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Israelis Develops AI that predicts PsA Four years before Symptoms begin

The team’s algorithm can speed up the diagnosis of Psoriatic Arthritis (PsA), which currently takes 2.5 years from the beginning of symptoms.

Israelis Develops AI that predicts PsA Four years before Symptoms begin
Israelis Develops AI that predicts psoriatic arthritis (PsA) Four years before Symptoms begin

Researchers in Israel developed an algorithm that can speed up the diagnosis of psoriatic arthritis (PsA), which currently takes 2.5 years from the beginning of symptoms.

The study team has demonstrated that a novel machine-learning method they developed can predict psoriatic arthritis up to four years before the beginning of symptoms. The new way reduces the risk of permanent joint damage and declining function in patients.

The findings were presented on Friday at the European Academy of Dermatology and Venereology’s (EADV) Spring Symposium in Ljubljana.

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PsA is a progressive inflammatory illness that mainly affects psoriasis sufferers’ joints and connective skin (a chronic skin disease). Joint pain and swelling, ranging from mild to severe, are the most prevalent symptoms, but many patients also develop erosive joint disease and abnormalities.

The PredictAI study analyzed the medical database of Maccabi Healthcare Services, the second-largest health medical organization in Israel, which has over 2.5 million members. Over 2000 verified PsA cases were used to train the algorithm, which was then evaluated on a different sample of confirmed PsA patients and correctly detected 32-51% of them one to four years before a clinician’s diagnosis.

32 percent of patients in the research were identified four years before to their PsA diagnosis, and 43 percent were recognized one year prior to their PsA diagnosis. When analyzing solely the medical records of psoriasis patients, 51 percent of undiagnosed PsA patients were found one year before their initial diagnosis.

Because the symptoms of PsA may be less specific than those of rheumatoid arthritis and PsA may be under-recognized in community medical practice, the authors of the research feel it would have the most impact in a primary care environment.

Since 10% of psoriasis patients may have PsA without being aware of it, we have an opportunity to inquire about joint pain, according to Dr. Jonathan Shapiro, dermatologist, medical advisor to Predictive Med analytics LTD, and manager of the tele-dermatology service at Maccabi in Israel.

Dr. Shapiro added, “Many psoriasis patients may be unaware they have PsA and will visit a general practitioner or orthopedic specialist for joint or back discomfort, without connecting it to their skin disease due to the non-specific nature of these symptoms.”

He added, “PredictAI brings the opportunity to scan large medical databases and use AI methods to search for clues such as complaints of joint pain, orthopedic specialist consultations, lab results, and many other parameters that can help to identify an undiagnosed PsA patient up to 4 years before first suspicion of PsA and can detect over 50% of these patients.”

The results have been described as “A step towards an improved treatment pathway for patients with this painful condition,” by Professor Dedee Murrell, Professor of Dermatology at the University of New South Wales, Sydney and Chair of the EADV Communications Committee.

“Arthritis due to psoriasis can cause permanent damage to the joints and may present years before any psoriasis in the skin is apparent,” she added.

“Early diagnosis and thus earlier treatment which could prevent pain and permanent joint destruction would be welcomed.

“I would be interested to know if these patients already had joint destruction and a randomised prospective study could be done to determine if earlier diagnosis prevented joint destruction and the future development of other co-morbidities associated with psoriasis.”

The team is planning to continue the research to allow the tool to increase its accuracy and sensitivity.



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