Factors predictive of Ponseti casting for treating clubfoot: analysis of Bayesian Poisson regression model

Clubfoot is a growing public health concern in Bangladesh, with the incidence of approximately 0.64 to 6.8 in every 1000 live births. For over a decade, Ponseti method has been considered a gold standard for treating the clubfoot. Despite few studies have been estimating the number of casts required to correct the clubfoot deformities by Ponseti method, the subject of interest has always remained. Therefore, this current study aimed to investigate the significant predictive factors for the number of casts required to correct congenital clubfoot.

In this retrospective cohort study, we used Bayesian Poisson Regression Model to investigate the influencing factors that could predict how many casts are needed to correct the clubfoot. We included 69 patients with 99 affected feet, who completed their corrective phase of treatment in the Ponseti method. For this cohort study, we integrated only pre-tenotomy casting data with no age restrictions. We used Bayesian Poisson regression analysis technique to estimate the predictive factors.

In Bayesian Poisson model, age was the most influencing predictive factor (24.3%) for increasing the number of castings to correct the clubfoot deformity. The clubfoot offspring of the ≤1-year-old was positive, and the incidence rate increased significantly with the casting number. The number of Ponseti casts in male clubfoot children was 28% higher than in female, and this was marginally statistically significant. There was no marked change estimated in the pattern of clubfoot, foot involvement and Pirani score of the severity.

We concluded that the age factor may influence the number of casts required for the correction of clubfoot and specifically ≤ 1-year-old children are highly impacted. Treating clubfoot at an early age is suggested in this study to increase the success of clubfoot treatment and decrease the risk of relapse.