Neonatal cholestasis: development of a diagnostic decision algorithm from multivariate predictive models.

ABSTRACT

Despite the recent advances involving molecular studies, the neonatal cholestasis (NC) diagnosis still relays on the expertise of medical teams. Our aim was to develop models of etiological diagnosis and unfavourable prognosis which may support a rationale diagnostic approach. We retrospectively analysed 154 patients born between January 1985 and October 2019. The cohort was divided into two main groups (A) transient cholestasis and (B) other diagnosis (with subgroups) and also in two groups of outcomes: (I) unfavourable and (II) favourable. Multivariate logistic regression analysis identified the lower gestational age as the only variable independently associated with an increased risk of transient cholestasis and signs and/or symptoms of sepsis with infectious or metabolic diseases. Gamma-glutamyl transferase serum levels > 300 IU/L had a positive predictive value for both diagnosis of biliary atresia and for alpha-1-antitrypsin deficiency (A1ATD) and for unfavourable prognosis. A model of diagnosis for A1ATD (n = 34) showed an area under the ROC curve = 0.843 [confidence interval (CI) 0.773-0.912].Conclusion: This study identified some predictors of diagnosis and prognosis which helped to build a diagnostic decision algorithm. The unusually large subgroup of patients with A1ATD in this cohort emphasizes its predictive diagnostic model. What Is Known • The etiological diagnosis of neonatal cholestasis (NC) requires a step-by-step guided approach, and diagnostic models have been developed only for biliary atresia. • Current algorithms neither address the epidemiology changes nor the application of the new molecular diagnostic tools. What Is New • This study provides diagnostic predictive models for patients with A1ATD, metabolic/infectious diseases, and transient cholestasis, and two models of unfavourable prognosis for NC. • A diagnostic decision algorithm is proposed based on this study, authors expertise and the literature.