Automated Author Profile

Lindeman, R.

Current S-Index

1.2

Sum of Dataset Indices for all datasets

Average Dataset Index per Dataset

0.6

Average Dataset Index per dataset

Total Datasets

2

Total datasets for this author

Average FAIR Score

84.6%

Average FAIR Score per dataset

Total Citations

0

Total citations to the author's datasets

Total Mentions

0

Total mentions of the author's datasets

S-Index Interpretation

S-Index Over Time

Cumulative Citations Over Time

Cumulative Mentions Over Time

Datasets

Supplementary Material for: Automated Spectral EEG Analyses of Premature Infants during the First Three Days of Life Correlated with Developmental Outcomes at 24 Months

Background: Spectral EEG analysis using automated quantification of total absolute band power (tABP) for long-term brain monitoring is reliable. We hypothesised that tABP during the first critical days of life could be a useful tool for predicting later developmental outcomes. Objective: To determine whether measuring EEG background activity in premature infants with automated tABP quantification during the first 3 days of life correlated with their developmental outcomes at 24 months. Methods: Preterm infants (group 1, gestational age, GA 24–28 weeks and group 2, GA 28–31 weeks) were continuously monitored by EEG for 3 days after birth. Their developmental outcomes were assessed using the Bayley-II and Peabody-2 developmental tests at 24 months. Their respective indices were calculated. Normal (index ≥85) and abnormal (index <85) outcomes were correlated with the tABP. Results: In group 1, the tABP was significantly lower in the abnormal infants than in the normal infants. The specificity and negative predictive value were also high for all of the tests that were applied in this group. In group 2, there was no correlation between the tABP and developmental outcome. Conclusion: This study found that extremely premature infants with poor developmental outcomes had significantly lower tABP values in their first days of life compared to infants from the same group with normal outcomes. This method may be useful in predicting later outcomes in extremely premature infants and has the advantage of being automated.

Authors

  • Schumacher, E.M. ;
  • Larsson, P.G. ;
  • Sinding-Larsen, C. ;
  • Aronsen, R. ;
  • Lindeman, R. ;
  • Skjeldal, O.H. ;
  • Stiris, T.A.
0 Citations0 Mentions85% FAIR0.7 Dataset Index
10.6084/m9.figshare.51243852013

Supplementary Material for: Automated Spectral EEG Analyses of Premature Infants during the First Three Days of Life Correlated with Developmental Outcomes at 24 Months

Background: Spectral EEG analysis using automated quantification of total absolute band power (tABP) for long-term brain monitoring is reliable. We hypothesised that tABP during the first critical days of life could be a useful tool for predicting later developmental outcomes. Objective: To determine whether measuring EEG background activity in premature infants with automated tABP quantification during the first 3 days of life correlated with their developmental outcomes at 24 months. Methods: Preterm infants (group 1, gestational age, GA 24–28 weeks and group 2, GA 28–31 weeks) were continuously monitored by EEG for 3 days after birth. Their developmental outcomes were assessed using the Bayley-II and Peabody-2 developmental tests at 24 months. Their respective indices were calculated. Normal (index ≥85) and abnormal (index <85) outcomes were correlated with the tABP. Results: In group 1, the tABP was significantly lower in the abnormal infants than in the normal infants. The specificity and negative predictive value were also high for all of the tests that were applied in this group. In group 2, there was no correlation between the tABP and developmental outcome. Conclusion: This study found that extremely premature infants with poor developmental outcomes had significantly lower tABP values in their first days of life compared to infants from the same group with normal outcomes. This method may be useful in predicting later outcomes in extremely premature infants and has the advantage of being automated.

Authors

  • Schumacher, E.M. ;
  • Larsson, P.G. ;
  • Sinding-Larsen, C. ;
  • Aronsen, R. ;
  • Lindeman, R. ;
  • Skjeldal, O.H. ;
  • Stiris, T.A.
0 Citations0 Mentions85% FAIR0.6 Dataset Index
10.6084/m9.figshare.5124385.v12013