Thromb Haemost 2021; 121(02): 131-139
DOI: 10.1055/s-0040-1715832
Coagulation and Fibrinolysis

A Risk Score for Predicting the Incidence of Hemorrhage in Critically Ill Neonates: Development and Validation Study

Rozeta Sokou
1   Neonatal Intensive Care Unit, “Agios Panteleimon” General Hospital of Nikea, Piraeus, Greece
,
Daniele Piovani
2   Department of Biomedical Sciences, Humanitas University, Milan, Italy
3   Humanitas Clinical and Research Center, IRCCS, Milan, Italy
,
Aikaterini Konstantinidi
1   Neonatal Intensive Care Unit, “Agios Panteleimon” General Hospital of Nikea, Piraeus, Greece
,
Andreas G. Tsantes
4   Laboratory of Haematology and Blood Bank Unit, “Attiko” Hospital, School of Medicine, National and Kapodistrian University of Athens, Athens, Greece
,
Stavroula Parastatidou
1   Neonatal Intensive Care Unit, “Agios Panteleimon” General Hospital of Nikea, Piraeus, Greece
,
Maria Lampridou
1   Neonatal Intensive Care Unit, “Agios Panteleimon” General Hospital of Nikea, Piraeus, Greece
,
Georgios Ioakeimidis
1   Neonatal Intensive Care Unit, “Agios Panteleimon” General Hospital of Nikea, Piraeus, Greece
,
Antonis Gounaris
5   Neonatal Intensive Care Unit, University Hospital of Larissa, Larissa, Greece
,
Nicoletta Iacovidou
6   Neonatal Department, Aretaeio Hospital, National and Kapodistrian University of Athens, Athens, Greece
,
Anastasios G. Kriebardis
7   Department of Biomedical Science, Laboratory of Reliability and Quality Control in Laboratory Hematology, School of Health and Caring Science, University of West Attica, Egaleo, Greece
,
Marianna Politou
8   Department of Blood Transfusion, Aretaieion Hospital, School of Medicine, National and Kapodistrian University of Athens, Athens, Greece
,
Petros Kopterides
9   Intensive Care Unit, Excela Health Westmoreland Hospital, Greensburg, Pennsylvania, United States
,
Stefanos Bonovas
2   Department of Biomedical Sciences, Humanitas University, Milan, Italy
3   Humanitas Clinical and Research Center, IRCCS, Milan, Italy
,
Argirios E. Tsantes
4   Laboratory of Haematology and Blood Bank Unit, “Attiko” Hospital, School of Medicine, National and Kapodistrian University of Athens, Athens, Greece
› Author Affiliations

Funding None declared.
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Abstract

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.

Supplementary Material



Publication History

Received: 19 April 2020

Accepted: 21 July 2020

Article published online:
24 August 2020

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