Threat-measuring capabilities of the NTISS scale in the pre-transport phase of neonatal preparation

Abstract

Introduction. Medical evacuation of newborns in critical condition remains an important area of neonatal intensive care. The study of threat-metric tools for assessing severity during the inter-hospital transport phases is of considerable practical interest.The aim of the study was to determine the ability of the NTISS scale to predict neonatal outcomes during the pre-transplant preparation phase, depending on the score obtained.Materials and Methods The cohort study includes data from 604 visits of the resuscitation and consultative center (RSCC) transport team to newborns under remote monitoring by the RSCC between August 1, 2017, and December 31, 2018. Division of the total sample into subgroups according to the score on the studied scale, with subsequent comparison of characteristics and outcomes in these subgroups was performed.Results In the subgroup of patients with a score of 30 or more there was a significant predominance of children with a birth weight of less than 1000 grams (85.72 %); in the subgroup with a score of 0–9, children with a birth weight of more than 2500 grams accounted for 83.33 %. Similar patterns were observed in the analysis of gestational age. Analysis of the volume of intensive care indicates an increase in the proportion of patients requiring high-frequency ventilatory ventilation, dopamine and adrenaline infusion as the NTISS score increased. When analyzing outcomes in the overall sample, there was an increase in the proportion of fatal outcomes from 0.00 % to 75.00 % as the NTISS score increased.Discussion The NTISS scale, being a therapeutic profile instrument, divided the sample according to the need for intensive care, which was significantly associated with birth weight and gestational age. Thus, the observed differences in outcomes are a legitimate result of the prevalence of extremely premature infants at high NTISS scores.Conclusion The NTISS scale demonstrates a reliable division of patients by severity and predicts the outcomes of the hospital phase of treatment.