Background: The relationship between peripheral oxygen saturation (SpO2) and the inspired oxygen concentration is non-linear. SpO2 is frequently used as a dichotomized predictor, to manage this non-linearity. We propose the saturation virtual shunt (VS) as a transformation of SpO2 to a continuous linear variable to improve interpretation of disease severity within clinical prediction models.
Method: We calculate the saturation VS based on an empirically derived approximation formula between physiological VS and SpO2. We evaluated the utility of the saturation VS in a clinical study predicting the need for facility admission in children in a low resource health-care setting.
Results: The transformation was saturation VS = 68.864 × log10(103.711 - SpO2) - 52.110. The ability to predict hospital admission based on a dichotomized SpO2 produced an area under the receiver operating characteristic curve of 0.57, compared to 0.71 based on the untransformed SpO2 and saturation VS. However, the untransformed SpO2 demonstrated a lack of fit compared to the saturation VS (goodness-of-fit test p value < 0.0001 vs 0.098). The observed admission rates varied non-linearly with the untransformed SpO2 but varied linearly with the saturation VS.
Conclusion: The saturation VS estimates a continuous linearly interpretable disease severity based on SpO2 and improves clinical prediction.