Acutelines started in 2020 and is the world's first database with data of acutely ill people on this scale. The collection of data and biological samples is not dependent on the specific diagnosis of the patient, but on the degree of illness. This way the researchers want to understand which factors contribute to (fast) recognition and timely treatment of specific acute conditions, among other things.
It happens that a patient does not survive a pneumonia. Pneumonia can lead to sepsis, a strong reaction to an infection, such as a virus or bacteria that has entered the body, causing organ damage. Sepsis is a common condition in the emergency room and requires rapid and appropriate care. It is unknown why some patients' infections lead to sepsis and others get little ill from it. To understand this, research with a lot of data from large numbers of acutely ill patients is needed, say internists Acute Medicine Hjalmar Bouma and Jan ter Maaten, and Rijk Gans, chairman of the Centre for Acute Care at the UMCG. "As with sepsis, in many other acute diseases we do not understand well enough which person is at risk of deterioration, who exactly you should - and who should not - admit to hospital and what the long-term consequences are."
With some disorders, you can deteriorate very quickly, even if you are already in the emergency department. "Some patients recover quickly, while others become much sicker. How is this possible? We want to understand that difference between people", explains Ter Maaten. Some people suffer residual damage. In the emergency department, we want to know: which people should we admit immediately to limit damage, and which people can go home after treatment?" Gans adds: ''Yes, what you ultimately want to know is: how will they be doing in a year's time?"
According to the founders, we mainly know too little about the first hours of acutely ill patients. In the Acutelines biobank, they collect results of blood tests, passport photographs, heart rate, and many other parameters, even the composition of the hair, and the nurse's gut feeling are documented. With the patient's consent, data from before the admission, e.g. from the GP and the pharmacy, is also linked to this later on. Not only the known parameters such as blood pressure, heart rate and respiration, but also a certain protein in the blood, the variation in the heart rate or someone's background can be a predictor. It is often about finding that combination of parameters that provides the most information, the founders emphasise.
Of course, all that information has to be stored in an organised way. The databiobank was set up to efficiently collect relevant data and biological samples from large numbers of patients. Smart automation helps to process large quantities of data. Bouma explains enthusiastically: ''In fact, Acutelines consists of a large number of smaller databases that are linked to each other. The data is obtained via a digital link from the patient record, through questionnaires that patients fill in themselves on paper or on their smartphone, and because we collect extra data as part of the research. We have also created software that can temporarily store data from devices that measure patients' vital functions. If it turns out later that the bed was occupied by someone taking part in Acutelines, then the temporarily stored data will be permanently stored for future research.
Acutelines also uses Artificial Intelligence: they use this technology to build an algorithm based on the collected data. This helps the doctor decide in how he should act in order to achieve a successful outcome. Ter Maaten explains: ''An algorithm can be seen as a kind of calculation that enables the best possible outcome or decision, using the situation at that moment. This does not mean that the clinical view is no longer important; we include it in our data collection! We then hope to discover what it is, in that clinical view, that makes you decide that one patient should be admitted and the other is allowed to go home. Is it the respiration of the patient, the colour of the face? We want to understand exactly what it is and be able to put it into statistics.”
Ultimately, it's about prevention: preventing unnecessary residual organ damage, unnecessary death, or unnecessary admissions. But the databiobank is also of benefit to patients now. Through cooperation with companies, Acutelines researchers can test new devices. Bouma: 'An example is a watch with which one can continuously measure the amount of oxygen in the blood. We work together with the manufacturer to ensure that the data from the watch goes straight into the databiobank. This is of immediate benefit to the patient in the emergency room and during the subsequent admission, because you notice it sooner if something goes wrong."
In the UMCG, much experience has been gained with medical biobanks such as Lifelines, TRAILS, TransplantLines, and Cardiolines. Therefore, the hospital already had a lot of experience with protocols for processing the samples that are collected in a databank. But the application in the emergency room is still unique in the world. Ter Maaten: 'You have to see it as result of the fairly recent development of Emergency Medicine and Acute Internal Medicine as medical specialities. When these specialised doctors started working in the emergency room, the need for scientific research became clear.
Within Acutelines there is a steering committee, which is supervised by a manager, who is responsible for the day-to-day running of the project and who manages a large team of researchers, supported by developers. Self-managing teams of researchers with different backgrounds collect the data on the workfloor together with nurses and doctors in the emergency department from early in the morning until late at night. Acutelines is embedded within the Centre for Acute Care and is accountable to the board. The organisation of Acutelines forms a solid basis for future expansion of research into patient groups with acute conditions from all medical specialisms.
