Presenter Information

Kyle Burk, University of Utah

Location

Orbital ATK Conference Center

Start Date

5-7-2018 9:10 AM

Description

Introduction: The oxyhemoglobin dissociation curve describes the relationship between the partial pressure of oxygen and the percent of hemoglobin saturated with oxygen. This relationship is a sigmoidal shaped curve. The oxyhemoglobin dissociation curve varies from patient to patient. If patient variability could be determined patient specific oxygen flow rates could be delivered. We have developed a model for characterizing patient specific variations in SpO2. Our model predicts saturation by generating a patient-specific oxyhemoglobin dissociation curve. The purpose of this study was to determine the effectiveness of our patient-specific model. Methods: We Probed SpO2 level at various oxygen inhalation amounts to provide input to our model. We linearized the relationship between SpO2 and EtO2 for each participant. We then fit a line to those linearized data points. We used model fit error techniques to show the ability of the model to fit volunteer and patient SpO2. Fit results were generated by using the fitted patient specific curve shift to estimate oxygen concentrations. Fit errors were used to assess the model’s ability to fit SpO2 and to make an accurate patient specific oxyhemoglobin dissociation curve. Results: Thirty subjects participated in our volunteer study. The nominal average line is quite close to the standard curve. The cumulative density plot of the model fit error for the entire data set in our volunteer study and the average for each volunteer had greater accuracy than the standard fit. Sixty patients participated in our clinical trial. The nominal average line is quite different than the standard curve. The cumulative density plot of the model fit error for the entire data set in our clinical study and the average for each patient both had greater accuracy than the standard fit. Discussion: This study has shown that our model is able to fit patient saturation values with higher accuracy compared to using the standard oxyhemoglobin dissociation curve. We have also shown that the variability of the ODC from patient to patient is quite large, making predicting patient saturation quite difficult. We have developed and tested a model for fitting the oxyhemoglobin dissociation curve to patients. We have shown improved fit when compared to the standard oxyhemoglobin dissociation curve. This model could potentially be used to predict time to desaturation specific to a patient.

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Session 1

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May 7th, 9:10 AM

A Model for Determining a Patient-specific Oxyhemoglobin Dissociation Curve

Orbital ATK Conference Center

Introduction: The oxyhemoglobin dissociation curve describes the relationship between the partial pressure of oxygen and the percent of hemoglobin saturated with oxygen. This relationship is a sigmoidal shaped curve. The oxyhemoglobin dissociation curve varies from patient to patient. If patient variability could be determined patient specific oxygen flow rates could be delivered. We have developed a model for characterizing patient specific variations in SpO2. Our model predicts saturation by generating a patient-specific oxyhemoglobin dissociation curve. The purpose of this study was to determine the effectiveness of our patient-specific model. Methods: We Probed SpO2 level at various oxygen inhalation amounts to provide input to our model. We linearized the relationship between SpO2 and EtO2 for each participant. We then fit a line to those linearized data points. We used model fit error techniques to show the ability of the model to fit volunteer and patient SpO2. Fit results were generated by using the fitted patient specific curve shift to estimate oxygen concentrations. Fit errors were used to assess the model’s ability to fit SpO2 and to make an accurate patient specific oxyhemoglobin dissociation curve. Results: Thirty subjects participated in our volunteer study. The nominal average line is quite close to the standard curve. The cumulative density plot of the model fit error for the entire data set in our volunteer study and the average for each volunteer had greater accuracy than the standard fit. Sixty patients participated in our clinical trial. The nominal average line is quite different than the standard curve. The cumulative density plot of the model fit error for the entire data set in our clinical study and the average for each patient both had greater accuracy than the standard fit. Discussion: This study has shown that our model is able to fit patient saturation values with higher accuracy compared to using the standard oxyhemoglobin dissociation curve. We have also shown that the variability of the ODC from patient to patient is quite large, making predicting patient saturation quite difficult. We have developed and tested a model for fitting the oxyhemoglobin dissociation curve to patients. We have shown improved fit when compared to the standard oxyhemoglobin dissociation curve. This model could potentially be used to predict time to desaturation specific to a patient.