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Background <p>Mid-arm circumference (AC) is typically measured in person to determine cuff size for ambulatory blood pressure monitoring (ABPM). Our objective was to develop a model to predict cuff size using electronic health record (EHR) data to enable virtual ABPM programs.</p> Methods <p>We developed a prediction model for youth 3–21&#xa0;years in the National Health and Nutrition Examination Survey. Using linear regression, we considered piecewise and polynomial effects of age, sex, height, and weight as predictors of AC. We selected the model with the lowest bootstrapped root-mean-square error (RMSE) and predicted residual error sum of squares with leave-one-out cross-validation. We validated the model in pediatric hypertension clinics at an academic medical center.</p> Results <p>Based on 34,517 youth in the derivation cohort (median 12&#xa0;years (25th, 75th percentiles: 7, 16), 49.0% female, 16.6% obesity), the final model included age, age<sup>2</sup>, sex, height, weight, weight<sup>2</sup>, weight<sup>3</sup>, and all possible interactions between age and height and between age and weight (adjusted <i>R</i><sup>2</sup>, 0.97; RMSE, 1.20). In the external validation cohort of 107 youth (median 14&#xa0;years (25th, 75th percentiles: 10, 17), 35.5% female, 61.7% obesity), observed and predicted AC were highly concordant (⍴<sub>c</sub>, 0.94) with mean bias of −0.5&#xa0;cm (95% limits of agreement, −5.2; 4.1). Overall agreement for the correct cuff size was 87.5% in the derivation cohort (weighted κ, 0.92) and 83.2% in the validation cohort (weighted κ, 0.90).</p> Conclusions <p>We found substantial agreement between observed and predicted AC using basic EHR data. This model may facilitate ABPM when in-person visits are not feasible.</p> Graphical abstract <p></p>

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Development and validation of a cuff size prediction model for pediatric blood pressure measurement outside the office

  • 期刊论文

  • 发表日期：

    2026年5月28日

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  • James T. Nugent,
  • Victoria Cueto,
  • Hugh Medvecky,
  • Morgan Harper,
  • Varshini Batti,
  • Jason H. Greenberg,
  • Veronika Shabanova

摘要

Background

Mid-arm circumference (AC) is typically measured in person to determine cuff size for ambulatory blood pressure monitoring (ABPM). Our objective was to develop a model to predict cuff size using electronic health record (EHR) data to enable virtual ABPM programs.

Methods

We developed a prediction model for youth 3–21 years in the National Health and Nutrition Examination Survey. Using linear regression, we considered piecewise and polynomial effects of age, sex, height, and weight as predictors of AC. We selected the model with the lowest bootstrapped root-mean-square error (RMSE) and predicted residual error sum of squares with leave-one-out cross-validation. We validated the model in pediatric hypertension clinics at an academic medical center.

Results

Based on 34,517 youth in the derivation cohort (median 12 years (25th, 75th percentiles: 7, 16), 49.0% female, 16.6% obesity), the final model included age, age2, sex, height, weight, weight2, weight3, and all possible interactions between age and height and between age and weight (adjusted R2, 0.97; RMSE, 1.20). In the external validation cohort of 107 youth (median 14 years (25th, 75th percentiles: 10, 17), 35.5% female, 61.7% obesity), observed and predicted AC were highly concordant (⍴c, 0.94) with mean bias of −0.5 cm (95% limits of agreement, −5.2; 4.1). Overall agreement for the correct cuff size was 87.5% in the derivation cohort (weighted κ, 0.92) and 83.2% in the validation cohort (weighted κ, 0.90).

Conclusions

We found substantial agreement between observed and predicted AC using basic EHR data. This model may facilitate ABPM when in-person visits are not feasible.

Graphical abstract