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http://dx.doi.org/10.1007/s00134-018-5139-3 | DOI Listing |
Curr Opin Crit Care
January 2025
Department of Critical Care Medicine.
Purpose Of Review: Neuroprognostication after acute brain injury (ABI) is complex. In this review, we examine the threats to accurate neuroprognostication, discuss strategies to mitigate the self-fulfilling prophecy, and how to approach the indeterminate prognosis.
Recent Findings: The goal of neuroprognostication is to provide a timely and accurate prediction of a patient's neurologic outcome so treatment can proceed in accordance with a patient's values and preferences.
Curr Opin Crit Care
January 2025
Spaulding Rehabilitation Hospital, Department of Physical Medicine and Rehabilitation, Charlestown.
Purpose Of Review: To increase knowledge of the natural history of recovery and long-term outcome following severe traumatic brain injury (sTBI).
Recent Findings: Recovery of consciousness and complex behaviors that presage subsequent functional recovery frequently occurs well beyond the first 7 days after injury, which is typically the time period widely used in the ICU for prognostic decision-making and establishing goals of care for. Similarly, recovery of functional independence occurs between 1 and 10 years postinjury in a substantial proportion of patients who do not recover command-following during the acute hospitalization.
Objectives: Intensive care unit (ICU) clinicians stop antibiotics more often, with a negative infection: point-of-care test (PCR-POCT). Simulated cases of diagnostic uncertainty regarding infection resolution led clinicians to choose options such as procalcitonin (PCT) and/or PCR-POCTs +/- de-escalation to aid stop decisions. We hypothesised that a direct infection indicator, PCR-POCT, would influence stop judgements more than indirect PCT.
View Article and Find Full Text PDFBMJ Open
December 2024
Health Services and Systems Research, Duke-NUS Medical School, Singapore.
Introduction: As surgical accessibility improves, the incidence of postoperative complications is expected to rise. The implementation of a precise and objective risk stratification tool holds the potential to mitigate these complications by early identification of high-risk patients. Moreover, it could address the escalating costs from resource misallocation.
View Article and Find Full Text PDFJ Med Internet Res
January 2025
ETH Zurich, Zurich, Switzerland.
Background: The escalating global scarcity of skilled health care professionals is a critical concern, further exacerbated by rising stress levels and clinician burnout rates. Artificial intelligence (AI) has surfaced as a potential resource to alleviate these challenges. Nevertheless, it is not taken for granted that AI will inevitably augment human performance, as ill-designed systems may inadvertently impose new burdens on health care workers, and implementation may be challenging.
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