Predictive monitoring for early detection of sepsis in neonatal ICU patients

@article{Fairchild2013PredictiveMF,
  title={Predictive monitoring for early detection of sepsis in neonatal ICU patients},
  author={Karen D. Fairchild},
  journal={Current Opinion in Pediatrics},
  year={2013},
  volume={25},
  pages={172–179}
}
  • K. Fairchild
  • Published 1 April 2013
  • Medicine
  • Current Opinion in Pediatrics
Purpose of review Predictive monitoring is an exciting new field involving analysis of physiologic data to detect abnormal patterns associated with critical illness. The first example of predictive monitoring being taken from inception (proof of concept) to reality (demonstration of improved outcomes) is the use of heart rate characteristics (HRC) monitoring to detect sepsis in infants in the neonatal ICU. The commercially available ‘HeRO’ monitor analyzes electrocardiogram data from existing… 
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Predictive monitoring for sepsis and necrotizing enterocolitis to prevent shock.
Predicting Neonatal Sepsis Using Features of Heart Rate Variability, Respiratory Characteristics, and ECG-Derived Estimates of Infant Motion
TLDR
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.
Predictive analytics in the pediatric intensive care unit for early identification of sepsis: capturing the context of age
Early recognition of patients at risk for sepsis is paramount to improve clinical outcomes. We hypothesized that subtle signatures of illness are present in physiological and biochemical time series…
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This analysis will strengthen the ability of health care organizations to evolve as learning health systems, in which bioinformatics data are applied to improve patient outcomes by incorporating AI into knowledge tools that are successfully integrated into clinical practice by health care providers.
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TLDR
HRV and Adaptive Boosting algorithm can be used to identify new-borns with higher risk of suffering neonatal sepsis during their first 48 hours, according to a minimally invasive and cost-effective tool.
Heart rate characteristic index monitoring for bloodstream infection in an NICU: a 3-year experience
TLDR
Elevated HRC scores had limited ability to detect BSI, and BSI was infrequent at any time during hospitalisation in infants with significantly elevated HRC scores.
Effective Biomarkers for Diagnosis of Neonatal Sepsis.
  • V. Bhandari
  • Medicine
    Journal of the Pediatric Infectious Diseases Society
  • 2014
TLDR
The diagnostic utility of the following biomarkers seems to be most practical in the early (interleukin [IL]-6, IL-8, tumor necrosis factor-alpha, neutrophil CD64), mid, mid and late phases of neonatal sepsis.
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TLDR
Study results will inform the design of an interventional study using temperatures and/or heart rate as a predictive tool to alert clinicians of cardiac and autonomic instability present with infection.
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TLDR
This study shows that a combination of electrocardiogram-based, respiration- based, and motion-based features enables the prediction of late-onset sepsis hours before the clinical crash moment, based on multiple patient monitoring signals 24 hours before onset.
Prediction Models for Neonatal Health Care–Associated Sepsis: A Meta-analysis
TLDR
Prediction models for health care–associated bloodstream infection in neonates should be considered as guidance rather than an absolute indicator because they all have limited diagnostic accuracy.
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References

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TLDR
It is found that the clinical diagnosis of neonatal sepsis is preceded by abnormal heart rate characteristics (HRC) of reduced variability and transient decelerations, and a predictive HRC monitoring strategy based on multivariable logistic regression analysis that was developed at one tertiary care NICU and validated at another.
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TLDR
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TLDR
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TLDR
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TLDR
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