Background: Transportation of sick newborns is a major predictor of outcome. Prompt identification of the sickest newborns allows adequate intervention and outcome optimization. An optimal scoring system has not yet been identified. Aim: To identify a rapid, accurate, and easy-to-perform score predictive for neonatal mortality in outborn neonates. Material and methods: All neonates admitted by transfer in a level III regional neonatal unit between 1 January 2015 and 31 December 2021 were included. Infants with congenital critical abnormalities were excluded (N = 15). Gestational age (GA), birth weight (BW), Apgar score, place of birth, time between delivery and admission (AT), early onset sepsis, and sick neonatal score (SNS) were collected from medical records and tested for their association with mortality, including in subgroups (preterm vs. term infants); GA, BW, and AT were used to develop MSNS-AT score, to improve mortality prediction. The main outcome was all-cause mortality prediction. Univariable and multivariable analysis, including Cox regression, were performed, and odds ratio and hazard ratios were calculated were appropriate. Results: 418 infants were included; 217/403 infants were born prematurely (53.8%), and 20 died (4.96%). Compared with the survivors, the non-survivors had lower GA, BW, and SNS scores (p < 0.05); only the SNS scores remained lower in the subgroup analysis. Time to admission was associated with an increased mortality rate in the whole group and preterm infants (p < 0.05). In multiple Cox regression models, a cut-off value of MSNS-AT score ≤ 10 was more precise in predicting mortality as compared with SNS (AUC 0.735 vs. 0.775) in the entire group and in the preterm infants group (AUC 0.885 vs. 0.810). Conclusions: The new MSNS-AT score significantly improved mortality prediction at admission in the whole study group and in preterm infants as compared with the SNS score, suggesting that, besides GA and BW, AT may be decisive for the outcome of outborn preterm infants.

Background/Objectives: Over the past three decades, emergency medicine in Romania has evolved from a developing specialty into a cornerstone of the national healthcare system. As we reflect on these 30 years, it becomes evident that the lessons learned and the systems developed form a vital foundation for the future. This study aims to explore how the accumulated experience can guide us toward building a more resilient emergency medical system, one that prioritizes quality, ensures patient and provider safety, and embraces modern principles of healthcare management. The objectives of this study were to explore the long-term perspectives of physicians and nurses working in emergency departments (EDs), to determine the triggering factors that may lead to abandoning the specialty, and to identify of malpractice risks arising from doctor–patient interaction. Methods: This study employed an observational design and utilized an opinion questionnaire to assess the participants’ perspectives. Qualitative data were presented as frequencies and percentages. Quantitative data were expressed as means and standard deviations after verifying normal distribution with the Shapiro–Wilk test. Comparisons between groups for qualitative variables were conducted using the chi-square test. For comparisons of quantitative variables between two groups, Student’s t-test was employed following confirmation of homogeneity of variances with Levene’s test. A p-value of < 0.05 was considered statistically significant. Results: Out of 1228 estimated responders, 641 completed the questionnaire. A total of 577 of participants met the inclusion criteria: 256 (44.4%) nurses and 321 (55.6%) doctors, with an average age of the responders of 40.06 years. Nurses reported the highest level of managerial support (83.2%, p < 0.001). EPs had the highest rate of non-participation in working groups for procedures/protocols/guidelines (49.5%, p < 0.001). Intensive care unit medical doctors (ICU-MDs) and EPs were the main groups reporting a deficiency in employer-provided resources to manage conflict situations (63.7%, 61.7%; p <0.001). EPs (28%) reported practicing defensive medicine (inadequate educational support, the absence of clear protocols). Workplace burnout was reported by the ICU-MDs and EPs responders (96.3%; 93.4%; p < 0.001), and 26% of EPs expressed interest in professional reorientation. Conclusions: This study highlights four strategic directions for rebuilding a resilient healthcare system focused on improving quality of care and safety: development of procedures/protocols, managerial reorganization, restoration of healthcare professionals’ trust through new strategies, and academic development.

Background: Neonatal transportation of sick newborns is a major predictor of outcome. Prompt identification of the sickest newborns allows immediate corrective intervention and outcome optimization. Multiple severity scores were developed, however an optimal score has not yet been identified. Aim: To identify a rapid, accurate, and easy to perform score predictive for neonatal mortality in outborn neonates. Material and methods: All neonates, irrespective of gestational age, admitted by transfer in our level III regional neonatal unit between 01.01.2015 and 31.12.2021 were included. Infants with congenital critical abnormalities were excluded. Sick neonatal score (SNS) was calculated and compared between survivors and non-survivors. Gestational age (GA), birth weight (BW), gender, Apgar score, place of birth, time between delivery and admission (AT), early onset sepsis were collected from medical records and compared between study groups. Subgroup analysis was performed based on gestational age (preterm versus term infants). A new score was elaborated, including GA, BW, and AT, namely MSNS-AT score, to further improve mortality prediction. The main outcomes were mortality prediction using SNS and MSNS-AT score. Univariable and multivariable analysis, including Cox regression, were performed using SPSS Statistic 22.0. P-value was considered statistically significant if <0.05, 95% confidence intervals, odds ratio and hazard ratios were calculated were appropriate. Results: A total of 418 outborn infants were admitted during study period; 15 infants were excluded due to critical congenital defects. Out of 403 outborn infants, 217 born prematurely (53.8%), 224 males (55.6%), 20 died (4.96%). Compared to the survivors, the non-survivor neonates had significantly lower GA, BW, and SNS score (p<0.05), although only SNS score remained significantly lower in all subgroups (preterm vs term infants). A SNS score ≤8 was associated with mortality both in the whole study group and in subgroups (p<0.001). Time to admission was significantly associated with increased mortality rate in the whole group (p0.05). In univariable and multivariable Cox regression models, MSNS-AT score, with a cut-off optimal value of ≤10 was more precise in predicting mortality compared to SNS (AUC 0.735 vs. 0.775) when applied to the entire group, had a lower accuracy in the term infants (AUC 0.765 vs 0.809) and a better accuracy the preterm infants group (AUC 0.885 vs. 0.810). Conclusions: The MSNS-AT score – calculated by adding GA, BW, and AT to the SNS score - significantly improved mortality prediction at admission in the whole study group as compared to SNS score. The best accuracy prediction of MSNS-AT score was observed in preterm infants suggesting that, besides GA and BW, TA may be decisive for the outcome of outborn preterm infants. Further studies are necessary to confirm the predictive value of MSNS-AT score and to identify variables that can improve its value in term infants without affecting the simplicity, ease, and rapidity of the scoring system.