[dipl] Perustieteiden korkeakoulu / SCI

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Browsing [dipl] Perustieteiden korkeakoulu / SCI by Author "Aalto, Roosa"

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  • Plethysmographic waveform-based dynamic preload indices in predicting fluid responsiveness
    (2023-03-20) Aalto, Roosa
     Perustieteiden korkeakoulu | Master's thesis
    Evaluating the fluid responsiveness of a patient before administrating fluids is vital, since both restrictive and liberal protocols of fluid therapy are associated with increased rate of complications. Mechanical ventilation-related cardiopulmonary interactions induce changes in pulse oximeter plethysmographic waveform that can predict cardiac output response to changes in preload, i.e., fluid responsiveness. The aim of this thesis was to evaluate the reliability of non-invasive plethysmography-based dynamic parameters compared to conventional invasive arterial pressure parameters and identify and find solutions to current challenges regarding dynamic parameters. The data was collected from ten domestic swine during blood withdrawal (450 ml) and fluid autotransfusion (450 ml). Arterial and plethysmographic waveforms were recorded simultaneously, and dynamic parameters were computed from both waveforms. Main interests were pleth amplitude variation (PAV) and pleth variability index (PVI) which were compared to pulse pressure variation (PPV) in arterial blood pressure waveform. Additionally, the influence of ventilator settings to dynamic parameters were studied. Blood volume reduction of 15-20% induced significant increases in PAV, PVI and PPV. Fluid infusion returned the parameters back to baseline. PAV had strong correlation with PVI (r=0.95) and PPV (r=0.89). Other dynamic parameters performed notably worse. Ventilator parameters, particularly respiratory rate, lung compliance and ventilator pressures, were found to have a significant effect on the magnitude of the parameters. Dynamic parameters were not able to predict fluid responsiveness in spontaneously breathing humans. PAV and PVI have potential to predict fluid responsiveness of a patient noninvasively. However, they must be interpreted carefully due to inherent limitations of plethysmographic waveform-based analysis such as low perfusion index, arrhythmias, spontaneous breathing and varying ventilator settings which are all common in ICU patients. Their performance could be improved by introducing complementary information from standard hemodynamics and ventilator settings into the algorithm.