The aim of the study was to develop and validate a prediction model for hemorrhage in critically ill neonates which combines rotational thromboelastometry (ROTEM) parameters and clinical variables. This cohort study included 332 consecutive full-term and preterm critically ill neonates. We performed ROTEM and used the neonatal bleeding assessment tool (NeoBAT) to record bleeding events. We fitted double selection least absolute shrinkage and selection operator logit regression to build our prediction model. Bleeding within 24 hours of the ROTEM testing was the outcome variable, while patient characteristics, biochemical, hematological, and thromboelastometry parameters were the candidate predictors of bleeding. We used both cross-validation and bootstrap as internal validation techniques. Then, we built a prognostic index of bleeding by converting the coefficients from the final multivariable model of relevant prognostic variables into a risk score. A receiver operating characteristic analysis was used to calculate the area under curve (AUC) of our prediction index. EXTEM A10 and LI60, platelet counts, and creatinine levels were identified as the most robust predictors of bleeding and included them into a Neonatal Bleeding Risk (NeoBRis) index. The NeoBRis index demonstrated excellent model performance with an AUC of 0.908 (95% confidence interval [CI]: 0.870–0.946). Calibration plot displayed optimal calibration and discrimination of the index, while bootstrap resampling ensured internal validity by showing an AUC of 0.907 (95% CI: 0.868–0.947). We developed and internally validated an easy-to-apply prediction model of hemorrhage in critically ill neonates. After external validation, this model will enable clinicians to quantify the 24-hour bleeding risk.

BackgroundWe aimed to develop and validate a diagnostic model for sepsis among neonates evaluated for suspected sepsis, by incorporating thromboelastometry parameters, maternal/neonatal risk factors, clinical signs/symptoms and laboratory results.MethodsThis retrospective cohort study included 291 neonates with presumed sepsis, hospitalized in a NICU, from 07/2014 to 07/2021. Laboratory tests were obtained on disease onset and prior to initiating antibiotic therapy. Τhromboelastometry extrinsically activated (EXTEM) assay was performed simultaneously and Tοllner and nSOFA scores were calculated. Sepsis diagnosis was the outcome variable. A 10-fold cross-validation least absolute shrinkage and selection operator logit regression procedure was applied to derive the final multivariable score. Clinical utility was evaluated by decision curve analysis.ResultsGestational age, CRP, considerable skin discoloration, liver enlargement, neutrophil left shift, and EXTEM A10, were identified as the strongest predictors and included in the Neonatal Sepsis Diagnostic (NeoSeD) model. NeoSeD score demonstrated excellent discrimination capacity for sepsis and septic shock with an AUC: 0.918 (95% CI, 0.884–0.952) and 0.974 (95% CI, 0.958–0.989) respectively, which was significantly higher compared to Töllner and nSOFA scores.ConclusionsThe NeoSeD score is simple, accurate, practical, and may contribute to a timely diagnosis of sepsis in neonates with suspected sepsis. External validation in multinational cohorts is necessary before clinical application.

No abstract

No abstract

Background Our aim was to investigate the role of thromboelastometry (ROTEM) parameters, including maximum clot elasticity (MCE) and platelet component (PLTEM MCE and PLTEM MCF), in early prediction of bleeding events in thrombocytopenic critically ill neonates. Material and methods This single‐center, prospective cohort study included 110 consecutive thrombocytopenic neonates with sepsis, suspected sepsis, or hypoxia. On the first day of disease onset, ROTEM EXTEM and FIBTEM assays were performed and the neonatal bleeding assessment tool was used for the evaluation of bleeding events. Results Most EXTEM and FIBTEM ROTEM parameters significantly differed between neonates with (n = 77) and without bleeding events (n = 33). Neonates with bleeding events had significantly lower PLTEM MCE and PLTEM MCF values compared to those without bleeding events (P < .001). Platelet count was found to be strongly positively correlated with EXTEM A5 (Spearman's rho = 0.61, P < .001) and A10 (rho = 0.64, P < .001). EXTEM A10 demonstrated the best prognostic performance (AUC = 0.853) with an optimal cutoff value (≤37 mm) (sensitivity = 91%, specificity = 76%) for prediction of bleeding events in thrombocytopenic neonates. Conclusions EXTEM A5 and EXTEM A10 were found to be strong predictors of hemorrhage, compared to most ROTEM variables quantifying clot elasticity and platelet component in thrombocytopenic critically ill neonates.