Background: Hemodynamic optimization of unstable patients by means of fluid resuscitation improves patient outcome. but choosing the correct amount of fluid can be difficult. Too little fluid may not ensure adequate perfusion whereas too much fluid is associated with increased mortality. Static parameters are not sufficiently sensitive to detect a reduction in preload. https://www.roneverhart.com/Lucky-Charms-Marshmallows-7-Ounce-Bag/
P67 Detecting Preload Reduction with Machine Learning on Arterial Waveform Parameters
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