitor a patient's health over time and craft personalized treatment plans. These plans can include optimizing medication dosages based on pain levels and scheduling proactive follow-up appointments.
Remote Patient Monitoring.
AI-driven wearable devices are revolutionizing patient care. These devices continuously collect data on a patient's vital signs, such as heart rate, oxygen levels, and pain indicators. In the UK, the National Health Service has launched a scheme to track those with sickle cell disease with a smartwatch.
AI algorithms examine this data and can notify healthcare providers of concerning trends, enabling timely interventions and enhancing clinical research.
Case study: AI assesses pain levels in people with sickle cell disease
In 2021, Dr Daniel Abrams at Northwestern University and his team developed an AI tool to objectively assess the pain levels of individuals with sickle cell disease using commonly taken vital signs.
Pain's subjective nature makes standardized measurement challenging, prompting Abrams to explore whether routinely collected physiological data like body temperature, heart rate, and blood pressure could objectively assess pain.
Their study involved 46 patients with sickle cell disease during 105 hospital stays. By combining physiological data with patient-reported pain scores and employing machine learning, they developed models capable of deducing pain levels and detecting changes. Comparing these models to existing ones that rely solely on patient-reported data, the new models exhibited superior performance, potentially offering a more quantitative approach to pain management.
In the future, the technique could be used to help doctors prescribe better dosages of pain medication for those suffering from sickle cell disease. The innovation also has significant potential elsewhere including in pediatric care, where children often struggle to articulate their pain.
The team’s goal is to compile extensive data from millions of hospitalizations, encompassing various pain conditions, including post-operative and chronic pain, paving the way for more effective pain management practices.
What does the future hold?
AI- and ML-powered technologies are potential game changers in the fight against sickle cell disease, redefining patient care. However, it’s crucial to acknowledge a significant hurdle the field faces: there is not enough research and not enough funding. Sickle cell disease has long been overlooked in research, despite being one of the most common genetic disorders globally.
That’s why advocacy efforts and increased awareness are essential to mobilize funding and research interest, ensuring that AI and other cutting edge technologies can fully realize their potential in advancing sickle cell disease treatment.
As technology continues to advance, we look forward to even more innovative applications of AI in the field of healthcare, ultimately improving the lives of individuals affected by sickle cell disease.
