A study led by Susan Searles Nielsen, PhD, MS, assistant professor of neurology at the Washington University located in St. Louis, Missouri, looked into a new method that utilizes past medical records in order to predict whether or not a patient will develop Parkinson’s disease. This approach was made possible by the creation of a unique algorithm that only relies on medical records.
The new, proposed method of predicting cases of Parkinson’s disease could serve as a ground-breaking tool, as most of the discoveries of any sign of Parkinson’s are made when the symptoms have already “settled” within the respective patient.
This method can be especially important for patients because it could lead to the proper treatments being utilized at the earliest time possible, so as to potentially prevent the disease altogether.
Brad A. Racette, MD, professor of neurology at Washington University explains how this method works for patients: “Using this algorithm, electronic medical records could be scanned and physicians could be alerted to the potential that their patients may need to be evaluated for Parkinson’s disease… One of the most interesting findings is that people who are going to develop Parkinson’s have medical histories that are notably different from those who don’t develop the disease… This suggests there are lifelong differences that may permit identification of those likely to develop the disease decades before onset.”
The technique could prove to be an important approach for patients, even if used for standard initial screenings for a potential prevalence of Parkinson’s disease.
The efforts began with an analysis of 89,790 cases from the year 2014 to 2019 of which patients were diagnosed with Parkinson’s disease. In order or develop the algorithm that made the method possible, the team took into account a variety of distinguishing factors of patients. The traits included each patient’s respective gender, age, ethnicity, history of smoking, as well as some key clinical factors, such as psychiatric conditions, past experiences with trauma, fatigue, sleep disorders, diabetes, as well as others.
As a result, the developed algorithm was capable of predicting, with over 85 percent accuracy, whether or not a patient would in fact develop Parkinson's disease. In terms of the population used to test the algorithm, a total of 73 percent were identified as having a likelihood of a Parkinson’s disease diagnosis.
One key contribution that helped the researchers to identify the specific patients that had the possibility of developing Parkinson’s disease included the factors associated with the disease itself. The factors that proved to be helpful included symptoms such as tremors, bad posture, and cognitive or psychiatric deficiencies. Relating to the early signs of potential Parkinson’s disease patients, Racette states, “We want to be able to catch people as early as possible… If I know someone may be in the beginning stages of Parkinson’s disease, I would evaluate their gait and balance to determine if they have unrecognized impairments that could lead to falls, or whether they have difficulty performing activities of daily living. Either of these scenarios may benefit from treatment.”
The researchers are hopeful that with time, their algorithm will improve even further, with the potential to open doors into even more opportunities. Their efforts already stand a chance at laying down a new path by which medical professionals can follow when assessing their patients.
The program could benefit the Parkinson’s community as a whole, as it will be one of the first methods of its kind to predict the onset of such a difficult disease.
What is Parkinson’s disease?
Parkinson’s disease is classified as a type of neurodegenerative disease, and is said to affect up to 10 million people across the globe. The disease is most commonly connected to failure in controlling patients' movements, however the disease is much more than this single symptom. In addition to this motor deficiency, patients may experience rigid muscles, a weakened and abnormal posture, the loss in automatic movements (such as blinking or smiling), as well as changes in the ability to speak and write. Other complications that can potentially be experienced by patients include trouble focusing, swallowing, sleep disorders, bladder problems, constipation, overtiredness, and changes in blood pressure.
While the cause of Parkinson’s disease has yet to be discovered, doctors believe that a variety of factors contribute to the development of the condition. These risk factors can include a patient’s age, their gender (men are more commonly diagnosed with the disease), exposure to certain types of toxins, as well as a family history of Parkinson’s disease. If some of these factors are seen in a patient, a doctor may suggest said patient begin the diagnosis process. Diagnosis of Parkinson’s utilizes a variety of different tests that help doctors assess a patient's respective condition. While there is not a test specifically designed to diagnose Parkinson’s disease, physicians will often suggest a patient undergo various imaging tests, such as an MRI, ultrasound of the brain, SPECT scan, and a PET scan.
In regards to treatment, no specific remedy will completely cure the symptoms that are tied to Parkinson’s disease. Many different treatment options exist that serve the purpose of suppressing these symptoms. These approaches can include medications like carbidopa-levodopa, carbidopa-levodopa infusion, dopamine agonists, MAO-B inhibitors, catechol-O-methyltransferase (COMT) inhibitors, anticholinergics, and amantadine.
In addition to these, certain medical procedures can be utilized as well. The most common surgical procedure for this application includes that of deep brain stimulation (DBS) surgery.
The future for Parkinson’s disease patients
As can be seen by these research efforts, there is hope for patients who may develop Parkinson’s disease. An important step in making the entire screening process be more effective, however, will rest on how diligent the population is as a whole. In order to utilize the software that was developed, patients must be able to identify if they have some of the key factors that hint at a potential diagnosis of Parkinson’s. Without these proactive efforts, the algorithm would be useless. With the use of such equipment, paired with the many other growing resources, the Parkinson's population can look forward to a more improved way in which doctors diagnose and predict Parkinson’s disease.