Losing your memory is a scary thing. It’s even more scary when you lose it as a complication from staying in the Intensive Care Unit (ICU). While mild confusion and disorientation after major medical interventions like surgery or mechanical ventilation are common, more research is showing that patients can also suffer from chronic memory loss due to noise levels and lack of rest in ICU settings.
Delirium vs. Dementia
Delirium is an acute confusional state characterized by changes in attention, awareness, and cognition that fluctuate over time. Delirium is a common complication after surgery, especially in older adults, and it is estimated to affect up to 50% of older adults undergoing surgery. Delirium is also common in the ICU, where it is estimated to affect up to 80% of patients. Families are often not concerned with their loved one’s new “confusion,” assuming it is a temporary situation. However, patients that experience ICU-induced delirium are at risk for not regaining their pre-admission cognitive level of function. This also means that these patients require additional unanticipated support once they return home. Imagine how tragic it is for fully active patients (and their families) to be admitted for surgery and return home not being able to function independently.
Dementia, on the other hand, is a chronic neurodegenerative disorder characterized by progressive cognitive decline. While delirium is an acute condition, dementia is a chronic condition that is not reversible. Surprisingly, surgery and ICU stays can also contribute to the development or worsening of dementia in older adults.
Noise, Noise, Noise
Studies show that exposure to high noise levels, including alarm noise, in ICUs can adversely affect the quality and duration of sleep for both patients and healthcare staff. This lack of sleep can increase the risk of developing delirium or even dementia in patients. Bedside staff are also affected, for the noise of alarms and IV pumps gets stuck in their heads, making it difficult to sleep when at home.
One study published in the Journal of Medical Systems found that higher levels of noise are significantly associated with a greater incidence of delirium in ICU patients. Another study published in the Society of Critical Care Medicine found that “excess noise has been associated with changes in physiological variables in critically ill patients.”
Patients are aware of the noise levels and their impact on not only recovery, but also their mental state while in the ICU. In an interview with The Atlantic, COVID survivor Kyle Mullicane (who spent more than a month in the ICU last year), states, “I would not wish the experience on my worst enemy.”
The prevalence of delirium and dementia after surgery and in the ICU highlights the importance for hospitals and physicians to be aware of the risk factors and consequences of these conditions.
AI For Good: Predicting and Reducing ICU Delirium
Artificial intelligence (AI) and machine learning has the potential to prevent and manage delirium and dementia in the ICU through:
- Predictive modeling: Machine learning algorithms can be trained on patient data to identify those at highest risk of developing delirium or dementia in the ICU. This can allow healthcare providers to take preventive measures before these conditions occur.
- Early detection: AI can be used to monitor patient behavior and vital signs to detect early signs of delirium or dementia. This can allow for prompt intervention and potentially prevent the condition from worsening.
- Optimizing Recovery: AI can be used to remediate factors that hinder patient recovery (such as alarm noise). Quieting non-actionable alarms can allow patients to rest and heal.
New research from Johns Hopkins shows that machine learning algorithms can predict which patients are at high risk for developing ICU delirium/dementia. The Hopkins team developed two models: a static model that uses a single snapshot of patient data, and a dynamic model that monitors patient data over the course of a patient’s stay. Hopkins reports that these prediction models have shown high performance when implemented into live clinical workflows at multiple hospitals.
While Hopkins’s AI models are useful for identifying ICU delirium/dementia, what about reducing the risk of these disorders in ICUs? CalmWave has an AI model that can help with that.
CalmWave: Optimizing Patient Recovery
Humans need sleep to recover, especially from traumatic events like surgery or systemic disease. But it’s disheartening that the ICU is not an optimal recovery spot due to the large amount of noise pollution coming mainly from medical alarming systems. CalmWave’s AI platform can reduce non-actionable alarms by up to 81%. Eighty. One. Percent. Think of how conducive it would be for recovery in an ICU with so little unnecessary noise.
By integrating data from numerous vital signs monitors that patients are already hooked up to, combined with electronic health record (EHR) data, CalmWave’s platform optimizes alarm thresholds for specific hospital wards and even each individual patient within two hours of admission. The platform also instructs clinicians on how to manually change alarm settings so that they are empowered to make the ICU a more peaceful place for patients to recover.
Overall, using CalmWave’s AI-based platform to optimize alarm thresholds has the potential to decrease patients’ risk of ICU delirium/dementia by quieting the ICU and providing patients with an optimal environment for rest, recovery, and healing. Schedule a demo today at calmwave.ai/demo to learn more.
Sources:
- Cavallazzi, et al., “Delirium in the ICU: an overview”
- Sangari et al., “Delirium Variability is Influenced by the Sound Environment (DEVISE Study): How Changes in the Intensive Care Unit soundscape affect delirium incidence”
- Peterson, “Alarms, Noise, and Delirium in the ICU”
- Zhang, “What Life Is Like After Being Taken Off a Ventilator”