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Edited by
David M. Greer, Boston University School of Medicine and Boston Medical Center,Neha S. Dangayach, Icahn School of Medicine at Mount Sinai and Mount Sinai Health System
Shared decision making (SDM) is a collaborative process that allows patients, or their surrogates, and clinicians to make healthcare decisions together, taking into account the best scientific evidence available, as well as the patient’s values, goals, and preferences. This definition of SDM proposed by the Informed Medical Decisions Foundation [1] was endorsed by the American College of Critical Care Medicine (ACCM) and the American Thoracic Society (ATS) (Figure 1.1). Informed medical decision making may be used synonymously with SDM.[2] Critically ill patients may be too unstable or otherwise incapacitated (e.g., due to intubation, sedation), and may not be able to speak for themselves.
Edited by
David M. Greer, Boston University School of Medicine and Boston Medical Center,Neha S. Dangayach, Icahn School of Medicine at Mount Sinai and Mount Sinai Health System
The first intensive care units (ICUs) were established in the 1950s in the wake of a pandemic in order to rescue patients with respiratory failure from certain death, launching an entirely new field referred to today as critical care medicine.[1] The mortality associated with critical illness has improved substantially over the decades,[2,3] and long-term patient- and family-centered outcomes have emerged as important new targets for intervention. The post-intensive care syndrome (PICS) was defined in 2012 [2] as a constellation of cognitive, mental health, or physical impairments that occur after treatment in the ICU and persist well beyond discharge (Figure 12.1). A key feature of PICS is that these symptoms lead to a quality of life that is worse than expected based on the patient’s initial acute illness.[2,4] PICS may be overlooked during or shortly after hospital discharge, when success means simply surviving a critical illness, but these symptoms may result in substantial long-term disability months or even years later in one-half or more patients with critical illness.[5]
Edited by
David M. Greer, Boston University School of Medicine and Boston Medical Center,Neha S. Dangayach, Icahn School of Medicine at Mount Sinai and Mount Sinai Health System
Edited by
David M. Greer, Boston University School of Medicine and Boston Medical Center,Neha S. Dangayach, Icahn School of Medicine at Mount Sinai and Mount Sinai Health System
Edited by
David M. Greer, Boston University School of Medicine and Boston Medical Center,Neha S. Dangayach, Icahn School of Medicine at Mount Sinai and Mount Sinai Health System
Edited by
David M. Greer, Boston University School of Medicine and Boston Medical Center,Neha S. Dangayach, Icahn School of Medicine at Mount Sinai and Mount Sinai Health System
Edited by
David M. Greer, Boston University School of Medicine and Boston Medical Center,Neha S. Dangayach, Icahn School of Medicine at Mount Sinai and Mount Sinai Health System
Edited by
David M. Greer, Boston University School of Medicine and Boston Medical Center,Neha S. Dangayach, Icahn School of Medicine at Mount Sinai and Mount Sinai Health System
Edited by
David M. Greer, Boston University School of Medicine and Boston Medical Center,Neha S. Dangayach, Icahn School of Medicine at Mount Sinai and Mount Sinai Health System
Neuroprognostication in patients with primary neurological diagnoses as well as in critically ill patients with concomitant neurological diagnoses is increasingly complex. With advances in critical care, the focus of the field is progressively moving from survivorship to improving patients' quality of life. This evidence-based resource provides an in-depth analysis of different aspects of prognostication in neurologically critically ill patients, covering how to gather the correct data and synthesize this information at the bedside. Delving into disease specific prognostication such as traumatic brain injury, acute ischemic stroke and delirium, guidance is provided for choosing management strategies based on overall perception of prognostication and shared decision making. Other topics covered include religious and legal issues, palliative care, chronic critical illness and new frontiers including machine learning and biomarkers usage. An online version of the book with expandable figures can be accessed on Cambridge Core, via the code printed inside the cover.
In this chapter the basic principles of neuromonitoring will be reviewed. Evidence-based applications, advantages, and disadvantages of various invasive and noninvasive techniques for monitoring intracranial pressure, brain tissue oxygenation, cerebral blood flow, brain metabolism, electroencephalography, and evoked potentials will be covered.