The Influence of Fetal and Postnatal Growth on Heart Rate Variability in Young Infants

Cardiology ◽  
2001 ◽  
Vol 95 (2) ◽  
pp. 80-83 ◽  
Author(s):  
Martial M. Massin ◽  
Nadia Withofs ◽  
Kristel Maeyns ◽  
Françoise Ravet
Keyword(s):  
Heart Rate ◽  
Heart Rate Variability ◽  
Postnatal Growth ◽  
Young Infants

Heart Rate Variability During Attention Phases in Young Infants

1991 ◽  
Vol 28 (1) ◽  
pp. 43-53 ◽  
Author(s):  
John E. Richards ◽  
Betty Jo Casey
Keyword(s):  
Heart Rate ◽  
Heart Rate Variability ◽  
Young Infants

Early prediction of serious infections in febrile infants incorporating heart rate variability in an emergency department: a pilot study

2021 ◽  
pp. emermed-2020-210675
Author(s):  
Shu-Ling Chong ◽  
Gene Yong-Kwang Ong ◽  
John Carson Allen ◽  
Jan Hau Lee ◽  
Rupini Piragasam ◽  
...  
Keyword(s):  
Heart Rate ◽  
Heart Rate Variability ◽  
Vital Signs ◽  
Model Performance ◽  
Diagnostic Challenge ◽  
Poincaré Plot ◽  
Time Frequency ◽  
Young Infants ◽  
Serious Infections ◽  
Non Linear

BackgroundEarly differentiation of febrile young infants with from those without serious infections (SIs) remains a diagnostic challenge. We sought to (1) compare vital signs and heart rate variability (HRV) parameters between febrile infants with versus without SIs, (2) assess the performance of HRV and vital signs with reference to current triage tools and (3) compare HRV and vital signs to HRV, vital signs and blood biomarkers, when predicting for the presence of SIs.MethodsUsing a prospective observational design, we recruited patients <3 months old presenting to a tertiary paediatric ED in Singapore from December 2018 through November 2019. We obtained patient demographic characteristics, triage assessment (including the Severity Index Score (SIS)), HRV parameters (time, frequency and non-linear domains) and laboratory results. We performed multivariable logistic regression analyses to predict the presence of an SI, using area under the curve (AUC) with the corresponding 95% CI to assess predictive capability.ResultsAmong 203 infants with a mean age of 38.4 days (SD 27.6), 67 infants (33.0%) had an SI. There were significant differences in the time, frequency and non-linear domains of HRV parameters between infants with versus without SIs. In predicting SIs, gender, temperature and the HRV non-linear parameter Poincaré plot SD2 (AUC 0.78, 95% CI 0.71 to 0.84) performed better than SIS alone (AUC 0.61, 95% CI 0.53 to 0.68). Model performance improved with the addition of absolute neutrophil count and C reactive protein (AUC 0.82, 95% CI 0.76 to 0.89).ConclusionAn exploratory prediction model incorporating HRV and biomarkers improved prediction of SIs. Further research is needed to assess if HRV can identify which young febrile infants have an SI at ED triage.Trial registration numberNCT04103151.

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