Prediction bias in spirometry reference equations can arise from combining equations for different age groups, rounding age or height to integers or using self-reported height. To assess the bias arising from these sources, the fit of 13 prediction equations was tested against the Global Lungs Initiative (GLI) dataset using spirometric data from 55,136 healthy Caucasians (54% female). The effects on predicted values of using whole-year age versus decimal age, and of a 1% bias in height, were quantified. In children, the prediction bias relative to GLI ranged from -22% to +17%. Switching equations at 18 yrs of age led to biases of between -846 (-14%) and +1,309 (+38%) mL. Using age in whole years rather than decimal age introduced biases from -8% to +7%, whereas a 1% overestimation of height introduced bias that ranged from +1% to +40%. Bias was greatest in children and adolescents, and in short elderly subjects. Using a single spirometry equation applicable across all ages and populations reduces prediction bias. Measuring and recording age and height accurately are also essential if bias is to be minimised.

译文

肺活量测定参考方程中的预测偏差可以通过组合不同年龄组的方程,将年龄或身高四舍五入为整数或使用自我报告的身高而产生。为了评估这些来源产生的偏差,使用来自55,136名健康高加索人 (54% 名女性) 的肺活量测量数据,针对全球肺部倡议 (GLI) 数据集测试了13个预测方程的拟合度。量化了使用全年年龄与十进制年龄以及身高1% 偏差对预测值的影响。在儿童中,相对于GLI的预测偏差范围为-22% 至 + 17%。在18岁时切换方程导致-846 (-14%) 和 + 1,309 (+ 38%) mL之间的偏差。使用整年的年龄而不是十进制年龄会导致从-8% 到 + 7% 的偏差,而对身高的1% 高估会导致从 + 1% 到 + 40% 的偏差。偏见在儿童和青少年以及矮小的老年人中最大。使用适用于所有年龄和人群的单个肺活量测定方程可以减少预测偏差。如果要最小化偏差,准确测量和记录年龄和身高也是必不可少的。

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