A paramedic gurney flies through the trauma bay carrying an unconscious elderly gentleman. He is already intubated and has a hive of doctors and nurses running alongside, placing intravenous lines and injecting medicine into his blood stream. He’s suffered a serious head injury in a car accident. With every passing minute, blood accumulates in the space above his brain, pressing on vital structures.
It was a cold winter afternoon in 2017, and the patient had been taken to a major regional hospital. When he arrived, the neurosurgeon on call had minutes to counsel the family on the man’s prognosis, and together they needed to decide whether to operate; surgery could save the patient’s life, but it could also commit him to a life dependent on a ventilator and a feeding tube, trapped in a coma or with limited brain function. Sometimes the quality of life matters more than just the presence of it. The challenge is how can doctors and family members make the right decision in these rushed and emotional moments.
It’s a dilemma that confronts neurosurgeons all too often. The decision to operate is complex, as they must weigh numerous factors such as the severity of the brain injury, prognosis, age, and other injuries. Doctors have long relied on relatively simple algorithms to guide their decision-making, but now researchers at a number of institutions around the world are designing and beginning to test artificial intelligence systems to more accurately predict likely outcomes and help surgeons decipher whether to operate on a patient with a traumatic brain injury.
This article is exclusive to STAT+ subscribers
Unlock this article — and get additional analysis of the technologies disrupting health care — by subscribing to STAT+.
Already have an account? Log in
Already have an account? Log in
To submit a correction request, please visit our Contact Us page.
STAT encourages you to share your voice. We welcome your commentary, criticism, and expertise on our subscriber-only platform, STAT+ Connect