Critical care : the official journal of the Critical Care Forum
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A diagnosis of ARDS serves as a pretext for several perilous clinical practices. Clinical trials demonstrated that tidal volume 12 ml/kg increases patient mortality, but 6 ml/kg has not proven superior to 11 ml/kg or anything in between. Present guidelines recommend 4 ml/kg, which foments severe air hunger, leading to prescription of hazardous (yet ineffective) sedatives, narcotics and paralytic agents. ⋯ Each of three pillars of the prevailing Berlin definition is extremely flimsy and the source of confusion and unscientific practices. For doctors at the bedside, none of the revisions have enhanced patient care over that using the original 1967 description of Ashbaugh and colleagues. Bedside doctors are better advised to diagnose ARDS on the basis of pattern recognition and instead concentrate their vigilance on resolving the numerous hidden dangers that follow inevitably once a diagnosis has been made.
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Heat stroke (HS) is a life-threatening systemic disease characterized by an elevated core body temperature of more than 40 ℃ and subsequent multiple organ dysfunction syndrome. With the growing frequency of global heatwaves, the incidence rate of HS has increased significantly, which has caused a huge burden on people's lives and health. Liver injury is a well-documented complication of HS and usually constitutes the direct cause of patient death. ⋯ In addition to the comprehensive effect of systemic factors such as heat cytotoxicity, coagulopathy, and systemic inflammatory response syndrome, excessive hepatocyte cell pyroptosis, dysfunction of Kupffer cells, abnormal expression of heat shock protein expression, and other factors are also involved in the pathogenesis of HS-induced liver injury. Furthermore, we have also established the current therapeutic strategies for HS-induced liver injury. Our study is of great significance in promoting the understanding of the pathogenesis and treatment of HS-induced liver injury.
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Cardiac arrest (CA) is a major cause of morbidity and mortality frequently associated with neurological and systemic involvement. Supportive therapeutic strategies such as mechanical ventilation, hemodynamic settings, and temperature management have been implemented in the last decade in post-CA patients, aiming at protecting both the brain and the lungs and preventing systemic complications. A lung-protective ventilator strategy is currently the standard of care among critically ill patients since it demonstrated beneficial effects on mortality, ventilator-free days, and other clinical outcomes. ⋯ The management of hemodynamics and temperature in post-CA patients represents critical steps for obtaining clinical improvement. The aim of this review is to summarize and discuss current evidence on how to optimize mechanical ventilation in post-CA patients. We will provide ten tips and key insights to apply a lung-protective ventilator strategy in post-CA patients, considering the interplay between the lungs and other systems and organs, including the brain.
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Acute kidney injury (AKI) is common in the critically ill. Inadequate renal medullary tissue oxygenation has been linked to its pathogenesis. Moreover, renal medullary tissue hypoxia can be detected before biochemical evidence of AKI in large mammalian models of critical illness. ⋯ Clinical studies have shown that bladder PuO2 correlates with cardiac output, and that it increases in response to elevated cardiopulmonary bypass (CPB) flow and mean arterial pressure. Clinical observational studies in patients undergoing cardiac surgery involving CPB have shown that bladder PuO2 has prognostic value for subsequent AKI. Thus, continuous bladder PuO2 holds promise as a new clinical tool for monitoring the adequacy of renal medullary oxygenation, with its implications for the recognition and prevention of medullary hypoxia and thus AKI.
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Machine learning algorithms have recently been developed to enable the automatic and real-time echocardiographic assessment of left ventricular ejection fraction (LVEF) and have not been evaluated in critically ill patients. ⋯ Machine learning-enabled real-time measurements of LVEF were strongly correlated with manual measurements obtained by experts. The accuracy of real-time LVEF measurements was excellent, and the precision was fair. The reproducibility of LVEF measurements was better with the machine learning system. The specificity to detect left ventricular dysfunction was excellent both for experts and for novices, whereas the sensitivity could be improved.