A look at the past
Despite the lack of aseptic techniques and anesthesia, the ancient doctors did surprisingly well with trauma patients. The Roman Empire organized valetudinaria - hospitals for wounded legionnaires. They were able to immobilise fractured bones, stop hemorrhages and perform amputations. In Peru, exploratory trepanations of the skull were carried out, rescuing patients with post-traumatic hematomas. Indian surgeons even dared to perform laparotomy and treat intestinal injuries. However, these treatments were bearing a horrendous risk of death and most of the patients didn't survive.
On the other hand, therapies for acute medical conditions were not that intuitive and the development of emergency medicine in this field was less spectacular. Loss of consciousness was commonly treated with ammonia smelling salts. In hypertensive crisis, leeches were used to draw out the blood. After near-drowning events, it was often attempted to resuscitate victims with tobacco smoke applied by enema.
"Tobacco glyster, breath and bleed.
Keep warm and rub till you succeed.
And spare no pains for what you do;
May one day be repaid to you."
— Houlston, 1774
From a modern point of view, it is not surprising that the effectiveness of such a form of resuscitation in sudden cardiac arrest was nonexistent.
Here and now
Many years have passed. After a large number studies, we moved away from treatments of unconfirmed effectiveness. Clinical procedures are currently based on the results of reliable scientific research. This approach got its own name - “evidence-based medicine” (EBM). Algorithms, triage systems, ultrasound scanners, point-of-care testing devices and capnographs are now present in the emergency departments.
The distinction between the distant or near past and the present is becoming clearer and wider.
In the era of standardized procedures, is there still room for another surge in effectiveness of life saving? Will the new technologies call the tune for it?
Wave of the future
Krystian, 45 years old. He's been avoiding physical effort for several months now and has recently stopped rowing training. Half of his family died of heart disease at a young age. The man was diagnosed with long QT syndrome type I, he was advised to take the maximum dose of atenolol and referred to the electrophysiology lab. Awaiting the completion of diagnostics and qualification for surgical treatment, he is wearing a defibrillator vest for most of the day, which, after detecting ventricular tachycardia, will discharge.
One morning Krystian felt a strange weakness in his left hand. He called the cardiology clinic where he was recieved treatment and asked if it had something to do with his heart. The cardiologist on call, after the remote transmission of the vest recording, verified that the man does not have arrhythmia and the device did not perform any discharges. He suggests presenting to the nearest hospital emergency department.
Meanwhile, Krystian's wife entered her husband's symptoms into an online algorithm identifying the potential cause of the ailment. Suddenly, she turned pale - the application stated that the most likely diagnosis was a stroke. The platform redirected her phone to the emergency number, and the automated dispatch system analyzed the reported symptoms, location and Krystian's electronic health record. The system ordered a neurological emergency team.
A minute later, a new entry appeared in the Paramedic app and someone knocked on the man's apartment door shortly after. It's Marcin, a nursing student, who registered in the database of volunteer paramedics and is ready to provide first aid while waiting for the ambulance. If necessary, he will also ask for the delivery of an AED by one of the hundreds of drones flying over Warsaw.
Ten minutes later, the emergency medical team arrives with an ambulance equipped with a CT scanner and a prepared alteplase bolus. Unfortunately, after analyzing the images by an artificial intelligence, the algorithm confirmed a hemorrhagic focus located in the right frontal lobe, and therefore the patient does not qualify for pre-hospital thrombolytic treatment.
During the transport to the nearest neurosurgical center, Krystian's face is being observed by EDGE - an artificial intelligence equipped with a camera that analyzes facial expressions and informs the paramedics in the event of deterioration, even before the RPM system reports dangerous trends in the monitored critical parameters.
A fast lane for Krystian was prepared in the hospital. The nurses at the ED collected blood for tests. The patient travels quickly to the radiology lab, where he has an angio-MRI. Behind the tinted glass, the images are looked at together by a radiologist, neurosurgeon and AI algorithm, trained in recognizing neurological diseases, thanks to machine learning. At the same time, the two doctors and the program indicate a massive hematoma near the temporal lobe. A ruptured middle cerebral artery aneurysm is visible right next to it.
The decision is made on a hybrid procedure - neurosurgical decompressive craniectomy and endovascular embolization of the aneurysm.
The anesthesiologist has already received universal artificial blood and activated the robot performing automatic intubation. The surgery can be started.
Less than an hour from the onset of symptoms, the patient ends up on the operating table.
Thanks to the efficient action, Krystian returns home after three days, without any neurological defects.
Reality or fiction?
Sounds futuristic, doesn't it? However, it seems like a similar story may happen in the near future. All these technological innovations are real and already existing. Part of them are currently being improved and implemented for clinical use. Some are already saving lives.
Artificial intelligence (AI) models are likely to play the biggest role, especially those based on machine learning. Doctors learn to recognize and treat diseases by working with patients and gradually gaining experience. Similarly, by processing millions of data, algorithms learn to categorize various findings adequately.
Currently, new technologies are most widely used in radiology (analysis of radiographs, CT, MRI), dermatology (diagnostics of the causes of skin lesions in dermatoscopic images), pathomorphology (histological staining examination) and cardiology (analysis of ECG records). The COVID-19 pandemic showed that many visits can take place via telemedicine tools (phone, video call, chat), and in the case of alarming symptoms, the patient can be directed to the right place (primary care, ambulatory care, ED).
Emergency medicine draws on all of this, integrating innovations from various fields of medicine.
Softwares predicting potential diseases are becoming more and more common. At the Kings County Hospital Center in New York City and the Parkland Memorial Hospital in Dallas, for a long time, the triage system has been provided by electronic stands at which patients indicate their ailments.
Maybe futuristic visions of tomorrow's medicine are nothing, compared to the real upcoming breakthrough in the emergency procedures? Time will tell.
● Defibrillator vest
● Smartwatch for cardiovascular incidents detection
● Diagnosis of SCA on the basis of a phone call - AI4EMSsoftware
● Disease prediction based on symptoms
● Paramedic app - notifying volunteer paramedics whenhelp is needed
● StayingAlive app - a map of the nearest AEDs
● AED transport drones in the ERC Guidelines 2021
● AED transport drones in Poland
● Blood and AED transporting drones
● CT in the ambulance
● AI in the ambulance - EDGE system
● Monitoring of the vital signs
● Detection of sepsis based on vital signs
● Brain aneurysms diagnostics with angio-MRI
● AI algorithm analyzing chest CT scans
● Algorithm analyzing fractures in X-ray images
● Synthetic blood
● Intubating robot
● Automated triage systems
● Overview of AI technology in emergency medicine