Your browser doesn't support javascript.
loading
Clinical outcome prediction with an automated EEG trend, Brain State of the Newborn, after perinatal asphyxia.
Montazeri, Saeed; Nevalainen, Päivi; Metsäranta, Marjo; Stevenson, Nathan J; Vanhatalo, Sampsa.
Afiliación
  • Montazeri S; BABA Center, Pediatric Research Center, Children's Hospital, University of Helsinki and Helsinki University Hospital, Helsinki, Finland; Department of Physiology, University of Helsinki, Helsinki, Finland. Electronic address: saeed.montazeri@helsinki.fi.
  • Nevalainen P; BABA Center, Pediatric Research Center, Children's Hospital, University of Helsinki and Helsinki University Hospital, Helsinki, Finland; Department of Clinical Neurophysiology, Epilepsia Helsinki, Full Member of ERN Epicare, HUS Diagnostic Center, University of Helsinki and Helsinki University Hospi
  • Metsäranta M; Department of Pediatrics, Children's Hospital, University of Helsinki and Helsinki University Hospital, Helsinki, Finland.
  • Stevenson NJ; Brain Modelling Group, QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia.
  • Vanhatalo S; BABA Center, Pediatric Research Center, Children's Hospital, University of Helsinki and Helsinki University Hospital, Helsinki, Finland; Department of Physiology, University of Helsinki, Helsinki, Finland; Department of Clinical Neurophysiology, Epilepsia Helsinki, Full Member of ERN Epicare, HUS Di
Clin Neurophysiol ; 162: 68-76, 2024 Jun.
Article en En | MEDLINE | ID: mdl-38583406
ABSTRACT

OBJECTIVE:

To evaluate the utility of a fully automated deep learning -based quantitative measure of EEG background, Brain State of the Newborn (BSN), for early prediction of clinical outcome at four years of age.

METHODS:

The EEG monitoring data from eighty consecutive newborns was analyzed using the automatically computed BSN trend. BSN levels during the first days of life (a of total 5427 hours) were compared to four clinical outcome categories favorable, cerebral palsy (CP), CP with epilepsy, and death. The time dependent changes in BSN-based prediction for different outcomes were assessed by positive/negative predictive value (PPV/NPV) and by estimating the area under the receiver operating characteristic curve (AUC).

RESULTS:

The BSN values were closely aligned with four visually determined EEG categories (p < 0·001), as well as with respect to clinical milestones of EEG recovery in perinatal Hypoxic Ischemic Encephalopathy (HIE; p < 0·003). Favorable outcome was related to a rapid recovery of the BSN trend, while worse outcomes related to a slow BSN recovery. Outcome predictions with BSN were accurate from 6 to 48 hours of age For the favorable outcome, the AUC ranged from 95 to 99% (peak at 12 hours), and for the poor outcome the AUC ranged from 96 to 99% (peak at 12 hours). The optimal BSN levels for each PPV/NPV estimate changed substantially during the first 48 hours, ranging from 20 to 80.

CONCLUSIONS:

We show that the BSN provides an automated, objective, and continuous measure of brain activity in newborns.

SIGNIFICANCE:

The BSN trend discloses the dynamic nature that exists in both cerebral recovery and outcome prediction, supports individualized patient care, rapid stratification and early prognosis.
Asunto(s)
Palabras clave
Texto completo
Añadir a Mi BVS
Imprimir
XML
PubMed Links
Buscar en Google

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Asfixia Neonatal / Encéfalo / Electroencefalografía Límite: Child, preschool / Female / Humans / Male / Newborn Idioma: En Revista: Clin Neurophysiol Asunto de la revista: NEUROLOGIA / PSICOFISIOLOGIA Año: 2024 Tipo del documento: Article Pais de publicación: Países Bajos
Texto completo
Añadir a Mi BVS
Imprimir
XML
PubMed Links
Buscar en Google

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Asfixia Neonatal / Encéfalo / Electroencefalografía Límite: Child, preschool / Female / Humans / Male / Newborn Idioma: En Revista: Clin Neurophysiol Asunto de la revista: NEUROLOGIA / PSICOFISIOLOGIA Año: 2024 Tipo del documento: Article Pais de publicación: Países Bajos