CalmWave Blog

Physiologic Incidents Over Alarms

Authored by: Dinesh Rai, MD

 

Vital signs are crucial in evaluating a patient’s health status in clinical settings. Blood pressure and heart rate reflect the patient’s hemodynamic stability, while respiratory rate and SpO2 provide insight into pulmonary function. The vital signs monitor is pivotal in determining a patient’s physiology and can play a significant role in life-or-death situations. However, it is essential to note that vital signs only offer a limited view of the patient’s overall health and should not be relied upon as the sole source of information.

 

The current state of vitals signs monitors

 

Vital sign monitor alarms are set off based on predefined threshold values, but these values may not always apply to the specific patient and their medical history. For instance, a patient with a history of low blood pressure may trigger a threshold alarm indicating a critical change in their vital signs even though that blood pressure reading may be normal for them. Conversely, for a patient with a history of hypertension, a normal blood pressure reading could be a sign of shock, especially if accompanied by other symptoms such as rapid heart rate or dizziness. Given that current alarm thresholds are ‘one-size-fits-all,’ neither of these critical conditions would’ve been caught, potentially leading to serious medical outcomes for the patients involved. 

 

Shifting focus to physiologic incidents

 

In order to provide efficient and effective patient care, healthcare providers must go beyond just monitoring single-parameter and single-moment vital signs and also focus on Physiologic Incidents (PIs), defined here as combinations of various factors, including multiple vital signs and their trends, laboratory values, physical exam findings, and patient-specific data. Some examples of PIs already provide valuable information to medical teams. For instance, the shock index and the modified shock index are simple calculations of heart rate and blood pressure that can predict the risk of morbidity and mortality in cases of potential shock. Another example is the cardiac index, which assesses a patient’s cardiovascular efficiency by measuring cardiac output to body surface area. Some scoring systems use parameters that do not involve vital signs. The Glasgow Coma Score is one example that assesses a patient’s level of consciousness. Changes in the patient’s level of consciousness, skin color, temperature, and urine output can provide critical information about their hydration status, oxygenation, and overall health. Therefore, it is crucial for healthcare providers to consider PIs in addition to single-parameter vital signs in order to provide accurate and timely patient care. Healthcare teams can make more informed decisions and improve patient outcomes by considering multiple factors.

 

Why PIs are crucial to patient monitoring and outcomes

 

Several medical conditions highlight the importance of monitoring trends in vital signs via PIs. For instance, in chronic obstructive pulmonary disease cases, a gradual increase in baseline heart rate can predict increased mortality. Similarly, in hypothyroidism, a gradual decrease in heart rate and a compensatory increase in blood pressure may occur. Septic shock is a life-threatening medical emergency that occurs when an infection triggers a widespread inflammatory response. Early changes in vital signs can play a critical role in promptly diagnosing and treating sepsis. Early detection of these diseases can help with prevention and survival. In cases of vascular injury, the estimation of blood loss and transfusion requirements can be based on trends in heart rate, with a rate up to 100 indicating a loss of 15-30% and a rate over 140 indicating a loss of 40%

 

Early Warning Systems are thus essential for healthcare providers, because they consider multiple parameters including vital signs, medical history, current medications, and trends, to give a clearer picture of the patient’s health. Technological advancements have improved how hospitals can monitor patients in real time. The Modified Early Warning System is a composite score that can be calculated instantaneously, taking into account multiple vital signs and the patient’s level of alertness to determine the risk of deterioration. In the future, patient monitoring will involve a much more comprehensive range of data analysis, including the calculation of composite scores incorporating vital signs, medical history, and other relevant data. Fluid responsiveness, pain level, and mentation are often factors that are ignored by existing Early Warning Systems, but are critical when interpreting a patient’s clinical condition. Advancements in machine learning and data analytics will usher in new, more comprehensive, more specific, and more precise composite scores that will help healthcare providers deliver a whole new level of care.

 

Conclusion

 

It’s important to note that while vital signs play a crucial role in monitoring a patient’s physiological stability, they have certain limitations. Incorporation of physiologic incidents into the clinical assessment can improve patient outcomes. CalmWave has created the first AI-based technology that groups vitals signs and other patient characteristics into physiologic incidents. CalmWave’s Incident Patterns can provide early warning signs of severe medical conditions and give insight into the progression of the patient’s condition over time. This information, combined with snapshot vital signs, can generate a more comprehensive assessment of the patient’s health and help healthcare providers make better decisions regarding the patient’s care. Schedule a demo today at calmwave.ai to learn more about our cutting-edge Incident Pattern technology. 

 

Sources:

 

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Streeten, D. H., Anderson, G. H., Howland, T., Chiang, R., & Smulyan, H. (1988). Effects of thyroid function on blood pressure. recognition of hypothyroid hypertension. Hypertension, 11(1), 78–83. https://doi.org/10.1161/01.hyp.11.1.78

Torabi, M., Mirafzal, A., Rastegari, A., & Sadeghkhani, N. (2016). Association of Triage Time Shock Index, modified shock index, and age shock index with mortality in emergency severity index level 2 patients. The American Journal of Emergency Medicine, 34(1), 63–68. https://doi.org/10.1016/j.ajem.2015.09.014

Torabi, M., Moeinaddini, S., Mirafzal, A., Rastegari, A., & Sadeghkhani, N. (2016). Shock index, modified shock index, and age shock index for prediction of mortality in emergency severity index level 3. The American Journal of Emergency Medicine, 34(11), 2079–2083. https://doi.org/10.1016/j.ajem.2016.07.017 

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