Heart Rate Characteristics and Clinical Signs in Neonatal Sepsis

@article{Griffin2007HeartRC,
  title={Heart Rate Characteristics and Clinical Signs in Neonatal Sepsis},
  author={M. Pamela Griffin and Douglas E. Lake and Thomas Michael O'Shea and J. Randall Moorman},
  journal={Pediatric Research},
  year={2007},
  volume={61},
  pages={222-227}
}
Key MethodTo test the hypothesis that heart rate characteristic (HRC) monitoring adds information to clinical signs of illness in diagnosing neonatal sepsis, we prospectively recorded clinical data and the HRC index in 76 episodes of proven sepsis and 80 episodes of clinical sepsis in 337 infants in the University of Virginia NICU more than 7 d old. We devised an illness severity score based on clinical findings and tests relevant to sepsis.
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Predicting Neonatal Sepsis Using Features of Heart Rate Variability, Respiratory Characteristics, and ECG-Derived Estimates of Infant Motion
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For the 49 infants studied, features of HRV, respiration, and movement showed characteristic changes in the hours leading up to the clinical suspicion of sepsis, namely, an increased propensity toward pathological heart rate decelerations, increased respiratory instability, and a decrease in spontaneous infant activity.
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Abnormal Heart Rate Characteristics Prior to Clinical Diagnosis of Necrotizing Enterocolitis
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Earlier diagnosis and treatment of necrotizing enterocolitis in preterm infants, before clinical deterioration, might improve outcomes and suggest that continuous HRC monitoring may facilitate earlier detection and treatment.
Are vital signs indicative for bacteremia in newborns?
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Monitoring vital signs closely might be helpful in a newborn infant to define a BSI, and a respiratory and blood pressure predictive monitoring system such as heart rate variability index may be developed for newborn patients with sepsis.
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Earlier diagnosis and treatment of necrotizing enterocolitis in preterm infants, before clinical deterioration, might improve outcomes and suggest that continuous HRC monitoring may facilitate earlier detection and treatment.
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Harnessing and analyzing the vast amounts of physiologic data constantly displayed in ICU patients will lead to improved algorithms for early detection, prognosis, and therapy of critical illnesses.
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TLDR
It is found that measurements of standard deviation, sample asymmetry and sample entropy are highly related to imminent clinical illness.
Predictive monitoring for sepsis and necrotizing enterocolitis to prevent shock.
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