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

Presentation Outline

• HeRO RCT PI: Randall Moorman,MD

– Supported by NIH and Medical Predictive

Science Corporation (MPSC)

– Translational research lessons from HeRO

• Potential systems engineering research

• Pretty pictures from ongoing projects

• Big Data => study rare events like SIDS

• Accurate entropy estimation (math stuff)

Abnormal HRC in neonatal sepsis

• Decreased heart rate variability

• Repetitive decelerations

Normal HRC

Abnormal HRC

2004-2010 Randomized Clinical Trial:HRC monitoring in VLBW NICU patients

3003 VLBW infants admitted to 9 NICUs had HRC monitoring

HRC display Non-display

randomize

22 % relative reduction in mortality in HRC display group (8.1 % versus 10.2%, p = 0.04)

Moorman et al, J Pediatrics, Dec 2011

High Impact Beyond NICU

• 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!)

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)

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!

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

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

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

Periodic Breathing and Vital

Sign Entrainment

Sepsis ?

Necrotizing enterocolitis (NEC) ?

SIDS?

Adults?

Recent Unexpected NICU death

• 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