Nomogram for predicting early hypophosphatemia in term infants

TL;DR

This study developed a nomogram to predict early hypophosphatemia in term infants based on risk factors like maternal diabetes and birth weight.

Contribution

A validated nomogram was created to predict early hypophosphatemia in term infants using clinical risk factors.

Findings

Male gender, maternal diabetes, and cesarean delivery were identified as independent risk factors for early hypophosphatemia.

The nomogram showed good predictive accuracy with a C-index of 0.732 and strong clinical utility confirmed by decision curve analysis.

Abstract

Physiological processes rely on phosphate, which is an essential component of adenosine triphosphate (ATP). Hypophosphatasia can affect nearly every organ system in the body. It is crucial to monitor newborns with risk factors for hypophosphatemia and provide them with the proper supplements. We aimed to evaluate the risk factors and develop a nomogram for early hypophosphatemia in term infants.

We conducted a retrospective study involving 416 term infants measured serum phosphorus within three days of birth. The study included 82 term infants with hypophosphatemia (HP group) and 334 term infants without hypophosphatemia (NHP group). We collected data on the characteristics of mothers, newborn babies, and childbirth. Furthermore, univariate and multivariate logistic regression analyses were performed to identify independent risk factors for hypophosphatemia in term infants, and a nomogram was developed and validated based on the final independent risk factors.

According to our analysis, the multivariate logistic regression analysis showed that male, maternal diabetes, cesarean delivery, lower serum magnesium, and lower birth weight were independent risk factors for early hypophosphatemia in term infants. In addition, the C-index of the developed nomogram was 0.732 (95% CI = 0.668–0.796). Moreover, the calibration curve indicated good consistency between the hypophosphatemia diagnosis and the predicted probability, and a decision curve analysis (DCA) confirmed the clinical utility of the nomogram.

The analysis revealed that we successfully developed and validated a nomogram for predicting early hypophosphatemia in term infants.

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