MedTech start-up launches AI-driven AF risk prediction solution

STABILITY platform from Rinicare uses AI technology to provide advanced clinical risk prediction and acts as an early warning system for patient deterioration

STABILITY AF helps to provide an early warning system for AF among high-risk patients

Manchester-based MedTech start-up, Rinicare, has launched a new application for its ground-breaking clinical risk prediction platform, STABILITY.

The solution is focused on highlighting patients’ risk of developing atrial fibrillation (AF), initially in those who have undergone cardiac surgery.

The product will use Rinicare’s AI-driven clinical risk prediction software to provide clinicians with an effective early warning system for AF, leading to improved patient outcomes and safety.

Rinicare is currently in discussions with a number of key stakeholders about implementing STABILITY AF into critical care units around the UK, alongside its existing STABILITY UO solution.

STABILITY AF utilises routine pre- and post-operative physiological data inputted by clinicians managing patients in critical care units.

Using a proprietary algorithm, it then analyses this data and provides clinicians with an easy-to-understand risk score for how likely a patient is to develop atrial fibrillation in the near-term, informing patient management decisions for those patients.

Each patient receives a pre-operative risk score, and a post-operative risk score, which is updated to take intra- and post-operative events into account, allowing clinicians to quickly and accurately identify those patients most at risk.

Atrial fibrillation is the most-common arrhythmia complicating cardiac surgery, and puts patients at increased risk of stroke, congestive heart failure, and haemodynamic instability.

Post-operative AF (POAF) usually occurs 2-5 days after surgery, and, on average, patients with POAF typically incur $10,000–$20,000 in additional hospital treatment costs, spend 12–24 hours longer in intensive care, and have an additional 2-5 days in the hospital.

Rinicare’s STABILITY platform can identify subtle signs of patient deterioration, and acts as an early warning system for clinical teams in critical care units.

This gives clinicians the opportunity to make earlier interventions to prevent AF developing.

In addition, the STABILITY AF module also allows clinicians to identify low risk patients, potentially allowing them to be safely transitioned out of the critical care unit more quickly.

The STABILITY AF launch marks the second application for Rinicare’s STABILITY platform, following STABILITY UO (urine output).

STABILITY UO employs sophisticated analysis of urine output data to predict a patient’s risk of developing renal complications or acute kidney injury following cardiac surgery, and allow for early, preventive intervention.

Powered by a clinically-validated algorithm, its predictive power has been shown to accurately predict dangerous episodes of low urine output that correlate strongly with increased morbidity and mortality.

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