Cardiogenic Shock Diagnosis and Management: Improving Accuracy

Thousands of people experience cardiogenic shock every year. What can make treating shock difficult is that the current management recommendations are largely empirical or based on the results of the few trials adequately powered to detect differences in clinical outcomes. Many different issues can cause it. For example, blood loss as a result of injury can lead to shock. Cardiogenic shock is a complex pathology that verifies when the blood is not circulating correctly.

The variation between different conditions and shock patients can make treating it difficult. This post will look at some of these complications and a new tool helping to overcome these challenges.

The Challenges of Treating Shock

Let’s say a patient suffers cardiogenic shock from a heart attack. The symptoms of cardiogenic shock include low urine production (<30 mL/hour), cool arms and legs, and an altered level of consciousness. Once the doctor has given a diagnosis of shock, taking quick action is critical. Mortality rates for shock are high. Many survivors also experience complications.

Catecholamine is generally a standard part of cardiogenic shock treatment, but many other options exist. A doctor might order several types of medical devices and drugs. There may also come times when the doctor decides to wind down different treatments.

The trouble is that shock patients might respond differently to different treatments. They may also respond in different ways to treatments being altered or decreased. These decisions are critical, but the standard guidelines are often vague. It can often lead to suboptimal treatment.

It is these difficult decisions that lead to bad outcomes. The high fatality rate of shock, long stays in the hospital, and the need for re-admission. However, a new tool is being developed to help doctors make better decisions when treating shock patients.

A New Solution

Outcomes are often determined by decisions made during the management of shock. Once a physician makes a diagnosis of shock, so much can hinge on the prescribed treatments. Unfortunately, shock is a complex condition. Patients in similar situations may respond very differently to the same treatments.

This is where Altegos from Computational Life comes in to improve treatment for shock. Altegos is a software tool designed to simulate the outcomes from various approaches to the management of shock. The simulation can then guide the decisions of the physician.

The software can be fed various information about the situation. It can integrate with electronic health records and even read data from different monitoring devices. It can then build a digital twin of the patient. Using that digital twin, the software predicts the outcomes you can expect from various treatment options.

Altegos is more reliable than an AI-based system because it uses deterministic models. It is based on actual human physiology and the processes that occur during real incidences of shock management. With this powerful tool, doctors can make better decisions that will lead to better outcomes.

With improved treatment based on feedback from Altegos, hospitals could cut the fatality rate of shock patients. It can also reduce the average recovery time of patients and the number of patients who require re-admission. It could also help reduce medical costs.

Shock is difficult to manage, and conventional approaches often lead to bad outcomes. With a software tool like Altegos, this could change. This predictive tool could support physicians in providing better care that will save the lives of shock patients and cut costs.

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