A perinatal stress calculator for the neonatal intensive care unit: an unobtrusive approach.
Physiol Meas
; 41(7): 075012, 2020 08 11.
Article
in En
| MEDLINE
| ID: mdl-32521528
ABSTRACT
OBJECTIVE:
Early experience of pain and stress in the neonatal intensive care unit is known to have an effect on the neurodevelopment of the infant. However, an automated method to quantify the procedural pain or perinatal stress in premature patients does not exist.APPROACH:
In the current study, EEG and ECG data were collected for more than 3 hours from 136 patients in order to quantify stress exposure. Specifically, features extracted from the EEG and heart-rate variability in both quiet and non-quiet sleep segments were used to develop a subspace linear-discriminant analysis stress classifier. MAINRESULTS:
The main novelty of the study lies in the absence of intrusive methods or pain elicitation protocols to develop the stress classifier. Three main findings can be reported. First, we developed different stress classifiers for the different age groups and stress intensities, obtaining an area under the curve in the range [0.78-0.93] for non-quiet sleep and [0.77-0.96] for quiet sleep. Second, a dysmature EEG was found in patients under stress. Third, an enhanced cortical connectivity and increased brain-heart communication was correlated with a higher stress load, while the autonomic activity did not seem to be associated to stress exposure.SIGNIFICANCE:
The results shed a light on the pain and stress processing in preterm neonates, suggesting that software tools to investigate dysmature EEG might be helpful to assess stress load in premature patients. These results could be the foundation to assess the impact of stress on infants' development and to tune preventive care.
Full text:
1
Collection:
01-internacional
Database:
MEDLINE
Main subject:
Stress, Physiological
/
Pain Measurement
/
Infant, Premature
/
Intensive Care Units, Neonatal
Type of study:
Prognostic_studies
Limits:
Female
/
Humans
/
Newborn
/
Pregnancy
Language:
En
Journal:
Physiol Meas
Journal subject:
BIOFISICA
/
ENGENHARIA BIOMEDICA
/
FISIOLOGIA
Year:
2020
Document type:
Article