The injured monocyte: The link to chronic critical illness and mortality following injury
Joseph Cuschieri,
Lucy Kornblith,
Shibani Pati
et al.
Abstract:Background
This study aimed to understand the altered innate immune response in severely injured patients leading to chronic critical illness (CCI). Specifically, it focused on characterizing the monocyte populations and their correlation with CCI development and long-term complications.
Methods
Over a 3-year period, we monitored patients with severe injuries for up to 1-year post-injury. CCI was defined as an ICU stay exceeding 14 days with persistent … Show more
Purpose of review
For augmented intelligence (AI) tools to realize their potential, critical care clinicians must ensure they are designed to improve long-term outcomes. This overview is intended to align professionals with the state-of-the art of AI.
Recent findings
Many AI tools are undergoing preliminary assessment of their ability to support the care of survivors and their caregivers at multiple time points after intensive care unit (ICU) discharge. The domains being studied include early identification of deterioration (physiological, mental), management of impaired physical functioning, pain, sleep and sexual dysfunction, improving nutrition and communication, and screening and treatment of cognitive impairment and mental health disorders.
Several technologies are already being marketed and many more are in various stages of development. These technologies mostly still require clinical trials outcome testing. However, lacking a formal regulatory approval process, some are already in use.
Summary
Plans for long-term management of ICU survivors must account for the development of a holistic follow-up system that incorporates AI across multiple platforms. A tiered post-ICU screening program may be established wherein AI tools managed by ICU follow-up clinics provide appropriate assistance without human intervention in cases with less pathology and refer severe cases to expert treatment.
Purpose of review
For augmented intelligence (AI) tools to realize their potential, critical care clinicians must ensure they are designed to improve long-term outcomes. This overview is intended to align professionals with the state-of-the art of AI.
Recent findings
Many AI tools are undergoing preliminary assessment of their ability to support the care of survivors and their caregivers at multiple time points after intensive care unit (ICU) discharge. The domains being studied include early identification of deterioration (physiological, mental), management of impaired physical functioning, pain, sleep and sexual dysfunction, improving nutrition and communication, and screening and treatment of cognitive impairment and mental health disorders.
Several technologies are already being marketed and many more are in various stages of development. These technologies mostly still require clinical trials outcome testing. However, lacking a formal regulatory approval process, some are already in use.
Summary
Plans for long-term management of ICU survivors must account for the development of a holistic follow-up system that incorporates AI across multiple platforms. A tiered post-ICU screening program may be established wherein AI tools managed by ICU follow-up clinics provide appropriate assistance without human intervention in cases with less pathology and refer severe cases to expert treatment.
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