An Equation to Estimate PICC Catheter Length in Very Low Birth Weight Infants

Peripherally inserted central catheters (PICCs) are essential for very low birth weight infants (VLBWIs), but optimal insertion depth remains challenging. Existing estimation methods often yield suboptimal accuracy. This study aimed to develop and validate anthropometric parameter-based formulas to predict lower extremity PICC insertion depth using the first popliteal crease as an anatomical landmark in VLBWI, seeking to improve first-attempt success rates and procedural safety.

A prospective study was conducted in a tertiary NICU, enrolling 329 VLBWIs who underwent lower limb PICC insertion between May 2023 and May 2024. Data collected included sex, target vein for catheterization, body weight, length, head circumference at insertion, and vertical distance from the puncture site to the first popliteal crease. Pearson correlation and linear regression analyses were performed to examine associations between anthropometric parameters and optimal catheter length. Univariate prediction formulas (weight-based, length-based, and head circumference-based models) and multivariate regression models were established. Bland-Altman analysis was used to validate model agreement.

Univariate regression analysis yielded the following: weight-based model: total insertion depth (cm) = [8.31 + (5 × body weight [kg])] ± PS-PTC distance, where "+" applies when the puncture site is distal to the popliteal crease and "-" applies when proximal; 8.31 is the regression intercept and five is the regression slope coefficient. Length-based model: total insertion depth (cm) = [1.13 + (0.35 × body length [cm])] ± PS-PTC distance; 1.13 is the intercept and 0.35 is the slope coefficient. Head circumference-based model: total insertion depth (cm) = [2.33 + (0.43 × head circumference [cm])] ± PS-PTC distance; 2.33 is the intercept and 0.43 is the slope coefficient. Multivariate regression analysis established four combination models, with Model IV (weight + length + head circumference) showing optimal performance.

Anthropometric parameter-based prediction formulas provide precise guidance for lower extremity PICC placement in VLBWI, enhancing placement success and safety. This approach supports individualized care and is especially valuable where ultrasound guidance is limited.