Heart Rate Monitoring Saves Lives of Premature Infants: Results of HeRO Clinical Study
1. Heart Rate Monitoring Saves
Lives of Premature Infants:
Results of HeRO Clinical Study
Douglas E. Lake, PhD
Research Associate Professor
Cardiovascular Division and Statistics *
University of Virginia
dlake@virginia.edu
* MPSC (www.heroscore.com) shareholder
2. Presentation Outline
• HeRO RCT PI: Randall Moorman,MD
– Supported by NIH and Medical Predictive
Science Corporation (MPSC)
– Translational research lessons from HeRO
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Potential systems engineering research
Pretty pictures from ongoing projects
Big Data => study rare events like SIDS
Accurate entropy estimation (math stuff)
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4. Abnormal HRC in neonatal sepsis
• Decreased heart rate variability
• Repetitive decelerations
Normal HRC
Abnormal HRC
5. 2004-2010 Randomized Clinical Trial:
HRC monitoring in VLBW NICU patients
3003 VLBW infants admitted to 9 NICUs
had HRC monitoring
randomize
HRC display
Non-display
22 % relative reduction in mortality in HRC display
group (8.1 % versus 10.2%, p = 0.04)
Moorman et al, J Pediatrics, Dec 2011
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7. High Impact Beyond NICU
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No new drugs / procedure
No invasive device
No alarm or mandatory action required
Takes data already available and repackages
into clinically useful display
• Clinical benefit rigorously demonstrated
• More clinical significance than published
“statistical significance”
• Pioneering FDA “approval” (Don’t ask!)
8. Predictive Monitoring at UVA
• Massive monitoring data collection infrastructure
– Every NICU heartbeat since 1999 (~50 gigabeats)
– Neonatal Apnea GO grant (stimulus funding 2009)
– BedMaster: 75 bed licences (~10GB per day)
• Adult ICU: Predictive monitoring in patients with
trauma (PreMPT): Coulter award
• Pre-Rescue Anticipatory Monitoring (PRAM)
– 300 beds funded by UVA hospital for implementation
– >100GB a day
• Collaboration w/ Columbia, UCSF, INOVA, … =>
even BIGGER data (~3000 beds)
9. Lessons Learned
• Translating academic research to health care
system difficult and lengthy process
– Ask right clinical question
– Keep asking yourself “So what?”
• Collect lots and lots of data (then collect more)
– Automate as much as possible
– Massive storage required for waveform data
– Electronic medical records / research not there yet
• Objective end points (no arbitrary thresholds)
• Don’t let big data paralyze progress
• Prominent role for systems engineering!
10. SIE and Predictive Monitoring
• Data collection / visualization
– EMR / clinical data / text mining
– Graphical User Interface
– Rapid retrieval of archived waveforms
– Human factors / alarm fatigue
• Analytics (modern data mining)
– Black box -> Grey Box
– Meaningful objective functions (e.g. $)
– Missing / noisy data
11. SIE and Signal Processing
• Multiple signals
– Correlation / entrainment
– Pairwise and global
• Entropy estimation
• Multivariate probability density estimation
– Kernel methods
– Big Data mitigates curse of dimensionality
• Unsupervised clustering of signals
– Incredibly brilliant or stupid
12. Continuous Physiological Monitoring
System Benefits / Challenges
• Provides valuable diagnosis information
– Analyze trends and detect abrupt changes, but …
• Repeated dependent measures a pain
– Robust estimates of covariance (sandwich estimate)
– Bootstrap estimates of CI’s and P-values
• Modern data mining (datamininglab.com)
– Yet to be fully adapted to health care applications
– Messy data sporadically available
– Real-time implementation issues
14. Recent Unexpected NICU death
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Five week old infant born at gestational age 25
Stable in step-down unit
Sudden acute apnea=>code=>died 3 hours later
Presumed but unconfirmed sepsis
Monitor data reviewd 3 days later
– Extreme periodic breathing > 12 hours prior to death
– Periodic SPO2 and HR => extreme correlation
– Largest change in HR-SPO2 (i.e. brady/desat)
• Same phenomena seen in adults
