PDF(Pubmed)
Abstract：
UNASSIGNED: Questions about the accuracy of pulse oximeters in measuring arterial oxygen saturation ( SpO 2 ) in individuals with darker skin pigmentation have resurfaced since the COVID-19 pandemic. This requires investigation to improve patient safety, clinical decision making, and research.
UNASSIGNED: We aim to use computational modeling to identify the potential causes of inaccuracy in SpO 2 measurement in individuals with dark skin and suggest practical solutions to minimize bias.
UNASSIGNED: An in silico model of the human finger was developed to explore how changing melanin concentration and arterial oxygen saturation ( SaO 2 ) affect pulse oximeter calibration algorithms using the Monte Carlo (MC) technique. The model generates calibration curves for Fitzpatrick skin types I, IV, and VI and an SaO 2 range between 70% and 100% in transmittance mode. SpO 2 was derived by inputting the computed ratio of ratios for light and dark skin into a widely used calibration algorithm equation to calculate bias ( SpO 2 - SaO 2 ). These were validated against an experimental study to suggest the validity of the Monte Carlo model. Further work included applying different multiplication factors to adjust the moderate and dark skin calibration curves relative to light skin.
UNASSIGNED: Moderate and dark skin calibration curve equations were different from light skin, suggesting that a single algorithm may not be suitable for all skin types due to the varying behavior of light in different epidermal melanin concentrations, especially at 660 nm. The ratio between the mean bias in White and Black subjects in the cohort study was 6.6 and 5.47 for light and dark skin, respectively, from the Monte Carlo model. A linear multiplication factor of 1.23 and exponential factor of 1.8 were applied to moderate and dark skin calibration curves, resulting in similar alignment.
UNASSIGNED: This study underpins the careful re-assessment of pulse oximeter designs to minimize bias in SpO 2 measurements across diverse populations.
UNASSIGNED: We aim to use computational modeling to identify the potential causes of inaccuracy in SpO 2 measurement in individuals with dark skin and suggest practical solutions to minimize bias.
UNASSIGNED: An in silico model of the human finger was developed to explore how changing melanin concentration and arterial oxygen saturation ( SaO 2 ) affect pulse oximeter calibration algorithms using the Monte Carlo (MC) technique. The model generates calibration curves for Fitzpatrick skin types I, IV, and VI and an SaO 2 range between 70% and 100% in transmittance mode. SpO 2 was derived by inputting the computed ratio of ratios for light and dark skin into a widely used calibration algorithm equation to calculate bias ( SpO 2 - SaO 2 ). These were validated against an experimental study to suggest the validity of the Monte Carlo model. Further work included applying different multiplication factors to adjust the moderate and dark skin calibration curves relative to light skin.
UNASSIGNED: Moderate and dark skin calibration curve equations were different from light skin, suggesting that a single algorithm may not be suitable for all skin types due to the varying behavior of light in different epidermal melanin concentrations, especially at 660 nm. The ratio between the mean bias in White and Black subjects in the cohort study was 6.6 and 5.47 for light and dark skin, respectively, from the Monte Carlo model. A linear multiplication factor of 1.23 and exponential factor of 1.8 were applied to moderate and dark skin calibration curves, resulting in similar alignment.
UNASSIGNED: This study underpins the careful re-assessment of pulse oximeter designs to minimize bias in SpO 2 measurements across diverse populations.
摘要：
■自COVID-19大流行以来，关于脉搏血氧计在测量皮肤色素沉着较深的个体的动脉血氧饱和度（SpO2）的准确性的问题再次出现。这需要进行调查以提高患者的安全性，临床决策，和研究。
■我们旨在使用计算建模来识别深色皮肤个体中SpO2测量不准确的潜在原因，并提出实用的解决方案以最大程度地减少偏差。
■开发了人类手指的计算机模拟模型，以探索改变黑色素浓度和动脉血氧饱和度（SaO2）如何影响使用蒙特卡洛（MC）技术的脉搏血氧计校准算法。该模型为FitzpatrickI型皮肤生成校正曲线，IV,和VI，SaO2在透射率模式下的范围在70%和100%之间。通过将计算的浅色和深色皮肤的比率比率输入到广泛使用的校准算法方程中以计算偏差（SpO2-SaO2）来得出SpO2。这些通过实验研究进行了验证，以表明蒙特卡洛模型的有效性。进一步的工作包括应用不同的倍增因子来调整相对于浅色皮肤的中等和深色皮肤校准曲线。
■中度和深色皮肤校准曲线方程与浅色皮肤不同，这表明，由于不同表皮黑色素浓度下的光行为变化，单一算法可能不适合所有皮肤类型，尤其是在660nm。在队列研究中，白种人和黑种人对浅色和深色皮肤的平均偏倚比为6.6和5.47，分别,来自蒙特卡洛模型。将1.23的线性倍增因子和1.8的指数因子应用于中度和深色皮肤校准曲线，导致类似的对齐。
■这项研究支持对脉搏血氧计设计进行仔细的重新评估，以最大程度地减少不同人群的SpO2测量偏差。
■我们旨在使用计算建模来识别深色皮肤个体中SpO2测量不准确的潜在原因，并提出实用的解决方案以最大程度地减少偏差。
■开发了人类手指的计算机模拟模型，以探索改变黑色素浓度和动脉血氧饱和度（SaO2）如何影响使用蒙特卡洛（MC）技术的脉搏血氧计校准算法。该模型为FitzpatrickI型皮肤生成校正曲线，IV,和VI，SaO2在透射率模式下的范围在70%和100%之间。通过将计算的浅色和深色皮肤的比率比率输入到广泛使用的校准算法方程中以计算偏差（SpO2-SaO2）来得出SpO2。这些通过实验研究进行了验证，以表明蒙特卡洛模型的有效性。进一步的工作包括应用不同的倍增因子来调整相对于浅色皮肤的中等和深色皮肤校准曲线。
■中度和深色皮肤校准曲线方程与浅色皮肤不同，这表明，由于不同表皮黑色素浓度下的光行为变化，单一算法可能不适合所有皮肤类型，尤其是在660nm。在队列研究中，白种人和黑种人对浅色和深色皮肤的平均偏倚比为6.6和5.47，分别,来自蒙特卡洛模型。将1.23的线性倍增因子和1.8的指数因子应用于中度和深色皮肤校准曲线，导致类似的对齐。
■这项研究支持对脉搏血氧计设计进行仔细的重新评估，以最大程度地减少不同人群的SpO2测量偏差。
